ISMS 2016

3RD INTERNATIONALSYMPOSIUM ON MINESAFETY, SCIENCE AND
ENGINEERING

Operational and Environmental Mine Health and
Safety Practice and Innovation
Symposium Proceedings
http://isms2016.proceedings.mcgill.ca
August 13-19, 2016
McGill University, Montreal, CANADA

Editors: H.S. Mitri, S. Shnorhokian, M.K. Kumral, A. Sasmito, A. Sainoki

Operational and Environmental Mine Health and Safety Practice and Innovation

Published by McGill University (2016)
ISBN: ISBN 978-1-77247-005-5

EDITORSHANI S. MITRISHAHE SHNORHOKIANMUSTAFA KUMRAL
AGUS SASMITO
ATSUSHI SAINOKITable of Contents
Prefacev

Organizing Committee

vi

International Advisory Committee and Editorial Board

vii

Part 1b-value as a criterion for the evaluation of rockburst hazard in coal mines

1

Quantitative evaluation of stope damage induced by seismic waves

6

Grzegorz Mutke, Aleksandra Pierzyna, Adam Barański

Atsushi Sainoki, Hani S. Mitri

Influence of weak planes on rockburst occurrence

12

Amin Manouchehrian, Ming Cai
A model of rockburst including geological dynamic conditions and mining
Jun Han, Ting Ren, Tianwei Lan, Feng Zhu, Chen Cao,
Hongwei Zhang, Guoshui Tang

18

Rockburst experiences in Cheves Hydropower Project, PerúSantiago Veyrat, Jose-Miguel Galera, Marcos Sancho,
H. Andersson, W. Thoese, and, C. Rietschel

24

Rockburst mitigation experiences on underground projects in the Cheves Hydropower
project in the Peruvian Andes

38

Santiago Veyrat, Jose-Miguel Galera, Marcos Sancho

Destress blasting on the border of safety pillars

45

Petr Konicek, Jiri Ptacek, Alejandro Mazaira

Powered support selection for longwall workings in dynamic load conditions

54

Evolution of grouting methods for dynamic supports in broken ground60

Stanisław Prusek, Sylwester Rajwa, Andrzej Walentek, Wojciech Masny

Francois Charette, Trond Skogseth

Large scale panel destress blasting parametric study

65

Isaac Vennes, Hani Mitri

Improving ground control safety in deep vein mines

71

Joseph Seymour, Donovan Benton, Michael Raffaldi, Jeffrey Johnson,
Lewis Martin, Shawn Boltz, Jerald Richardson

Numerical investigation of EDZ development around a deep polymetallic ore mine

78

Mountaka Souley, Marwan Al Heib, Vincent Renaud

Estimating the probability of unsatisfactory performance associated with the instabilityof mine developments

84

Wael Abdellah, Hani MitriiNumerical modelling of time-dependent skin degradation of an isolated pillar

90

Atsushi Sainoki, Hani S. Mitri

Quantitative analysis of haulage system instability in deep hard rock mines using
numerical modeling96

Shahé Shnorhokian, Bryce MacNeil, Hani Mitri

Minimum strength required for resisting cyclic softening/failure of cemented paste
backfill at early age

102

Tikou Belem, Mamert Mbonimpa

Analysis of failure in a salt room and pillar mine

108

Farid Laouafa, Mehdi Ghoreychi

Lessons in slope stability management from Kinross’ Tasiast mine, Mauritania

114

Korhan Tasoren, Gillian Gardhouse, P.Eng., Dr. Jerry Ran, P.Eng.

Effect of buttress on reduction of rock slope sliding along geological boundary

121

Ryota MORIYA, Daisuke FUKUDA, Jun-ichi KODAMA, Yoshiaki FUJII

Validation of empirical rock mass classification systems for rock slopes

127

Hassan Basahel, Hani Mitri

Application of InSAR for monitoring deformations at the Kiirunavaara Mine

133

Karola Mäkitaavola, Britt-Mari Stöckel, Jonny Sjöberg, Stephen Hobbs,
Jonas Ekman, Michael Henschel, Anura Wickramanayake

Modelling the impact of particle flow on rigid structures: experimental andnumerical investigations

140

M.A. Meguid, Ge Gao, M.M. Abouelkair and M.Z. Abdelrahman

A versatile model for the evaluation of subsidence hazards above
underground extractions

145

Peter Cain, Ph.D., P.Eng., Dr. Ing. Karsten Zimmerman

Slope stability analysis and prediction based on the limit equilibrium methodof Luming Molybdenum Mine's West-I and North Region

154

HUANG Zhi-an, LIU Fang-zhe, WANG Hui, GAO Yu-kun

Study on the similar materials simulation of the slope stability of the west-Ⅰ
zone in Luming Molybdenum Mine

159

Huang Zhian, YangFei, Wang Hui, Zhang Yinghua, GaoYukun

Stability and access implications of open pit mining through old undergroundmine workings

165

John G. Henning

Thermomechanical impact of Underground Coal Gasification exploitation

170

Laouafa Farid

Escapeway Solutions

176

Allison Deadman, Steven Durkin, Vincent Lawrenceii

Estimating stope vein footwall stability using various constitutive
modelling techniques

181

Andrew Pyon, Atsushi Sainoki, Hani S. Mitri

Redesigning the geometry of the Makala Coal Mine to improve safety
and productivity

187

Jean-Pierre Tshibangu, Fanny Descamps

Shear behaviour of regular and irregular rock joints under cyclic conditions

193

S. M. Mahdi Niktabar, K. Seshagiri Rao, Amit Kumar Shrivastava

3D geological modelling method based on hybrid data model199

Xue-xi Chen, De-fu Che

Measurement and analysis of virgin-rock temperature in Huanren Metal Mine

204

CHANG De-qiang, LIU Jing-xian, MAO Ning, GE Shuang-you

The tensile properties of GFRP bars at different loading rates

208

Wenxue Chen, Jun Wu, Yuzhao Jiao, Jiewen Zheng, Xue Li

Part 2A definition and evaluation index system of aging mines214

MA Hui, LIAN Huiqing, ZHU Hongjie

Numerical simulation of thermodynamic performance in a honeycomb ceramic channel

219

Bo Lan, You-Rong Li

Dust Dispersion Analysis Based on the Rosen-Rammler Distribution Function225

Yao Haifei, Zhang Qun

Fuzzy comprehensive evaluation of emergency capability of port coal storage basewith G1 method

231

Siheng Sun, Guozhong Huang, LongzheJin, Yage Li, Xue Zhao

Study on External Protective System of Waterproofing Refuge Chamber in
Guilaizhuang Gold Mine

236

Shengnan Ou, Longzhe Jin, Song Li, Shu Wang, Yage Li, Zhiling Huang

Hazard detection and comprehensive control technologies of the integrated
resource coal mine goafs in China

243

Wen LI

Multi-bed type oxidation reactor applied to the coal mine ventilation air methane

248

Weifeng Zou, Bo Lan, Jiandong Kang

Water disaster investigation and control in coal mine of Southern China

254

LIANG Qing-hua

The lifting and separating system for ground maneuvering rescue equipment

258

GAO Yukun, GONG Xuejiao, HUANG Zhian, ZHANG Yinghua

Safety and stability of the maneuvering rescue platform

264

GAO Yu-kun, Ji Yu-Chen, HUANG Zhi-an, ZHANG Ying-huaiii

The performance optimization experiment of a wet high-frequency vibrating grid

268

Zhang Yinghua, Liu Jia, Huang Zhian*, Gao Yukun

Borehole docking system design for underground refuge chamber and groundmaneuver rescue equipment

276

ZHANG Ying-hua, SONG Shou-yi, HUANG Zhi-an, GAO Yu-kun

Use of the Analytic Hierarchy Process in safety control of rescue equipment

281

Zhang Yinghua, Sun Qian, Huang Zhian, Gao Yukun

Research on new high-water solidified materials to reinforce coal and eliminate
gas outburst

285

Yinghua Zhang, Peiling Zhou, Zhian Huang, Yukun Gao, Qiang Luo

Key technologies for extinguishing large-area goaf fires in closely spaced
shallow coal seams

291

Botao Qin, Quanlin Shi, Junzhe Yang, Hetang Wang, Lihui Zhang

The assessment of emergency capability of coal mines based on AHP-fuzzycomprehensive method

296

Shu Jiao Tong, Zong Zhi Wu, Ru Jun Wang, Ying Quan Duo

Study on local temperature controlling technology and equipment in heatdisaster coal well

302

Haijun Wu, Haifei Yao, Changfu Xu, Haiyan Wang, Laizai Tan

Effect of forming technology on oxygen supply performance of oxygen
candles in refuge spaces

308

Liu Jian-guo, Jin Long-zhe, Gao Na, Wang Wei-xiang, Shen Jie

Experimentation on a new type of mining emergency rescue relay cabin

314

Shen Jie, Gao Na, Jin Long-zhe, Fan Lin-yu, Wang Wei-xiang, Liu Jian-guo

Chemical equipment failure probability correction model based on theMulti-layer Grey Evaluation Method

319

Yue Zhang, Wentao Yang, Yuanyue Zhu, Kai Zhang

Mechanisms and applications of formatting unsafe behaviour motivation

325

Yuebing Zhang, Zhiliang Wang

Examining safety and sustainability in longwall coal mining through casestudies of disasters and reviewing global trends in environmental stewardship329

Ben de Wit, Xinglong Zhao, Malcolm Scoble

Research on Safety Incentive Model of Coal Miners and Strategy Analysis

335

Cao Qinggui, Xie Changzhen, Zhang Shouming, Zhang Sai, Liu Weihua

A new Virtual Reality training system for underground coal mines

341

Hui Zhang, Xueqiu He, Baisheng Nie, Hani Mitri

iv

Study of roadside packing to go with gob-side entry retaining technology on
crisp surrounding and blasting face in the Xinzhuang mine

346

Ya-ge LI, Wei-xiang WANG, Long-zhe JIN, Shu WANG, Jiang LU

Optimization of bit nozzle parameters of reverse circulation sampling usedin coal mines

351

Kang Jianning, Hu Qianting, Zhang Rui

Electrical equipment certification in Canadian underground coalmines – problem solved?

358

Ronald (Ron) F. King, P.Eng., Peter Cain, Ph.D., P.Eng.

Improving shovel safety using SAFEmine’s situational awareness technology

364

Marco de Werk, Todd Ruff

An evaluation of Soma underground coal mine disaster with respect to risk
acceptance and risk perception

368

From operational hazards to organizational weaknesses: changing the focus
for improvement375

H. Şebnem Düzgün, Evren D. Yaylacı

Georges Loiselle, Dragan Komljenovic, Mustafa Kumral

Risk management in the mining sector through complex systems

381

Maria S. Q. Domingues, Adelina L. F. Baptista, Miguel T. Diogo

Application of Cognitive Task Analysis in mining operations

387

Serenay Demir, Elie Abou-Jaoude and Mustafa Kumral

Avoiding workplace accidents: the importance of pre-job safety analyses

393

Colin Morrish

Notification systems and risk management

398

Maria M. Antunes, Miguel T. Diogo, Joaquim Góis

Full-scale fire experiments in an underground mine

403

Rickard Hansen

Diesel exhaust exposures in an underground mine

409

Hugo Coulombe, Guillaume Lachapelle,
Eve Neesham-Grenon, Stéphane Hallé, Maximilien Debia

Liquid-solid coupling analysis of tailings dam under complex
engineering conditions

413

Shuren Wang, Haiqing Zhang, Zhengsheng Zou, Xiliang Liu

Numerical analysis of Westwood Mine tailings embankment stability
during the restoration phase

419

Yaya Coulibaly, Tikou Belem, Li Zhen Cheng

Application of an economy comparison model for mine cooling system technology

426

Miao Dejun, Chang Dehua, Tan Dongweiv

Behaviour of cable bolts in shear: experiment and mathematical modelling432

Naj Aziz, Ali Mirza, Haleh Rasekh, Jan Nemcik, Xuwei Li

Operating conditions of a mine fan under conditions of variable resistance

442

Zhang Yinghua, Chen Li, Huang Zhian, Gao Yukun

Analysis of slag debris flow initiation based on laboratory tests of slag

447

Hongbiao Zeng, Hongming Yu

Hydrogeological challenges and strategies at McArthur River Operation

453

Xiaoyou Yun, Baoyao Tang, Greg Murdock, Brian McGill, Brian Mattie

Experimental Study on Bolt Pull-Out Property Coupled by Plate and Shotcrete

459

Xiliang LIU, Jiaqi GUO, Long Wan, Jianhua Wang

Part 3Mathematical model for gas diffusion from non-homogeneous coal particles

465

Yanwei Liu, Mingju Liu, Hani S. Mitri

Permeability prediction for coal reservoirs and reconstruction of a different
scales pore-fractures network

471

Ni Xiaoming, Chen Wenxue, Li Zheyuan, Gao Xiang

Quantitative risk assessment on large-scale oil depots of opencast coal mine

477

Ru Jun Wang, Shu Jiao Tong

Development and realization of a coal and gas outburst simulation device

482

NIE Baisheng, HU Shoutao, LI Xiangchun, MENG Junqing, FAN Penghong

The distribution and origin of hydrogen sulfide abnormal enrichment
coal mines in China

487

Deng Qigen, Liu Mingju, Zhang Sai, Cui Xuefeng, Wen Jiejie

Accumulation pattern of groundwater containing Hydrogen Sulfide in thesouthern Junggar basin in China

494

Deng Qigen, Liu Mingju, Cui Xuefeng, Wen Jiejie

Application research on gas drainage technology at low permeability coal seam

498

Shengchu Huang, Li Zhang

Influence of temperature on gas desorption-diffusion laws of coal particles

503

Linchao Dai

Numerical simulation of gas migration tule in mining-induced fractures field

508

Cao Jie, Li Minghui, Li Wenpu

Methods of measuring the effective drainage radius of 3# coal seam in
Huoerxinhe coal mine

514

Linchao Dai, Kai Wang, Jie Cao, Bo Wang

Temperature Variation of Coal during the Gas Adsorption Process

520

vi

Tao Yang, Baisheng Nie, Xuexi Chen, Peng Chen

Statistical analysis of coal mine accidents in China from 2005-2013

527

Xinsheng Hu, Zongzhi Wu, Rujun Wang, Yingquan Duo

Analysis of coal crack and permeability characteristics slotted by water jet
and the effect on gas outburst

531

Chunming Shen, Baiquan Lin, Lang Zhang, Dong Wang

Numerical simulation on Gob gas migration law

536

He Ning, Xiang Cong

Research on the negative pressure distribution law and its application forboreholes in coal seam bedding gas extraction

540

Linchao Dai, Kai Wang

Mathematical simulation and experiment of CBM detection

547

LIANG Qing-hua

Numerical modelling and rescaled range analysis on spontaneous combustion
under surface methane drainage in a Chinese coal mine

552

Xincheng Hu, Shengqiang Yang, Wei Victor Liu, Jiawen Cai, Xiuhong Zhou

The strength properties of fibre glass dowels used for ground control in coal mines

557

Naj Aziz, Wenxue Chen, Ali Mirzaghorbanli, Jiao Yuzhao

Numerical simulation for propagation characteristics of outburst shock
wave and gas flow when outburst prevention facilities fail564

Zhou Aitao, Wang Kai, Kong Yuyu, Liu Ang

Influence of Fundamental Internal Parameters to Low-Temperature Critical
Temperature in Coal Self-Ignition Process

574

WANG Hai-yan, YAO Hai-fei, ZHENG Zhong-ya, XU Chang-fu,
ZHANG Qun, ZHU Hong-qing

Experimental study of negative pressure gas drainage influences oncoal moisture content

581

Shaojie Chen, Longzhe Jin, Xianglong Liu

The laws of gas-solid coupling of coal-bed gas in deep high gassy coal seams

585

Zhou Aitao, Wang Kai, Shen shangkun

Grey Correlation Model of influence factors analysis of ventilation time insingle-way tunnel

591

Yang Cao, Hongguang Ji

Numerical research on the airflow distribution in mine tunnels

595

Cui DING, Xueqiu HE, Baisheng NIE

Application of a Ventilation Management Program for improved air quality

600

Euler De Souzavii

Numerical Study of simultaneous methane and coal dust dispersion in aroom and pillar mining face

605

Yueze Lu, Saad Akhtar, Agus P. Sasmito, Jundika C. Kurnia

Reducing Heat Stress Exposure in Mines

611

Ryan Anderson, Euler De Souza

Effect of hydrogen on explosion of methane-air mixture

616

YANG Chunli, LI Xiangchun, Xu Teng, Qu Wenzhong, Liu Yanli

Drilling escape and rescue system in Wangjialing coal mine

622

Zhiling Huang, Longzhe Jin, Yuntong Ma, Hongmin Zhu

Effects of immediate roof thickness on lower sub key strata movement inends of large mining height panel

628

Chuang LIU, Huamin LI, Dongjie JIANG, Huigui LI, Junfa FENG

Study on the performances of a protective door in coal permanent refuge havens

634

Gao Na, Jin Long-zhe, Fan Lin-yu, Shen Jie, Wang Wei-xiang, Liu Jian-guo

Numerical modelling of the goaf: methodology and application

640

Samar S. Ahmed, Marwan ALHeib, Yann Gunzburger, Vincent Renaud, Jack-Pierre Piguet

A coal enterprise scientific-technical progress evaluation system basedon the Internet

647

Shanyang Wei, Longlong Yang, Zhongbei Li, Shiwei Ding

Simulation of strata behaviour laws of a coal mine in Jungar Coalfield

651

Zhu Bin, Li Ge, Kou Weifeng, Li Haibin

Goaf area exploration in Anjialing surface mine based on the C-ALS

658

WANG Jun, ZHOU You, ZHAO Ruhui

Application of the strength reduction method in coal mine roof support design

659

Gabriel Esterhuizen, Ihsan Berk Tulu

Numerical simulation of the migration laws of supports and surrounding rockfor coal seams of large dip angle

666

Huang Zhian, Feng Caiyun, Wang Hui, Zhang Yinghua, Gao Yukun

Theoretical analysis of support stability in large dip angle coal seam
mined with fully-mechanized top coal caving

672

Zhang Yinghua, Ji Yucheng, Huang Zhian, Gao Yukun, Ji Yuchen

Theoretical research on roof damage of the fully mechanized top-caving
mining coal seam with deep dip angle

677

ZHANG Ying-hua, LUO Qiang, HUANG Zhi-an, GAO Yu-kun

Characteristics of acoustic wave velocity variation in the process ofdeformation and failure of loading coal681

LI Xiangchun, NIE Baisheng, YANG Chunli, CUI Zhe, MAO Yanjun

viiiNumerical Simulation Technique for Gateroad Stability Analysis under Fractured
Ground Condition

687

Lishuai Jiang, Atsushi Sainoki, Hani S.Mitri, Nianjie Ma

Author Index

692

ix

ORGANIZING COMMITTEE
Xueqiu HE – International Chair
University of Science and Technology Beijing
Xiaolin YANG – International Chair
Henan Polytechnic University
Hani S. MITRI – General Chair
McGill University
Baisheng NIE – Technical Program Co-chair
China University of Mining and Technology Beijing
Mustafa KUMRAL – Technical Program Co-chair
McGill University
Agus SASMITO – Technical Program Stream Chair
McGill University
Longzhe JIN – Technical Program Committee
University of Science and Technology Beijing
Mingju LIU – Technical Program Committee
Henan Polytechnic University
Atsushi SAINOKI – Technical Program Stream Chair
McGill University
Shahe SHNORHOKIAN – ISMS Secretary
McGill University
Wenxue CHEN – ISMS Secretary
Henan Polytechnic University
Xiangchun LI – ISMS Secretary
China University of Mining and Technology Beijing
Na GAO – ISMS Secretary
University of Science and Technology Beijing
Monika SKONIECZNY – Tradeshow
McGill University
Isaac VENNES – Field Trips
McGill University
Andrew PYON – Workshop
McGill University
Hui ZHANG – Web site
China University of Mining and Technology Beijingx

INTERNATIONAL ADVISORY COMMITTEE AND EDITORIAL BOARD
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Marwan AL-HEIB
Victor ARAD
Naj AZIZ
Manoj BAGDE
Ming CAI
Euler DE SOUZA
José-Miguel GALERAYann GUNZBURGER
John HENNING
Guozhong HUANG
Vlad KECOJEVIC
Jun-ichi KODAMA
Petr KONICEK
Farid LAOUAFA
Xiliang LIU
Rudrajit MITRA
Jan NEMCIKVic PAKALNIS
Jack-Pierre PIGUET
Stanislaw PRUSEK
Jerry RAN
Mani Ram SAHARAN
Malcolm SCOBLE
Jean-Pierre TSHIBANGU
Yongqiang YU
Yinghua ZHANG

xi

PREFACE
The mining industry faces significant challenges associated with the extraction of deeper ore deposits having
increasingly more complex geotechnical and geological conditions. This inevitably led to much greater attention
to personnel and equipment safety research and practice. In addition to this development, safety science itself has
made remarkable progress in recent decades owing to leap advancements in engineering technologies, humanphysiology, data analysis and processing, as well as new business and organization structures. In this scope,mining, nuclear and aerospace industries allocate important resources and create initiatives to engage increasingly
more safety science and research. In line with this, McGill University organized and hosted the 3rd International
Symposium on Mine Safety Science and Engineering (ISMS 2016) in Montreal in collaboration with its partners,
the University of Science and Technology Beijing, China University of Mining and Technology (Beijing), andHenan Polytechnic University. The symposium was held from August 13 to 19, 2106 with the theme “Operational
and Environmental Mine Health and Safety Practice and Innovation”.
Essential objectives of ISMS 2016 were to discuss safety-related problems; to create awareness, synergy andrecognition to mine safety; and, to ensure knowledge transfer and mobilization amongst industry practitioners,
mining engineers and academics. The authors of the 119 papers in this volume of proceedings come from 12
countries – a testimony to the true international flavour of this symposium. The volume is organized in three main
sections: (i) Hardrock (Seismicity and rock burst, blasting, support design, pillar and backfill stability, groundcontrol, subsidence and slope stability); (ii) Technology (equipment, occupational health and safety, organizations
and human factors); and (iii) Coal (gas and ventilation, ground control and coal mining techniques). All papers
included in this set of proceedings have been peer-reviewed, edited and formatted to a uniform layout. The
proceedings can be found online at
http://isms2016.proceedings.mcgill.ca
We would like to thank all the symposium sponsors for their generous support. We are indebted to members of
the International Advisory Committee for their relentless efforts. Special thanks are due to the paper reviewers.
We sincerely hope that this volume of proceedings will be interest to mine safety practitioners, researchers andtechnology developers.

Editors
Hani S. Mitri
Shahe Shnorhokian
Mustafa Kumral
Agus Sasmito
Atsushi Sainoki

xiiPart 1

Hardrock

ISMS 2016

Paper No. 146

b-value as a criterion for the evaluation of rockburst hazard in coal mines
Grzegorz Mutke a, Aleksandra Pierzyna b, Adam Barański caDepartment of Geology and Geophysics, Central Mining Institute, Katowice, Poland, 40-166
Bobrek Mine, Polish Coal Company, Bytom, PolandcDepartment of Mining Hazard, Polish Coal Company, Katowice, 40-039b

ABSTRACT
Every year, a few rockbursts with fatalities and several hundred meters of damaged excavations have occurred in themines of the Upper Silesia Coal Basin (USCB) in Poland. This paper presents a method for assessing the levels ofseismic and rockburst hazards, using continuous seismological observation in the Bobrek coal mine. This
assessment is based on the study of the Gutenberg-Richter (G-R) relation for current and past mining in the coal
field. According to many laboratory and field studies, the b-value may be an indicator of fluctuations in stress levels(Scholz, 1968; Gibowicz, 1974; 1979), and the consequent seismic hazard.
The novelty of the presented research is the development of a quantitative criterion based on b-value changes,
calculated in moving time windows with a 1-day step, and the anomalies resulting from the comparisons of thetemporal values of b with its average value for the past seismicity in the field of coal mining; AG-R =[(bm –b)/bm]·100% (where bm is the average value of b for the field of coal mining and b is the temporal value ofcoefficient b, calculated in time windows). This approach allows us to standardize the criterion to the current valuesof b in the investigated area (Table 1). In many measurement examples, high values of the temporal anomaly AG-R
and at the same time downwardly trending and low b-values before the occurrence of strong mining seismic eventswere documented in this paper and in studies by Pierzyna (2014). Particularly interesting results were obtained frommining and geological conditions that led to the formation of local zones of stress concentration (Dubiński, 1989),
and increases in seismic activity and seismic hazard.
The b-value criterion is in agreement with the four basic levels of rockburst hazard used in Polish coal mines (Mutke
et al., 2015).
KEYWORDS: Mining induced seismicity; b-value; seismic criterion

1. INTRODUCTION
The Gutenberg-Richter Law (G-R) is the mostcommon model of a relation between the magnitudeand number of seismic events (Gutenberg andRichter, 1954; Utsu, 1999). It is well documented in
global earthquake seismology. Weak tremors aremuch more common than strong ones, and thefrequency-magnitude relation takes on a logarithmic
scale of the form log N (M) = a – b˖M, where N is thenumber of seismic events with magnitude equal to or
larger than magnitude M, M is the magnitude and a
and b are coefficients related to seismicity.
The coefficient b in this law is used globally instatistical seismology to characterize and compare thelevels of seismic activity in different areas of theearth’s crust (Utsu, 1999; Shearer, 2009). This factor
varies over time on regional or local scales(Gibowicz, 1974; 1979), and it reflects the change inthe level of stress around the average value.
Specifically, the b-value decreases prior to theoccurrence of strong earthquakes (high state of stress)
and increases after its occurrence (lower stress level
after relaxation).
Corresponding author – gmutke@gig.eu

Relatively few uses of this factor to characterize
the level of seismic and rockburst hazard inunderground coal mines can be found in the literature(Lasocki, 1990; Holub, 1995; Fritschen, 2009; Mutke
and Pierzyna, 2010; Pierzyna, 2014). The frequencymagnitude law works even down to magnitude -4.4 indeep mining (Kwiatek et al., 2011). Low b-values
imply that strong mining seismic events prevailed in
the studied set. In an assessment of rockburst hazard
in Poland, strong mining tremors located close to the
excavations and high stress level played fundamentalroles (Mutke et al., 2015).

2. METHODOLOGY
In this work, a systematic analysis of the b-value
and anomaly of the b-value, determined in time
windows, was correlated with observed seismicity intime and with the geological and mining conditions.
To calculate the b-value in the G-R Law,
applying the method of maximum likelihood has
been proposed (Aki, 1965; Utsu, 1965; 1999;
Marzocchi and Sandri, 2003):

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016b = (log e) / (Ma -Mmin)whereeis the base of natural logarithm, Ma
is the sampling average of the magnitudes, and Mminis the threshold of magnitude completeness.
The evaluation of its standard deviation in thisstudy was based on the formula derived by Shi and
Bolt (1982).
It should be emphasized that to calculate the bvalue, the selection of a set of tremors is made inaccordance with the principle of catalog
completeness. It is identified on the basis of
cumulative quantity histograms at magnitudeintervals and also on the basis of the technicalthreshold of the seismological network capabilities inrecording all seismic events.
The ongoing assessment of seismic hazard in LP
No. 3/503 (backward analysis) was made byanalyzing variations of the b-value, calculated in time
windows with a moving 1-day step. A 20-day
window was selected as optimal for the technologicalprocess (based on stationarity of the seismic process
in mines (Lasocki, 1990), and the number of seismic
events in a window of time (more than 30)). The
useful quantitative category classifications forseismic and rockburst hazard levels provide ananomaly of the b-value, defined as follows:
AG-R =[(bm – b)/bm]·100%
wherebis the temporal coefficient value,calculated in time windows, and bm is the averagevalue of b, determined for the entire catalog ofseismic events previously recorded in the field panelof coal mining.
A high anomaly of the b-value should correlatewith the preparation of the rock mass for theoccurrence of strong mining related seismic events.

the longwall panel was approximately 1000 m long,located 700 m below the ground surface. In total,(1)2996 seismic events were recorded with magnitudes
ranging from ML =0.1 to ML =3.8 (ML – local
magnitude calculated using the empirical formuladeveloped for Upper Silesia between seismic energy
and magnitude calculated from the body wave: log E= 1.8 + 1.9ˑML; (Dubiński and Wierzchowska, 1973))
The hypocenters of the strongest seismic events werelocated 300-800 m deeper than the level of the 503
coal seam (Marcak and Mutke, 2013).
Seismic monitoring in the “Bobrek-Centrum”
mine was performed with a 64-channel undergroundseismic network (Seismological Observation System(SOS) designed by the Central Mining Institute in
Katowice, Poland) consisting of 1 Hz velocity
DLM2001 and DLM3D type probes. SEISGRAM
and MULTILOK software were used to process andanalyze the seismic data. Seismic stations were
deployed underground as shown in Figure 1. The
locations of the 2,996 seismic events are also shownin Figure 1.
A method for evaluating the completeness ofseismic events during extraction of LP No. 3/503,
due to technical reasons, involves an assumption thatall seismic events will be triggered when the signal
on the nearest five sensors exceeds the seismic noiselevel by two times. In the case of the LP No. 3/503
contour, the most distant of the five seismic sensors(2)
is located at a distance of 700 m. In such conditions,
it is possible to obtain catalog completeness ofmining tremors of local magnitude ML=0.6 andhigher. For the whole area of the Bobrek Mine, theseismic catalog completeness begins from magnitude
ML=0.9.

3. MONITORING SEISMICITY IN PANEL
3/503 AT THE BOBREK MINE
The field measurements and study of the b-value
were performed in the Bobrek Mine, one of the deep
coal mines in USCB, Poland. The database used forback analysis in the Bobrek Mine included seismic
data as well as geological, mining, and technological
data for 5 longwall panels (LP). Studies of the bvalue were conducted for the seismicity during
extraction of the 503 coal seam by LP No. 2 and No.
3, of the 509 coal seam by LP No. 91a and No. 92a,and of the 510 coal seam by LP No. 6 (Mutke andPierzyna, 2010; Pierzyna, 2014). In this paper, weshow a study of LP 3/503 in detail, mined from April
2009 to June 2010. Coal seam 503 was 3.0 m thick,the excavation face was approximately 350 m, andFigure 1: Bobrek Mine field site – deployment of seismic
sensors around LP 3/503 (blue diamonds) and location of themining tremors hypocenters (circles). Color of the circle
indicates the size of the magnitude.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4. GUTENBERG-RICHTER RELATIONSFOR THE BOBREK MINE
4.1 The mean b-value for seismicity induced bymining in the Bobrek Mine in the years 1990-2013
The calculation of the frequency-magnituderelation at the Bobrek Mine was made for the seismic
events of magnitude ML ≥ 0.9 recorded during the
1990-2013 years. The seismic catalog included 15700
seismic events.
The results of the GR distribution for the Bobrek
Mine are illustrated in Figure 2. It is apparent that,for the higher magnitudes, i.e., in the range of 2-3.8,
a slight downward deviation of the empirical values
occurs from the theoretical straight line of the
Gutenberg-Richter law. The average b-value
amounted to bm=1.34 for the 23-year period ofmining and will be used as a reference for further
calculation of rockburst hazard in the Bobrek Mine.

Figure 2: The cumulative distribution of seismic events
above magnitude ML=0.9 registered in the Bobrek Mine in
the 1990-2013 years.

4.2 The changes in the b-value and anomaly of the bvalue during the extraction of coal in panel No. 3/503
The mining in LP No. 3/503 induced very highseismicity with magnitudes higher than ML=3.5. The
coefficient of b for this seismicity reached a value of0.99 and was 27% lower than the b-value obtained
for mining in the whole area of the Bobrek Mine in
the 1990-2013 years. This means that the mining in
LP No. 3/503 took place under potentially higher
seismic hazard than past mining in the Bobrek Mine.
The main reasons for the high level of seismic hazard
in LP No. 3/503 are due to mining in the axis of
Bytom through the zone where there is high tectonic
stress and in the local zones of stress concentration
resulting from past mining conditions (remnants,
edges).
The ongoing assessment of the seismic hazard
level in LP No. 3/503 was made by analyzing
fluctuations of the b-value calculated in 1-day time
windows. The 1-day moving variations of the b-value

and 6 strongest tremors during the extraction of coalin LP No. 3/510 are plotted in Figure 3. The
occurrence dates of these strong seismic events areindicated by arrows. The values of the b coefficientduring the strongest seismic events ranged from 0.55
up to 0.9 and were much lower than the averagevalue of bm=1.35 calculated for seismicity in the
Bobrek Mine.

Figure 3: The changes in the b-value of the GutenbergRichter law, calculated in a time window of 20 days with a
1-day moving step in LP No. 3/503 during the period ofApril 2009 – June 2010. The darker lines represent theerror bars calculated for every window’s data using theequation derived by Shi and Bolt (1982). The strongest
tremor of magnitude ML=3.7 occurred on 16.12.2009 while
the coefficient of b reached the lowest level.

They were also lower than the global averagevalues of the b factor for seismicity, adopted in theliterature as 1.0 for the world (Shearer, 2009). By
referring these values to bm, it can be found that theseismic anomaly ranged from 59% to 33%. The studyof LP 3/503 clearly indicates that strong mining
induced seismic events occurred when the observed
b-value level was low and the anomaly of b was veryhigh.
Particularly interesting results were obtained byDubiński (1989) for representative mining andgeological situations that led to the formation of local
zones of stress concentration and, as a consequence,an increase in seismic activity and seismic hazard. In
Figure 4, an example of mining conditions’ influenceon the distribution of the b-value is shown. The bvalues were calculated in moving windows of time
during the passage of LP No. 3/503 in the zone of
impact of the 501 coal seam edge, located 27 meters
higher. Lower values of b were obtained when theextracted face of LP No. 3/503 was on the unminedside of coal seam 501. During this time, the seismic
activities increased significantly. The GR seismic
anomaly reached a very high value, AG-R = 59%.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 4: The distribution of the b-values obtained during
the passage of the LP 3 coal face under the edge of the 501
coal seam.

5. CRITERION OF ROCKBURST HAZARD
IN THE BOBREK MINE
The novelty of the results of the researchpresented lies in the development of quantitative
criteria based on the analysis of the G-R distribution
in a moving time window with a 1-day step, taking
into account the anomalies of the b-value. Thisapproach allows us to standardize criterial values tothe temporal value of b calculated in time windows.
In many examples described in the paper, high valuesof the anomaly of coefficient b and downwardly
trending low b-values were documented before theoccurrence of the strongest tremors. The b-value
criterion corresponds to the four levels of rockburst
hazard used in Polish mines (Table 1). In cases when
the b-value criterion is used, it is easier to select andmonitor the effectiveness of prevention activities.
The primary prevention activities are based on theperformance of blasting and rock fracturing ahead of
the LP face line to induce stress relaxation in the areaof mining. Another preventive action was theselection of appropriate support in the zones withhigh seismic hazards.
Table 1: b-value empirical criterion of rockburst hazard in
the Bobrek coal mine.
Level of
Anomaly of bb-value
rockburst
value, %condition
hazardlack
AG-R < 0b > bmlow
25> AG-R ≥ 0b ≤ bmmedium50>AG-R ≥ 25b < bmhigh
AG-R ≥ 50
b < bm

6. DISCUSSION
The results indicate the usefulness of b-valuechanges in moving time windows and the anomaly
coefficient of b for evaluating the preparation of rockmass to induce strong seismic events in the Bobrek
Mine.

As a result of the work described in this article,
calculations were presented that led to theformulation of a local criterion for the ongoingassessment of seismic and rockburst hazards in the
Bobrek Mine. This quantitative criterion, using the bvalue and anomaly of b calculated in moving time
windows, is novel in the field of the assessment ofseismic and rockburst hazards in deep coal mines.
Documenting and analyzing the results ofobservations under the geological and mining
conditions that cause stress concentration areespecially important from the point of view of safe
mining. This study presents the results of calculated
distributions of b-values and anomaly of b for thefollowing typical and frequently encountered mining
situations and geological conditions:− mining within the impact of coal seam edges,− mining within the influence of remnants,− mining within the influence of the fault,− mining within the influence of tectonic
stresses throughout.
Good results can be obtained when several
indicators are used to assess the seismic hazard level(Mutke et al., 2015).

7. CONCLUSIONSThe use of the G-R law provides a reliableevaluation of potential areas of high seismicity inunderground coal mining. The assessment isperformed on the basis of estimating the b-value andits distribution for the current mining extent, using 1day moving time windows.
Seismicity in mines primarily depends on thegeological and mining conditions under which theoperation is conducted. Studies have shown effective
efforts to link changes of the b-value with various
geological and mining conditions prone to stressconcentration (e.g., edges of old exploitations,remnants, faults or other geological structures).
The novel result of this research lies in thedevelopment of a quantitative criterion of rockburst
hazard assessment in the Bobrek Mine, elaborated on
the basis of the b-value and on the anomaly of the bvalue.
High anomalies of the b, the low value of b and a
downward trend in b were documented before highseismic activity and the strongest seismic events. The
b-value criterion was developed in accordance withthe "complex criterion", which corresponds to thefour levels of rockburst hazard assessment and is oneof several seismological criteria used in Polish mines.
The diverse mechanisms of seismic events in deepmining require the use of various seismic indicators.
The method presented in this paper can be used
to assess seismic hazard in deep mines after4

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

verification of the quantitative level of the b-value
criterion. This should be done through analysis offormer seismic data due to the variety of geologicaland mining conditions, i.e., back analysis. It should
lead to improvement in the effectiveness of rockburst
prevention and increases in the safety of the miners.

8. REFERENCES
Aki K. (1965). Maximum likelihood estimate ofb in the formula log N = a – bM and its confidence
limits. Bull. Earthquake Res. Inst. Tokyo Univ., 43,
pp. 237-239.
Dubiński J. (1989). Sejsmiczna metoda
wyprzedzającej oceny zagrożenia wstrząsami
górniczymi w kopalniach węgla kamiennego. Prace
Naukowe GIG – seria dodatkowa. (The seismic
profiling in seam method to mining tremors hazard
assessment in coal mines. Scientific Work of GIG).(in
Polish)Dubiński J. and Wierzchowska Z. (1973).
Metody obliczeń energii wstrząsów górotworu na
Górnym Śląsku. Prace GIG – komunikat 591.
(Methods for calculation of seismic energy of mine
tremors in Upper Silesia). (in Polish).
Fritschen R. (2009). Mining-induced seismicity
in the Saarland, Germany. Pure and AppliedGeophysics 167, pp 77-89. DOI 10.1007/s00024009-0002-7.
Gibowicz S. J. (1974). Frequency-magnitude,
depth, and time relations for earthquakes in an island
arc: North Island, New Zealand, Tectonophysics 23,
p. 283.
Gibowicz S. J. (1979). Space and time variationsof the frequency-magnitude relation for mining
tremors in the Szombierki Coal Mine in the Upper
Silesia, Poland. Acta Geophys. Pol. 27, pp. 39-49.
Holub K. (1995). Analysis of b-value in the
freguency-energy distributions. Publs. Inst. Geophys.
Pol. Acad. Sc. M-19 (281), pp 153-162.
Kwiatek G., Plenkers K., Nakatani M., Yabe Y.,
DresenG.
(2011).
Frequency
Magnitude
characteristics down to magnitude -4.4 induced
seismicity recorded at Mponeng Gold Mine, South
Africa. Bull. Seism. Soc. Am, Vol.100. No. 3, pp.
1165-1173.
Lasocki S. (1990). Predykcja silnych wstrząsów
górniczych. Prediction of strong mining tremors.
Zesz. Nauk. AGH. ser. Geofizyka Stosowana nr. 7.
(1360), Kraków-AGH, 110 p.(in Polish)
Marzocchi W., Sandri L. (2003). A review and
new insights on the estimation of the b-value and its
uncertainty. Annals of Geophysics, vol. 46, No 6, pp.
1271-1282.
Mutke G. and Pierzyna A. (2010). Czasowe
zmiany parametru „b” relacji Gutenberga-Richtera
dla oceny zagrożenia sejsmicznego w ścianie 2 i 3 w

pokładzie 503 w kopalni „Bobrek-Centrum”.
(Temporary changes the b-value of GutenbergRichter relationship to the assessment of seismic
hazard in the longwall panels No. 2 and No. 3 in coalseam No. 503 in the mine "Bobrek-Centrum"). Prace
Naukowe GIG. Górnictwo i Środowisko. Kwartalnik
Nr 4/3/2010, pp. 298-309. (in Polish)
Marcak H. and Mutke G. (2013). Seismic
activation of tectonic stresses by mining. Journal of
Seismology. Vol. 17/4, pp.1139-1148. DOI
10.1007/s10950-013-9382-3.
Mutke G., Dubiński J., Lurka A. (2015). New
criteria to assess seismic and rock burst hazard incoal mines. Archive of Mining Sciences, Vol.60,
No.3., pp. 743-760. DOI: 10.1515/amsc-2015-0049.
Electronic version: ftp://mining.archives.pl.
Pierzyna A. (2014). Ocena stanu zagrożenia
wstrząsami górniczymi z wykorzystaniem relacji
Gutenberga-Richtera (Assessment of the State of
Mining Tremors Hazard Using the GutenbergRichter Relationship). PhD Thesis. (in Polish)
Scholz C. (1968). The frequency-magnituderelation of microfracturing in rock and its relation toearthquakes. Bull. Seism. Soc. Am. 58, pp. 399-415.
Shearer P.M. (2009) Introduction to seismology.
Cambridge University Press. 396p. ISBN 978-0-52170842-5.
Shi Y. and Bolt B. A. (1982) The standard errorof the magnitude-frequency b-value, Bull. Seismol.
Soc. Am., 72, pp. 1677– 1687.
Stec K. (2007). Characteristic of seismic activityof the Upper Silesian Coal Basin in Poland.
Geophysical Journal International ,168, pp. 757-768.
Utsu T. (1965). A metod for determining thevalue of b In formula log N = a – bM, schowing themagnitude-frequency relation for earthquakes.
Geophys. Bull. Hokkaido Univ. 13.
Utsu T. (1999). Representation and Analysis of
the earthquake size distribution: a historical review
and some new approaches. Pure and AppliedGeophysics. No. 155, pp. 509-535.

5

ISMS 2016

Paper No. 180

Quantitative evaluation of stope damage induced by seismic waves
Atsushi Sainoki *, Hani S. Mitri
Department of Mining and Materials Engineering, McGill University, Montreal, Canada, H3A 0E8

ABSTRACTIn the present study, a methodology to evaluate damage around underground openings due to seismic waves arisingfrom mining-induced fault-slip is proposed. First, expressions for an associated flow rule with a failure criterion
developed for biaxial stress conditions are derived, which are newly implemented into FLAC3D code. With thecode, stope extraction is simulated using a 3D mine-wide model encompassing a fault running parallel to a steeply
dipping orebody. The failure criterion for biaxial stress conditions is applied to only the rockmass in the vicinity ofstopes within the hanging wall. After extracting stopes in the orebody, mining-induced fault-slip is simulated indynamic conditions, considering its trigger mechanism, i.e., stress drop caused by instantaneous shearing of fault
surface asperities, using Barton’s shear strength model. Damage to the rockmass caused by seismic waves is thenevaluated with the increase in plastic strain. The proposed methodology takes into account the mechanism ofmining-induced fault-slip, propagation of seismic waves, biaxial stress conditions on the surface of openings, andplastic strain as damage criterion.
KEYWORDS: stability of mine opening; mining-induced fault-slip; seismic waves; biaxial stress condition

1. INTRODUCTION
Stress redistribution caused by mining activities,
such as stope extraction, can lead to the reactivationof pre-existing faults. As a result, fault-slip can occur,
producing seismic waves. When the seismic waves
hit underground openings, rockbursts could takeplace. Thus, in order to ensure a safe working
environment and stable production, it is paramount tounderstand the mechanism of mining-induced faultslip and elucidate the relation between the seismic
waves and the damage to mine openings.
It is common that the numerical modelling ofmining-induced fault-slip is conducted with theconventional Mohr-Coulomb failure criterion in static
conditions (Hofmann and Scheepers, 2011).
Importantly, the method does not replicate the actual
mechanism of mining-induced fault-slip. In reality,
the surface of faults in underground mines isundulating and has asperities that interlock with eachother. Instantaneous stress drop caused by theshearing of such asperities, which is related to theoccurrence of mining-induced fault-slip, cannot be
accurately modelled with the conventional method.
Furthermore, the numerical analysis in static
conditions is incapable of producing seismic waves
arising from fault-slip; hence it is impossible toevaluate damage to nearby mine openings inflictedby the seismic waves.
Recently, Sainoki and Mitri (2014a) havedeveloped the methodology to simulate mininginduced fault-slip with Barton’s shear strength model(Barton, 1973) in dynamic conditions, considering

the stress drop induced by asperity shear. The
methodology is capable of modelling mining-induced
fault-slip in a more robust way than the use of theMohr-Coulomb failure criterion. Furthermore, as theanalysis is performed in dynamic conditions, thepropagation of seismic waves can be simulated.
Although a number of studies have been undertaken
about the effect of seismic waves on the stability ofan underground opening, studies especially focusedon the effect of seismic waves arising from mininginduced fault-slip have not been undertaken
sufficiently. Recently, Wang and Cai (2015) examine
the effect of seismic waves on an excavation whileconsidering a point source of a fault-slip event, but
the magnitude of fault-slip is an input parameter, thatis, it fails to estimate damage induced by fault-slip
that could take place under the ambient stress state.
Another important aspect to be considered is thata failure criterion around an opening where stressstate is biaxial. It has been demonstrated that theconsideration to the intermediate stress is required(Yun et al., 2010) in order to predict the failure ofrock under biaxial stress conditions, where spalling
resulting from extension fractures is expected(Diederichs, 2007). Due to the difficulty ofconsidering or implementing failure criteria for suchbiaxial stress conditions, to the author’s knowledge,
such failure criteria have never been applied in the
numerical modelling of underground openings.
In light of a literature review, the present study is
focused on estimating the damage around anunderground opening induced by seismic waves*Corresponding author – email: atsushi.sainoki@mail.mcgill.ca

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

arising from mining-induced fault-slip whilst
considering the failure of rockmass under biaxial
stress conditions. The fault-slip is modelled in staticand dynamic conditions whilst considering theasperity shear as its source mechanism, and damage
induced by the seismic waves to a stope in a deep
hard rock mine is evaluated whilst taking into
account the failure under biaxial stress conditions.

2.2 Failure criterion under biaxial stress state and its
implementation to FLAC3D
Yun et al. (2010) perform biaxial tests for several
types of rock and establish a failure criterion under
biaxial stress conditions, which are the stressconditions that take place on the surface ofunderground openings. The failure criterion isexpressed as follows:

2. METHODOLOGY

σ 
σ1
σ
= A + B 2 + C  2 
σc
σc
σc 

2.1 Constitutive model for fault
As discussed in the introduction, the effect of
fault surface asperities is taken into consideration
with the Barton’s shear strength model (Barton
1973), which is expressed as follows: JCS  + φb  σn 

τ max = σ n tan  JRC log10 (1)where τmax and σn are the maximum shear strengthand the normal stress acting on a fault; and JRC, JCS
and φ are joint roughness coefficient, joint wallcompressive
strength,andfrictionangle,
respectively. Comparison of Barton’s shear strength
model with the classical Mohr-Coulomb model isshown in Figure 1. As can be seen in the figure, theshear strength calculated from Barton’s model isinvariably greater than that from the Mohr-Coulomb
model.
Barton’s shear strength model is implemented
into the ubiquitous joint model of FLAC3D (Itasca,2009). The implementation procedure is based on theplastic flow rule, i.e., the increment of plastic strain isdetermined with the derivative of potential function
with respect to its stress components and a scalarvariable derived from the consistency condition. The
detailed procedure of the implementation is provided
in Sainoki and Mitri (2014a). In order to simulate
fault-slip triggered by the shearing of fault surface
asperities, JRC is instantaneously decreased during a
dynamic analysis, which is described in more detaillater.

2(2)

where σ1, σ2 and σc are the maximum compressive
stress, intermediate stress and uniaxial compressive
strength (UCS), respectively; and A, B, and C are
material constants. In order to implement theequation as a yield criterion into FLAC3D,
compression needs to be defined as a negative
quantity and the equation is multiplied by UCS,
consequently giving the following equation:(σ )2F = σ 1 + Aσ c − Bσ 2 + C 2(3)
σcNote that compression has a negative quantity inEquation (3). Following the same procedure shown in
Sainoki and Mitri (2014a), the scalar variable that
determines plastic strain increments is expressed asfollows:
λ={∂F / ∂σ}T [D]{∆ε}{∂F / ∂σ}T [D]{∂g / ∂σ}(4)where [D] is an elastic matrix that relates strain withstress, and ∆ε is a strain increment vector. In thepresent study, an associated flow rule is assumed.
The derivatives of the yield function with respect toeach stress component are as follows:
∂F
=1
∂σ 1

(5)

σ
∂F
= − B + 2C 2
σc
∂σ 2

(6)

∂F
=0
∂σ 3

(7)

Then, the increments of plastic strain follow theplastic flow rule as follows:{∆ε }= λ  ∂∂(gσ )
p





(8)

where ∆εp is a plastic strain increment vector, and gis plastic potential. As the plastic strain increments do
not contribute to the stress increments, the stresscorrection to be made at each step during the iterative
analysis of FLAC 3D is expressed as follows:{∆σ} = −λ [D] ∂g 
 ∂ (σ ) Figure 1: Barton’s shear strength model.

(9)

Figure 2 shows the failure criterion of granite
under biaxial stress conditions derived from
regression analysis (Yun et al. 2010). The material

7

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

constants, A, B, and C in Equation (3) are 0.998,
1.873, and -1.533, respectively. The present study
uses the material constant of granite, although therock type to which the failure criterion is applied isnorite. Both norite and granite are hard rocks.

orebody induces regional stress re-distribution thateventually triggers fault-slip, such long stope strike
length is adopted rather than extracting numerous
stopes on each level. Note that the stopes arebackfilled immediately after the extraction.

Figure 2: Failure criterion of granite under biaxial stressconditions.

2.3 Numerical model description
The present study focuses on an undergroundmine with a fault running parallel to a steeply
dipping, tabular orebody. Such tabular orebodies are
frequently encountered in hard rock mines in Canada
and are extracted with sublevel stoping methods(Zhang and Mitri, 2008). Figure 3 depicts anumerical model encompassing such geologicalstructures. As can be seen in the figure, the height,
width, and length of the model are 300 m, 332 m, and
300 m, respectively. The dimensions are basically thesame as that analyzed by Sainoki and Mitri (2014a),
who determined that the effect of the externalboundaries on the stress state around the orebody andthe fault is negligible. The fault runs parallel to theorebody and steeply dips at 80˚. Dense meshes are
generated near the orebody and the fault in order tosimulate stress re-distribution caused by mining
activities as accurately as possible, while meshdensity decreases towards the model outerboundaries. The total numbers of zones and grid
points in the model are 215040 and 230643,
respectively.
Stopes are modelled in the orebody and extracted
according to the mining sequence as per sublevelstoping method with delayed backfill. Figure 4 shows
stope dimensions and the mining sequence. It can beseen from the figure that each sublevel contains two
stopes. In total, 18 stopes are designed. The mining
sequence starts from the bottom and proceeds
upwards. For each sublevel, the stopes on the
hanging wall side are extracted first. As for
dimensions of the stopes, the height is 30 m and thestrike length is 200 m as shown in Figure 4(a) and(b), respectively. As a large amount of extraction of

Figure 3: Isometric view of numerical model analyzed
encompassing a fault running parallel to the orebody.

Figure 4: Stopes modelled within the orebody and mining
sequence as per sublevel stoping method: (a) cross-section,(b) plan view at z = 150 m.

2.4 Analysis procedure
First, static analyses are performed, in which thestopes in the orebody are extracted and backfilled inaccordance with the mining sequence after simulating
in-situ stress state. The stope extraction is continued

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

until Stope7L, at which point the fault is adequately
unclamped, consequently increasing potential for
fault-slip sufficiently as shown in the study (Sainoki
and Mitri, 2014b). Subsequently, based on the stressstate after extracting stope7L, dynamic analysis isconducted. At the beginning of the dynamic analysis,
the boundary condition is changed to viscous in orderto prevent seismic waves arising from fault-slip fromreflecting on the boundaries. At the same time, thestress state on the fault is examined, and then for thearea where plastic shear movements are taking place
along the fault, the JRC and friction angle of the fault
are decreased, thereby inducing an instantaneousstress drop that drives fault-slip. The decrease in JRC
represents shearing of fault surface asperities, while
the reduction in friction angle denotes the transition
from static to kinetic friction. At each step during the
dynamic analysis, the stress state on the fault ischecked and the change in the mechanical properties
is performed if the conditions are satisfied. In thisway, fault-slip is driven during the dynamic analysis.
Model construction

According to the study, rock types for the hanging
wall, orebody, and footwall are rhyolite tuff, massive
sulphide, and rhyolite, respectively, and themechanical properties estimated from laboratory
experiments are converted to those for rockmasses
with the rockmass rating system proposed by(Bieniawski, 1989). Table 1 lists deformation
modulus, E, cohesive strength, C, friction angle, φ,unit weight, γ, tensile strength, σT, and dilation angle,
ψ. Note that the tensile strength is assumed to be onetenth of the uniaxial compressive strength calculated
from the cohesion and friction angle (Tesarik et al.,2003) and the dilation angle is assumed to be onefourth of the friction angle (Hoek and Brown, 1997)
except that for the backfill (Traina, 1983).
Table 1: Mechanical properties of rockmass and backfill.
Hanging
Ore
FootwallBackfillwall
E (GPa)
31
115
49
2.5
C(MPa)
2.6
11.5
4.3
0.1
38
48
39
35
φ (˚)
γ (kN/m3)
25.5
25.5
25.5
23.0
σT (MPa)
1.1
5.9
1.8
0.3
9.3
12.0
9.5
0.0
ψ (˚
)

Apply mechanical properties
and simulate initial stress

The mechanical properties of the fault that are
applied to the ubiquitous joint model are listed inTable 2. The modulus of elasticity is set to one-tenththat of the hanging wall. According to Barton andChoubey (1977), basic friction angles of typical rocks
range from 21˚ to 38˚. The adopted value is anintermediate value of the range. Likewise, typically,
JRC ranges from 0 to 20 (Barton, 1973), thus giving
the intermediate value of 10. Regarding the dynamic
friction angle, φd, the same value as that used by
Sainoki and Mitri (2014a) is applied. It should be
noted that the dynamic friction angle is applied tozones where the shear stress acting on the fault
reaches the maximum shear strength during the
dynamic analysis.

Extract and backfill stopes
in static conditions

After extracting stope7L,
boundary conditions arechanged to viscousStress state on the fault is
examined.

For the zones where shear failure
is taking place, JRC and ϕ isdecreased.

Table 2: Mechanical properties of a fault.
E (GPa)JRC
φ (˚)φd (˚)

Dynamic analysis

3.1

No
t >tmax?

30

10

15

γ
(kN/m3)25.5

t = t + dt
Yes

End

Figure 5: Analysis procedure for static and dynamic
analyses.

2.5 Mechanical properties of rockmass and fault
Mechanical properties of the rockmasses arederived from the case study (Henning, 1998).

Regarding the material constants in Equation (2),the influence of geological conditions is taken into
account with RMR (Bieniawski, 1989). Specifically,
the equation proposed by Mirti (1994) is applied to B
and C. As a result, the two parameters, B, and C, aredecreased to 0.79, and -0.65, respectively. Regarding
parameter A, it remains the same because UCS in theequation is directly decreased with the Hoek-Brown
parameter s (Hoek and Brown, 1997).

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3. RESULTS AND DISCUSSION
Figure 6 shows the particle velocity (PV) of grid
points during the dynamic analysis in the sectionalview at y = 150 m as well as the extent of fault-slipon the fault 0.4 s after the onset of the analysis. Notethat the white-colored region in the figure is Stope7L.
The propagation of seismic waves arising from thefault-slip can be clearly seen from the figure. Figure6(a) shows PV after 0.01 s. It is found that extremely
high PV exceeding 1 m/s takes place in the vicinityof the fault. As time goes by, regions with relatively
high PV move away from the fault, indicating the
propagation of seismic waves. After 0.04 s, groundmotion occurs in extensive regions as a result of the
wave propagation. At the same time, the maximum
PV in the section decreases to 0.5 m due to wave
attenuation. Note that the present study adopts the
local damping system embedded in FLAC3D,
assuming a local damping coefficient of 5 %.
Comparison of PV amongst the different stages
suggests that the most intensive PV takes place near
the stope after 0.02 s. Afterwards, the magnitude of
PV near the stope continuously decreases due to thewave attenuation and propagation. Thus, the damage
induced by the seismic waves is evaluated at thestage, i.e., 0.02 s after the onset of dynamic analysis.

Figure 8 shows damage induced solely by theseismic waves arising from fault-slip, i.e., damage
due to the plastic strain induced by the extraction ofstope is subtracted. It is interesting that damage does
not increase uniformly in the region between thestope and the fault. For instance, a noticeable
increase in damage can be observed within thefollowing three locations: backfill under the stope,
the hanging wall, and the upper part of the stope.
Detailed discussion on the reason why thediscrepancy in damage occurs is not made in thepresent study, but it is speculated that theconcentration of damage is attributed to the state ofstress before the fault-slip takes place and PV at the
moment when the damage is computed. Hence, thedistribution of damage might change at some degree
if the damage is computed at different elapsed time.
Note that emphasis should be placed on thedeveloped methodology to evaluate damage induced
by seismic waves quantitatively that considers themechanism of mining-induced fault-slip.

Figure 7: Schematic illustration to show damage
calculation.

Figure 6: Particle velocity (PV) in the sectional view of themodel at y = 150 m: (a) 0.01 s after the onset of the
dynamic analysis, (b) 0.02 s, (c) 0.04 s, and (d) extent offault-slip on the fault after 0.04 s.

In the present study, damage to the rockmasses isevaluated with the ratio of plastic strain to elasticstrain as shown in Figure 7. The quantity or its
variations are widely employed to evaluate damage.
For instance, its inverse is used as the elastic damage
model (Zhu et al., 2014).

Figure 8: Damage induced by seismic waves.

4. CONCLUSIONS

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The present study proposes a methodology toevaluate damage induced by seismic waves arisingfrom fault-slip. In order to replicate the actual
mechanism of mining-induced fault-slip, the effect of
fault surface asperities is taken into account, whereby
fault-slip is driven in dynamic conditions by an
instantaneous stress drop due to the shearing of theasperities. The dynamic analysis enables theobservation of the propagation of seismic waves, i.e.,
particle velocity, at given elapsed time after the onset
of fault-slip. A methodology to evaluate damage
induced by the seismic waves is proposed. It is thendemonstrated that damage does not distribute
uniformly around the stope. The proposed
methodology helps to identify locations where
noticeable damage takes place and to estimate theseverity of the damage.
5.

ACKNOWLEDGEMENT

This work is financially supported by a grant by
the Natural Science and Engineering ResearchCouncil of Canada (NSERC) in partnership with ValeLtd – Sudbury Operations, Canada, under the
Collaborative Research and Development Program.
The authors are grateful for their support.
6.

REFERENCES

Barton, N. (1973). Review of a new shearstrength criterion for rock joints Engineering
Geology, Volume 7, pp. 287-332
Barton, N., & Choubey, V. (1977). The shear
strength of rock joints in theory and practice. RockMechanics, Volume 10, pp. 1-54
Bieniawski, Z. T. (1989). Engineering rock massclassifications. New York: Wiley.
Diederichs, M.S. (2007). The 2003 Canadian
Geotechnical Colloquium: Mechanistic interpretationand practical application of damage and spalling
prediction criteria for deep tunnelling. Canadian
Geotechnial Journal, Volume 44, pp. 1082-1116.
Henning, J. (1998). Ground control strategies atthe bousquet 2 mine. (Master), McGill University,
Montreal, QC, Canada.
Hoek, E. (2007). Practical rock engineering.
Hoek, E., & Brown, E.T. (1997). Practicalestimates of rock mass strength. International Journalof Rock Mechanics and Mining Science, Volume 34,
No. 8, pp. 1165-1186.
Hofmann, G.F., & Scheepers, L.J. (2011).
Simulating fault slip areas of mining induced seismic
tremors using static boundary element numericalmodelling. Mining Technology, Volume 120, No. 1,
pp. 53-64.
Itasca. (2009). FLAC3D - fast Lagrangian
analysis of continua (Version 4.0). U.S.A.: Itasca
Consulting Group Inc.

Mitri, H.S., Edrissi, R., & Henning, J. (1994).
Finite element modelling of cable-bolted stopes in
hardrock ground mines. Paper presented at the SME
Annual Meeting, Albuquerque, New Mexico.
Sainoki, A., & Mitri, H.S. (2014a). Dynamic
modelling of fault slip with Barton's shear strength
model. International Journal of Rock Mechanics andMining Science, Volume 67, pp. 155-163
Sainoki, A., & Mitri, H. (2014b). Evaluation of
fault-slip potential due to shearing of fault asperities.
Canadian Geotechnial Journal, Volume 52, No. 10,
pp. 1417-1425.
Tesarik, D.R., Seymour, J.B., & Yanske, T.R.
(2003). Post-failure behaviour of two mine pillars
confined with backfill. International Journal of RockMechanics and Mining Science, Volume 40, No. 2,
pp. 221.
Traina, L.A. (1983). Experimental stress-strain
behaviour of a low strength concrete under multiaxial
states of stress. Kirtland Air Force Base, NM: Air
Force Weapons Laboratory.
Wang, X., & Cai, M. (2015). Influence of
wavelength-to-excavation span ratio on groundmotion around deep underground excavation.
Tunnelling and Underground Space Technology,
Volume 49, pp. 438-453.
Yun, X., Mitri, H.S., Yang, X., & Wang, Y.
(2010). Experimental investigation into biaxial
compressive strength of granite. International Journalof Rock Mechanics and Mining Science, Volume 47,
pp. 334-341.
Zhang, Y., & Mitri, H. (2008). Elastoplastic
stability analysis of mine haulage drift in the vicinityof mined stopes. International Journal of RockMechanics and Mining Science, Volume 45, pp. 574593.
Zhu, W.C., Wei, C.H., Li, S., Wei, J., & Zhang,
M.S. (2013). Numerical modeling on destressblasting in coal seam for enhancing gas drainage.
International Journal of Rock Mechanics and Mining
Science, Volume 59, pp. 179-190.

11

ISMS 2016

Paper No. 176
Influence of weak planes on rockburst occurrence
Amin Manouchehrian, Ming Cai *Bharti School of Engineering, Laurentian University, Sudbury, Canada, P3E 2C6MIRARCO, Laurentian University, 935 Ramsey Lake Road, Sudbury, Canada P3E 2C6State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academyof Sciences, Wuhan, 430071, China

ABSTRACT
Geological structures such as faults, joints, and dykes have been observed near excavation boundaries in many
rockburst case histories. In this paper, the role of weak planes around tunnels in rockburst occurrence was studied.
The Abaqus-Explicit code was used to simulate dynamic rock failure in deep tunnels. Firstly, the tool’s usefulness
for modelling geomaterials was improved by introducing material heterogeneity using Python scripting. The
modelling results showed that heterogeneous models resulted in more realistic failure modes than homogeneousmodels. Secondly, rock failure near the excavation boundary of a tunnel without any adjacent geological structure
was modelled and released kinetic energy from rock due to failure and velocity of failed elements at the tunnel wall
were calculated. Then, a weak plane was added to the model. This resulted in more released kinetic energy andhigher element velocity, indicating that rock failure became more violent in the models with weak planes. The
modelling results confirm that the presence of geological structures in the vicinity of deep excavations is a necessary
condition for the occurrence of rockburst. It can be used to explain localized rockburst occurrence in civil tunnels
and mining drifts. The methodology for rockburst analysis presented in this paper can be useful for rockburst
anticipation and control during mining and tunneling in highly stressed grounds.
KEYWORDS: Numerical simulation; excavation; heterogeneity; weak plane; rockburst

1. INTRODUCTION
Rockburst is an unstable and violent rock failure,and one of the most hazardous problems in deep
mines and civil tunnels. Rockburst is associated with
rapid ejection of broken rocks and is accompanied bya large amount of energy release (Hedley et al., 1992;
Andrieux et al., 2013). The rockburst problem
increases as mining activities progress to deeper
grounds. Some efforts have been made to understandwhy rockburst happens, to anticipate where it will
happen, and to predict how large a rockburst event
will be. Having this knowledge would be valuable forrock support design.
Rockburst case histories reveal that rockburst
damage locations are not uniform. In the other words,
damage extent in a tunnel caused by a rockburst
varies at different locations. The localized rockburst
phenomenon originates from the complex mechanismthat drives rockburst and the contribution of different
factors on rockburst occurrence. Many factors that
influence rockburst damage have been identified(Kaiser and Cai, 2012) but no one knows the exact
conditions for the occurrence of a rockburst in acomplex underground setting. Studies havedocumented the presence of geological structures
such as faults, shears, and dykes in vicinity of
rockburst locations (Hedley et al., 1992); however,*Corresponding author – email : mcai@laurentian.ca

their role in rockburst occurrence and damage is notwell understood.
Numerical models have been used to simulate
unstable rock failure in laboratory tests (Kias andOzbay 2013; Manouchehrian and Cai, 2016) andunderground openings (Jiang et al., 2010; Gu andOzbay 2015). A missing factor in the previous
numerical works is the influence of geologicalstructures on rockburst occurrence and damage. In
this paper, the influence of weak planes (e.g. faults
and shears) on rockburst occurrence and damagearound underground openings is investigated using
Finite Element Method (FEM).

2. ROCK FAILURE SIMULATION USINGABAQUS
Unstable rock failure is a dynamic phenomenon
and should be treated as a nonlinear dynamic
problem. Studies have shown that the explicit
numerical method is more suitable than the implicit
numerical method for solving nonlinear dynamic
problems because the problem of convergence iseliminated. Abaqus is a FEM-based numerical tool
which is equipped with implicit and explicit solvers,
making it applicable for solving a large variety ofphysical and engineering problems (Dassault System,2010). Manouchehrian and Cai (2016) simulated

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

uniaxial and poly-axial compression tests using the
Abaqus-Explicit tool and demonstrated the suitabilityof the tool for simulating unstable or dynamic rock
failure. In this study, this tool is used to simulate
rockburst in deep tunnels.
Despite Abaqus’s capability for simulating alarge variety of engineering problems, its applicationin the geomechanical field is limited. A key
characteristicofgeomaterials
ismaterial
heterogeneity, which cannot be readily modelled in
Abaqus through GUI. Fortunately, Abaqus provides
windows for adding and improving its capability
using scripting and programming. Hence, formodelling rock-like materials, it is possible tointroduce material heterogeneity into the models to
produce more realistic results. In this section, asimulation of rock failure processes in compression
using homogeneous material models is presented
first, followed by an introduction of material
heterogeneity into Abaqus models and a simulationof rock failure processes in compression using
heterogeneous material models.
2.1 Homogeneous model
To study the failure mechanism using Abaqus,
the laboratory tested mechanical properties of T2b
marble (Table 1) are used as the base case. T2b
marble is the host rock of the diversion tunnels at the
Jinping II hydropower station in China (Zhang et al.,2012).
Unconfined and confined compression tests are
simulated to investigate the failure mechanism ofhomogeneous rocks. An elasto-plastic MohrCoulomb strain-softening model with homogeneousmaterial properties is used to model the strength
behaviour of the T2b marble. Table 2 presents thecalibrated parameters for defining the strain-softening
behaviour of the rock in the homogeneous model. A
rectangular specimen with a height of 250 mm and awidth of 100 mm is used for the simulation. In theunconfined compression test simulation, one end of
the specimen is fixed in the maximum stress direction
and the other direction is free (roller constraint) and aconstant velocity of 0.03 m.s-1 is applied directly tothe other end to load the specimen. The same end
boundary conditions are applied to the specimens in
the confined compression test simulation and theconfinements applied are 5, 10, 20, and 40 MPa. In
the developed homogeneous model, a uniaxial
compressive strength (UCS) of 113.6 MPa, a friction
angle of 30°, and a cohesion of 32.9 MPa arecalculated, which are similar to the reported
laboratory test data (Table 1).
Figure 1b shows the failure pattern in thehomogeneous models indicated by the maximum
principal plastic strain. The figure shows that

confinement does not affect the failure pattern in thehomogeneous model because all of them show
distinct shear failure. Despite that the mechanicalparameters of the T2b marble are captured by thehomogeneous model, it fails to capture the splitting
failure under low confinement.
Table 1: Physical and mechanical properties of the T2b
marble (Zhang et al., 2014).
Parameter
Value
Density, ρ (kg.m-3)
2780
Young's modulus, E (GPa)55
Poisson's ratio, ν
0.27
Uniaxial compressive strength, UCS (MPa)110.7*
Cohesion, c (MPa)32.6
29
Friction angle, φ (°)* UCS of the T2b marble was reported between 100 and 160 MPa
in (Zhang et al., 2014). This value was calculated according to2𝑐.𝑐𝑜𝑠𝜑𝑈𝐶𝑆 =for the present study.
(1−𝑠𝑖𝑛𝜑)

Table 2: Strain-softening parameters of the homogeneousmodel.
Cohesion
Tension cut-off
Cohesion
Shear
Tension cutTensile
yield stressplastic
off stressplastic strain(MPa)strain
(MPa)
32.2
0
5.5
0
0.01
0.2
0.1
0.001

2.2 Heterogeneous model
In order to introduce heterogeneity into models,the material properties of each element are assigned
randomly following normal distribution functions.
The introduction of material heterogeneity cannot be
conducted using the GUI and Python scripting isneeded.
The developed Python script assigns randomly
distributed material properties of E, c, and φ to theelements and the properties follow normal
distribution functions. One example of execution of
the developed technique to simulate a rectangularmodel with 4000 elements and 100 materials ispresented in Figure 2 (each color represents one
material). In this figure, μ and σ are the averages andthe standard deviations of each parameter (E, c, andφ).
Heterogeneous model is used to simulate themechanical properties of the T2b marble (Table 1). A
UCS of 113.5 MPa, a friction angle of 29.7° and acohesion of 32.7 MPa are estimated for theheterogeneous model, which are similar to thelaboratory test results.
Figure 1a shows photographs of the failed T2b
marble specimens in laboratory tests (Zhang et al.,2014) and Figure 1c presents snapshots of the plasticstrain obtained by the numerical models. It is seenthat in the heterogeneous model, the failure modes

13

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016change from splitting failure at zero confinement toshear failure at high confinements. The homogeneousmaterial models cannot capture axial splitting at zeroconfinement but the heterogeneous material model
successfully captures this failure mode. Hence, thedeveloped heterogeneous material model in Abaqus
enhances its capability for adding value to the tool insolving geotechnical engineering problems.
(a) Laboratory tests

boundary width and height are 15 times of the tunnel
diameter to ensure that stress redistribution aroundthe fault does not affect the modelling results. Figure
3 illustrates the model geometry.
Before any excavations, in situ stresses areapplied to the outer boundaries and then theboundaries are fixed with roller constraints. Tunnel
excavation is then simulated. The horizontal (σx) andvertical (σz) in situ stresses are assumed to be 30 and
60 MPa, respectively. Gradual excavation of thetunnel is simulated by stress reduction at the tunnelboundary in ten steps.
σz = 60 MPa(b) Homogeneous model

l

Fault
θ

Host rock(150 m × 150 m)dσx = 30 MPa

σx
Tunnel(r = 5 m )(c) Heterogeneous modelσz

Figure 3: Model geometry and boundary conditions.

0 MPa

5 MPa

10 MPa20 MPa40 MPaFigure 1: Failure patterns at different confinements from(a) laboratory tests (Zhang et al., 2014), (b) homogeneousmodel, and (c) heterogeneous model.

Rectangular specimen
with 4000 elements and
100 different materials

An elasto-plastic Mohr-Coulomb
strainsoftening model with heterogeneous material
properties is used to model a rock mass with its
physical and mechanical properties presented inTable 3. In the developed heterogeneous model, themean values of E, c, and φ are 21 GPa, 22 MPa, and31°, respectively and coefficients of variation (COV)of them are 5%. The adjusted parameters for defining
the strain-softening behaviour of the rock mass arepresented in Table 4.

x-3σ -2σ -1σ

µ

1σ

2σ 3σ

µE = 52 GPa, σE = 7.80 GPaµc = 39 MPa, σc = 5.85 MPaµφ = 37° , σφ = 1.85°

Figure 2: Generated heterogeneous material in Abaqus by
Python scripting.

3. ROCKBURST SIMULATIONIn this section, models are developed to study the
influence of weak planes on rockburst occurrence anddamage numerically. A circular tunnel with a radius(r) of 5 m is modelled. In the numerical models, theouter boundary width and height should be at least
ten times of the tunnel diameter to exclude the effectof the outer boundary on stress redistribution aroundthe tunnel. In this study, the models also include afault with a varying length. Hence, the outer

Table 3: Physical and mechanical properties of the rockmass.
Parameter
Value
Density, ρ (kg.m-3)
2500
Young's modulus, E (GPa)20
Poisson's ratio, ν
0.2
Uniaxial compressive strength, UCS (MPa)69.3
Cohesion, c (MPa)20
Friction angle, φ (°)
30
Table 4: Parameters with COV = 5% for defining the postpeak behaviour of the rock mass.
Cohesion
Tension cut-off
Cohesion
Shear
Tension cutTensile
yield stressplastic
off stressplastic strain(MPa)strain
(MPa)
22.0
0
3.0
0
0.01
0.2
0.1
0.005

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Firstly, a tunnel without any adjacent geologicalstructure is modelled. Shear and tensile failuresaround the tunnel, indicated by the maximum
principal plastic strains, are illustrated in Figure 4.
The figure shows a symmetric failure around thetunnel, with shear failure zones located at 3 and 9
o’clock because the maximum in situ principal stressdirection is vertical.

(a)

(b)

0

10 m

Step 10

10 m(a) Shear failure(b) Tensile failure

Figure 4. Failure zones around the tunnel without any
nearby geological structures.

Figure 5a shows the velocity of elements aroundthe tunnel at the beginning of Step 10 (at the time of
failure). The figure shows a maximum velocity of
1.78 m.s-1 in one node at the tunnel surface. The
minimum velocity of the failed elements is 0.14 m.s1
. In this study, the velocity of all failed elements
around the tunnel during the running time is tracked
and then an average velocity (Vmax) is calculated. The
maximum of the average velocity (𝑉𝑚𝑎𝑥 ) during therunning time is picked to interpret the results. In thiscase, the average of maximum velocity of the failed
elements around the tunnel ( 𝑉𝑚𝑎𝑥 ) is 0.58 m.s-1.
When failure is stable, the ejection velocity of thefailed rocks is low (Milev et al., 2002). The
maximum kinetic energy per unit volume (KEmax)
from the failed rocks, which can be used as anindicator of rock failure intensity, is 0.65 kJ.m-3. In
this case, failure can be considered as stable; if itwere in the field, the failure would be in the form of
spalling, spitting, or shallow slabbing.
(a)

(b)

Fault

Step 4

Step 9

Step 10Figure 6: Failure development around the tunnel with anearby fault: (a) shear failure, (b) tensile failure (l = 80 m, d
= 2.5 m, and θ = 45°).

Next, a fault with a dip of θ = 45°, a length of l =80 m and at a position of d = 2.5 m from the tunnel
wall is added to the model (see Figure 3). A Coulomb
model with a friction coefficient of 0.4 and zerocohesion is used to model the fault.
Development of failure around the tunnel at
Steps 1, 4, 9, and 10 is shown in Figure 6. The figure
shows initiation of tensile and shear fractures at the
tip of the fault at Step 1 excavation. Then, the shear
fractures propagate toward the tunnel face (Step 4)
and rocks between the fault and the tunnel areruptured. Meanwhile, tensile fractures are initiated at
the bottom of the tunnel. Figure 7 shows the relative
movement of the fault at four different points along
the fault (the fault tip and three other points at a
distance of 1 m from each other). A relative slip ofthe fault of about 25 mm occurs at point p-1 after the
excavation is completed. The slip rate is the highest
at Step 9. Slip of the fault due to excavation causes
compression at positions of 1 to 4 o’clock (Step 9).
At Step 10, the failed rocks on the right tunnel
wall would blow out violently with a 𝑉𝑚𝑎𝑥 = 3.4 m.s1
(Figure 5b) and a failure pit with a depth of 3 mwould be created. The maximum unit kinetic energy

Velocity (m/s)
1.8
1.6
1.5
1.3
1.2
1.0
0.9
0.7
0.6
0.4
0.3
0.1
0.0

Velocity (m/s)
9.0
8.2
7.5
6.7
6.0
5.2
4.5
3.7
3.0
2.2
1.5
0.7
0.0

Figure 5: Velocity of the elements in the models (a) withoutand (b) with a nearby fault.

Figure 7: Relative movement of the fault during therunning time.

15

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
is 6.97 kJ.m-3.
Tunneling near a fault with different fault lengths
is simulated to understand the influence of the fault
length (l) on rockburst damage. The length of thefault (l) is varied at l = 0, 20, 40, 60, and 80 m,
resulting in l/r ratios of 0, 4, 8, 12, and 16,
respectively. The same modelling proceduredescribed above is used.
The influence of l on 𝑉𝑚𝑎𝑥 and KEmax ispresented in Figure 8. The figure indicates that anincrease in the fault length results in increases of both
𝑉𝑚𝑎𝑥 and KEmax. According to Figure 8, when l = 0(i.e. there is no fault), the Vmax is low (0.58 m.s-1) andthe rock failure can be considered as stable. 𝑉𝑚𝑎𝑥 andKEmax increase rapidly as the l/r ratio increases. For
example, for l/r = 16, 𝑉𝑚𝑎𝑥 = 3.4 m.s-1 and KEmax =6.97 kJ.m-3, which indicates that the rock failure ismore violent than the models with shorter fault
length. In such a case it can be expected that a
rockburst is likely to occur. The failure zones aroundthe tunnel for various l/r ratios are presented in
Figure 9, with tensile and shear failure zones shown
separately. It is seen that as the l/r ratio increases, thefailure zone becomes large.
8
KEmax (kJ.m-3)

Vmax (m.s-1)

4
3
2
1
0
0

4

6
4
2
0

8 12 16 20

0

4

8

12 16 20

l/r

l/r

(a)

(b)

�max and (b)Figure 8: Influence of fault length on (a) V
KEmax.
(a)

(b)

0

10 m

l/r = 0l/r = 4l/r = 8l/r = 12l/r = 16

Figure 9: Failure zones around the tunnel in models withdifferent fault lengths: (a) shear failure, (b) tensile failure.

Figure 10 shows the total displacement
distribution around the tunnel at the end of Step 9

l/r = 0l/r = 4l/r = 8
Displacement (mm)
> 60
55
50
45
40
35
30
25
20
15
10
5
0

l/r = 12l/r = 16

Figure 10: Displacement around the tunnel in models withdifferent fault lengths.

excavation (before the sidewall fails). The figure
shows that when the fault is longer, a larger volumeof hanging wall rock can move toward the tunnel andpush the rocks near the tunnel wall boundary,particularly the rocks on the right wall side. Hence,
more strain energy release is possible if there is asudden rock failure. This explains why the unit
maximum kinetic energy is high for large l/r ratios.
Furthermore, the displacement field also indicatesthat the mine system stiffness is low when the l/r
ratio is high because the rocks surrounding the failed
rocks can have more deformation.
The concept of mine system stiffness has beenused by some researchers to explain rockburst inunderground mines (Aglawe, 1999; Wiles, 2002).
Although it is difficult to calculate mine system
stiffness quantitatively in a tunnel setting, an analogy
to Loading System Stiffness (LSS) in laboratory
testing can be made. Laboratory test results show thatthe modes of failure (stable and unstable) depend on
the relative stiffness of the rock and the loading
system (Wawersik and Fairhurst, 1970). A softloading system is capable of storing more strainenergy than a stiff loading system. Thus when a rockspecimen fails, the failure is stable under a stiff
loading system and unstable under a soft loading
system. Despite the difference in the loading in thefield and in laboratory, it can be seen that an increaseof l decreases the mine system stiffness and as aresult, unstable rock failure can happen around thetunnel. This can be clearly seen from the resultspresented in Figure 8 to Figure 10.
Reduced mine system stiffness can be considered
as a main effect of weak planes near openings in deep
underground mines, which can potentially lead torockburst. According to the simulation results, it isseen that the size of a weak plane is an importantfactor that influences rockburst damage.

16

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4. CONCLUSION
In this paper, the Abaqus-Explicit code was used
to study the role of weak planes in rockburst
occurrence and damage. Firstly, Abaqus’s usefulness
for modelling geomaterials was improved byintroducing material heterogeneity using Python
scripting. The modelling results showed thatheterogeneous models resulted in more realistic
failure modes than homogeneous models. Secondly,
rock failure near the excavation boundary of a tunnel
without any adjacent geological structure wasmodelled and the released kinetic energy due to rock
failure and velocities of elements at the tunnelboundaries were calculated. When a weak plane wasadded to the model, it resulted in more released
kinetic energy and higher element velocity, indicatingthat rock failure became more violent in the modelwith the weak plane. The modelling results indicatedthat the failure became more violent when the weakplane length was longer.
It was shown that weak planes around a tunnel
may change the loading system stiffness of the failed
rocks and induce rockburst because when there is aweak plane near an underground opening, a large
volume of rock is able to move. The approachpresented in this study can capture dynamic responseof a rock mass. In particular, the ability to estimate
ejection velocity and released kinetic energy provides
a new approach for dynamic rock support design.

5. ACKNOWLEDGEMENT
Financial supports from the Natural Sciences andEngineering Research Council (NSERC) of Canada,
Vale, LKAB, CEMI, MIRARCO, and the Open
Research Fund of the State Key Laboratory ofGeomechanics and Geotechnical Engineering,
Institute of Rock and Soil Mechanics, Chinese
Academy of Sciences (Grant NO. Z015001) for thiswork are gratefully acknowledged.

6. REFERENCES
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Ground. Queen's University.
Andrieux, P., Blake, W., Hedley, D. G. F.,
Nordlund, E., Phipps, D., Simser, B., and Swan, G.
2013. Rockburst Case Histories: 1985, 1990, 2001 &2013, Sudbury, Ont: CAMIRO Mining Division for
the Deep Mining Research Consortium; 2013.
Dassault System, (2010). ABAQUS 6.10 Users’manual. Providence, RI, USA: HKS Inc.
Gu, R., and Ozbay, U. (2015) Numericalinvestigation of unstable rock failure in undergroundmining condition. Computers and Geotechnics,
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Hedley, D. G. F., Mineral, C. C. f., Technology,
E., Association, O. M., and Laboratories, M. R.
(1992) Rockburst Handbook for Ontario Hardrock
Mines: Energy, Mines and Resources Canada,
Canada Center for Mineral and Energy Technology.
Jiang, Q., Feng, X.T., Xiang, T. B., and Su, G.-S.
(2010) Rockburst characteristics and numericalsimulation based on a new energy index: a case studyof a tunnel at 2,500 m depth. Bulletin of engineering
geology and the environment, Volume 69, No. 3, pp.
381-388.
Kaiser, P. K., and Cai, M. (2012) Design of rock
support system under rockburst condition. Journal ofRock Mechanics and Geotechnical Engineering,
Volume 4, No. 3, pp. 215-227.
Kias, E., and Ozbay, U. (2013) Modeling
Unstable Failure of Coal Pillars in Underground
Mining Using the Discrete Element Method. Paper
presented at the 47th Rock Mechanics/Geomechanics
Symposium. Paper ID: ARMA 13-174.
Manouchehrian, A., and Cai, M. (2016)
Simulation of unstable rock failure under unloading
conditions. Canadian Geotechnical Journal, Volume
53, No. 1, pp. 22-34.
Milev, A., Spottiswoode, S., Noble, B., Linzer,
L., Van Zyl, M., Daehnke, A., and Acheampong, E.
(2002) The meaningful use of peak particle velocities
at excavation surfaces for the optimisation of the
rockburst criteria for tunnels and stopes. SIMRAC
Final Project Report GAP, 709.
Wawersik, W. R., & Fairhurst, C. (1970) A studyof brittle rock fracture in laboratory compression
experiments. International Journal of RockMechanics and Mining Sciences & Geomechanics
Abstracts. Volume 7, No. 5, pp. 561-575.
Wiles, T. (2002) Loading system stiffness-aparameter to evaluate rockburst potential. Paper
presented at the First International Seminar on Deepand High Stress Mining, Australian Centre forGeomechanics, Perth, Australia.
Zhang, C., Feng, X. T., Zhou, H., Qiu, S., andWu, W. (2012) Case histories of four extremely
intense rockbursts in deep tunnels. Rock mechanics
and rock engineering, Volume 45, No. 3, pp. 275288.
Zhang, C., Feng, X. T., Zhou, H., Qiu, S., andYang, Y. (2014) Rock mass damage induced byrockbursts occurring on tunnel floors: a case study of
two tunnels at the Jinping II Hydropower Station.
Environmental Earth Sciences, Volume 71, No. 1, pp.
441-450.

17

Paper No. 126

ISMS 2016

A model of rockburst including geological dynamic conditions and mining
Jun Hana,b, * Ting Rena,b, Tianwei Lana,c, Feng Zhua, Chen Caob, Hongwei Zhanga, Guoshui
TangaaCollege of Mining, Liaoning Technical University, Fuxin, China, 123000
School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia, 2522c
Center of Geodynamics of the Earth’s Interior of Moscow State Mining University, Moscow, Russia, 119991b

ABSTRACT
Rockburst poses a serious threat to mining safety and can occur under certain combinations of geological andmining conditions. A model of fault-slip burst based on the energy distribution in the rock mass was developed toinvestigate the mechanics of rockburst and to determine guidelines for safe excavation and operation of undergroundcoal mines. In this model, the energy of the fault involved in the rockburst is assumed to be spherical. The rockburst
energy is a combination of the energy from the spherical fault-slip rock mass and the elastic energy from the rockmass ahead of the roadway excavation. We derive the threshold energy for rockburst occurrence from the criticalenergy condition based on the balance of dissipated and released energy. This method can be applied to estimate thesafe distance that tunnel excavation can advance towards the geological structure before rockburst occurs.
KEYWORDS: rockburst; energy; mechanics; geological structure; spheroid

1.

INTRODUCTION

Rockburst is a sudden and violent failure of alarge volume of overstressed rock, resulting in the
instantaneous release of large amounts ofaccumulated energy (Mine Safety and HealthAdministration, 1984). Rockburst often leads to rock
failure and collapse. It can cause damage to mines,
injuries to mine workers, and disruption to mining
activity. Several factors are known to affect rockburst:
the depth of mining, properties of the rock mass(lithology, elastic modulus, strength, and quality),
thickness of the mined deposit, the geologicalstructure of the mine area, and geotechnicalcharacteristics of the rock mass. Additionally, somemining factors can influence the occurrence of
rockburst: the mine design, mining method, roof
control method, pattern of deposit excavation,
concentration of mining operations, and the spatial
limits of the mining operations (Dou and He, 2001;
Hudyma, 2004; Zhang et al., 2009; Butra, 2010).
The occurrence of rockburst, a sudden rock
failure characterized by the breaking up andexpulsion of rock from its surroundings, implies thata large amount of energy was released. Cook (1966)
defined rockburst as an energy phenomenon anddeveloped the energy release rate (ERR) method.
Hoek and Brown (1980) provided graphic
illustrations of explosive brittle fracturing in deep
hard-rock mines. The only feature common to mostrockbursts is that the rock failure is sudden and thestrain energy is released from a volume of stressedrock (Ortlepp 1983). Salamon (1983) investigated the*Corresponding author – email : hanj_lntu@163.com

energy changes that occur during mining activities
and showed that part of this energy is stored in therock mass surrounding the excavation. Generally, theinstability occurs if the elastic energy released in the
deformation process is greater than the fractureenergy. He also pointed out three sources for thisenergy release: a) the strain energy stored in thesurrounding rock mass, b) the change in the potential
energy of the rock mass, and c) the slippage along therock wall contact. Petukhov and Linkov (1983)
associated the instability of rock mass with rockburst
or coal bump and noted that if the potential energy
accumulated in the high-stress zone is high enough todestroy the rock near the mine’s working area, a
rockburst will occur. Mitri et al. (1999) used theenergy storage rate (ESR) as a measure of theunderground conditions rather than as an indicator ofseismicity. Beck (2002) proposed a quantitative
assessment and interpretation of rockburst in a hardrock mine using the “factor of safety”. Zhao et al.
(2003) proposed the minimum energy principle ofrock dynamic failure. Xie et al. (2009) established astrength-loss criterion associated with the intensity ofenergy dissipation and a failure criterion associatedwith the strain energy release.
Rockbursts occur under certain combinations ofgeologic and mining conditions. The connection
between rockburst and the geology of the mining area
was made following the first reported rockburst,
which occurred on the 2500 level of the Sunshine
Mine in April 1939 (Whyatt, 2002). Brown (1984)
indicated that rockbursts induced by mining are3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

associated with unstable equilibrium states that may
involve: a) slips on pre-existing discontinuities; b)fracturing of rock mass. This leads to the definitionof two broad classifications of rockbursts: (1) TypeΙ rockburst, resulting from fault slip events; (2) TypeII rockburst, resulting from the failure of the rockmass itself, including strain burst and pillar burst. A
degree of rockburst hazard is inevitably associatedwith the stress near the mine working area and the
distance between the mine wall and the maximum
stress zone (Petukhov and Linkov, 1983).
Recognition of the geologic features that contributeto rockburst events is an important part of strategicplanning aiming to minimize these hazards. Many
rockburst events are associated with geologicalfactors such as faults, folds, irruptive rock, andtectonic stress. (Batugina and Petukhov, 1990; DriadLebeau et al., 2005; Wang et al., 2012; Drzewiecki,2013). The authors used the term ‘geologicaldynamic condition’ to describe this state (Han et al.,2013; 2014). Experience in the Coeur d’Alene districtin Idaho, USA indicates that certain rock types andvarious kinds of discontinuities increase the risk of
rockburst. Whyatt (2002) showed that ultimate stressstate is created by the action of the pre-mining andmining induced stresses. The in-situ stress, as well as
the rockburst hazards, varied with the geologicalfeatures in the Coeur d’Alene district (Whyatt 2000).
In China as of 2012, there are 142 coal mines
which have had rockbursts. As mining operations
become deeper, the frequency and intensity of
rockbursts has been increasing accordingly. The
prediction and prevention of rockburst is very
important for mining safety and continuous operation.
Many rockbursts are affected by the geologicalstructure around the mine area and by the mining
operation. The current study investigates the energyof the rock mass in mines and the processes of energy
release and equilibrium, in order to gain a better
understanding of the occurrence of rockburst in
various geological and mining conditions.

2. ENERGY OF ROCK MASS

state. For a certain load, a dynamic equilibrium exists
among the work of the external load, the thermalenergy, and the internal energy; thus, the rock is in a
steady state. When the external load become too large,
the steady state of the rock moves to the nonlinear
non-equilibrium region, away from the equilibriumzone; hence, the rock mass becomes unstable. At thecritical state (Figure 1, Position b), the rock statechanges abruptly to another state (Figure 1, Position c)with relatively low internal energy, leading to thecollapse of the rock. The high stress level destabilizes
the rock; whether the rock fails is determined by theinternal energy dissipation and the nonlinear dynamic
mechanism (Peng, 2011).

Figure 1: Thermodynamic change during rock deformationand failure (Peng, 2011).

According a rock volume element produce
deformation under loading, the total input energy
produced by external load is U, as shown in Figure 2
U=Uid+Uie(1)
where Uid is the dissipated energy and Uie is thereleasable elastic strain energy.
The releasable elastic strain energy Uie can be
described as
U ie =

1
2
2
2[σ 1 + σ 2 + σ 3 − 2µ（σ 1σ 2 + σ 2σ 3 + σ 1σ 3）
]
2E

(2)

where E is the elastic modulus; μ is the unloading
Poisson’s ratio; and σ1, σ2 and σ3 are the major
principal stress, intermediate principal stress, andminor principal stress, respectively.

The conservation of energy in rock during its
deformation and failure is a dynamic process that
represents energy conversion and the equilibrium of
the mechanical energy produced by external loads,
thermal energy, and the internal energy of the rockaccording to the non-equilibrium thermodynamic
theory. Initially, the rock is in a stable equilibrium
state (Figure 1, Position a). After external loading,
the rock begins to deform. The mechanical energy
produced by the external load and thermal energy iscontinuously converted into internal energy of therock. Therefore, the internal rock energy increases
and the rock gradually departs from the initial stable

19

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 2: Relationship between dissipated energy andreleasable strain energy of rock volume element (Xie et.al2005).

3. ROCKBURSTOCCURRENCEAT
MININGANDGEOLOGICALSTRUCTURE
We constructed a model of a fault-slip rockburstthat includes the mining conditions and geologicaldynamic conditions. The model simulates a fault
ahead of the roadway excavation work. The area
influenced by the fault is a sphere with a radius R. As
the roadway is excavated, a plastic and an elastic
zone are produced ahead of it. The distance between
the sphere boundary and the working end of the
roadway excavation is L. Lp and Le are the lengths ofthe plastic zone and elastic zone that develop aheadof the excavation, respectively. H is the height of the
roadway and Lo is the length of the undisturbed zone
- original zone. The stress in the plastic and elastic
zones is lower than in the original zone (Figure 3.a).
The rock mass attains energy from thedeformation of the rock mass at the in-situ stress field;
it depends on the volume of the rock mass and the insitu stress. We assume that the energy source of thegeological structure involved in the rockburst is
contained within the sphere. The elastic energy of thesphere UG is
UG =

2π 2
[k1 + k 22 + k 32 − 2 µ (k1 k 2 + k1 k 3 + k 2 k 3 )]ρ 2 g 2 H 2 R 3
3E

(a)

(b)
Figure 3: A model of mining and geological dynamic
condition.

(3)

where ρ is the density of the overburden; g is thegravitational acceleration; H is the depth; E isthe elastic modulus of the rock; k1, k2, and k3 are
the ratios of σ1/ σh, σ2/ σh, and σ3/ σh,respectively, where σh = γgH is the pressure of
the overlying strata.
As the roadway is excavated, the fracturing of
the coal and rock extends forward, the head of the
excavation becomes closer to the sphere of influence,and the volume of the elastic zone gradually
decreases (Figure 3.b). When the elastic zone is too
small to resist the superimposed stress, rock failure
will occur and a large amount of energy will be
released (Figure 4). The sphere will also releasemuch energy. This leads to the occurrence of a
rockburst. The energy released from the sphere after
failure is:∆U = U G − U Z(4)

Figure 4: The energy calculation diagram of rockburst.

where UZ is the gravitational energy. According to
the principle of minimum energy of the failed rock,the minimum energy of the failed elastic zone is
U SD =

σ c2V
2E

(5)

where V is calculated as followsθθ11
V = cos 2 sin πR 3 +
3
2
2
3

cos

sin

θ
2

=

cos 4

θ

θ

[

2hR ± 2 h 2 R 2 + (2 R + l )l 4(l + R) 2 + h 2θθ= 1 − cos 2
2
2

θ

cos 2
sin 2
2 R − R − l )32(
2 πR 3 − 1 π
e
θ
θ
θ
3
sin
cos 2
sin
2
2
2

4(l + R) 2 + h 2

]

(6)
(7)
(8)

The parameters in equations (6), (7), and (8) are20

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

shown in Figure 4.
The elastic energy of this zone is
U SE =

1[σ 12 + σ 22 + σ 32 − 2µ (σ 1σ 2 + σ 1σ 3 + σ 2σ 3 )]dV (9)2E ∫The energy released in the rockburst UC can be
expressed as(10)
UC=ΔU +USD-USD
where ΔU is the energy released from the sphere, USE
is energy of the elastic zone, and USD is the energy
released from the elastic zone during rock failure.
The minimum energy required for the rockburst
to occur is expressed as1(11)
U = ρ .ν 2
min

2

0

where v0 is the velocity of the ejected rock during the
rockburst event, and v0 ≥ 10 m/s (Ortlepp and Stacey,
1994; McGarr, 1997).
If UC≥Umin, then rockburst will occur. Thus,
UC=Umin is the critical condition for rockburst
occurrence.
This method can be applied to calculate thelength of the elastic zone le and then determine thedistance of rockburst treatment.

4. CASE STUDY OF THE LAOHUTAICOAL MINE

The overlying rocks include argillite, shale, andoil shale. The thickness of the main coal seam, coalseam No.1, varies from 0.6 to 110.5 m, with anaverage thickness of 58 m. The main geologicalstructure of the Laohutai coal mine is a syncline
trending NEE. The wings of the syncline areasymmetric; the south wing extends smoothly while
the north wing inclines abruptly, and is even inverted.
There are 14 large faults, including F1, F7, F26, andF18. The largest one is F1 which has a drop of morethan 1000 m. The deepest buried depth of the coalseam is more than 1000 m.
The Laohutai coal mine is one of the largest
state-owned coal mines in China and has been
operating for more than 100 years. The mining
method is fully mechanized top coal caving and theannual production is about 3 million tons. The
Laohutai mine has been associated with various
operational challenges such as gas outburst,
rockburst, spontaneous combustion, and water inrush
and is considered one of the most hazardous mines in
China. Rockburst events occurred in 1975 andreached a peak in 2001 (Figure 6). The maximum
magnitude of rockburst at the Laohutai mine wasML3.7. Figure 6 shows the mine rockbursts andassociated seismicity during 1993–2014.

4.1 Background
The Laohutai coal mine is located in the central
Fushun coal field, Fushun city, Liaoning Province.
To the east lies the Longfeng coal mine and to thewest is the Shengli coal mine. The length of the coalseam strike from east to west is 5 km and the widthalong the dip in the north–south direction is 2 km
(Figure 5).

Figure 6: Rockburst and mine seism during 1993-2014.

4.2 Rockburst of Longwall 73005
Longwall 73005 (LW73005) is located in thecentral part of the Laohutai coal mine at a depth of
749–802 m. Figure 7 shows the layout of LW73005.
There are eight faults in LW73005: F3, F7, F26, F32,
F36, F37, F38, and F39.

Figure 5: Location and regional geology of Laohutai coal
mine.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

6.

Figure 7: Layout and geological structures of LW73005.

Fault F36 was encountered during the excavationof the air return roadway. We use our model toestimate the special range of the energy released bydrilling or/and blasting near the fault. According toin-situ stress measurements of the Laohutai coalmine, the ratios k1, k2, and k3 in Eq. (3) are 2.0, 1.0,
and 0.7. The energy of the sphere can then be
described asUG =2π（5.49 − 8.2µ）ρ 2 g 2 H 2 R 3
3E

(12)

When the rockburst occurs, the energy released
from the sphere is
2π (10.2 µ 2 − 12.69 µ + 4.49)γ 2 H 2 R 3
(13)
∆U =
3E (1 − µ )The result is shown in Table 1. The bigger the
ΔU of sphere, the bigger the le, and the longer the
distance of treatment. Based on the calculation, thesafe distance of treatment is 36 m. Thus, when thedevelopment of roadway reaches a distance of 36 mfrom F36, drilling and/or blasting should be carriedout to release energy and prevent a fault-slip burst.
Table1: Parameters of spheroid and distance of treatment.
Work
H
h
R
lp
ΔU
ls
No.
face
(m) (m) (m) (m) (MJ) (m)1

LW73005

778

3.6

6.3

2

91

36

5. CONCLUSIONS
According to the theory of energy exchange andequilibrium in rock mass we constructed a model offault-slip burst in a mining environment. The
geological structure is included and assumed as asphere during the rockburst occurrence. The
rockburst energy is a combination of the energy ofthe sphere and the energy of the elastic zone thatdevelops ahead of the tunnel excavation. Part of theenergy is dissipated in the elastic zone. When thatenergy rises above the critical rock failure energy,
rockburst will occur. This method can be applied toestimate the safe distance and the rockburst treatmentthat should be taken when performing roadway
excavation towards a geological structure, before
rockburst occurs.

ACKNOWLEDGEMENT

The work presented in this paper was financially
jointly supported from the General Project of the
National Natural Science Foundation of China (Grant
No. 51104085, 51274117), the Natural Science
Foundation of Liaoning (Grant No. 201204407) and
Program for Liaoning Excellent Talents in University(Grant No. LJQ2013035).
The authors are especially grateful to Dr. Hai
Rong for fruitful discussions and advice. Thanks arealso due to Mr. Bob Kininmonth for improving theEnglish of this paper.

7.

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ISMS 2016

Paper No. 157
Rockburst experiences in Cheves Hydropower Project, PerúSantiago Veyrat a, Jose-Miguel Galera b,*, Marcos Sancho c, H. Anderssond, W. Thoesee, and, C.
RietschelfaSubterra Ingeniería SL, Madrid, Spain, 28015
Subterra Ingeniería Ltda., Santiago, Chile, 7750181
c
Subterra Perú SAC, Lima, Perú, 18dConstructora Cheves, SAC (joint venture Hochtief Solutions AG, SalfaCorp SA and ICCGSA), Lima, Perúe
Constructora Cheves, SAC (joint venture Hochtief Solutions AG, SalfaCorp SA and ICCGSA), Lima, Perúf
Constructora Cheves, SAC (joint venture Hochtief Solutions AG, SalfaCorp SA and ICCGSA), Lima, Perúb

ABSTRACTCheves Hydropower Project is located in Peru and consists in approximately 20 km of tunnels and two caverns.
Most of the Headrace tunnel has been excavated in igneous and metamorphic rocks with high overburden. A highnumber of stress release events took place during the excavation of the tunnels and caverns. The intensity of these
events varies from acoustic emission to a violent rockburst. The paper describes the methodology developed tomitigate the rockburst hazard.

1. INTRODUCTION
Cheves hydropower project is located on Huaura
River and Checras River, under the Andean
Mountains of Peru, North of Lima (see Figure 1).

Figure 1: Cheves Hydropower Project location.

Cheves Project was developed by Empresa deGeneración Eléctrica Cheves S.A, a company of the
Statkratf Group. The construction was executed byConstructora Cheves, SAC (joint venture Hochtief
Solutions AG, SalfaCorp SA and ICCGSA).

*Jose Miguel Galera: jmgalera@subterra-ing.com

In reference to the design of the project, Empresade Generación Eléctrica Cheves engaged Norconsult
with responsibility for the design of the permanent
works including the layout, overall stability, andpermanent support of the underground works.
Meanwhile Subterra Ingeniería developed theinitial support design to Constructora Cheves SAC
according to the scope including in the contract
signed between the Owner and the Contractor.
Constructora Cheves and Subterra Ingenieria didn’t
have responsibility for the final layout and the longterm stability of the works.
This paper and all the above comments arereferring only to the scope of work carried out by
Constructora Cheves and Subterra Ingeniería.
The project is composed of three small dams andthe underground works that dominate theinfrastructure, representing approximately 20 km of
tunnels:- Transfer tunnel, between the Huaura Intake
and the Checras reservoir presents a lengthof 2,580 m.
- Headrace tunnel is 9,693 m long (22.6 m2
and 30.1 m2), with an upper section at agrade of 2 % and a lower section inclined 14%. An intermediate adit with a length of 700
m, and a surge tunnel were built at thejunction of the lower and upper tunnels, withapproximately 700 m long, also inclined 14%. The end of the Headrace tunnel splits
into two short penstock tubes, taking theflow to the generating units in the3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

powerhouse cavern (60 m long by 32 m highand 15.5 m wide). The transformer cavern(27.5 m long by 14 m high and 11.2 m wide)
is immediately adjacent, connected both
caverns through an access tunnel. A tunnel
access as well as several tunnels completes
the Power House complex.
- Tailrace tunnel is 3,312 m long (24.9 m2
cross section) tailrace tunnel discharge thewater downstream the project.
Kaiser and Cai (2013) define a rockburst as
damage to an excavation that occurs in a sudden andviolent manner and is associated with a mininginduced seismic event. This general term ‘rockburst’is independent of the cause of damage and thus isused for strain, pillar, and fault slip bursts.
During the construction of the Cheves Project
more than 850 stress release events were recorded.
The most important part of these events took place inthe Headrace Tunnel, and a large number of themwere recorded around the Powerhouse complex.
Initially, the stress events turned out in the area
under the influence of the Powerhouse, especiallywhen the excavation of the cavern began. In
December of 2011 and during January 2012 several
stress relief events were reported and described as
banging or cracking sounds. On January 2012 a
minor rockburst with projections of rocks andshotcrete occurred at the access tunnel about 15 m
behind the face.
During the followings months, evidence of stressreleases continued with events of low intensity,
mainly loud relief, slight crumbling, crackling andbanging sounds. These events were mainly reported
in the by-pass tunnels around the powerhouse.
Consequently, these areas were reinforced.
However, on the 21st of March 2012 a strong
stress event occurred in the Powerhouse area
affecting various tunnel sections. The main stressdischarges were reported as two short delayed bursts
in the tunnel access and by-pass tunnels. A follow up
investigation at the same day in the afternoon
revealed that after the main bursts further cracking
and minor bursting occurred in the powerhouse
cavern.
The areas around the powerhouse were
reinforced as a consequence of these events. The
excavation of the Powerhouse continued, whereas theworks in some tunnels were stopped.

Figure 2: Areas affected by the stress event occurred on
21/03/2012 and a picture of the effects in the by-passtunnel.

Once the excavation of the Headrace tunnel
started from the Powerhouse complex towards the
Checras dam, stress events were reported
continuously during the excavation, mainly as
banging or cracking sounds (acoustic emissions).
Finally, a rockburst from the face took place at thetunnel face on July 2012. A complete methodology
was developed to mitigate the rockburst hazard
during the excavation of the tunnels after this event.

Figure 3: Rockburst at the tunnel face in the Headracetunnel.

2. GEOLOGICAL AND
FRAME

GEOTECHNICAL

Cheves Hydropower Project is located in the
Huaura basin in the Andes. The Geology is complex
withsedimentary,
volcanic,
igneous,andmetamorphic formations along the project. Accordingwith its position in the Andes, the area is under active
tectonic and seismicity is moderate in the projectarea.
The Headrace tunnel and the Powerhousecomplex have been excavated in relatively hard rock.
The geology in the area of the caverns proved to be
structurally complex given the presence of major
tonalites intrusions with associated sub-horizontal
shear joints. Careful consideration was given to
aspects such as in situ stresses and rock massstrength. Figure 4 shows the geological section of the
Headrace tunnel.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 4: Headrace tunnel geological profile.

2.1 Lithologies and Basic geomechanical data
In this section a geotechnical characterization of
the different rocky formations that were found in thedownstream part of the Headrace Tunnel aredescribed.
- Churin Bajo Stock. Consist in intrusive
rocks with tonalite / quartz-monzonite
composition. In general, they show a highstrength, low to moderately weathered in thesurface, showing thin coats of iron oxides infractures, which are persistent. The contact
with Casma Group andesites produces
silicification processes resulting in hornfels,
which present highly brittle behaviour andsevere fracturation.
- Casma Group. This group corresponds tostratified sequences of volcanic rocks withinterbedded sedimentary rocks. Volcanic
rocks consist mainly in andesites whichappear severely brecciated with aporphyritic texture. In general, they show ahigh strength, except when intercalations of
sedimentary rocks are detected. Sedimentaryrocks consist in sandstones, white quartzites,brown to grey shales and layers of limestone
with isolated intercalations of marls.
- Chimu Formation. It is composed byquartzite banks with interbedded with thinquartzose sandstone strata, bituminous shale
and occasional coal lenses. In general,quartzites banks show very high strength but
brittle behaviour with many fractures
showing thin coats of iron oxides. Shales
and quartzose sandstones appear highly
fractured, with low strength and stiffness
and also ductile behaviour.
- Hornfels. The contact with Casma Group
andesites produces silicification processes
resulting in hornfels, which present highly
brittle behaviour and severe fracturation.
The representative values for these formations at
intact rock level are shown in Table 1 below:

Table 1: Intact rock properties.
RQD
(%)
40-60
70-90

ρap
(t/m3)

Tonalites(Fault zone)

1100-1200

30-50

2.62

80-12090

400

Hornfels

525-700

30-50

2.62

80-12090

135-200
250-350
175-525

30-50
40-60
60-80

2.62

70-120100-150
120-200

80
110
130

500-525

10-30

30-80

40

LITHOLOGY

Churin Bajo
Stock (KsTiqzmo)

Tonalites

Churin Bajo
Stock (KsTi-hf)
Casma Group(Ki-ca)Chimu Formation(Ki-ch)σci (MPa)
RANGE VALUE
110
100-150125

OVERBURDEN(m)
580-700
700-780

LITHOTYPE

Andesites (Fault Zone)
Andesites
Quartzites with shales
and sandstones
interbedded (Fault
Zone)
Quartzites with shales
and sandstones
interbedded

2.62

2.62
25-200200-450450-600

2.2 Structure
The Headrace tunnel presents a complex
geological structure as it is excavated in sedimentarydeposits (coal seam included), volcanic rocks,
igneous rocks and metamorphic rocks.
The initial part of the tunnel excavated in the
Chimu formation is strongly folded and affected byfault systems. The contact between volcanic materials
and sedimentary deposits is also defined by fault
systems. An igneous intrusion (Churin Bajo Stock) is
in contact with the volcanic deposits (Casma Group).

10-30
30-50
10-30

Modulus
Ratio

Ei
(MPa)
44,00050,000

v

mi

0.24

25

36,000

0.24

25

550

49,500

0.24

19

400

32,00044,00052,000

0.24

25

0.24

20

400

15,000375

30-80
60-120
30-80

40
70
40

15,00026,25015,000The contact with Casma Group andesites produces
silicification processes resulting in hornfels, which
present highly brittle behaviour and severe
fracturation.
2.3 Overburden and natural stress field
Initially, the natural stress field assumed wasderived from regional information as well as from thetectonic frame. It was considered an unfavourable
scenario with the vertical stress according to the
overburden (lithostatic load) and the following ratio

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

between horizontal and vertical stresses: KH=1.5(with a strike of N-60º-E) and Kh=1.0.
This stress frame is a key matter for design
purposes, thus three different stress measurements
were developed, the first using overcoring techniques
and the last two using hydro fracturing stressmeasurements.
The measurements using overcoring provided
magnitudes of the maximum principal stress σ1
ranging between 18.6 to 59.8 MPa. According to themean value the resulting relation between horizontal
and vertical stresses would be around 1.2 and an
orientation quite similar to the one obtained bygeological estimations (N-45º-E), but the scatter ofthe results was relatively high.
For this reason, two different on sitemeasurementsusinghydro-fracturing
were
established. The obtained magnitudes were similar inboth cases, with relatively low values of horizontal
stresses. Consequently, the natural stress field was
defined as follows:- σv between 21.7 and 22.1 MPa- σh between 12.8 and 13.7 MPa (Kh=0.62)- σH between 20.3 and 21.3 MPa (KH=0.96)
The orientation of the maximum horizontal stress
was N-95º-E.

3. ROCKBURST HAZARDMETHODOLOGYMITIGATION

Rockburst and stress releases took place mainlyin the Headrace tunnel and the powerhouse complex.
Headrace tunnel was excavated in sedimentarydeposits (coal and sandstones), andesite, volcanic
breccias, granodiorites, and hornfels. Most part of theevents took place in areas excavated in igneous andmetamorphic rocks.
A specific stress risk assessment was done inaddition to the geological assessment at the tunnel
face during the tunnel excavation, in order to collect
all the information coming from the tunnel. Threestages were defined to manage the risk of rockburst

or stress releases. These measures can be classified in
prediction, prevention and protection.
3.1 Prediction
It was considered that rockburst and/or stressreleases are highly unpredictable. Basically, theunique method for rock burst prediction that is
considered as partially efficient is to implement a
microseismic monitoring net. These systems havebeen developed in deep mines and require longrecord periods with some years for calibration to
perform reliable predictions. It must also be
considered that a mine usually has a well-developed
layout of roadways and excavation allowing the
installation of seismic nets. For these reasons theapplication of this technique to Cheves wasconsidered unreal.
The
proposalforpredictionisthesystematization of all the stress events, registering
them in a systematic and precise way from simple
noises, fissures progression on the shotcrete, minor
projections and spalling or popping. Consequently, it
is proposed to increase the efficiency of the highstress events records to ensure that all of them are
duly registered:- Stresses events at the face: noises, rockcracks, minor projections, spalling orpresence of platy rock chips.
- Stresses events behind the face: fissures andcracks at the shotcrete, spalling at the walls.
- Statements from key personnel in thevicinity.
According to Kaiser and Cai (2012) there aremany factors that have an influence on rockburst
damage and the severity of the damage. Table 2
summarizes the main factors and groups them into
four categories, i.e. seismic event, geology,
geotechnical, and mining. Factors in the first twogroups (seismic event and geology) determine theintensity of dynamic load at the damage locations,and the factors in the last two groups (geotechnicaland mining) determine site response due to seismic
impulses.

Table 2: Main factors influencing rockburst damage (modified from Kaiser and Cai, 2012)
Seismic event

Geology

Geotechnical

Event magnitude
Seismic energy release
Distance to seismic source

In situ stress
Rock Type
Beddings
Geological structures(dykes, faults, and shears)

Rock Strength
Joint fabricRock brittlenessA sheet record was defined to collect all valuable
information after every stress event:- Production: Date/Time; Blast time; Phase of
production cycle;-

MiningMining induced static and dynamic stresses
Excavation span
Extraction ratio
Mine stiffness
Excavation sequence (stress-path), blasting
Installed rock support system
Backfill
Production rate

Geometry: chainage, section, area affected,
overburden.
Geology: lithology, structural geology

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016-

Stress classification: stress effect andconsequences.
A stress release classification was developed forthe project based on previous experiences from themain contractor in the Gothard Tunnel. This
classification was divided in four categories
according to the characteristics and effects of stressreleases.
Table 3: Stress Release Classification developed for
Cheves Hydropower Project.
Stress Class
0
1

2

3

Description
Loud Relief, slight crumbling: crackling, banging,crumbling in surrounding rock mass
Stress-induced spalling without rock fall: rocksurface cracks suddenly, creating scales up to 5cm,
appearance of dust clouds
Stress-induced loosening or rock fall at lateral rocksurface or face in unsupported area: rock breaks
rough and very loud. Rock support system might beslightly damaged (Fissures in shotcrete).
Heavy Bangs with explosive rock fall: pieces orslabs of rock are thrown suddenly with loud bangs inradial direction from lateral rock surface (insupported and unsupported areas). The rock support
system is damaged (Cracks in shotcrete, torn-off
anchors, bent ring beams).

3.2 Prevention
The prevention of these types of stressphenomena is rather complicated but sometechniques can be implemented. The three following
measures were recommended:- Preconditioning blasting ahead of the face
- Change of the shape of the face to a concave
geometry- Reduction of the round length
In relation to the use of preconditioning blasting
ahead of the tunnel face, these blasts can minimize
the effects of future possible rockbursts at the face
(face burst), reducing the stress magnitudes at andahead the face. This technique consists basically inthe execution of blast drill holes ahead of the face at
specific depths and locations using high velocity
detonation explosives and full confinement of it. As aresult, the rock mass quality beyond the face isdecreased artificially, “distressing” the rock mass inthe vicinity of tunnel to be excavated, and allowing
the release of tension that otherwise could result in arock burst.
The design of the preconditioning blast is basedon the following criteria:- Not generate an intense fracture the rock but
yes “distressing” the rock mass, in order tonot difficult following blast and support atface- Focus the decompressing effect within theperimeters of the tunnel section by

generating fractures in the rock that allow toadjust the stress.
The preconditioning blast was executed by 3holes of 51 mm and 4 m long, loaded on the last 2
meters with bulk Slurrex explosive. These holes were
proposed to be drilled on a vertical alignment withthe tunnel axis, in between production holes.
Analysing the energy distribution, we can predictthat energy from production holes interacts with preconditioning holes. These combinations of energies
are expected to create a tunnel free face with a set ofcracks concentrated vertically. After a first test shot it
must be evaluated how those perform. Proper
performance implies both a continuous set of verticalcracks interconnected and a good enough rock mass
to be drilled around pre-conditioning holes.
Because cracks induced on fully confined holes
are due to tension created by a shock wave, it is notintended to use the gas energy of the explosive for
either crack extension or rock displacement. For thisreason, explosive charges can be unconfined. Expect
however a flyrock potential increase that can damage
equipment or infrastructure if not properly protected.
Figure 5 below shows the energy distribution at 2.2 m (top left), -3 m (top centre) and -4 m (top right)
with a 3-hole configuration at 51 mm with Slurrex.

Figure 5: Energy distribution of preconditioning blast witha 3-hole configuration at 51 mm with Slurrex.

A second measure recommended was to change
the face excavation shape from planar to a concave

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

geometry as planar planes always accumulate higher
stresses than curved planes. In relation with this same
effect it was also suggested to the Owner the
possibility of changing the shape of the tunnel section
to a Horse-shoe or even more, with curved walls withhigh potential risk of rockburst. Nevertheless, thismeasure was not finally implemented.
Finally, the reduction of the round length wasconsidered a less effective measure with a minor
effect in the release of stresses and consequently inthe rockburst occurrence, but it has a notable effecton shortening the construction cycle and therefore
decreasing the exposure of the personnel at the face.
3.3 Protection
Two different types of measures were proposedin order to protect the tunnel workers at the face:- To reduce the vulnerability and exposure of
the personnel.
It was recommended to reduce the vulnerability
and the exposure of the tunnel workers at the tunnel
face as risks factors. For this reason, basic measures
were adopted, as to carry out scaling using
mechanical facilities and protective cages for workers
and machinery.
- To install a temporary support at the face.
Two different support elements were basicallyused: shotcrete and/or rock bolts (swellex). In bothcases the purpose was to avoid rock fragmentejections from the face.
According to previous experiences in Gothard
Tunnel, it was recommended that a layer between 5.0
and 10.0 cm of shotcrete with steel fibres, as well as avariable number of swellex bolts be installed at theface. These bolts were always longer that the advanceround length.

4. ROCKBURSTS RECORDHEADRACE TUNNEL

AT

THE

As mentioned before, 859 stress events werereported between Aug. 2012 and Jul. 2014, 48% of
which were recorded as banging noises without rockejections or support damages, 41% of the events wereclassified as Stress Class 2 and 3 with rock support
damages, and only 16% of the events involved
violent rock ejections or/and support. Figure 6 shows
the distribution of the events according to intensity.

Figure 6: Stress Events intensity distribution according to
CCH classification.

About 90% of the events were recorded in the
Headrace tunnel. The rest of the events were recordedin the tunnels surrounding the Powerhouse.

Figure 7: Distribution of stress events around the Powerhouse.

An analysis of the stress events over time shows
an erratic distribution of events. There were several
months in which the stress events had more influence
over the project. Figure 8 shows the distribution of
the stress events and the number of events in eachtunnel over time.
The data demonstrates that Headrace tunnel has
been the most affected by stress events, and theinfluence of these events has three clear steps. From
Jan. 2012 to Dec. 2012 it is possible to define anincreasing tendency, a quiet period during Jan. 2013,
and an increasing tendency from Feb. to Apr. 2013.
The chart also shows that the stress events
continued after the tunnels completion, when the
support was removed in some tunnels to execute therequired concrete plugs.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 8: Stress Events distribution according to CCH classification and tunnels.

5. PARAMETRICAL ANALYSIS OF THE
STRESS EVENTS
A detailed record of all stress events was carriedout and statistical analysis was implemented tounderstand the rockburst phenomena in the project.
The analysis confirmed that the overstress in thetunnels was related with the following factors:- Overburden- Lithology- Jointing and other structures- Rock mass quality- Time after blasting- Round length
The follow describes the particular analysis for
Headrace tunnel.
5.2 Overburden
Headrace tunnel was designed with a positive
slope of 14%. The overburden considered in thevertical tunnel axe shows an increasing tendency.
The overburden is close to 850 m at the powerhousearea and rises to approximately 1.450 m. Figure 9shows the topographical longitudinal section with theoverburden.

Figure 9: Headrace tunnel overburden.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

It will be shown later that minor changes in the
overburden due to the presence of irregular
topography will have a significant influence on the
stress release.
The next figure shows the relationship between
stress events and depth. It would be expected that

there would be more events deeper is the excavation,
however, it was observed that major events occurred
between 1000 and 1150 m in the Headrace tunnel andabout 800 m around the Powerhouse.

Figure 10: Stress Events vs. Depth.

5.3 Lithology
Headrace tunnel has been excavated in different
lithology: hornfels, quartzmonzonite, subvolcanic
breccias, and granodiorite. The influence of the stressevents on each lithology has been different along the
excavation period. The geological conditions after
each event were recorded, considering the lithology
and the rock mass quality.

A statistical analysis of the results clearly showsthat lithology with higher brittle behaviour had
suffered a higher number of stress events. It has also
been checked that not only areas with good rockconditions are affected by overstress, but also zones
where rock mass quality in terms of RMR values are
considered fair ground. Figure 11 shows the
distribution of stress events in relation to lithology.

Figure 11: Stress Events vs. Lithology.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 12: Stress Events vs. RMR.

5.4 Geological Structure
The presence of the same joint set family was
detected in most of the stress events. An analysis of
the stronger events and information from coredrillings executed at the tunnel face confirmed thatrockbursts are highly controlled by the geologicalstructures. Only eleven (11) events represent the 60%of the events described in Headrace tunnel and sum
the 79% of the Stress Class 3 events reported. The
joint system at the areas where this rockburst took
place was analyzed, as shown in Table 4.

Table 4: Structural data mapped after rockburst events.
CHStart
9+557,50
9+555,50
9+553,00
9+490,70
9+487,80
9+408,30
9+405,50
9+403,30
9+297,90
9+295,109+246,40
9+226,10
9+208,70
9+203,60

End
9+555,50
9+553,00
9+550,20
9+487,80
9+485,50
9+405,50
9+403,30
9+400,70
9+295,10
9+292,50
9+244,20
9+223,80
9+205,90
9+201,20

JOINTSJ1
J2J3
DIP DIP DIR. DIP DIP DIR. DIP DIP DIR.
Metamorphic Rock-Hornfels
10
320
75
220
80
190
Metamorphic Rock-Hornfels
11
308
49
347
74
140
Metamorphic Rock-Hornfels
18
300
50
155
45
280
Subvolcanic breccia contact with Hornfels 45295
60
5Metamorphic Rock-Hornfels
75
5
60
305
Metamorphic Rock + Qz-Monzonite
65
100
15
300
Metamorphic Rock + Qz-Monzonite
72
115
35
240
Metamorphic Rock + Qz-Monzonite
35
328
55
154
5
140
Metamorphic Rock + Qz-Monzonite
70
140
20
290
45
200
Metamorphic Rock + Qz-Monzonite
83
148
11
109
50
320
Metamorphic Rock + Qz-Monzonite
35
280
55
165
80
55
Metamorphic Rock + Qz-Monzonite
20
260
85
320
Metamorphic Rock + Qz-Monzonite
25
220
70
250
43
330
Metamorphic Rock + Qz-Monzonite
44
285
84
140
Lithology

Figure 13 shows the stereographic analysis ofthese joints system. As it can be observed thepresence of two joint sets with two parallel systems
each one were deduced.

TUNNELSTRIKE

Joint
Set

Dip

Dip
Direction

J1

13

294

J2

41

285

J3

52

159

J4

78

142

According to this analysis, the presence of subhorizontal joints dipping to the left wall, and subvertical joints dipping to the right wall of the tunnel
have to be considered as a sign of possible stressrelease.
It was also detected that when shear zones
associated to the joints system were encountered at
the face, the stress events usually turned out. This
fact was also detected in the core drillings carried out
at the tunnel face. This is clear in the photos shown in
Figure 14.

Figure 13: Stereographic analysis.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

5.5 Rock mass quality
The rock has been described according the Rock
Mass Rating. In all cases the RMR represents a goodquality rock mass. Figure 15 shows the relation
between the stress events and the RMR value.

Figure 14: Tunnel face at rockburst events in Headracetunnel.

Figure 15: Rock Mass rating (RMR) vs. Lithology.

5.6 Time after Blasting
A detailed analysis of the time in which the event
took place after blasting was carried out for the stressevents that took place in the Headrace tunnel. In afirst analysis the relationship between the stress classof the event and the time in which it took place wasanalysed. Figure 16 shows this analysis.

Figure 16: Stress class vs. Time Event.

The chart shows that the violent events occurredin range of 10 hours after blast; meanwhile it ispossible to detect lighter stress releases in a wide
range of more than 24 hours.
A statistical analysis of these events were carriedout in order to analyse the possibility of
implementing a re-entry strategy as it is usual in otherprojects or in mining activities. Figure 17 shows the
distribution of the stress events in relation with timeafter blasting.
Both analyses show that the time event
occurrence after blast presents a broad range thatmakes difficult to define a re-entry strategy.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 18: Normal distribution of the round length inrounds with stress event. (Theoretical curve).
Figure 17: Normal distribution of the Stress Event timeafter blast. (Theoretical curve).

5.7 Round Length
A rounds length analysis was carried out during
the excavation of Headrace tunnel in cases with stressreleases as a first step. Figure 18 presents the normal
distribution of round length in those cases in which astress releases occurred.

According to the results, rounds in which stressreleases turned out are between 2.5 and 3.5 m long.
In Figure 19 the number of stress releases per roundis presented. This chart shows clearly that the majorpart of the events occurred with rounds longer than
2.5 m. However, the tendency is not so clear.
The distribution of events according to stressclasses established by CCH and in relation with theround length has been analyzed. The Figures 20(a)(d) represent these analyses. The charts clearly showthat stress releases are more likely in longer rounds,
from 2.5 to 3.5 m.

Figure 19: Number of stress events vs. round length.

Figure 20(a)-20(d): Number of stress events per each stress class vs. round length.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

5.8 Global analysis
A final analysis considering all the previous
described parameters was done in order to define theweight of each factor and in order to define alarm
signs that permit to anticipate risk areas.

The overall analysis for the Headrace tunnel isshown in Figure 21. The stress events recorded ateach chainage have been represented in this chart,
according to the stress event classification developed,
in conjunction with the rock mass rating (RMR), theoverburden, the round length, and the lithology.

Figure 21: Stress factors comparison.

Based in the results, it is clear that the main
factor was the lithology, as most of the events andintense events were recorded in quartzmonzonite,meanwhile other lithologies such as volcanic breccias
presented less rockburst prone conditions. In
Quartzmonzonite, rockburst and/or stress releaseoccurred systematically. Meanwhile in subvolcanic
breccias “quiet periods” were recorded for a stretchof approximately 60 m. In massive intrusive rock
(granodiorite) some periods without stress released
evidences were detected, however it is not clear thereason for this lack of stress activity.

6. ROCKBURSTSUPPORT

PRONE

CONDITIONS

Several support measures were implemented tomitigate the rockburst prone conditions during the
excavation of the tunnels in the Cheves project, bothat the face and behind the face. The support design
included the following items:- Reduce the round length-

Destress the rock in advance with preconditioning blasting- Pre-stabilise the face with swellex bolts,
longer that the round length- Double shotcrete layer and welded wire
mesh to support the advanced section in
combination with rockbolts
During the excavation of the Headrace tunneland due to the intensity/severity of the stress events
several changes were introduced in the support withsuccessful results.
- Continuous monitoring of stress releases- Increased the bolt pattern in some areas- Fully grouted bolts (with a sleeve to protect
the beginning of the bolts) were
implemented in fault/shear areas with a huge
improvement in the rock support- The use of a high tensile chain link meshfixed to the section with split set bolts andmechanically installed- Modifications in the shotcrete thickness
were also implemented with good results

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016-

Additional swellex (3 m long) were
instructed to provide a pre-stabilization of
the section with good results- Different rounds length according to thereported stress behaviour
However, the design support has been working
out on the limit of its capacity as it has been affected
several times by huge stress events with dramaticconsequences. The designed system consisted of twolayers of shotcrete and welded wire mesh has been
affected several times in such way that it was
required a complete repair works in order to provide
enough safety environments to continue with theadvance of the tunnel.
The damages on the rock support have varied
from fissures on the shotcrete to collapse/projectionof concrete slabs, going through the welded wiremesh.

7. CONCLUSIONS
Rockburst has been extensively described indeep mining, but nowadays there are several civil
projects that require the construction of deep tunnels.

Under these circumstances it is necessary to consider
an overstress analysis of the projects in the design
stage.
It is important to establish an adequate
classification of the stress release events that takeplace during the excavation of the tunnels, and record
all relevant information in order to carry out acontinuous analysis of the project.
The stress classification developed for theCheves project has provided good results to avoid
misunderstanding of what is a stress release and what
can be considered a rockburst. However, it needs tobe improved and for this reason it has been
considered to subdivide the stress class 3 in three
categories considering the intensity of the damage.
Moreover, the damage severity classification
established by Kaiser et al. (1996) has been
considered.
It is important to differentiate between stressreleases, that not caused damaged (only cracking andbanging sounds), and rockburst where a damage tothe excavation and/or support took place.

Table 5: Stress classification proposed.
Stress Class

Denomination

0

Stress relief

1

Spalling

2

Intense Spalling3

3.I

Minor Rockburst

Damage severity > 0.25 m

3.II

Moderate Rockburst

Damage severity > 0.75 m

3.III

Major Rockburst

Damage severity > 1.50 m

Support measures to mitigate the rockburst
conditions have to be continuously adapted to thestress and ground conditions. However, it has been
proven that welded wire mesh provides safe
conditions to avoid rock and shotcrete slabs ejections.

8. ACKNOWLEDGEMENTS
The authors would like to express their gratitude
to SN Power, specifically Paul Lazenby and Kjell
Ingemarsson, for granting permission to publish thiswork.

9. REFERENCES
Aydan, Ö., Genis, M., Akagi, T., Kawamoto, T.
2001. Assessment of Susceptibility of Rock Burstingin Tunnelling in Hard Rocks. Modern Tunneling

Description
Loud Relief, slight crumbling: crackling, banging, crumbling insurrounding rock mass
Stress-induced spalling without rock fall: rock surface cracks
suddenly, creating scales up to 5cm, appearance of dust clouds
Stress-induced loosening or rock fall at lateral rock surface or facein unsupported area: rock breaks rough and very loud. Rocksupport system might be slightly damaged (Fissures in shotcrete).
Heavy Bangs with explosive rock fall: pieces or slabs of rock arethrown suddenly with loud bangs in radial direction from lateralrock surface (in supported and unsupported areas). The rock
support system is damaged (Cracks in shotcrete, torn-off anchors,bent ring beams).

Science and Technology, Adachi et al (eds), 2001
Swets & Zeitlinger.
Barton, N. 2002. Some new Q-value correlations
to assist in site characterization and tunnel design.
Int. J. Rock Mech. & Min. Sci. Vol. 39/2:185-216.
Bieniawski, Z. T. 1976. Rock MassClassification in Rock Engineering. Proceedings,
Symposium on Exploration for Rock Engineering,
Johannesburg, pp. 97-106.
Bieniawski, Z. T. 1989. Engineering Rock MassClassifications. New York: Wiley.
Brox, D. 2013. Evaluation of overstressing ofdeep hard rock tunnels. World Tunnel Congress 2013
Geneva Underground – the way to the future! G.
Anagnostou & H. Ehrbar (eds).
Cai M. and Champaigne D. 2009. The Art ofRock Support in Burst-Prone Ground. RaSiM7:Controlling Seismic Hazard and Sustainable
Development of Deep Mines.

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Cai M. 2011. Rock Mass Characterization andRock Property Variability Considerations for Tunnel
and Cavern Design. Rock Mech Rock Eng (2011)
44:379–399.
Castro, S.O., Soler, J. P., Andrade C.F and
Delucchi H.A. Rock Mass Stress Release in the
Alfalfal Main Water Tunnel: Evidence and Remedial
Actions.
Diederichs, M.S., J.L. Carvalho and T.G. Carter,
2007. A modified approach for prediction of strengthand post yield behaviour for high GSI rock masses instrong, brittle ground,1st Canada-U.S. Rock Mech.
Symp., 249-257.
Hoek, E. Brown, E. 1980. Underground
Excavations in Rock. Institution of Mining andMetallurgy.
Hoek, E., P.K. Kaiser and W.F. Bawden, 1995.
Rock Support for Underground Excavations in Hard
Rock. A.A. Balkema, Rotterdam, 215 p.
Hoek, E. & Diederichs, M. S. 2006. Empirical
Estimation of Rock Mass Modulus. Int. J. RockInternal
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ChevesHydropower Project. Constructora Cheves, SAC(joint venture Hochtief Solutions AG, SalfaCorp SA
and ICCGSA), Lima, Peru. Not published.
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ChevesHydropower Project. Contract Documents. Basic
Design Report. SNPower and Norconsult, Lima,
Peru. Not publishedMech. Min. Sci., 43, pp. 203-215.
Kaiser, P.K., Diederichs, M.S., Martin, C.D.,
Sharp, J. and Steiner, W. (2000) Underground Worksin Hard Rock Tunnelling and Mining, in ProceedingsInternational Conference on Geotechnical andGeological Engineering (GeoEng2000), 19–24
November 2000, Melbourne, Australia, pp. 841–926.
Kaiser, Peter K. 2006. Rock Mechanics
Considerations for Construction of Deep Tunnels in
Brittle Rock. Asian Rock Mechanics Symposium,
Singapore.
Kaiser, P. K. 2011. How highly stressed brittle
rock failure impacts tunnel design
Kaiser, P. K., S. Maloney, P. Vasak and G.
Wang, 2009. Seismic excavation hazard evaluation inunderground construction. 7th RaSiM6, Dalian,
China, 1-26.
Kaiser, P. K. and Cai M. 2012. Design of rock
support system under rockburst condition. Journal ofRock Mechanics and Geotechnical Engineering.
2012, 4 (3): 215–227
Kaiser, P. K. and Cai M. 2013. Critical review ofdesign principles for rock support in burst-prone
ground – time to rethink! Ground Support 2013 — Y.
Potvin and B. Brady (eds).
Lee, S.M., Park, B.S., Lee, S.W. 2004. Analysisof rockburst that have occurred in a water way tunnel

in Korea. Paper 3B 24 — SINOROCK2004
Symposium Int. J. Rock Mech. Min. Sci. Vol. 41, No.
3.
Malek, F.; Suorineni, F. T., Vasak, P. Strategies
for Rockburst Management at Vale Inco Creighton
Mine.
Martin, C.D., P.K. Kaiser and D.R. McCreath,
1999. Hoek-Brown parameters for predicting thedepth of brittle failure around tunnels. Canadian
Geotechnical Journal, 36(1):136-151.
Norwegian Geotechnical Institute, NGI (2013).
Using the Q-system (handbook). Rockmass
classification and support design.
Palmstrøm A. 1995. Characterizing Rock Burstand Squeezing by the Rock Mass Index. Design andConstruction of underground Structures, New Delhi,
23 - 25 February 1995
Palmstrøm A. 1996. Characterizing Rock Masses
by the RMi for Use in Practical Rock Engineering.
Tunnelling and Underground Space Technology, Vol.
11, No. 3, pp. 287-303.
Rocscience Inc. 1997, Examine3D Version 4.0 3D Engineering Analysis for Underground
Excavations. www.rocscience.com, Toronto, Ontario,
CanadaRocscience Inc. 2002, RocLab Version 1.0 Rock Mass Strength Analysis using the Generalized
Hoek-Brown failure criterion. www.rocscience.com.
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Rocscience Inc. 1999, Dips Version 5.0 Graphical and Statistical Analysis of Orientation
Data. www.rocscience.com, Toronto, Ontario,
Canada.
Stillborg, E.B. and Hamrin, H. 1990. Solving therock burst problem with Swellex. Tunnels
Tunnelling, p.67, 5pp., (in English), Mar. 1990.
Toper, A.Z., Kabongo, K.K., Stewart, R.D. andDaehnke, 2002. A. The mechanism, optimization andeffects of preconditioning. The Journal of The South
African Institute of Mining and Metallurgy

37

ISMS 2016

Paper No. 156

Rockburst mitigation experiences on underground projects in the Cheves
Hydropower project in the Peruvian Andes
Santiago Veyrat a, Jose-Miguel Galera b,*, Marcos Sancho caSubterra Ingeniería SL, Madrid, Spain, 28015
Subterra Ingeniería Ltda., Santiago, Chile, 7750181
c
Subterra Perú SAC, Lima, Perú, 18b

ABSTRACTThe main problems related with the design and construction of tunnels and caverns under high overburden are
analyzed in this paper. As an example, the recent experiences during the construction of the Cheves Hydropower
project in the Peruvian Central Andes are described. During its construction, 850 rockburst events were recorded,
enabling designers to collect data and make some correlations that may be useful for future projects.
KEYWORDS: tunnel, cavern, depth, rock support, rockburst.

1.

INTRODUCTION

Cheves Hydropower plant is located in thecentral highlands of Peru, close to Lima, in the basinsof the Huaura and Checras rivers. The project wasdeveloped by the “Empresa de Generación Eléctrica
Cheves SA”, a company of the Norwegian group
Statkraft. The construction, with a $400 million
budget for the civil works, is currently inoperation.The company responsible for construction
is a consortium (Constructora Cheves) formed by
Hochtief Solutions AG (Germany), SalfaCorp (Chile)and ICCGSA (Peru). In relation to the project design,
Norconsult, as Owner Engineering, was theconsultant company in charge of the permanent
works design, including the layout, the long-term
stability and the final support of the undergroundworks. Subterra, acting as the Contractor
Engineering, was in charge of the initial support of
the underground works, as well as of the geotechnicalengineering during the construction. This article
therefore only describes the work developed by both
the Contractor and Subterra.
The project includes the construction of two
concrete dams upstream from the headrace tunnel(Huaura and Checras dams), interconnected through atransfer tunnel of 2.58 m long. The second dam leads
the water to the headrace tunnel of about 10 km long.
The project also considered a third dam downstream
from the powerhouse (Picunche dam), whosefunction is regulation and irrigation.
To summarize, the Cheves Hydropower project’s
components are described as follows:*Jose Miguel Galera: jmgalera@subterra-ing.com- Huaura dam (concrete dam of 13 m high),- Transfer tunnel (hydraulic channel that leads thewater form Huaura dam to Checras dam, with alength of 2.580 and a cross section of 16 m2),
- Checras dam (concrete dam of 25 m high),- Headrace tunnel (9.693 m long and crosssections between 22 and 30 m2, where the firststretch has an inclination of 0.9% and the lastone 14%),- Surge tunnel of 700 m long and 14% and one
adit tunnel with similar dimensions but no so
step,- Powerhouse cavern (60 m long, 32 m high and15.50 m width) and Transformer cavern (27.5 mlong, 14 m high and 11.20 m width),- Access tunnel to the powerhouse and drifts(1.700 m in total),- Tailrace tunnel (3.312 m long and 25 m2) and- Picunche dam (earth dam of 15 m high).
Therefore, the total length of the tunnels,
considering the access tunnel and all the drifts isabout 20 km.
Figure 1 shows a longitudinal section of the
project showing all the already described componentsof the hydropower project.
As it can be observed, there is a section in the
Headrace tunnel, linked to the steepest stretch where
the overburden is systematically above 1.000 m,
being the maximum around 1.500 m. Basically, thedynamic or stresses related events took place in thattunnel section as well as in the cavern complex at thePowerhouse area.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 1: Longitudinal section of Cheves Hydropower project.

-

2.

GEOLOGY

Cheves Hydropower project is located in the
Huaura River Basin, within the Central Andean
Range. This region is close to the Nazca plate, andtherefore affected by active tectonics and highseismicity.
The geology of the area is complex, withvolcano-sedimentary, volcanic rocks; plutonic andrelated contact metamorphic groups.
Figure 2 shows a longitudinal section of the
project showing all the described geological groups.
The headrace tunnel and powerhouse area, inwhich the dynamic events were recorded, have been
excavated in hard rock: granites and hornfels.
In the case of the caverns, both are located in a
structurally complex area due to the presence of
intrusions of tonalite associated with subhorizontal
shear joints and metamorphic rocks.
The properties of the geological groups are as
follows:

Chimu Formation: formed by quartzitebanks interbedded with layers of quartz
sandstone, shale, and occasionally coallayers. Quartzite has a high strength and abrittle response, with multiple fractures
filled with iron oxide.
- Volcano-sedimentary rocks: belonging to
the Chimu formation, are formed by blocks
embedded in a green matrix, with amoderate-high level of fractures andweathering.
- Casma Group: andesite with a porphyry
texture.
- Stock Churin Bajo: formed by intrusive
rocks as tonalite, granodiorite and quartzmonzonite. These rocks have high strength,
and low to moderate weathering, with ironoxides fillings in the fractures.
Hornfels: metamorphic rocks resulting from thecontact between the andesite and the intrusive rock.
They are very silicified and brittle. The representativevalues for these formations at intact rock level are
shown in Table 1.
-

Figure 2: Geological longitudinal section of the project39

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Intact rock properties.
LITHOTYPE
Churin Bajo Stock(KsTi-qzmo)
Churin Bajo Stock (KsTi-hf)

σci (MPa)
RANGE
VALUE
110
100-150
125

Ei
(MPa)
44,00050,0002.6280-12090

2.6280-1202.6270-120100-150

LITHOLOGYρap(t/m3)

Tonalites

2.62

Tonalites(Fault zone)
Hornfels
Andesites (Fault Zone)

Casma Group (Ki-ca)
Andesites

Chimu Formation (Ki-ch)

Quartzites with shales
and sandstones
interbedded (Fault Zone)
Quartzites with shales
and sandstones
interbedded

As it was explained before, rockburst eventswere related to the two latest groups, high strengthand stiff lithology.

3.

ROCKBURST AND OTHER STRESSRELATED EVENTS

Rockburst was first recorded in the deep minesof South Africa, but is now becoming more importantin the Civil Engineering sector due to theconstruction of deep tunnels. Rockburst is defined asa violent and sudden failure of the rock mass, clearly
linked to excavations in competent rock withsignificant overburden, as well as in the presence ofstructures and dykes. As long as the overburden goesup, the connection between the natural stress and thestrength and/or stiffness of the rock mass increases,
and therefore the likelihood of rockburst increases as
well.
Figures 3 and 4 show an example of two
rockbursts that happened in Cheves project, the firstone behind the excavation face, near the Powerhouse
cavern, and the second one at the excavation faceduring the construction of the Headrace tunnel.

2.62

v

mi

0.24

25

36,000

0.24

25

90

49,500

0.24

19

80
110

32,00044,0000.24

25120-200

130

52,00030-80

40

15,00030-8060-120
30-80

40
70
40

15,00026,25015,0000.24

20

Figure 3: Rockburst in a drift near
the Powerhouse Complex.

The impact of this phenomenon can besummarized in the following points: accidents in thetunnel that may affect the workforce, costs linked tothe production stoppage, damage in the facilities andextra charges due to the repair works in the tunnel
and replacement of equipment and machinery.

Figure 4: Rockburst at the face excavation in
the headrace tunnel.

3.1. Description of the recorded stress events
Rockburst events in Cheves project took place inthe tunnels excavation with overburdens above 900
m, mainly in two geological formations, the intrusive
and the metamorphic rock.
These events boost themselves in the presence ofbrittle rock and geological structures, happening
either at the face excavation or behind the face in thereinforced sections. Most of the events occurred after
the blasting in the unsupported area, provoking
events ranging from sounds and cracks to violent
rock ejections. In some cases the events happened
behind the excavation, up to 500 m, damaging the
installed rock support. Other dynamic events were40

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

induced by the simultaneous excavation of multiple
drifts, principally in the powerhouse area.
All the recorded events were assessed and aclassification was performed in order to establish themagnitude of the event and take actions directed todefine suitable rock support and to ensure safety(Figure 5).

Stress Class

Description

Crackling and bangs in the surrounding rockmass.
Stress-induced spalling without rock fall:rock surface cracks suddenly, creating scales
1
up to 5cm, dust clouds.
Stress-induced loosening or rock falls atlateral rock surface or face in the2
unsupported areas. Rock support system may
be slightly damaged.
Heavy bangs and violent rock falls. Rockblocks and slabs are violently ejected. The
3rock support system is damaged.
Figure 5: Rockburst at the face excavation in the headracetunnel.
0

3.2 Variables involved in Cheves Hydropower project
There are many aspects involved in the rockburst
phenomenon. Kaiser and Cai (2012) summarized allof the related causes, namely: seismic events,
geology (in situ stress, lithology, beddings, dykes,
faults, etc.), geotechnical features (rock strength,
joint fabric, rock brittleness, etc.), and mining (staticand dynamic stress induced by mining, excavation
span, extraction ratio, excavation sequence, rock
support, etc.).
Records and analysis of all the rockbursts that
happened during the construction of Cheves
Hydropower project enabled the designers todetermine the most significant variables involved in
the phenomenon and establish control and mitigation
procedures as well as designing special rock supports
to ensure safe excavation.
It must be emphasized that about 850 rockbursts
were recorded during the construction.
The main variables are summarized as follows:a) Overburden: rockbursts started to happen
above 850 m of overburden, where thenatural stress is particularly high at about 23
MPa.
b) Horizontal in situ stress: the knowledge ofthe natural in situ stress field is essential forthe numerical design of the excavations. For
this reason, overcoring and hydro-fracturing
tests were performed in the vicinity of thepowerhouse, obtaining the following

principal stresses: σ1 = 21.7 - 22.1 MPa, σ2 =20.3 - 21.3 MPa, σ3 = 12.8 - 13.7 MPa. The
stress ratios K0 vary from 0.62 to 0.96,
showing a relatively low value. The in situ
stress measured presents an orientation
similar to the one obtained by geologicalestimations (N-45º-E).
c) Lithology: the most severe rockbursts
turned up in the most brittle rock, linked to
the Hornfel group. There were also
rockbursts, but less severe, in the intrusive
rocks (granodiorite and quartz-monzonite),but in these cases always with overburdens
above 1.000 m. For this reason, the relation
between rockburst and geomechanical rockmass quality has been analyzed.
d) Joint sets and related structures: there
were very unfavorable joint systems during
the tunnel excavation, like subhorizontal
joints and subvertical and subparallel to theaxis tunnel. In particular, the more severe
rockbursts were recorded in relation withlow dip structures.
e) Induced stresses: the excavation of multiple
faces at the same time, as well as theexistence of close excavations played a keyrole in the probability of rockburst events.
This issue had a significant impact on the
powerhouse area due to the great number ofclose drifts, as can be observed in Figure 6,
in which the rockburst events arehighlighted in orange (medium intensity)and red (high intensity).
f) Seismicity and active tectonics: Cheveshydropower project is located in a highly
seismic area, where a correlation between
natural seismicity and rockbursts was clearlyobserved.

Figure 6: Rockbursts record in the Powerhouse area.

41

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.

ROCKBURST ANALYSISThe assessment of 850 rockbursts in Cheveshydropower project enabled the designers to collectsome results and conclusions that may be useful forother projects. The following charts provide the most
relevant results obtained after analyzing the data.
Figure 7 compares the rockburst intensity andthe overburden. It is noticeable that 75% of theevents took place between 1,000 to 1,150 m ofoverburden. In this stretch the average was more than
1.0 events per linear meter of tunnel, and events
between 1,100 and 1,150 m of overburden took place
at a ratio of 3.5 events per linear meter of tunnel.
This distribution is strongly conditioned byothers factors, in particular by the lithology.

Finally, the relation between the blasting lengthand the number of events is analyzed in Figure 10.
It´s worth mentioning an increase in the number of
rockbursts in parallel to the increase of the blasting
length. It can be observed that there is no clear
relation between rockburst occurrence and theblasting length

Figure 8: Rockburst intensity vs. RMR index.

Figure 7: Overburden vs. rockburst and event by meter.

The rock mass rating (RMR) and the rockburst
intensity are analyzed in Figure 8. Most of the severe
events (stress class 3) belong to rock class II and I,
i.e. when the RMR is higher than 61.
Another interesting analysis is the relation
between the rockburst intensity and the time after
blasting (Figure 9). It must be highlighted that themost severe events are located in the first ten hours
after the blasting was carried out.

Figure 9: Rockburst intensity vs. time after blasting.

Figure 10: Blasting length vs. number of events.

5.

ROCK SUPPORT AND MITIGATIONPROCEDURESWorldwide research on controlling the rockburst
phenomenon provides guidelines to minimize the42

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

consequences and mainly guarantee the safety of theworkforce inside the tunnel.
Rock supports will inevitably be damaged after a
rockburst event, requiring repair works andreinforcements, but a proper design must provide a
flexible support that is enough to resist the dynamic
loads set by the rockburst, and therefore comply withthe following aims: reinforce, retain (rock mass
bulking) and hold, avoiding violent rock projections.
Figure 11 shows this concept.

Figure 11: Requirements for an adequate support for
dynamic events (Kaiser and Cai, 2012).

a)

Mechanicalscalingandreinforced
machinery in order to protect the workforce
at the tunnel face.
b) Apply a “sacrificial” layer of fibre
reinforced shotcrete at the face and install
temporary swellex rockbolts also at the face,with the aim of avoiding rock ejections fromthe face.
c) Install temporary swellex rockbolts in the
cross section just after shotcreting the firstlayer, in order to stabilize the section andensure the safety of the workforce during theprocess of finishing the installation of theremaining rock support.
Thefollowingprocedures
were
also
implemented as prevention measures against the
rockbursts:a) Preconditioning
blasting
ahead
theexcavation face, performed before theregular blasting, with the aim of reducing
the rock mass quality by creating new cracks(Figure 13).

In the particular case of Cheves Hydropower
project, the rock support was specifically designed tocope with rockburst events and high stress levels,
consisting of long grouted rock bolts and double
layer of fibre reinforced shotcrete with a welded wire
mesh embedded in the shotcrete, which provided therequired ductility against the dynamic loads.
Therock support was made of a highperformance shotcrete with an UCS between 40 and
50 MPa and 6-7 kg/m3 of plastic fibers oralternatively 40 kg/m3 of steel fibers, obtaining morethan 1.400 J in the panel test, according to the
EFNARC requirements. Figure 12 shows this conceptof a double-layered support.

Figure 13: Energy distribution in a preconditioning blastingwith 3 holes of 51 mm diameter charged with Slurrex.

Figure 12: Rocksupport designed for high stress levels.

Additional protection measures were also
considered during the excavation in rockburst prone
conditions:b) Change the shape of the section to a concave
geometry, as straight sidewalls always
accumulate higher stress than a curved
geometry.
c) Reduction of the blasting length. As it was
mentioned before, a reduction of the blasting
length may help to decrease the likelihoodof severe dynamic events. It will also
shorten the construction cycle and the time43

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016that the workforce is exposed under anunsupported section.
The following figure shows a scheme of thetemporary rock support installed at the face and thepreconditioning blasting layout:

Figure 14: Combination of protection and prevention measures at the excavation face in rockburst prone conditions.

6.

CONCLUSIONS
Rockburst has been extensively described indeep mining, but nowadays there are several civil
projects that require the construction of deep tunnels.
Under these circumstances it is necessary to consider
an overstress analysis of the projects in the design
stage.
Specific support measures shall be implemented
in the tunnel design in order to mitigate the adverse
effects of the rockburst and stress releases, especiallyto provide a safe environment for workers.
Each project shall be analyzed, however theexperiences from Cheves Project specifically can beused for extrapolation.
The support measures described in this paper
were effective during the construction period. The
support consisted of an integrated system (1)reinforced the rock mass to strengthen it, (2) retained
broken rock to prevent fractured block failure, and(3) held fractured blocks and securely tied back theretaining element(s) to stable ground.

7.

8.

REFERENCES

Kaiser, P. and Cai, M. (2012). Design of rock
support system under rockburst condition. Journal ofRock Mechanics and Geotechnical Engineering.
Stacey, T., Rojas, E. (2013). A potential methodof containing rockburst damage and enhancing safety
using a sacrificial layer. The Journal of the Southern
African Institute of Mining and Metallurgy.

ACKNOWLEDGEMENT

The authors want to express their gratitude, toHochtief Solutions AG: Hans Andersson, Wolfgang
Thoese, Carsten Rietschel and Carlos Leal. And also
to Statkraft: Paul Lazenby.

44

ISMS 2016

Paper No. 64
Destress blasting on the border of safety pillars
Petr Konicek a, Jiri Ptacek a* and Alejandro Mazaira aaDepartment of Geomechanics and Mining Research, Institute of Geonics AS CR v.v.i., (Institute of Clean Technologies),
Ostrava, Czech Republic 71000

ABSTRACT
Destress blasting used at the border of safety pillars represents a special kind of destress blasting. The main goal ofthis type of destress blasting is to separate relatively more deformed mining areas from a non-mined safety pillar
area such as a shaft pillar or cross-cut pillar, in order to reduce the impact of high stress concentration in areas
within the safety pillar. Destress blasting is carried out in rigid, competent rocks adjacent to hardcoal seams 5 m to 6
m thick at depths ranging from 700 m to 1000 m below the surface. Total explosive charge of up to 3450 kg is fired
simultaneously in three to seven fan-pattern and line-pattern boreholes drilled from the maingate and the tailgate,when the longwall face approaches to within round 100 m of the safety pillar border. Use of this type of destressblasting from hardcoal longwall mining in the Czech part of the Upper Silesian Coal Basin is described here. Naturaland mining conditions are described together with the design parameters of destress blasting, registered seismic
activity during longwall mining, and evaluation of the stress relief effect calculated from the monitored
seismological data. The present study argues for using this kind of destress blasting as a proactive rockburst
prevention method during mining of thick hardcoal seams. Destress blasting can decrease high stress levels andconsequently minimize rockburst hazards on the border regions of the safety pillars.
KEYWORDS: Coal mining, rockburst, destress blasting

1. INTRODUCTION
Rockburst is one of the most hazardous problems
encountered during underground excavations. Thisphenomenon always involves a violent energy releasewith large rock deformation and rock ejection thatcan cause severe damage to openings, equipment, andmine facilities, potentially also causing fatalities(Linkov 1996; Kaiser and Cai 2012). Rockburst is an
inherent problem found in overstressed rocks. The
stress redistribution caused by excavations induceshigh stress concentrations around the openings,
especially when the excavation is surrounded bythick layers of hard, competent rocks which arecapable of storing high amounts of strain energy. At
great depth, the mining-induced stress interacts withthe high in situ stress of the rock mass causing
unfavourable stress concentrations that can trigger
explosive rockbursts.
Destress blasting is a very important proactive
measure to reduce rockburst risk in areas which arehighly prone to violent rock failure in many mining
regions. Destress blasting has been used for almost a
century mainly in ore mining, but it also presents avery important destress method in the hardcoal
mining industry. It is nowadays used as a standard
destress technique in high rockburst risk areas inlongwall mining in the sedimentary deposits of theUpper Silesian Coal Basin (UCSB).
Destress blasting performed at the borders ofmining safety pillars is a special type of destress*Corresponding author – email ptacek@ugn.cas.cz

blasting and is referred to as the ‘cutting destressblasting’ method. This method aims to decrease thestress concentrations within the safety pillar area, andto protect the pillar from deforming due to mining
activity.

Figure 1: Location of the Upper Silesian Coal Basin.

This paper presents the results of three casestudies of cutting destress blasting application at themining of coal seam No. 504 of the Lazy Colliery, in
the Czech part of the UCSB (Figure 1). The
methodology of each case is described, as well as theblasting efficiency, which is assessed by thecalculated seismic effect.
2.

DESTRESS MODEL

Safety pillars are non-mined zones where therock mass is kept relatively intact in order to protect

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

important openings, transportation, and ventilation
for areas acting as shafts and main roadways.
Safety pillars usually experience significant
stress concentrations due to the stress migration fromthe surrounding mined out areas (Dvorsky andKonicek, 2005).
Cutting destress blasting is a special destressblasting performed at the borders of the safety pillars.
This kind of destress blasting has the main goal of
creating a physical separation between the deformed
mining areas and the non-deformed safety pillar area
in order to decrease the impact of additional stressinduced inside the safety pillar area. In this way thehigh stress concentrations can be reduced in specificrock mass regions on the boundary of mined out
areas, and lower the risk of rockburst in intact areasin the rock mass. This separation is achieved by
cutting the rock mass to create an artificial
discontinuity plane that isolates the safety pillar areaand protects it from deforming (Dvorsky andKonicek, 2005). In this way, more uniform load andstress distribution occurs in rock mass.
A cutting destress blasting is typically performedby firing a number of blastholes, all located in thesame plane. These blastholes can be drilled either

using a lineal layout (i.e. parallel to each other with
fixed spacing between them) or using a fan layout(i.e. all of them drilled from the same location but atdifferent angles) (Figure 2). Blasting parameters,such as blasthole length, orientation, and the
explosive charge, vary depending on the specificconditions of each area. Groups of blastholes are
generally fired in different stages and no firing timedelay between blastholes is used at each stage. Usingno delay favours the formation of a single breaking
plane between the blastholes, instead of the formationof large fractures in all directions around theblastholes.
The cutting destress blasting projects studied inthis paper were carried out at the ending part of fivepanels of the coal seam No. 504. Blasting works ofcases No. 1 and No. 2 (panels 140 914 and 140 704,
respectively) were performed to protect the shaft
safety pillar located at the center of the colliery.
Blasting works of case No. 3 (panels 140 302, 140
304, and 140 306) were performed to ´cut out´ thesafety pillar of SW cross-cuts area

Figure 2: Profile of the cutting destress blasting layout.

3.

SITE CONDITIONS

3.1. Geology
The coal seam No 504 is up to 6 m thick and islocated up to 800 m below the surface in the lower
part of the Sedlove Members (Figure 3). This
formation is a sequence of sedimentary rocks that ismainly formed by thick layers of competentsandstones, conglomerates and sandy siltstones. The
uniaxial compressive strengths of these sandstones
and the conglomerates range between 70 MPa and120 MPa (Konicek et al., 2013).

Layers of non-competent rocks such as mudstoneand siltstone also occur, although they are muchthinner and are generally adjacent to coal beds. Coalseams No. 512 and No. 530 have a thickness up to
8 m and are located between 50 m and 80 m above
the seam No. 504, depending on the location andabout 800 m below surface. The coal of this area has
a laboratory compressive strength average of 15 MPa(Konicek et al., 2013).
The Lazy Colliery is highly affected by brittle aswell as ductile deformations. The main brittle
tectonic elements in this area are large extensional
faults with orientation N-S and E-W and amplitudesof tens of meters, and ductile asymmetric anticlinal

46

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

structure with N-S direction of fold axis. Main
structures establish the limits of different mining
blocks in the colliery. Tectonic elements can act assignificant stress relief zones, but they also create
unregular stress fields in rock mass.

Figure 3: Simplified lithological section of the Sedlove
Members in the Lazy Colliery.

3.2. Geomechanics
Mined out panels from upper coal seams No.
512 and 530 and from adjacent areas must be taken
into account for the geomechanical analysis of thestudied areas. Stress migrates from mined anddeformed areas into intact zones of the rock mass thathave not been exploited yet. This additional stress inintact rocks produces dangerous stress concentrations
that can trigger rockburst during the excavation of
new longwalls or galleries. Safety pillars are highly
prone to suffer high stress concentrations because of
their low deformation level. For that reason, mining
works approaching safety pillar borders may
significantly increase the risk of rock failure andconsequently the rockburst.
Since the energy produced by rock failure rises
with the increase of rock strength and brittleness, theoccurrence of thick, competent rock strata with highUCS overlaying the seam No. 504 permits theappearance of high stress concentrations that can
induce intense rockbursts. Rockburst produced inpanels close to safety pillars can seriously worsen thesafety and stability not only in the working area, but
due to another additional stress, also into the safety
pillar itself.

Figure 4: Location of the safety shaft pillar, the SW crosscuts safety pillar and the performed cutting destress blasting.

47

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3.3. Mining
Coal seams of the Lazy Colliery are mined using
the longwall caving method. Typical panel sizes areseveral hundred meters long. The position andorientation of extracted panels in different coal seams
are generally not superimposed, due to unevengeological properties and coal pillars left in them(lesser seam thickness, faults etc.) In some cases, coalpillars are left to protect certain zones, such as in thesafety pillar areas (Konicek et al., 2013) (Figure 4).

4. CASE NO 1 – LAZYLONGWALL 140 914

COLLIERY

Destress blasting works were performed at the
longwall 140 914 before and during its excavation.
These works included the special cutting destressblasting, which was carried out at the border of thecentral safety shaft pillar.

Figure 5: Scheme of the cutting destress blasting carriedout in the longwall 140 914 at the border of the safety
pillar.

In order to create a physical boundary between
the safety pillar and the longwall area, two groups offive blastholes (a total of 10 blastholes) were drilledfrom the north and south gate-roads into the
longwall’s overburden. All blastholes were drilled inexactly
the same vertical plane, forming twosymmetric blasthole fans (Figure 5). The lengths ofthe blastholes ranged from 93 m to 100 m and their
inclination angles varied from 4º to 35º (upwards).
They all were drilled with a diameter of 93 mm.
Each group of blastholes was fired separately in
two stages, i.e. blastholes No. 41–45 in stage No. 12
and No. 141–145 in stage No. 13 (the stages were
numbered for the entire panel mining). Explosives inholes of each stage were fired without a time delay.
The explosive charge of each blasthole varied from595 kg to 780 kg, according to its length andposition. The total charge fired in each stage (No. 12
and No. 13) was 3450 kg. The average percentage ofthe loaded lengths of these blastholes was 74%. All
holes were pneumatically charged with gelatine type
explosive Perunit 28E and sand was used for thestemming. Blasting parameters are summarized inTable 1.
These two blasting stages were fired when the
longwall face was located about 158 m and 152 mfrom them, respectively. This distance wasconsidered enough to prevent undesirable rockdeformations in the safety pillar before it was isolatedby the cutting destress blasting.
A continuous seismic monitoring was carried out
during mining of the longwall No. 140 914 using
local and regional seismic networks and geophones
installed in the gate-roads of the panel. The results ofseismic monitoring showed that the seismic activity
had noticeably grown in the regions loaded byadditional stress concentration at the edges of themined parts of the upper coal seams. The seismic
events induced during the longwall mining weremainly located in its overburden, in the area outsidefrom the vertical projection of the upper minedpanels of seams Nos. 512 and 530, where theadditional stress was concentrated.
From the seismic monitoring it is also clear thatthe seismic activity rose with the increase of the rateof longwall face advance, the rate of mined coalvolume and implementation of destress blasting.
The efficiency of the cutting destress blasting
was evaluated by the seismic effect (SE), which is
calculated by the equation
𝐸𝑂𝐾𝐶
𝑆𝐸 =
𝐾𝑂𝐾𝐶 𝑄
where EOKC is the seismic energy calculated fromseismic monitoring in the Ostrava-Karvina Coalfield(OKC), KOKC is a combined coefficient characterized48

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

by natural and mining conditions in OKC (i.e. KOKC =2.1), and Q is the explosive charge (Konicek et al2013).
In this case, the calculated SE in both blastingstages was 33.1 and 54.2 respectively. This meansthat the energy released by each blasting was 33.1
and 54.2 times larger than the energy from the
explosive. The excess of energy measured in bothstages corresponds to the release of the strain energy
accumulated in the rock mass.

Hence, it can be stated that the cutting destressblasting carried out in this case had a very highdestress effect. The calculated SE can be also
evaluated by a qualitative classification according to
the criteria shown in Table 2 (Konicek et al 2013).
Thus, the efficiency of these cutting destress blastingwas ‘excellent’. It is seen from the high SE values
that the stress concentration at the border of thesafety shaft pillar was significantly high and it could
have induced rockburst phenomena if the destressblasting had not been applied.

Table 1: Destress rock blasting parameters conducted in longwall 140 914.
Stage

Blasthole number

Explosive charge

Released seismic energy

(-)

(kg)

(J)

SE

SE
evaluation

(-)

(-)

12

41-45

3450

2.40E+05

33.1

Excellent13141-1453450

3.80E+05

54.2

Excellent

Table 2: Classification for evaluation of the seismic effect(Konicek et al 2013).

Seismic effectEvaluation ofseismic effect (SE)SE < 1.7

Insignificant

1.7 ≤ SE < 3Good

3 ≤ SE < 6

Very good

6 ≤ SE < 12

Extremely goodSE ≥ 12

Excellent

5. CASE NO. 2 – LAZYLONGWALL 140 704

also finished at the border of the safety shaft pillar
and, in consequence, special destress blasting had tobe applied to isolate and protect the safety pillar areafrom the mining activity.

COLLIERYThe area of the longwall 140 704 wassignificantly influenced by additional stress induced
from mined panels in the upper coal seams Nos. 512
and 530, and from mined panels from the same seam
located next to it, to the south and to the east. The
occurrence of competent rock strata overlaying theseam No. 504 led to critical stress concentrations thatinduced two intense rockbursts that occurred soonafter the start of mining in this longwall. The virgin
stress state (vertical components varied between 12
MPa and 21MPa) and induced stress have been
determined there. Induced stresses reached up to fivemultiples of the original stress state (Ptacek et al.,2015). Due to the high rockburst risk of this area,rock failure prevention measures were implemented
as soon as the mining of this panel started, including
destress blasting. Destress blasting carried out in the
longwall 140 704 were very similar than thosepresented in the case No. 1. In this case, the longwall

Figure 6: Scheme of the cutting destress blasting carriedout in the longwall 140 704 at the border of the safety shaft
pillar.

49

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Again, two groups of five blastholes (a total
number of 10 blastholes) were drilled upwards into
the overburden strata; one group from thenortheastern gate-road (blastholes Nos. 71–75) andthe other from the southwestern gate-road (blastholes
Nos. 171–175). Each group was drilled with a fanlayout and all blastholes from both groups where
located in the same vertical plane (Figure 6). The 95
mm diameter blastholes were drilled with inclination
angles between 4º and 34º. The length of theblastholes ranged from 93 m to 100 m. All blastholes
were fired in two stages (i.e. one group per stage),and the explosive in both stages were fired without
time delay.
The explosive charge of each blasthole varied
depending on its length and position, ranging from
415 kg to 700 kg. The total amount of explosive firedin each stage was 2900 kg in first stage and 2975 kg
in second stage. The average percentage of thegelatine loaded lengths of these blastholes was 68%.
All blastholes were charged pneumatically with agelatine type of explosive and sand was used for thestemming. Blasting parameters are summarized inTable 3. Both stages were fired when the longwall
face was located about 168 m and 132 m from theholes, respectively. This distance was consideredenough to prevent undesirable rock deformations inthe safety pillar before it was isolated by the cutting
destress blasting.
Local and regional seismic networks were used
to register the seismicity induced by destress blasting.
The calculated SE (see in previous section) of thesecutting destress blasting was 24.6 for the first stage
and 44.8 for the second stage. According to theevaluation criteria shown in Table 2, destressefficiency of these blasting works was considered‘excellent’. These results show a very high stressrelease at the border of the safety shaft pillar, whichsuggests that an important improvement of the safety
conditions in both the longwall and the safety pillar
area was achieved by using destress blasting (Ptacek
et al. 2015).

Table 3: Destress rock blasting parameters conducted in longwall 140 704.

Stage

Blastholenumber(-)
71-75
171-175

Explosivecharge
(kg)
2900
2975

Released
SESE
seismic energy(-)
evaluation
(J)
(-)
19
1.50E+05
24.6
Excellent
20
2.80E+05
44.8
Excellent
which were located next to the south-eastern borderof the safety pillar in the seam No 504 (Fig. 7).
6. CASE NO 3 – LAZY COLLIERY
A total of 52 blastholes were drilled within the
LONGWALLS 140 302, 140 304 AND
rock mass between the coal seams Nos. 504 and 512
140 306
from three different roadways. The length of the
A safety pillar had been left in the third mining
blastholes ranged from 25 m to 80 m and all of themblock of the Lazy Colliery in order to protect thewere drilled with a diameter of 93 mm. Blastholes
galleries of the SW cross-cuts (SWC). This intact
501–528 were drilled in a linear layout along therock area starts from the coal seam No 606+605 at
roadways 40 380 and 40 390 (both located in thethe depth 240 m below surface and continues
seam No. 504), with inclination angle of 41º
downwards vertically to the level of the coal seam
(upwards)
and with 7 m of spacing between them
No. 504 (at up to 670 m below the surface). The(Fig. 7). Blastholes 529–533 were drilled in a fansafety pillar area is about 900 m long and 200 m widelayout from the end of the roadway 40 390 (locatedand has NNE-SSW direction. Mining activity around
50 m above seam No. 504) with inclination angles
the SWC safety pillar in the seam No. 504 could
ranging from 4º to 35º from horizontal (upwards).
produce undesirable rock deformations in the
Blastholes 1–14 were drilled in a fan layout fromprotected area. Moreover, additional stress fromroadway 30 309-4 (located in the seam No. 504) withadjacent mined panels in seam No. 504 and frominclination angles ranging from -58º (downwards) tomined panels in upper seams Nos. 512 and 530 could
29º (upwards). Blastholes 15–19 were drilled in a fan
also produce dangerous stress concentration in thelayout from the roadway 40 315 with inclination
intact rock of the safety pillar, what might induce
angles ranging from 8º to 31º (upwards). All
intense rockbursts.
blastholes were drilled exactly in the same vertical
For that reason, a large cutting destress blasting
plane. Blasting parameters are summarized in Table
was performed to protect the safety SWC pillar from4.
rock deformation and dangerous rock failure.
The blasting was performed in 13 different
Destress blasting works were designed to isolate thestages.
The number of blastholes fired in each stage
intact rock mass of the SWC safety pillar from thevariedfrom
3 to 7. Depending on the blasthole lengthgoaf over longwalls 140 302, 140 304 and 140 306,

50

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

and its position, the lengths of the charges varied
between 18 m to 60 m and the stemming lengths
from 7 m up to 20 m. The amount of explosive firedin each stage ranged between 1130 kg and 2760 kg.

All charges in each stage were fired simultaneously(no delay). The blastholes were charged
pneumatically with plastic explosive Perunit 20 andsand was used for the stemming.

Figure 7: Scheme of the cutting destress blasting carried out in the longwalls 140 302, 140 304 and 140 306 at the border of theSW cross-cuts safety pillar.

Stages Nos. 1–5 were fired before the coal
extraction in adjacent longwalls 140 302, 140 304
and 140 306 had started. Stages Nos. 6–12 were fired
at a distance of 350 m to 240 m from advancing
longwall face 140 302. Stage No. 13 was fired at a
distance of 430 m from advancing longwall face 140
304 (longwall 140 302 was already finished).
According to registered seismicity in the area, the SEof each blasting stage has been calculated (seeprevious section). The blasting works at the border of
the SWC safety pillar presented different destressefficiency levels. Thus, stages Nos. 7 and 8 were‘extremely good’ (SE was 6.3 and 7.4), stages Nos.
1–6 and 10–13 were ‘very good’ (SE values ranged
from 3.2 to 5.9) and stage No. 9 was ‘good’ (SE was2.8). These results show an important destressefficiency at the border of the SWC safety pillar,
although it was lower than in the two cases presented
above. No rockbursts occurred during further
advancing of the mining works in the longwalls 140
302, 140 304, and 140 306 after the cutting destressblasting was performed. This fact can be considered
as a sign of improvement of the stress conditions in
the area surrounding the SWC safety pillar.

51

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 4: Destress rock blasting parameters conducted in longwalls 140 302, 140 304 and 140 306.
Stage

Blastholenumber

Explosivecharge(-)(kg)

Released

SESE

seismic energy

evaluation

(J)

(-)

(-)

1

501-504

1560

1,70E+04

5.2

Very good2516-5191656

1,50E+04

4.3

Very good3505-5081656

1,50E+04

4.3

Very good4

520-5231656

1,20E+04

3.5

Very good5

512-5151688

2,10E+04

5.9

Very good

6509-5111130

1,30E+04

5.5

Very good

7524-5271728

2,30E+04

6.3

Extremely good

8

1-7

1488

2,30E+04

7.4

Extremely good

9

12-14

1275

7,60E+03

2.8

Good

10

8-11

1296

1,50E+04

5.5

Very good11528-5301344

1,10E+04

3.9

Very good

12531-5331506

1,00E+04

3.2

Very good

13

15-19

2760

2,00E+04

3.5

Very good

7. CONCLUSION
Over the years, different safety pillars have been
established in the Lazy Colliery in order to protect
important mining infrastructures. Although mining
activity is not carried out in these protected areas,coal extraction in adjacent panels can induce
undesirable rock deformation and dangerous stressconcentration within the safety pillars. Proactive
destress measures have been used to avoid these
problems when the faces of the longwalls in the seamNo. 504 were approaching the central safety shaft
pillar, or the safety pillar of the SW cross-cuts. The
implementation of cutting destress blasting at theborder of these safety pillars has allowed to cut out
the rock mass to create an artificial boundary
between the safety pillar areas and the longwall areas.
This separation has reduced the stress concentrations
encountered in the intact rocks of the safety pillar
limits. Seismic monitoring showed that for all cases,
blasting induced beneficial stress release. The
calculated seismic effect of all blasting stages wasevaluated as good, very good, extremely good andexcellent. After the cutting destress blasting were
performed in the selected areas, coal extraction in thementioned longwalls finished satisfactorily without
any occurrence of rockbursts or other incidents inneither the longwall areas, nor the safety pillar areas.
Therefore, the main aims of the cutting destressblasting were achieved.

8. ACKNOWLEDGEMENT
This article was written in connection withproject ICT - Sustainability program. Identification
code: LO1406. Project is supported by the National
Program for Sustainability I (2013-2020) financed by
the state budget of the Czech Republic.

9. REFERENCES
Dvorsky, P., Konicek, P., 2005. Systems of rockblasting as a rock burst measure in the Czech part ofUpper Silesian Coal Basin, In Proceedings of the
Sixth International Symposium on Rockburst and52

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Seismicity in Mines, pp 493–496, (The Australian
Centre of Geomechanics: Perth).
Kaiser, P and Cai, M, 2012. Design of rock
support system under rockburst condition, Journal ofRock Mechanics and Geotechnical Engineering,
4(3):215–227.
Konicek, P, Soucek, K, Stas, L and Singh, R,
2013. Long-hole destress blasting for rockburst
control during deep underground coal mining,
International Journal of Rock Mechanics and Mining
Sciences, 61:141–153.
Konicek, P., Ptacek, J, Stas, L, Kukutsch, R,
Waclawik, P and Mazaira, A, 2014. Impact ofdestress blasting on stress field development ahead ofa hardcoal longwall face, Rock Engineering andRock Mechanics: Structures in and on Rock Masses Proceedings of EUROCK 2014 (ed: Alejano,
Perucho, Olalla and Jiménez ), pp 585–590 (Taylor
and Francis: London).
Linkov, AM, 1996. Rockbursts and theinstability of rock masses, International Journal ofRock Mechanics and Mining Sciences &Geomechanics Abstracts, 33(7):727–732.
Ptacek, J., Konicek P., Stas L., Waclawik P.&
Kukutsch R., 2015. The rotation of principal axes andchanges of stress due to mine induced stresses.
Canadian Geotechnical Journal, 2015, 52(10), 14401447.

53

Paper No. 58

ISMS 2016

Powered support selection for longwall workings in dynamic load conditions
Stanisław Pruseka, Sylwester Rajwab, Andrzej Walentekb and Wojciech Masnyb*ab

General Director of Central Mining Institute, Plac Gwarkow 1, Katowice, Poland.
Department of Extraction Technologies and Mining Support, Central Mining Institute, Plac Gwarkow 1, Katowice, Poland.

ABSTRACT
Currently in Poland hard coal is mined in two Coal Basins namely Upper Silesian and Lublin. In Poland, there were
30 underground hard coal mines that produced 72.5 million tons of coal in 2014. For underground hard coal (steamcoal and coking coal) seam extraction, the longwall method is used and retreat longwalls with natural roof caving in
the gob are the most common. Currently it is estimated that about half of the hard coal output in Poland originatesfrom seams located in areas of rock burst hazard. In this paper, the most important data concerning the geologicaland mining conditions in Polish hard coal collieries are presented with particular emphasis on tremors, rock bursts,
and fatalities. Moreover, the article shows information about seismic events which occurred between 2003 and 2012
in underground mines belonging to one of the coal companies in Poland. In addition, negative consequences of thosedynamic phenomena in the longwall workings are described. In order to avoid damage of powered supports in geomining conditions where dynamic phenomena occur, different types of protective means are applied. In the paper
the methodology of assessing the powered support yield ability is described.

1. INTRODUCTION
In Poland the production of hard coal (i.e. steamcoal and coking coal) is conducted in increasingly
harder geological and mining conditions, resulting
from the still growing depth of mining operations andnumerous former exploitations in the mined longwall
panels in the form of edges and/or residues. These
factors generally increase the level of natural hazard
in Polish mines. A very important one is rock burst
hazard associated with the occurrence of rock mass
tremors. The hazard directly affects both personnel
safety and the continuity of coal production.
Rock mass tremors induced by mining operations
may result in rock bursts or decompressions. According
to Polish regulations (Ordinance of the Minister ofInternal Affairs and Administration of 2002) a rock burst
is defined as a dynamic phenomenon caused by a rockmass tremor which results in destroying or damaging aworking, or its fragment, leading to the complete orpartial loss of its functionality or making it dangerous touse. While decompression is defined as a dynamic
phenomenon caused by a rock mass tremor which causes
damage to a mine working (or its fragment), it does not
result in loss of functionality nor renders it unsafe for
personnel.
Hard coal mining operations, in areas where
dynamic phenomena occur, requires considering both
static and dynamic load while designing support bothfor headings and longwalls, as, when a tremor occurs,
there is an increase in the value of load exerted on a
support, and the main task of a properly designed
support ought to be maintaining the stability of a*Corresponding author – email: w.masny@gig.eu

mine working and providing the proper level ofsafety for personnel.
This article presents basic information
concerning the hard coal mining industry in Poland,with special attention to data on rock mass tremors.
Then, the most common forms of damage to alongwall powered support resulting from dynamic
phenomena are characterised. There is also
information on a method applied in Polish mining
industry to secure a powered support against effects
of additional load resulting from rock mass tremors.

2. GENERAL CHARACTERISTICS
HARD COAL MINING IN POLAND

OF

Hard coal deposits in Poland are mined in twocoal basins, namely Lublin Coal Basin (LZW) andUpper Silesian Coal Basin (GZW). Lublin CoalBasin is located in the south-eastern part of Poland,near the border with Ukraine. At the moment one
coal mine - LW Bogdanka, operates there. The Upper
Silesian Coal Basin is located in the south of Poland
near an urban agglomeration, with Katowice in its
centre. Mining operations in the Upper Silesian CoalBasin have been conducted for over 200 years.
In 2014, there were 30 underground hard coalmines operating in Poland, which produced 72.5
million tons of coal. The basic hard coal mining
system is the longwall system with single gateroads.
In 2014, there were 118 operating longwalls(Cybulski and Malich 2015). The average depth ofmining operations was slightly over 700 m. In all themines coal is produced in multiple seams which often

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

results in an increase in rock burst hazard due toinfluences of former exploitation like edges orresidues of previously mined seams. There are also
other hazards in Polish mines: seismic, caving, gas,dust, water, climate, radiation and fire.
In the conditions of the Polish mining industry inlongwalls with roof cave-in, two-legged shield
supports with a lemniscate system are most common.
In the type of support, two-stage legs, more seldom
one-stage ones with mechanical or hydraulicextenders, are applied. The inside diameter of thelegs is usually between 200 and 250 mm. Recently,
there has been a tendency to increase the inside
diameter of the leg casings to 300 mm and more,which results in the necessity to increase the section
pitch to 1.75 m. An increase in setting load and yieldload of a section is tightly associated withdeteriorating mining conditions and its aim is toprovide good conditions for supporting the roof in a
longwall. The most numerous group of powered
supports are the ones of minimum height ranging
between 0.8 and 1.2 m, and maximum between 3.1
and 3.6 m. Supports of higher operation height range(up to 5.0 m), are rarely used (Rajwa et al. 2009).
Between 2003 and 2014 hard coal mining
operations in the Upper Silesian Coal Basin resulted
in approximately 14,000 tremors of seismic energy E≥ 105 (local magnitude, ML≥1.7) and 32 rock bursts
which caused material and personnel losses. In recent
years, 19 tremors have had energy E ≥ 10 8 J, and two
had E ≥ 109 J (Stec 2015).
Table 1 presents coal production in Poland
between 2003 and 2014, including production inseams threatened by rock bursts, and the number ofrock bursts, accidents, and length of damaged
workings in running meters (Patyńska 2015).
Data presented in Table 1 show that in 2003–
2014 hard coal production decreased from slightly
over 100.0 million tons to 72.5 million tons. In theanalysed period, between 39% and over 50% of coal
was produced in seams with rock burst hazard. As aconsequence of the rock bursts a total of 520 metresof mine workings was destroyed, and approximately
3,600 metres of mine workings was damaged.

3. MOST COMMON TYPES OF DAMAGE
TO POWERED SUPPORT CAUSED BY
ROCK BURSTS AND DECOMPRESSION
Within the framework of the project acronymed
I2Mine titled “Innovative Technologies and Concepts
for the Intelligent Deep Mine of the Future”, realized
by the Central Mining Institute, consequences of rockbursts and decompressions which occurred in 20032012 in all the coal mines of Kompania Węglowa
S.A (KWSA), the biggest producer of hard coal in theEuropean Union, were analysed. In the period, in
KWSA’s coal mines there were 18 rock bursts and 14
decompression events. It was observed that 76% of
the rock bursts and decompression events occurred
during mining operations in longwall panels, 24% ofthemoccurredwhile
driving
roadways.
Consequences of rock bursts and decompression,
which coincided with longwall operations, weremainly apparent in gateroads (49% of cases).
Moreover, in 31% of cases the damage was observedin longwalls themselves and in 20% in other adjacentmine workings.

Table 1: Total coal production, including production in seams threatened by rock bursts, accident rate, number of rock bursts,
number of accidents, and length of workings damaged by rock bursts in 2003–2014 - (Patyńska 2015).
Production in
Total
Accidents related
Consequences
seams threatened
production
to rock bursts
in workings
Accident rate
Numberby rock bursts(accidents/Yearof rock
other/production)
bursts% ofdestroyed anddamagedmillion tons
fatal(serious
totalcollapsed (m)(m)
and light)
2003
100.40
41.8
40.9
0.18
4
2
16
110
145
2004
96.99
39.2
39.4
0.11
3
0
11
0
358
2005
99.50
41.01)
41.21)
0.13
3
1
12
0
270
2006
94.50
42.15
44.6
0.25
4
4
20
0
> 510
2007
87.40
44.61) 49.431)
0.11
3
0
10
0
530
2008
83.60
41.92)
50.12
0.31
5
0
26
0
710
2009
77.50
34.33)
43.8
0.06
1
0
5
0
101
2010
76.10
35.84)
47.04
0.18
2
2
12
30
87
2011
75.50
34.25)
45.36
0.08
4
1
6
0
168
2012
79.20
37.60
47.47
0.04
1
1
2
1701
2101
2013
76.47
36.90
48.25
0.07
1
0
5
50
113
2014
72.50
36.00
49.66
0.00
1
0
0
160
390
1

- approximated data55

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 2 shows numerical values of the mostimportant parameters characterising dynamic
phenomena. Load coefficient ntz, presented in Table 2
is calculated with the following empiricaldependence presented by Biliński (2005).

Percentage of type of damage, %0 3 6 9 12 15 18 21 24 27 30 33 36
Coal burst from face
Longwall vertical convergence
Damaged roof support

Table 2: Basic parameters of rock bursts anddecompression occurring in Kompania Węglowa S.A.’s
mines, 2003-2012 (Prusek, Masny 2015)
Phenomenon
Parameter
Rock burst
Decompression
min

max

min

1.10

1.51

1.05

Roof sagFloor heave
Damaged support leg

max

Seismic energy of
7.0E+05 2.0E+08 4.0E+04 8.0E+07
tremor, (J)Peak particle
0.064
0.598
0.014*
0.353
velocity PPV, (m/s)
Depth of mine
630
1,085
545
1,130
working, (m)Distance between
tremor hypocentre
24
567
37
572
and tremor effects,(m)Vertical distance
between tremor
3
245
10
460
effects and tremorprone layer (m)coefficient ntz

Fractured coal face

Damaged construction of section
Floor cracking

Figure 1. Types of damage to longwalls and shield
support caused by dynamic phenomena, %(Prusek and Masny 2015).

Following the data presented in Figure 1, we canconclude that in longwalls, due to the dynamic
influence of the rockmass, coal bursts from the
sidewall into the working – 33% were most common(Figure 2a). In over 18% of longwalls there were roofsags (Figure 2b).

1.53

* PPV is estimated due to low accuracy to locate tremor
hypocenter

Data presented in Table 2 show that workings
and their support were damaged at seismic energy oftremor of 4.0E+04 J and relatively low loadcoefficient ntz=1.05. A probable cause of such asituation in such cases was significantly high staticload exerted on a support prior to a tremor, justbefore the dynamic phenomenon.
The calculated values of peak particle velocity
PPV, being an empirical criterion of assessing
stability of workings subjected to the influence ofmine tremors, or the analysed 18 rock bursts and 14
decompression events were contained between
0.014 m/s and 0.598 m/s. The values are confirmed
by Mutke’s (2008) research. He determined that in
the conditions of Polish hard coal mines workings
lose stability when PPV is between 0.050 and 1.000
m/s.
The conducted analyses of dynamic phenomena
in KWSA’s mines enabled determination of the mostcommon forms of damage to workings and support inlongwalls, see Figure 1.

Figure 2. Characteristic forms of damage to longwall
caused by rock bursts or decompressions (Prusek and
Masny 2015).

Coal bursts from sidewall into a working (Figure2a) result from the fact that the coal face, usually of
the lowest strength parameters, is the largest surface
of a longwall which is not secured with a shield
support. Only in two of the analysed rock bursts anddecompression events was a coal burst additionallyaccompanied by roof sag in the tip to face distance.
Another characteristic form of damage observed in
longwalls, associated with dynamic phenomena, isconvergence, as it is presented in Figure 2b. Moreoften it is caused by a floor heave than by a roof sag(Prusek and Masny 2015).

56

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Referring to the most common types of damage
to powered supports in a longwall, it can beconcluded that they affect mainly: legs, valve
batteries, spherical head connections between the legs
and canopy/base, and lemniscate bars. Hydraulic legs
are most often torn or their rod is broken, as shown in
Figures 3a and 3b.

Figure 3. Damage to hydraulic legs of powered roof
support caused by dynamic phenomena; a) - torn, b) –broken (Prusek and Masny 2015).

4.

PROTECTING POWERED SUPPORTFROM CONSEQUENCES OF ROCK
BURSTS

A lot of actions have been taken to limit
consequences of damage to powered support or ofstability loss in mine workings. It means preventing
rock bursts with periodic destressing in zones where
they concentrate or inducing rock mass tremors. The
most often applied methods are: watering a seam,
destressing drilling, loosening blasting, torpedo
blasting, directed hydrofracturing of rocks, directed
blasting fracturing, and destressing a seam throughmining adjacent seams (Brauner 1994; Junker et al.
2006). Moreover, there are also various types ofunderground tests (Li et al. 2014; Turek et al. 2015)
and laboratory tests (Player et al. 2008) aimed atassessing the influence of increased load induced byseismic phenomena on the support and stability ofmine workings.
According to Polish legislation (Ordinance of the
Minister of Economy of 2002) a powered roof
support which is to work in longwalls driven in areasof rock mass tremors has to be flexible to absorb
dynamic load. That is why, for many years, theCentral Mining Institute has been conducting
research into assessing the flexibility of powered roof
supports (Prusek et al. 2005; Rajwa et al. 2009;Stoiński 2015; Stoiński et al. 2015). By “support
flexibility”, according to GIG’s methodology, wemean the property of a powered roof support whichenables it to absorb dynamic load safely, without
exceeding values of its safety factor coefficient. The
Central Mining Institute’s method assumes thathydraulic legs and flow rate of the hydraulic system
are the key elements making a given support flexible.
The calculated minimal height of liquid column inthe under piston space of a hydraulic leg (PT) and thedetermined flow rate of the system (together with ayielding valve) allows determination of the operation
height range of a powered support, at which it isconsidered to be flexible under dynamic load(coefficient ntz). In the calculations the value ofmaximum load on a leg and its nominal load arecompared, in accordance with the following
condition:(1)
Fmax < k·FN
where:
Fmax – value of maximum expected load on leg,considering rock mass tremor energy, N
FN - leg nominal load, N.
k – safety factor coefficient for hydraulic leg
determined in laboratory (usually 1.5 or 2.0).
The value of maximum forecast load of a leg
Fmax is determined analytically with the course ofload versus time f(t), based on a model of one degreeof freedom, and the equation (Stoiński et al. 2015):
1{Fw + Fd [1 + kd e−δ ⋅t − sin(ωt − ϕ )]} (2)f (t ) =cos α
where:
FW – leg setting load, N,
Fd – dynamic force of load, Fd = ntz ⋅ Fr − Fw , N,
Fr – yield load, N,
ntz – load coefficient,kd – computational coefficient,ω – angular velocity, rad/s-1,
φ – shift angle of the force with respect to input
function, rad,α – yaw angle of the leg from the normal to the
support base, rad,57

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
δ – equivalent damping resulting from hydraulicvalves and rock displacement resistance, s-1,t – time, s.
Flexibility of a section is also associated withflow rate of the hydraulic system, applied to limit
pressure in the under piston space of a leg. It is
important the configured hydraulic system securing
the under piston space of a hydraulic leg does not
limit flow Qu in selected yielding valves. The
hydraulic system ought to have both optimised liquid
streams geometry, and determined characteristics offlow of given elements in the whole system. Flow ofliquid in the leg hydraulic system can be assessed inlaboratory tests (Stoiński 2015) or by using numericalmodelling based on ANSYS CFX software (Fig. 4)(Doległo et al. 2009). Figure 4 presents a sample
result assessing flow of liquid in the hydraulic systemsecuring the space under piston.

Figure 4. Assessment of flow of liquid in leg hydraulicsystem performed with ANSYS CFX software (Doległo etal. 2009).

The factors which in practice are most often
considered while assessing flexibility of the support
are: value of load coefficient ntz, flow rate of theyielding valve of a hydraulic leg Q and ratio ofsetting load and yield load n0. An example of theassessment of powered support flexibility at heights
between 1.8 and 3.4 m, applied in conditions whererock mass tremors occur are presented in Figure 5.
2,6Q=150 l/min
Q=400 l/min
Q=1000 l/min

2,4

ks=Fmax/FN

flexibility for k=2,0
no flexibility for k=1,5

1,8
1,6
1,4

Statistical data presented in the article andanalyses concerning the consequences of observedrock bursts and decompression events prove that they
are phenomena posing a threat to personnel safety,
and have a significant influence on the continuity of
production. Recent years’ practice showed that by
applying a proper set of rules and safety measures it
is possible to limit the above-mentioned threatssignificantly. According to the GIG’s method, toimprove flexibility of a powered roof support,
presented in the article, it is believed that sufficiently
strong construction of the leg is significant. The
construction ought to ensure its further operatingwhen pressure in its under piston space increases tothe double value of nominal pressure (safety factor
coefficient k=2.0). Then, the flow of the liquid stream
is optimized and a yielding valve of flow rate
resulting from the forecast dynamic load is selected.
Moreover, it is favourable, from the point of view of
the ability to absorb greater dynamic load by apowered roof support, to apply possibly the highest
values of setting load (value of coefficient n0
increases). It is also possible to try to lower values ofyield load. However, such a decision ought to bepreceded with other analyses concerning proper cooperation between the powered roof support and therock mass to stabilise the roof of a longwall.

Article presents a brief part of work carried out by
the Central Mining Institute within the frame ofresearch under the project: I2M Innovative
Technologies and Concepts for the Intelligent Deep
Mine of the Future. The project was implemented
under The Seventh Framework Programme of theEuropean Union.

no flexibility for k=2,0
no flexibility for k=1,5

k=2,0

5. SUMMARY

6. ACKNOWLEDGEMENTS

2,2
2,0

Proper selection of flow rate of yielding valves Q
has a significant influence on support shieldflexibility. In Figure 5 it can be observed that anincrease in flow rate of the yielding valve results in
an increase in the range of height of the support at
which it is flexible for the calculated (determined)
dynamic load. For the yielding valve of flow rate
Q=1000 l/min, the analysed shield support, with thelegs tested in laboratory conditions at safety factor
coefficient k=2.0, meets the flexibility condition in
the height range of 1.85–3.30 m, while for coefficient
k=1.5, it does in the height range of 2.35–3.30 m.

k=1,5
flexibility for k=2,0
flexibility for k=1,5

1,2
1,6

1,8

2,0

2,2

2,4

2,6

2,8

3,0

3,2

3,4

Section height, mFigure 5. Change in leg overload coefficient ks dependingon operation height of shield and flow rate of yielding
valve Q (assumptions: coefficient no=0.66; values ofload coefficient ntz=1.2) (Prusek 2015).

7. REFERENCES

Biliński A. (2005): Metoda doboru obudowyścianowych wyrobisk wybierkowych i chodnikowych
do warunków pola eksploatacyjnego (Method of58

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016selecting support for conditions in mining panel).
CMG Komag, Gliwice.
Brauner, G. (1994): Rockbursts in coal mines
and their prevention. Balkema, Rotterdam, str. 144.
Cybulski K., Malich B. (2015): Zagrożenie
pyłowe.: Raport roczny o stanie podstawowych
zagrożeń naturalnych i technicznych w górnictwiewęgla kamiennego 2014 (Dust hazard: Yearly reporton basic natural and technical hazards in hard coalmining in 2014). Praca zbiorowa pod kierunkiem J.
Kabiesza. pp. 41-60.
Doległo L., Gil J., Stoiński K. (2009):
Analityczna ocena wydajności objętościowej układu
hydraulicznego stojaka zmechanizowanej obudowyścianowej (Analytical assessment of volumetricefficiency of hydraulic system of a powered roof
support leg ). Maszyny Górnicze 4/2009 pp 9-18
Junker M. et al. (2006): Gebirgsbeherrschungvon Flözstrecken. Verlag Glückauf, Essen.
Li L., P. Hagan P., Saydam S. (2014): A review
of ground support systems performance subjected to
dynamic loading. Conference Paper, DOI:
10.1201/b16955-183 Conference: EUROCK 2014,
At Vigo, Spain, Volume: Rock Mechanics and RockEngineering: structures on and in rock masses.
Mutke G. (2008): Stability of the undergroundmine workings in the near-field zone of seismic
events. In : 21st World Mining Congress 2008 – New
Challenges and Vision for Mining. Underground
Mine Environment. 7-12 September 2008 – Poland –Cracow. University of Since & Technology (AGH),
pp. 89-97.
Patyńska R. (2015): Zagrożenie tąpaniami.:
Raport roczny o stanie podstawowych zagrożeń
naturalnych i technicznych w górnictwie węgla
kamiennego 2014 (Rock burst hazard: Yearly reporton basic natural and technical hazards in hard coalmining in 2014). Praca zbiorowa pod kierunkiem J.
Kabiesza. pp. 96-107.
Player, J. R., E. Villaescusa, and A. G.
Thompson. 2008. “An examination of dynamic test
facilities.” In 2008 Australian Mining Technology
Conference, Sep 16, 2008, Twin Waters Queensland:
The Australasian Institute of Mining and Metallurgy.
Prusek S. (2015) : Stateczność wyrobiskaścianowego podczas eksploatacji pokładów węgla
kamiennego z zawałem skał stropowych (Stability of
longwall during hard coal mining operations withroof caving). Książka w druku.
Prusek S., Masny W. (2015): Analysis ofdamage to underground workings and their support
caused by dynamic phenomena. Journal of Mining
Science, Vol. 51, No. 1, pp. 63–72.
Prusek S., Rajwa S., Stoiński K. (2005):
Kriterien zur Abschatzung des Risikos vonStrebschaden. Glückauf-Forschungshefte 2005, no 3,
pp. 92-95
Rajwa S., Masny W., Prusek S. (2009): Powered
Support in Conditions of Rock Mass Tremor
Occurrence in the Polish Mining Industry. Aachen
International Mining Symposia, 5th International
Symposium – High Performance Mining, RWTH
Aachen, pp. 359-373.
Rozporządzenie Ministra Gospodarki z dnia 28
czerwca 2002 r. Dz. U. Nr 139 poz. 1169 zpóźniejszymi zmianami, w sprawie bezpieczeństwa ihigieny
pracy,
prowadzenia
ruchu
oraz
specjalistycznego
zabezpieczenia
przeciwpożarowego w podziemnych zakładachgórniczych (Ordinance of the Minister of Economy
of 28 June 2002 on occupational health and safety,
management of operation and specialist fire
protection in mining facilities extracting mineral
resources).
Rozporządzenie Ministra Spraw Wewnętrznych i
Administracji z dnia 14 czerwca 2002 r. Dz. U. Nr
94, poz. 841 z późniejszymi zmianami, w sprawie
zagrożeń naturalnych w zakładach górniczych(Ordinance of the Minister of Internal Affairs andAdministration of 14 June 2002 on natural risks inmining plants)
Stec K. (2015): Zagrożenie sejsmiczne. W:
Raport roczny o stanie podstawowych zagrożeń
naturalnych i technicznych w górnictwie węgla
kamiennego 2014. Praca zbiorowa pod kierunkiem J.
Kabiesza. Główny Instytut Górnictwa (Seismic
hazard: Yearly report on basic natural and technicalhazards in hard coal mining in 2014), Katowice, pp.
82-95.
Stoiński K. (2015): Doświadczenia i obserwacje
własnez
wpływuoceny„upodatnienia”
zmechanizowanych obudów ścianowych na ich
optymalizację konstrukcji (Experience and own
observations of influence of assessing “flexibility” ofshield supports on optimising their construction). IX
Międzynarodowa Konferencja Techniki Urabiania
organizowana w ramach III Polskiego Kongresu
Górniczego Kraków-Krynica.
Stoiński K., Prusek S., Rajwa S. (2015): Dobór
przepływów w układzie zabezpieczającym stojak
zmechanizowanej obudowy ścianowej – opis
przypadku (Flow selection in the system securing ashield support leg. Case study). XXIII.
Międzynarodowa konferencja naukowo-techniczna
TEMAG 2015. Ustroń, 21-23.10.2015 r.
Turek M., Prusek S., Masny W. (2015):
Obudowa podporowo-kotwowa w kopalniach węgla
kamiennego (Steel arch support with roof bolts hardcoal mines). Monografia, wydaw. GIG.

59

ISMS 2016

Paper No. 165

Evolution of grouting methods for dynamic supports in broken ground
Francois Charette a, Trond Skogseth babRock Reinforcement Division, Normet Canada, Lively, Canada, P3Y 0B3
Rock Reinforcement Division, Normet International, Surnadal, Norway, 6650

ABSTRACT
Rockbursts are seismic events of deep or high stress mines that often lead to damages to the ground support system.
Even when the rock at the contour of the excavation is broken, rockbursts can occur behind this softened zone andfurther damage the support system. In these broken conditions, the ductility of the ground support system is stillcritical, but the installation of grouted tendons is rendered tedious or very inefficient by the problems associatedwith inserting cartridges of resin inside the boreholes. The same practical issues with resin cartridges arise whilebolting in squeezing ground conditions or in damaged pillars.
This study aims to investigate alternative methods of grouting dynamic rockbolts by methods other than thepolyester resin cartridges traditionally used by the mining industry. In particular, the use of injected resin grout for
reinforcement is analysed in the field. The static anchorage capacities of the injected resin is evaluated using DBolts and Self-Drilling Bolts (SDB) by the mean of pull out tests, and compared with the performance of similarbolts anchored with resin cartridges in hard rock conditions, and grouted with cementitious grout. Drop tests
evaluation of the resin were postponed due to scheduling difficulties.
The study also includes a field evaluation of the installation method, sequence and bolting speed, for typical length
tendons. The implications of the installation with injected grout on the resulting capacity and estimated safety
performance are discussed.

1. BACKGROUND
Rockbursts are seismic events of deep or highstress mines that often lead to damages to the groundsupport system. Even when the rock at the contour ofthe excavation is broken, rockburst can occur behind
this softened zone and still damage the support
system. In these broken conditions, the ductility of
the ground support system is still critical, but the
installation of grouted tendons is rendered tedious orvery inefficient by the problems associated withinserting cartridges of resin inside the boreholes(Pritchard and McClellan, 2011; Simser andPritchard, 2012).
Field studies performed by Normet haveestablished that the typical time to install a fully
grouted 2.4 metre long rock bolt with resin cartridges
in very broken ground can vary between 5 and 25
minutes. Beside the very low productivity of such an
operation, there is always the possibility that theanchorage may not be continuous along the bar, andthat the bolt performance can be negatively affectedby a poor anchorage capacity and risks of corrosion.
Because safety factors rely on an adequate
encapsulation of the rock bolt, uncertainty on the
grout continuity is a major parameter that will affectthe safety of the ground support.

Ground failures and rock ejection due toincomplete encapsulation of the rockbolt are rarely
published outside of a mining organization, but havebeen observed (Figure 1). As mines operate deeper
than ever before, the rockmass is increasingly understress and broken, and at risk of experiencing severeenergy release events. While the immediate contourof excavations rapidly deteriorates, leading to acrown of broken ground, the intact rock is still at risk
for strain bursts. Moreover, fault slip bursts can occur
at proximity of broken ground and lead to potentiallyserious damages to infrastructure and personnel
injuries.
Cost considerations have often relegatedpumpable resins to very specific applications, but
improvements in formulations and manufacturing
have led to basic volumetric cost similar to polyester
resin cost.

*Corresponding author – email : francois.charette@normet.com

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 1: Bolt and rock ejected during a rockburst due topoor encapsulation of the rockbolt in resin.

The reconditioning of damaged excavations andpillars is also an operation that is almost always
performed in broken ground conditions. Open
fractures hinder the insertion of resin cartridges, andincrease the time and costs related to therehabilitation of excavations. Increases of up to 30%of the resin costs due to resin loss or cartridges
deterioration have been observed in the field. Aswell, the uncertainty of full encapsulation creates apotential hazard that cannot be evaluated by pull
testing or field observation, and situations like theone described at Figure 1 can occur.
Very often, the use of friction bolts is the only
available solution to allow adequate anchorage of theground support system (Yao et al, 2014); albeit not apermanent solution, it provides consistent, although
limited, tendon capacity in difficult groundconditions.
The use of injected resin was
documented by Pritchard and McClellan (2011).

2. DIFFERENT ALTERNATIVES
As part of Normet’s development projects, apolyurethane resin grout specially formulated for

rockbolting was developed to be used in undergroundmines and tunnels. After laboratory installations andexploratory testing were successful, the resin wasthen to be tested in underground mine conditions. It
was necessary to evaluate the environmental andmechanical performance parameters in order toassess the potential of the resin as an alternative topolyester resin cartridges and cementitious grout.
The resin formulation leads to a highly
thixotropic behaviour that prevents the resin fromflowing out of vertical upholes after injection iscompleted. The resin becomes thick in a matter of
seconds and in most case will not flow readily
through fissures less than 25 mm wide. In case oflarger fissures, the resin will flow out but migration
will be halted by the thickening process and resin loss
will be minimized and the borehole completely filled.
Once the movement of the resin slows down, thesetting process begins. It should be noted that inthose open fissures cases, polyester resin in cartridge
will also flow out of the holes due to centrifugal force
created by the spinning of the rockbolt inside thehole, and it is not possible to know what is grouted
and what is not.
A first test using a mechanized bolting rig was
performed in an underground testing facility in
Finland (Figure 2). The operation was a success andthe bolts were pulled up to a load of 170 kN (yieldload of the D-Bolt 20 mm). The process was thenreviewed to be used in North American mining
operations, and the testing continued in Canada andUSA.

Figure 2: Drilling and injection of pumpable resin using afully mechanized bolting rig.

The approach of resin injection in Canada was
first evaluated under a reconditioning framework,with less time pressure on the operation than regulardevelopment bolting. A slower set resin was used andthe holes were drilled previous to the injection andbolts installation, allowing us to measure full
exposure to the chemicals and to perform bolt
tensioning shortly after installation. The site chosen

61

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

for this first field testing was the Norcat test mine,
located in Onaping, Ontario. The measurement of the
exposure levels was performed by Workplace Safety
North, a Division of the Government of Ontario
Ministry of Labor.
The resin injection application was then
expanded to the usage in extreme ground conditions,where Self-Drilling Bolts (SDB) are nearly the only
efficient way to install tendons. The undergroundmine site was located in Carlin, Nevada.

3. FIELD TESTING
3.1 D-Bolts Application
The first field evaluation included the injectionof resin and the installation of D-Bolts, a highstrength yieldable tendon (Figure 3). The D-Bolt isused extensively in Ontario and in Sweden, as ahighly energy resistant ground support. The
objectives of the tests were to evaluate if the
rockbolts could be installed and tensioned within areasonable amount of time, and if the loading
capacity was only realistic for reconditioning or if it
allowed a normal bolting sequence to take place. For
this small scale test, a small air operated pump wasused, and 22 kg containers of the resin materials
brought on site (Figure 4).

a)D-Bolt and plateb)

Self-Drilling bolt and accessories

Figure 4: Pump and resin containers used during the test
grouting of the D-Bolts.

The test with D-Bolts was performed withmanual drilling equipment, i.e. stoper and jackleg
drills. For the sake of simplicity, the holes were predrilled, which allowed to focus on the specifics of
installation and air quality monitoring. A total of 18
bolts were installed on the site, 6 at a lower wall leveland 12 in the back, from a scissor truck (Figure 5).
The bolts in the wall were used to get comfortablewith the operation and the air monitoring
instruments and procedures. Then for every holein the back, resin was injected and a rock bolt wasinserted
immediately.
The
operation
tookapproximately 10 minutes for the 12 bolts. Then, all
the rockbolts were immediately tightened toapproximately 150 lbs-ft; tensioning delay frominstallation varied from 10 minutes to approximately
5 minutes. From Van Ryswyk (1983), Tadolini(1991) and Barry et al. (1956), such tensioning torquevalues could lead to a load in the order of 6000 to
10000 lbs or 3 to 5 tons.

Figure 3: Normet bolts: a) D-Bolt rockbolt (top) used as
dynamic support in underground mines, and b) SelfDrilling Bolts (SDB) used in extremely broken groundconditions.
Figure 5: Scissor truck used to install rockbolts in the backof the excavation.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Unfortunately, it was not possible to pull thebolts immediately after the installation. Pull testing ofsome of the bolts (2 in the wall and one in the back)was performed after 24 hours and the results arepresented in Figure 6. For comparison, a typicallaboratory pull test result is also presented on thatgraph and it confirms the excellent anchorage of thebolt in the resin.

method was used on 2 operators as well as upwind
and downwind locations, and the measurements wereconducted during the injection in the wall, and in theback of the excavation. Results of sampling lead toan exposure level that was extremely low, for all
people participating to the sampling process.

RBG Test with D-Bolts
Pull tests #1, 4, 5

250.0
Pull 1 - Wall
200.0

Load (kN)

Pull 4 - Bolt
#6 Wall (pulltesterunstable)
Pull 5 - Back

150.0

100.0

50.0

Typical Lab.
Curve

0.0

0

5

10

15

20

25

30

Displacement (mm)Figure 7: Mechanized bolting rig used to install the Self
Drilling rock bolts.

Figure 6: Pull out results of D-Bolts anchored with RBG
grout.
Pull out SDB with RBG and cement grouts

3.3 Environmental Assessment
The measurement of the potentially hazardous
isocyanates was performed by a consultant hygienist
from Workplace Safety North. The Iso-Check

300.0
250.0
Bolt 2 @ 2h

200.0

Load (kN)

3.2 Self-Drilling Bolts Applications
The second trial was performed in very broken
and weak ground. Self-drilling bolts, referred here as
SDBs or often referred as Self-Drilling Anchors or
SDAs (Figure 3) were installed with a mechanizedbolting rig (Figure 7) and grouted using the RBG
resin grout, and pull tested after 2 hours, 3 hours, and24 hours. Another set of two (2) bolts were grouted
using regular cementitious grout. Results arepresented in Figure 8. The bars are hollow threaded
bars on which a one-time use drill bits can be fitted.
The pull out curves showed that the resin grout
allows at least 12 tons of pull out after 2 hours, andalso stiffens rapidly (3 hours pull out exhibit a muchsteeper loading curve than 2 hours pull out curve).
For this trial, the short term pull out were conducted
up to 12 tons only, to make sure the grout was notdamaged for future pull tests. Also, stiffness of theresin after 3 hours compares well with cement after
24 hours.
The 24 hours pull out results showed also thatthe bolts can be loaded to a very high level, and thetest on Bolt #4 and Bolt #9 were halted only due toissues with the pull testing equipment.

Bolt 2 @ 3 hBolt 3 @ 2hBolt 3 @ 3 h

150.0

Bolt 3 @ 24 hBolt 4 @ 2h

100.0

Bolt 4 @ 3 hBolt 4 @ 24 h

50.0

Bolt #7 Cement
Bolt #9 Cement

0.0
0

10

20
30
Displacement (mm)4050Figure 8: Pull out results of SDBs anchored with RBG
grout.

4. PERFORMANCE EVALUATION
During the field tests, basic operational data wasrecorded. Drilling time, installation time including
bolt handling, grouting, and tensioning was recorded.
Average values are listed in Table 1, and an estimateof the bolting rate was also calculated from the fielddata. For the case of the cemented self-drilling bolt,
the tensioning was performed during the next shift orday, so the performance of the next shift was affectedby the tensioning time. Using a faster setting resin
allows for a higher productivity but necessitates moreexperienced operators and well maintained
equipment. The calculations are based on a63

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

conservative 360 minutes of effective bolting
operation during the shift.
Table 1: Probable performance calculations based on fieldmeasurements.
Operation

Drilling
Grouting
Tensioning
Total:
Bolts/shift

DBolt/Rockbolt
Slow
Fast
resin
resin
(min.) (min.)

Slow
resin
(min.)SD Bolts
Fast
Cementresin
grout(min.)(minutes)

2
3
5
10
36

2
3
5
10
36

2
3
2
7
51

2
3
2
7
51

2
3
3+24h
8+24h
(36+25)/2=30

Note 1: basis of 360 minutes effective work per shift
Note 2: cement grout effective time is 360 minutes minus 36 bolts
from previous shift x 3 minutes tensioning per bolt = 252
minutes

5. CONCLUSIONS
The field testing of the RBG resin was successfulin showing the potential of using injection resin to
replace resin cartridges or cement injection in groundsupport operations in broken rock masses that makes
cartridges injection in boreholes difficult.
The first advantage of the method is to provide a
better and safer anchorage for the rockbolt. Becauseof the thickness of the injected resin, the bolt is fully
encapsulated in the borehole, also filled of resin.
Contrary to the rotation of the rebar or D-Bolt
necessary to mix resin cartridges, the insertion androtation do not push away the grout in the open
fractures in the borehole. The uncertainty of proper
encapsulation is eliminated or reduced to a minimum.
The anchorage capacity of the resin is also
equivalent to the polyester resin used in cartridges,
with a similar stiffness after a few hours. The
anchorage capacity is also as good as when using
cementitious grout.
Cost wise, the pumpable resin is not really more
expensive than resin in cartridge when one considers
the resin loss, broken cartridges and handling timeassociated with cartridges in broken ground.
Although it would be seen as using more material
than resin in cartridge, it is because the hole is filled
and the bolt fully encapsulated. Some resin loss infissures will not negatively alter the performance ofthe bolt, and will likely reinforce the rock mass. So inthat sense, the injected product is cost competitive
with polyester resin cartridges and offers a highperformance alternative in broken ground conditions
that reduces tremendously the risk of anchorage
failure due to poor encapsulation.

making this initial trial a success. As well, the authors
want to thanks Newmont Mines personnel for theirexpertise, support and discussions. Also, thecontributions of Martin Robbins of Normet
International and Jason Chevrier of WSN for theirexpertise, support and enlightening comments before
and during the tests was deeply appreciated.
7.

REFERENCES
Barry, A.J., Panek, L.A., McCormick, J.A.,
1956. Use of torque wrench to determine load in roof
bolts. Part 3, Expansion type 5/8 inch. R.I. 5228, 8p.
Pritchard, C.J., McClellan, R.S. (2011).
Injectable resin, A highly adaptable ground support
anchoring system. In Proc. CIM Conference andExhibition, Montreal, Canada.
Simser, B., Pritchard, C.J. (2012), Innovative
ground control at Xstrata’s Nickel Rim South mine,
Sudbury, Ontario. In Proc. Workplace Safety North
Ground Control Conference, Sudbury, Canada, April.
Van Ryswyk, R. (1983). Mechanical rockbolt
performance evaluated from pull tests. In:
Proceedings of the International Symposium on Rock
Bolting,
Abisko,August
28-September 2,
Stephansson, O., editor. Balkema.; pp. 473-476.
Yao, M., Forsythe, A., Punkkinen, A. (2014).
Examples of ground support practices in challenging
ground conditions at Vale’s operations in Sudbury. In
Proc. Workplace Safety North Ground Control
Conference, Sudbury.

6. ACKNOWLEDGEMENT
The authors want to acknowledge the personnelof the Norcat Test Mine for their contribution in

64

ISMS 2016

Paper No. 226
Large scale panel destress blasting parametric study
Isaac Vennes*, Hani Mitri

Department of Mining and Materials Engineering, McGill University, Montreal, Canada, H3A 0E8

ABSTRACTThe purpose of this parametric study is to quantify the effect of panel destressing on a steeply dipping remnant ore
pillar. A large-scale destress blast program is simulated in the hanging wall of the ore pillar using the finite
difference program FLAC3D. The simplified model consists of a 10MT ore pillar divided into 20 stopes on twolevels. Two panels are destressed in the hanging wall to cover 8 stopes, followed by the mining of 4 stopes in the
stress shadow in a retreat sequence. The varied parameters are the rock fragmentation factor (α) and stress reduction
factor (β) of the destress panel. The effect of panel destressing is evaluated based on the volume of ore at risk in the
stress shadow as well as the sudden stress change in the stope caused by the destress blast. Overall, a successful
blast with a realistic stress reduction factor and rock fragmentation factor reduces the major principal stress in thenearest stopes by 10 MPa to 25 MPa. This yields a reduction of ore at risk volume ranging from 8% to 50% in the
stress shadow as the first 4 stopes are mined.

1. INTRODUCTION
Rockbursts occur when the rock has been loaded
beyond its failure point, manifesting as a sudden andviolent failure of rock. Contributing factors to theoccurrence of rockbursts are high stress, stiff strata,
rapid mining rate, and large excavation area among
others.
Destress blasting is a rockburst control techniquewhich employs explosives to fracture the rock,
reducing its stiffness and releasing stored elasticstrain energy. To reduce the risk of rockbursts,
destress blasting can be directly applied to the rock to
be extracted such as for drift development and crownpillar destressing for overhand cut and fill. Anotherstrategy is panel destressing, where relatively large
volumes of rock (greater than 10 Kt) are destressed in
the hanging wall of the orebody, such that the ore to
be bulk mined lies in the stress shadow of thedestress panel. In this case, panel destress blasting
aims to reduce the risk of rockbursts by reducing themagnitude of the major principal stress in the ore to
be mined. This strategy has been applied Star
Morning Mine (Karwoski and McLaughin 1975), in
Brunswick mine (Andrieux 2005; Andrieux, et al.
2000) and Fraser mine (Andrieux 2005). The twolatter applications were deemed successful based onrecorded stress changes, seismicity, and measured
displacements. At Fraser Mine, a sudden decrease of
1.5 MPa in the direction major principle stress wasrecorded in the stress shadow 25 meters away frompanel. In Brunswick mine, a sudden 4 MPa stressdrop in the direction of the major principal stress wasmeasured 20 meters away from panel.
In both case studies, the magnitude of the sudden
and long term stress decrease in the stress shadow*Isaac Vennes – email : isaac.vennes@mail.mcgill.ca

appears to be a small proportion of the mining
induced major principal stress. To evaluate theeffectiveness of the panel destress blasting strategy,
the effect of this stress decrease on the burst
proneness of the ore in the pillar needs to be
examined. In this paper, a parametric study isconducted with a linear elastic numerical model. The
purpose is to quantify effect of destress blasting interms of stress reduction and ore at risk in the panel
stress shadow by varying the rock fragmentation
factor (α) and the stress reduction factor (β).

2. DESTRESS BLASTING MECHANISMS
Destress blasting is understood to reduce thestress borne in rock by inducing fracturation,
demonstrated to be along pre-existing fracture planes(Lightfoot et al., 1996). This induced fracturation isthought to have multiple effects that reduce burst
proneness. Firstly, the induced fracturation reduces
the stiffness of the rock (Blake, 1972) as well as theload bearing ability. Secondly, as the blast induced
cracks propagate, the stored elastic strain energy is
dissipated as seismic energy (Tang and Mitri, 2001),
resulting in an instantaneous reduction of stresses in
the rock. Finally, destress blasting mobilizes the rockmass along pre-existing fractures, equivalent toplastic strain. As rockbursts are normally associatedto brittle elastic rock failure, a destressed zone will
yield gradually rather than fail suddenly as a
rockburst (Saharan, 2004). However, when
examining the effectiveness of panel destressing witha linear elastic model, the modification of the failure
mechanism in the panel will not affect the burst
potential of the destressed ore. Therefore, only the3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

former two effects need to be considered in thisstudy.

final stress tensor in the panel lies between the initialstress tensor and the residual stress tensor.

3. DESTRESS BLASTING MODEL

3.2 Panel Geometry
The total mass targeted by a destress blast can be
estimated based on the drill hole diameter (Andrieux,
2005). Assuming 2 rows of blastholes, the targetedmass Me can be estimated as:

3.1 Modelling Technique
Multiple techniques have been developed tosimulate destress blasting, starting with the rockfragmentation factor α (Blake, 1972), which reduces
the Young’s modulus of the rock targeted by thedestress blast. Tang (2000) expanded on Blake’s
fragmentation factor by adding the stress reduction
factor to take into account the strain energy that is
instantaneously released by the blast as seismicenergy. Tang deems the inclusion of β necessary inlight of case studies where α is unrealistically low; arealistic range for α is 0.4 – 0.6, combined with
β>0.4. Finally, Saharan (2005) proposed that α and βshould vary anisotropically, since blast induced
fractures tend to propagate in the direction of the
major principal stress.
In this study, the technique described by Tang
(2000) is applied to the destress panels. Six
combinations of α and β are tested, assumed to lie
along the line α+β=1. The most optimistic
combination with highest rock fragmentation andstress reduction tested is α=0 and β=1, equivalent to
the panel material being extracted. The combination
with lowest stress reduction and rock fragmentation
tested is α=0.8 and β=0.2. A base case model with nodestress blast is also run (α=1, β=0). The parameters
α and β are assumed isotropic.
To simulate a destress panel, the modulus ofelasticity is reduced in the panel by the factor αwhich ranges from 0 to 1:
𝐸𝑑𝑒𝑠𝑡𝑟𝑒𝑠𝑠 = 𝐸𝛼 [1]In addition, the residual stress tensor in thetargeted zones is applied following the equation:{𝜎𝐷 } = (1 − 𝛽) ∙ {𝜎} [2]where β ranges from 0 to 1, and where{𝜎}𝑇 = �𝜎𝑥𝑥 , 𝜎𝑦𝑦 , 𝜎𝑧𝑧 , 𝜎𝑥𝑦 , 𝜎𝑦𝑧 , 𝜎𝑥𝑧 � [3]The balanced stress state in the panel prior todestressing is replaced with the residual stress state{σD} defined by equation [3]. This removes a
proportion of the strain energy in the panel equal to
the factor β, causing an imbalance between the model
boundary work and strain energy in model. A newequilibrium reached after solving model where the

𝑀𝑒 = 2 ∗ (16 ∗ 𝑑) ∗ 𝐻 ∗ 𝐿 ∗ 𝜌𝑟 [4]where d is the blasthole diameter, H the height of thepanel, L the strike length of the panel, and ρr thedensity of the rock. The explosive energy applied inreported destress blasting case studies ranges from 10
cal/kg to 500 cal/kg (Andrieux, 2005). Since mostapplications of destress blasting aim to directly precondition the rock to be extracted, the applied
explosive energy is low and the drill hole diametersmall: 43 mm to 54 mm for Creighton Mine
(O'Donnell, 1992; Oliver et al., 1987), 45 mm forCampbell Mine (Makuch et al., 1987), and 35 mm to63.5 mm for Macassa Mine (Hanson et al., 1987).
However, panel destressing case studies all lie on
the high end of this range (200-500 cal/kg) with large
blasthole diameters ranging from 115 mm for Star
Morning mine (Karwoski and McLaughin, 1975) andFraser Mine (Andrieux, 2005) to 165 mm for
Brunswick Mine (Andrieux et al., 2000). Based onequation 4, the targeted panel thickness based on thereported blasthole diameters ranges from 3.7 m to 5.3
m. In this study, a 3 m panel thickness is assumed,
equivalent to two rows of 3.5ʺ (89 mm) blastholes.

4. EVALUATION OF STRAINBURSTPOTENTIAL
The first step of the study is to confirm need for
destress blasting. For a linear elastic numericalmodel, the available criteria are either based onenergy or stress state. Multiple methods based onenergy calculations have been proposed such as theEnergy Release Rate (ERR) (Cook, 1967), and the
Burst Potential Index (BPI) (Mitri et al., 1999).
However, a limitation of ERR is that rock masscritical strain energy is not factored in. The ERR is
therefore not a suitable criterion for this study, as it
does not evaluate the need for destressing, only its
effect. On the other hand, the BPI defined by Mitri is
for uni-axial conditions and therefore only applicableto stope and drift faces and not to bulk of pillar.
Finally, the brittle shear ratio (BSR) was
developed based on a study by Martin and Kaiser(1999), where rock was found to undergo brittle shear
as the ratio between the deviatoric stress and the uniaxial compressive strength exceeded 0.4. The BSR
proposed by Castro et al. (1997), is expressed as:66

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

𝐵𝑆𝑅 =𝜎1 −𝜎3

𝑈𝐶𝑆𝑖𝑛𝑡𝑎𝑐𝑡[5]

The risk of strainbursts was deemed significant when
the ratio exceeds 0.7. Therefore, ore zones with a
BSR exceeding 0.7 are termed ‘at risk’. With an
initial pillar BSR due to mining induced stresses at
0.2, there is no immediate need to destress. However,after the extraction of first 4 stopes, 11.4% of theremaining ore is at risk, equivalent to 36000 tonnes.

5. MODEL CONSTRUCTION

Figure 2: Model plan section view of the ore pillar.

The model boundary is set 160 meters awayfrom the pillar, such that the pillar extraction causes a
stress change smaller than 1% at the boundary. For
the mesh sensitivity analysis, the zone size in thepillar is kept constant at 1 m x 1 m x 1 m, while theboundary surface mesh is varied from 8 m x 8 m to
15 m x 15 m. Monotonic convergence of maximum
displacement is obtained at 10 m x 10 m boundary
mesh (see Figure 1). This yields an optimal modelwith 1500000 elements. The panel zones are 0.25
meters along the panel thickness, 1 m along the panel
strike, and 1 m along the panel height.
Maximum displacement(m)

5.1 Model Geometry
Pillar and panel zones are built manually withfinite difference numerical modelling software
FLAC3D. Host rock zones and ore zones that are notin pillar generated with Kubrix (Itasca, 2016). The
pillar hanging wall and footwall are vertical. The
pillar consists of 20 stopes on 2 levels, with 10 stopes
per level. On each level, there are 5 stopes along theorebody strike, 2 along the thickness. The stope
dimensions are 12 m x 15 m x 30 m (strike x
thickness x height). The panel dimensions are 15 m x
3 m x 60 m (strike x thickness x height).

7.70E-02
7.65E-02
7.60E-02
7.55E-02
7.50E-02
7.45E-02
8.00E+05

1.30E+06

1.80E+06

Number of zones

Figure 3: Model mesh sensitivity analysis.

5.2 Model Material Properties
Figure 1: Model elevation view along orebody thickness.
Strike of the orebody and pillar is 60 m in the x-direction.

Table 1: Material properties.

Ore
Host RockBackfill

Young’s
Modulus
(GPa)
27.6
37.8
2.0

Poisson’s
Ratio
0.28
0.24
0.30

Unit
Weight(MN/m3)
0.037
0.029
0.024

Intact
UCS
(MPa)
140
150
N/A

67

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

𝜎3 (𝑀𝑃𝑎) = 𝜎𝑧𝑧 = 0.029 ∗ 𝑑𝑒𝑝𝑡ℎ (𝑚) [6]The far field x and y stress are initialized in allzones following equations [7] and [8], adjusting forthe effect of Poisson’s ratio due to model weight. The
initial stresses are oriented such that the major
principal stress is perpendicular to the orebody andpanel strike.
𝜎1 (𝑀𝑃𝑎) = 𝜎𝑦𝑦 = 10.825 + 0.032 ∗ 𝑑𝑒𝑝𝑡ℎ (𝑚) [7]𝜎2 (𝑀𝑃𝑎) = 𝜎𝑥𝑥 = 8.687 + 0.024 ∗ 𝑑𝑒𝑝𝑡ℎ (𝑚) [8]5.4 Mining Sequence
To set up the ore pillar, the orebody is minedbottom up in 10 stages, with vertical lifts ranging
from 30 to 40 meters. The ore above the pillar ismined first. After each lift, the void is backfilled.
Each stope is mined in six 5 meter lifts. The pillar ismined in retreat from hanging wall to footwall, west
to east, bottom to top. For the parametric study, 2panels are destressed simultaneously and the first 4
stopes of the described sequence are mined in the
stress shadow.

6. RESULTS
The effect of panel destressing is quantified interms of the stress drop over the strike of the hanging
stopes and in terms of ore at risk (BSR>0.7) in the
stress shadow of the panel. To begin, the major
principal stress in the pillar is 80 MPa following
extraction of upper and lower orebody. The variationof major principal stress in the stress shadow forvarying destress blasting input parameters is shownin Figure 3. The stress drop in proportion to the initialstress in the stope is shown in Figure 4.
For a high rock fragmentation and stress
reduction effect (α=0.1, β=0.9), an immediate stressdrop of 10 MPa to 25 MPa is obtained in the hanging
wall stope (10% to 30% stress change). Immediately
after the destress blast, the volume of ore at risk inthe stress shadow is reduced by 10%. After extracting
4 stopes in the stress shadow, the destress blast
reduces the volume of ore at risk by 50% as shown in
Figure 5. On the other hand, for a low rock90

α=0, β=1
α=0.1, β=0.9
α=0.2, β=0.8
α=0.4, β=0.6
α=0.8, β=0.280Stress Reduction (MPa)

5.3 Model Loading
The model external x-face constrained in the x
direction, the model external y-face constrained in ydirection. Bottom face constrained in z-direction. The
top boundary free, with applied overburden stress.

fragmentation and stress reduction effect (α=0.8,
β=0.2), the obtained stress reduction is below 3 MPa(4% stress change). The destress blast yields an
immediate 2% reduction of ore at risk. After 4 stopes,
the destress blast reduces ore at risk by 5%.

70
60
50
40
30
20
10
0
-3

2

7

Distance from panel (m)1217Figure 4: σyy drop due to destress blast along observationline shown in Figures 1 and 2.

In both cases, the destressing effect is notdetectable immediately after the destress blast withthe ore at risk criterion. Since the bulk of the pillar
BSR is well below 0.7, the destress blasting stress
reduction in shadow does not necessarily translate to
reduction of ore at risk. Comparison with the destressblasting case studies of Brunswick mine and Fraser
Mine, where a 4 MPa drop at 20 meters and a 1.5
MPa drop 25 meters were measured in the directionof the major principal stress immediately after thedestress blast, suggests that 0.2<α<0.4 and0.6<β<0.8. Applying these destress blasting
parameters to the parametric study model yields a
reduction of ore at risk ranging from 8% to 50% in
the stress shadow during the extraction of the first 4
stopes.
0

0.2

0.4

0.6

0.8

1

-10%
YY Stress Change

The numerical model is linear elastic. The elastic
material properties are shown in Table 1, along with
the intact UCS. The properties are provided by a casestudy mine.

-30%
-50%
-70%
-90%

α, 1-βStope HW face
Stope Middle
Stope FW face

Figure 5: σyy change in HW stope. Observation points arealong the observation line shown in Figures 1 and 2.

683rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

70%

Stress Shadow Ore at Risk (Slot)
Stress Shadow Ore at Risk (α=0.1, β=0.9)
Stress Shadow Ore at Risk (α=0.2, β=0.8)
Stress Shadow Ore at Risk (α=0.4, β=0.6)
Stress Shadow Ore at Risk (α=0.8, β=0.2)

Stress Shadow Ore at Risk % Reduction

60%
50%
40%
30%
20%
10%
0%
-10%
2

5

8

11

14

17

20

23

26

Mining Step

Figure 6: Ore at risk reduction in stress shadow with respect to scenario with no destress blast. Shown are the destress blast (step2), extraction of stope 1 (steps 3-8), extraction of stope 2 (9-14), extraction of stope 3 (15-20), extraction of stope 4 (21-26).

7. CONCLUSIONSIn this study, panel destress blasting is shown to
reduce the volume of ore at risk in a highly stressedore pillar by 8% to 50% in the stress shadow, given
an obtained rock fragmentation factor between below
0.4 and a stress reduction factor above 0.6. These
values are realistic when compared to the observed
immediate stress changes at Brunswick Mine andFraser Mine following a panel destress blast, where
200-500 kcal/kg of explosive energy was applied.
Panel destressing can therefore be an effective tool toreduce risk to operations when bulk mining the ore
pillar.
However, it is assumed in the parametric study
that the pre-mining major principal stress is normal tothe destress panel. Also, the destressed modulus ofelasticity and stress release are assumed to be
isotropic. These results therefore reflect a best casescenario for a panel destressing program.

8. REFERENCES
Andrieux P (2005) Application of rockengineering systems to large-scale confined destressblasts in underground pillars. Laval University
Andrieux P, Brummer R, Liu Q, Mortazavi A,
Simser B (2000) Large-Scale Panel Destress Blast at
Brunswick Mine. In: 23rd Study Dession on Blasting
Techniques, vol. SEEQ, QuebecBlake W (1972) Rock-burst mechanics.
Quarterly of the Colorado School of Mines 67(1):164

Castro LAM, Grabinsky MW, McCreath DR(1997) Damage inititiation through extension
fracturing in a moderately jointed brittle shear rockmass. International Journal of Rock Mechanics andMining Sciences (34):110-113
Cook NGW (1967) Design of undergroundexcavations. In: 8th US Rock Mechanics
Symposium, Minnesota, pp 167-193
Hanson D, Quesnel W, Hong R (1987)
Destressing a Rockburst Prone Crown Pillar:
Macassa Mine. In, CANMET
Itasca (2016), Kubrix [Computer Software];retrieved from www.itascacg.com/software/kubrix
Karwoski WJ, McLaughin WC (1975) Rock preconditioning to prevent rockbursts - report on a fielddemonstration. In, vol. United States Department of
the Interior, Bureau of Mines
Lightfoot N, Kullman DH, Toper AZ, Stewart
RD, Gronder M, Rensburg ALJv, Longmore PJ(1996) Preconditioning to Reduce the Incidence ofFace Bursts of Highly Stressed Faces. In, vol. CSIR:MININGTEK
Makuch A, Neumann M, Hedley DGF, Blake W(1987) Destress Blasting at Campbell Red Lake
Mine. In: Canada/Ontario/industry Rockburst
Research Project, CANMET, Elliot Lake Laboratory
Martin CD, Kaiser PK (1999) Predicting thedepth of stress induced failure around undergroundexcavations in brittle rocks. In: 49th Canadian
Geothechnical Conference, St-John's, pp 105-114
Mitri HS, Tang B, Simon R (1999) FE modellingof mining-induced energy release and storage rates.

69

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The Journal of the South African Insitute of Mining
and Metallurgy:103-110
O'Donnell JDP (1992) The use of destressblasting at Inco's Creighton Mine. In: MASSMIN 92,
vol. SAIMM, Johannesburg, pp 71-74
Oliver P, Wiles T, MacDonald P, O'Donnel D(1987) Rockburst control measures at Inco's
Creighton Mine. In: 6th Conference on Ground
Control in Mining, West Virginia
Saharan MR (2004) Dynamic Modelling of RockFracturing by Destress Blasting. McGill University
Tang B (2000) Rockburst Control using Destress
Blasting. McGill University
Tang B, Mitri HS (2001) Numerical modellingof rock preconditioning by destress blasting. Ground
Improvement 5:1-11

70

ISMS 2016

Paper No. 87
Improving ground control safety in deep vein mines

Joseph Seymour*, Donovan Benton, Michael Raffaldi, Jeffrey Johnson, Lewis Martin, Shawn
Boltz, Jerald Richardson
Spokane Mining Research Division, National Institute for Occupational Safety and Health, Spokane, WA, USA, 99207

ABSTRACT
Researchers with the National Institute for Occupational Safety and Health (NIOSH) in Spokane, WA, USA are
conducting research in cooperation with the Hecla Mining Company at the Lucky Friday Mine in northern Idaho toimprove ground control safety in deep vein mines. Because Hecla is mining at depths of more than a mile beneath thesurface, the geology and ground stresses create unique requirements for mining and ground support. Special measures
are being implemented by Hecla to limit the intensity of mining-induced seismic events and to avoid compromising thestatic and dynamic capacity of their ground support systems. NIOSH researchers are collaborating in these efforts bymonitoring and assessing the fault slip mechanisms that initiate these seismic events and by quantifying theperformance characteristics of the ground support systems.
KEYWORDS: rockburst; seismicity; dynamic ground support

1. INTRODUCTION
NIOSH researchers in Spokane, WA are
conducting research in cooperation with the Hecla
Mining Company at the Lucky Friday Mine innorthern Idaho to develop improved methods forground control safety in deep vein mines. Hecla iscurrently using underhand cut-and-fill mining methods
to mine Ag-Pb-Zn ore from narrow, steeply dippingveins in the Gold Hunter deposit at a depth of over7000 feet. Mining-induced stress increases near a large
sill pillar in the mine’s main production vein havecreated challenges for mining in these rockburst-prone
ground conditions (Figure 1). As the sill pillar is being
mined, its vertical extent decreases, which concentrates
and progressively increases the stresses acting in theremaining portion of the pillar, thus increasing thepotential for strain bursts. As mining progresses, local
stresses are also being reoriented along the strikedirection of problematic faults that intersect the sill
pillar and dip 50° to 60° to the north. This compounds
the rockburst issue by increasing the potential for faultslip seismicity.
To reduce mining-induced seismic activity, thelocal stress field is being altered to reduce themagnitude of the stresses in the sill pillar and morefavorably reorient the stresses acting along the faults.
A nearby, sub-parallel, less-economic vein is being
mined and backfilled to create a stress shadow thatdiverts the high horizontal stresses away from themining horizon in the sill pillar and redistributes thesestresses to more stiff, intact rock beyond the peripheryof the mined shadow slot. The stress shadow also
reduces the potential for fault-slip seismic events by*Corresponding author – email: zia8@cdc.gov

reorienting and reducing the stresses that act along theorientation of these problematic faults.

Figure 1: Schematic of development entries (red),
backfilled stopes (brown), and faults (blue and green) in theGold Hunter extension of the Lucky Friday Mine.

Current research activities include the use of
seismic monitoring, photogrammetry, geotechnicalinstrumentation, 3D visualization, material property
testing, ground support testing, and numeric modeling.
This paper briefly discusses these research tasks andpresents some of the technical innovations that havebeen developed.

2. SEISMIC EVENT MONITORINGNIOSH researchers are monitoring mininginduced seismic events at the Lucky Friday Mine using
three seismic monitoring systems: Hecla’s in-mine
microseismic system, regional surface seismic stations,3rd international Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

and a third monitoring system called the Intermountain
Seismic Network (IMSN). The IMSN was developedand installed by NIOSH researchers to determine thesource mechanisms of large mining-induced events(i.e., >1.5 magnitude). This system is currently
comprised of eight close-in stations and one far-fieldstation; however, it is being expanded to include
additional far-field surface stations, as well as sensors
installed underground at the mine. The far-fieldstations will be positioned distant enough from theanticipated seismic sources so that P and S wave
arrivals will have sufficient separation to allow moredetailed assessment of source mechanisms.
As shown in Figure 2, each IMSN surface station
has a standard configuration consisting of anantenna/solar mast structure for the photovoltaic
system, a vault for the battery/power distribution
system, and another vault for telemetry/seismic
equipment. The station’s field-hardened, modular
design not only protects the sensitive seismic
equipment and electronics but also provides flexibility
for installing different seismometers. Having acommon configuration for each station simplifies theinstallation procedures, reduces troubleshooting time,and decreases the need for spare components.
Personnel installing and maintaining the stations areable to quickly locate equipment, components, andpower disconnects. The close-in stations are strongmotion stations with force-balanced triaxial
accelerometers and seismometers, whereas the farfield stations use broadband triaxial seismometers.
Seismic data is transmitted by radios or wirelesscellular modems depending on site telemetry
requirements.

Figure 2: Typical configuration of an IMSN surface station
for monitoring mining-induced seismic events.

Both the IMSN network and Hecla’s
microseismic monitoring system provide real-time
waveforms of a seismic event that are in turn used todetermine its location and magnitude. Because Hecla’s

in-mine sensors are located much closer to the active
workings than the IMSN surface stations, their in-mine
network can detect much smaller mining-induced
seismic events. Furthermore, because theirmicroseismic sensors are installed on different levels
within the mine, their underground network also
provides a much more accurate depth or elevation
component for the location of an event. Focal
mechanisms or moment tensors are calculated todetermine the source of the event (e.g., slip on an
existing fault or mining-induced rock mass fracturing).
It is essential to identify the mechanism that caused theevent in order to gain a better understanding of theground conditions and also to develop appropriate
methods for mitigating the effects of future events. The
seismic moment, a measure of the energy released
from an event, is also being determined and will becompared with numerical modeling results to gain
additional insight.

3. PHOTOGRAMMETRY
Photogrammetry is a valuable tool for monitoring
complex geometric changes on irregular surfaces.
NIOSH researchers are using this technology in thelaboratory to monitor large-scale tests with shotcrete
support systems (see Section 7) and also at the LuckyFriday Mine to monitor bulk movement inunderground entries and shear displacements along
exposed fault planes. An explanation of the NIOSH
photogrammetry system and further details concerning
the software, hardware, methodology, field
applications, and results are provided by Benton et al.
(2014; 2015; 2016).
Quarterly photogrammetric surveys of exposed
faults at the Lucky Friday Mine were initiated in
January 2013 and are currently ongoing. The surveys
are conducted at nine locations on seven different
sublevels where two faults intersect the 54 ramp near
the Gold Hunter orebody. As explained in Section 5,
three-dimensional point cloud reconstructions of thesesites are also used for mine visualization purposes.
Using photogrammetric data from these sites, crosssections of the faults are compared over time tovisualize and measure the geometric changes that haveoccurred. These cross sections may be developed at
any location and at any orientation, thereby providing
a comprehensive analysis of the movement at eachsite.
Photogrammetric measurement techniques arealso being used to aid in the interpretation of
displacement measurements from crackmeters thatwere installed by Hecla engineers to monitor fault
movement. As shown in Figure 3, the vibrating-wirecrackmeter measures displacement between two
anchor points and thus, provides only a unidimensional
measurement of the fault’s movement (i.e., a72

3rd international Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016displacement measurement along a single orientation).
In contrast, the point cloud measurements obtained
from photogrammetry provide a more complete threedimensional characterization of the fault’s movement
and thus, help identify and quantify bulk groundmovement, such as rib dilation, as opposed to actual
movement along the fault. Using photogrammetry, athree-dimensional displacement vector can becalculated for an individual point or an entire vector
field can be determined for a surface.
Figure 4: Single-acting closure meter and two earthpressure cells installed in the 5550-11W stope prior to
backfilling.

Figure 3: Crackmeter installed across an exposed fault in
the wall of a ramp entry at the Lucky Friday Mine.

4. GEOTECHNICAL INSTRUMENTATION
Besides the crackmeters mentioned above,
NIOSH researchers have also installed two sets ofbiaxial stressmeters (BSM’s) to monitor stress changes
in the host rock—five BSM’s near the 5550-14 stope
to measure stress changes during mining of the stressshadow stope and five BSM’s near the 5550-11 stope
to measure stress changes during production mining inthe 30 vein. As noted by Seymour et al. (1999), theBSM is a rugged and reliable vibrating-wire
instrument that is grouted in a drill hole to measure themagnitude and direction of the secondary principal
stress changes in a plane perpendicular to thelongitudinal axis of the instrument. Most of thestressmeters were installed in vertical drill holes tomonitor changes in horizontal stress at verticalhorizons near the sill pillar. Data from these
instruments is being analyzed in conjunction withseismic monitoring data to determine the effect ofmining advance and seismic events on stress
distribution.

Prior to backfilling, closure meters and earthpressure cells have been installed in the 5550-11 stope
and the 6350-15 stope to monitor hanging wall-tofootwall closure and horizontal stress changes within
the backfill as underhand cut-and-fill mining advances(Figure 4). Because of their robust design, the NIOSH
closure meters have been able to provide stope closure
measurements for over a year through more than fivesuccessive mining cuts beneath the location of the
instruments (Figure 5). The geotechnical instruments
are being monitored by underground data acquisition
systems that are in turn connected to a computer server
located on the surface, where the data is stored anddisplayed on a real-time basis.

Figure 5: Horizontal closure measurements for the
backfilled 5550-11 stope.

5. 3D VISUALIZATION
Complex spatial relationships between mining,
seismicity, and problematic faults are being tracked by
NIOSH researchers using a 3D visualization tool thatwas developed using the Unity® game engine (Unity73

3rd international Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Technologies, 2015). As illustrated in Figure 6, thissoftware tool integrates collected data and images byspatial location and time and thus helps the userinterpret and analyze the complex interactions ofdiverse spatial and temporal data via a single, concise,interactive display (Orr et al., 2015). The 3D
visualization contains a model of the mine workings,
pertinent
geologic
structure,andquarterly
photogrammetric surveys. Each of these components,
as well as areas of active mining, can be steppedthrough time to observe changes. The visualization
tool has two user modes. One mode allows the user tonavigate around the rock mass and view stored datasuch as seismic events and instrument measurements.
Another mode allows users to enter the mine workingsand view data associated with specific workings, suchas photogrammetric reconstructions (Figure 7). Futuredata may also include measured fault movements andthe locations and characteristics of ground fall
incidents.

6. MATERIAL PROPERTIES TESTING
Drill core recovered from the BSM holes was
logged and tested to characterize rock properties,
improve the interpretation of stressmeter readings, andalso provide inputs for numeric modeling. Standard
tests were performed with representative samples fromfour different rock types, including unconfinedcompressive strength (UCS) tests, indirect tensile
strength tests, and triaxial compressive strength tests.
Because the Gold Hunter host rock is comprised ofthinly bedded argillites, testing was performed bothparallel and perpendicular to the bedding to determine
anisotropic properties. Depending on rock type andbedding orientation, average UCS values ranged from97 to 122 MPa, while average tensile strengths ranged
from 4 to 11 MPa. Elastic properties were determinedfrom UCS tests with strain-gauged samples. Young’s
modulus ranged from 41 to 90 GPa, and Poisson’s
ratio varied from 0.11 to 0.27. Triaxial compression
tests were also conducted to determine Mohr-Coulomb
strength properties (cohesion and friction angle).
Similar tests were performed to measure thestrength and elastic properties of cemented paste
backfill samples recovered from the mine (Johnson etal., 2015). These tests indicated that the tensile strengthof the paste backfill ranged from about 1/9 to 1/12 of its
compressive strength. Furthermore, UCS tests withstrain-gauged samples provided a Young’s modulus
ranging from 2.28 to 3.59 GPa and a Poisson’s ratio of
0.17 (Figure 8). Elastic properties for cemented paste
backfill are difficult to measure and therefore, notwidely reported in the literature.

Figure 6: Unity visualization of Gold Hunter undergroundworkings with problematic faults denoted in red and purple
and seismic events represented by colored spheres.

Figure 8: Paste backfill sample equipped with strain
gauges.

7. GROUND SUPPORT TESTING

Figure 7: Unity visualization showing a photogrammetry
reconstruction of a ramp entry on the 5750 sublevel.

The ability of ground support to withstand loadingfrom a large seismic event depends in large part on its
ability to maintain its support capacity while yielding
and undergoing significant deformation. In deep
mines, energy-absorbing rockbolts are often used inconjunction with surface support such as mesh andshotcrete to retain rockburst-prone ground. To quantify
and evaluate the support strength and energy capacity74

3rd international Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016of ground support systems utilizing shotcrete, NIOSH
researchers designed and constructed a High-Energy
High-Displacement (HEHD) test machine for
conducting large-scale tests with reinforced shotcrete
panels (Figure 9).

Figure 9: High-Energy High-Displacement test machine for
conducting large-scale tests with reinforced shotcrete
panels.

During a test, a large shotcrete panel is restrainedby four rockbolts embedded in the concrete columns
and then loaded from beneath by a spherical loadinghead attached to a hydraulic ram. The force anddisplacement applied by the ram (136 metric tons and27 cm, respectively) are recorded during the test using
an advanced data acquisition system. A more detailed
explanation of the HEHD test machine is provided byMartin et al. (2015). Measuring the load-displacement
characteristics of a full-scale shotcrete panel while it isrestrained by rockbolts provides a more representative
indication of the actual ground support provided bythis material in an underground mine. As shown in
Figure 10, the type of reinforcement embedded within
the shotcrete has a major effect on the support capacityand behavior of the panel. As the force on the shotcrete
panel increases, the shotcrete deforms and cracks,
allowing the tensile loads in the panel to beredistributed to the more ductile fibers or mesh.

Figure 10: Force versus displacement graph for shotcrete
panels with different types of reinforcement.

Figure 11: Force, displacement, and crack width opening
for a shotcrete panel reinforced with chain-link mesh and
54-mm-long macro synthetic fibers at a 6.5-kg/m3 dosage.

Photogrammetry is used during the HEHD tests tomeasure the volumetric deformation of the panel andthe opening width of cracks that are developed within
the shotcrete. The force and energy applied to thepanel are referenced to these photogrammetricmeasurements as shown in Figure 11. Using thisinformation, the panel tests results are then comparedwith field observations in underground mines toestimate the remaining support capacity of the applied
shotcrete based on photogrammetric volume
calculations or visual observation of crack widths(Raffaldi et al., 2016a).

8. NUMERICAL MODELING
Map3D™ (http://www.map3d.com), a boundary
element software program, is being used to evaluate
mining-induced stress changes and fault stability in75

3rd international Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

response to sill pillar mining (Figure 12). As expected,
stresses in the sill pillar increase as the vertical extent
of the pillar decreases. As mining advances, thesestress increases result in an increased potential forstrain bursts in the pillar accompanied by a relaxationof the normal forces acting on the faults, which in turnlead to an increased potential for fault-slip seismicity.
In the model, horizontal closure of the backfill stopes
is roughly calibrated to actual in-mine measurements.

Figure 12: Map3D model geometry showing backfilled
stopes (purple), faults (green and red), and remaining sill
pillar and host rock (black).

The finite difference code, FLAC3D™
(http://www.itascag.com/software/flac3d), is being
used to model the Gold Hunter sill pillar. Host rockand backfill properties are based on the in situ
measurements and laboratory testing described earlier
in this paper. FLAC3D™ allows for a detailed
extraction sequence to be simulated in which theorebody is sequentially mined and backfilled. The
model has been used to back-calculate the rockmass
deformation modulus and cohesive strength in thevicinity of the Gold Hunter sill pillar.
The
discreteelement
code,
UDEC™
(http://www.itascag.com/software/udec), is being used
to perform fully dynamic simulations of rock fractureand ejection caused by seismic loading. A synthetic
rock mass was modeled consisting of a series of
discrete blocks that can fracture and shear or fully
detach from the model in response to loading (Raffaldi
and Loken, 2016b). This has been incorporated into amodel of a typical mine drift and is being used toinvestigate energy transfer between the ejected rockand the reinforcement and surface support componentsof the ground support system (Raffaldi and Loken,
2016c).

9. CONCLUSIONS
Research is being conducted by NIOSH incollaboration with the Hecla Mining Company at the
Lucky Friday Mine to develop improved technologies
for ground control safety in deep vein mines. To gain abetter understanding of mining-induced seismic eventsand fault-slip seismicity, a network of surface seismic
stations near the mine site are being monitored on areal-time basis along with geotechnical instruments
installed underground in the host rock, backfill, and at
fault locations. To provide further insight,
photogrammetry surveys are periodically being
conducted to monitor bulk movement in underground
entries and to measure shear displacement along
exposed faults. Much of this information is being
incorporated in 3D visualization software to help
synthesize and interpret the data in terms of the mine’s
infrastructure, production stopes, and geology.
Laboratory tests are being performed to measure thematerial properties of the mine’s host rock, shotcrete,and cemented paste backfill. Large-scale tests arebeing conducted to determine the ground support
characteristics of reinforced shotcrete systems. Finally,
several different types of numeric models are being
used gain a better understanding of the geomechanicalbehavior of the host rock and backfill, particularly inregard to seismic loading. Advances in these researchareas will hopefully lead to improved ground supportand mine design practices for deep undergroundmines.

10. ACKNOWLEDGEMENTS
The authors thank Mark Board, Bob Golden, andEric Zahl from the Hecla Mining Company for theirtechnical input and professional assistance with thisresearch. We also gratefully acknowledge the other
NIOSH researchers in Spokane who have contributed
to this project, most notably Steve Iverson, Doug
Tesarik, Bob Hammond, Derrick Chambers, Pete
Swanson, Curtis Clark, Heather Lawson, Mike Stepan,
Habte Abraham, Seth Finley, and Mark Powers.
Mention of any company or product does notconstitute endorsement by the National Institute for
Occupational Safety and Health. The findings andconclusions in this report are those of the author(s) anddo not necessarily represent the official position of
NIOSH.

11. REFERENCES
Benton DJ, Iverson SR, Martin LA, Johnson JC,
Raffaldi MJ (2016). Volumetric measurement of rockmovement using photogrammetry. Intl Journal of
Mining Science and Technology, Vol 26, Issue 1, Jan2016, pp.123-130.
Benton D, Boltz M, Raffaldi M, Iverson S(2015). Using photogrammetry to monitor
underground mining environments. ARMA eNewsletter: Imaging and Remote Sensing in RockMechanics, Spring 2015, Issue 15, pp. 11-16.
Benton D, Iverson S, Johnson J, Martin L(2014). Photogrammetric monitoring of rock mass76

3rd international Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
behavior in deep vein mining. In Proc 33rd Intl Conf
on Ground Control in Mining, Morgantown, WV,
July 29-31, 2014, pp. 221-227.
Johnson JC, Seymour JB, Martin LA, Stepan M,
Arkoosh A, Emery T. (2015). Strength and elastic
properties of paste backfill at the Lucky Friday Mine,
Mullan, Idaho. In Proc 49th U.S. Rock Mechanics /Geomechanics Symp, June 28 - July 1, 2015, San
Francisco, CA, ARMA 15-776, 12 pp.
Martin L, Clark C, Johnson J, Stepan M (2015).
A new high force and displacement shotcrete test.
SME Annual Meeting, Feb 15-18, 2015, Denver, CO:
Preprint 15-090, 8 pp.
Orr TJ, MacDonald BD, Iverson SR, HammondWR (2015). Development of a generic mine
visualization tool using Unity. In Proc 37th Intl Symp
on the Application of Computers and Operations
Research in the Mineral Industry, Fairbanks, AK,
May 23-27, 2015, F-2015-055, 7 pp.
Raffaldi MJ, Loken MC (2016b). Rock massmodeling approach for simulating wave propagation,rock fracture, and rock ejection. In Proc 50th U.S.
Rock Mechanics / Geomechanics Symp, June 26-29,
2016, Houston, TX, ARMA 16-0393, 12 pp.
Raffaldi MJ, Loken MC (2016c). Framework forsimulating fracture, ejection, and restraint of rockaround a mine drift subjected to seismic loading. In
Proc 50th U.S. Rock Mechanics / Geomechanics
Symp, June 26-29, 2016, Houston, TX, ARMA 160394, 16 pp.
Raffaldi M, Benton D, Martin L, Johnson J,
Stepan S (2016a). Assessing the mechanical behaviorof large-scale shotcrete panels. SME Annual
Meeting, Feb 15-18, 2016, Phoenix, AZ, Preprint 16036, 13 pp.
Seymour JB, Tesarik DR, McKibbin RW, JonesFM (1999). Monitoring mining-induced stresschanges with the biaxial stressmeter. In Proc 5th Intl
Symp on Field Measurements in Geomechanics,
FMGM99, Dec. 1-3, 1999, Singapore, pp. 55-60.
Unity Technologies (2015). Unity Manual.
http://docs.unity3d.com/Manual/index.html.

77

ISMS 2016

Paper No. 198

Numerical investigation of EDZ development around a deep polymetallic ore
mine
Mountaka Souley a*, Marwan Al Heib a, Vincent Renaud aa

INERIS, c/o Ecole des Mines de Nancy, Campus ARTEM, CS 14234, Nancy, France, F-54042

ABSTRACTThis paper deals with the development of a non-linear constitutive model of rock mass and its verification to predicta damaged zone. Simulations of triaxial compressions provide a verification of the implementation with a good
agreement between predictions and theoretical values of peak and residual strengths as well as the transition
between brittle failure and ductile response. The applicability of the model to predict potential failure around stopesof a deep polymetallic ore mine is checked. The present study highlights the interest to consider more realisticrheology of hard rock masses compared with the elastic perfectly plastic models of underground deep mines.
KEYWORDS: Brittle-ductile behaviour; constitutive model; verification; Garpenberg mine; numerical modelling

1. INTRODUCTION
Damage by microcracking is the maindissipation process associated with inelastic
behaviour and failure in most brittle materials such as
rocks, concrete and ceramic composites. Under highin situ and induced stresses and high anisotropic
stress ratios, an excavation damaged zone (EDZ) may
be formed around underground openings excavatedinto brittle rocks. The failure mechanism in thisdamaged zone is the initiation, growth andcoalescence of cracks and fractures and is directly
related to the constitutive behaviour of rock mass.
Experimental studies on brittle rocks have shown that
there are many different mechanisms by which cracks
can be initiated and grown under compressive
stresses (Steif, 1984; Horii and Nemat-Nasser,
1986,). The involved mechanisms include sliding
along pre-existing cracks and grain boundaries, porecrushing, elastic mismatch between mineral grains
and dislocation movement, etc. Indeed, irreversible
deformations and failure of rocks subjected tostresses occur through progressive damage as microcracks initiate and grow at small scale and coalesce toform large-scale fractures and faults. Over the past
decade, several constitutive models have beendeveloped providing a more realistic description ofdamage for brittle rocks in relation to experimental
observations (Zhu et al. 2009).
In the framework of the European program
I2Mine (http://www.i2mine.eu/), INERIS hasdeveloped an innovative tool (stress monitoring tool)
aimed to better understand the behaviour of the rockmass resulting from the mining process of
Garpenberg deep mine (superposed rooms and pillars
and vertical stopes between depths 1100 and 1300 m,*Corresponding author – email: Mountaka.Souley@ineris.fr

Figure 1) in Sweden. Several seismic sensors andstrain gauges were installed in a deep area of themine (approximately at 1150 m deep) to monitor theevolution of induced stresses during the exploitationand the related induced seismic activities.
The objective of this paper is to study themechanical behaviour of the main galleries and thepillars by incorporating the stages of the undergroundwork through advancing numerical modelling. At
first approach, we are limited to 2D models that take
into account the initial state of stress (anisotropic)
and the mine operations.
More precisely, the purpose of this paper is topresent: (a) a numerical implementation of anelastoplastic model obeying to the Hoek–Brown
criterion and taking into account the brittle/ductile
transition between the brittle failure and the ductile
behaviour depending on the mean stress as generally
observed on most rock samples: that is to say, theinitiation and growth of cracks for brittle rocks aremodeled by a softening behaviour in the post-peak in
the framework of plasticity theory, (b) the
corresponding verification based on simulation of
triaxial compression tests. Finally, the numericalmodelling provides the localization of EDZ and thepotential instability area in the vicinity of stopes
located around the pilot area of the mine works at theGarpenberg mine (New Boliden company).

2. PROPOSED RHEOLOGICAL MODEL
AND NUMERICAL IMPLEMENTATION
The mechanical behaviour of geomaterials is
widely varied and depends mainly on the confining
stress (or mean stress) and the loading paths. At low
stress confining levels, rocks break by the creation of

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 1: Experimental set-up (stress and microseismic measurements) in the Swedish mine Garpenberg: (a-left) the mine
location; (b-centre) operating plan and location of the pilot area; (c-right) 3D mesh of galleries and stopes.

one or more shear planes or bands accompanied by astrain-softening
behaviourcharacterizedbymicrocracks dilatancy and grains rotation at the
microscopic scale. Under high mean stresses, rocks
undergo a hardening behaviour which is
microscopically associated with volumetric strains.
More precisely, for most geomaterials subjected totriaxial compressions under low to moderateconfining pressures, it is generally observed thefollowing typical characteristics of stress-strain
curves: (a) a linear isotropic and elastic behaviour
after a short non-linear phase corresponding to theclosure of the initial pores and the progressive
contact walls of the original micropores andmicrocracks (b) a strain-hardening in the pre-peakregion corresponding to the initiation and the growthof microcracks modeled generally by the plasticity
theory or the damage mechanics through the conceptof effective stress and the hypothesis of strain
equivalence (c) a strain-softening after reaching thepeak strength (failure) associated with a progressive
loss in material cohesion and then a decrease instrength (d) a phase where the rock strength remains
practically constant. Relative to the elasto-brittle
materials where the initial microcracks closure andthe growth of microcracks in the pre-peak domain
can be neglected in a first approximation (as it is the
typical case of hard rock masses studied herein at theGarpenberg mine), the present study considers an
isotropic elastic linear behaviour before the peak.
The Hoek-Brown criterion widely used in thefield of rock mechanics and rock engineering, whose
limitations were documented by detailed discussionsof the simplifying assumptions (Hoek and Brown,1980), was generalized in terms of the three stressinvariants in this study. One of the most important
limitations is the non-dependency of the criterion on
the intermediate principal stress, σ2. Subsequent
experimental studies have since suggested that theintermediate principal stress has a substantial
influence on the rock strength (e.g. Haimson, 2006).
This has led to the development of several 3D
versions of the Hoek–Brown failure criterion (Priest,
2005; Zhang, 2008).
It is well known that the three principal stresses
σ1, σ2 and σ3 can alternatively be expressed in termsof mean stress (p), generalized deviatoric stress (q)and Lode’s angle (θ) and vice versa, which allows to
express the classical Hoek-Brown criterion in 3Dstresses space (p, q, θ). After some manipulations, thegeneralized yield function is proposed on the basis ofSouley et al. (2011):
𝐹𝑠 =cos 𝜃 sin 𝜃
4 cos2 𝜃 2𝑞 −𝑚�
−� 𝑞 + 𝑚 𝑝 − 𝑠𝜎𝑐 (1)
3
3 𝜎𝑐
√3

where σc is the uniaxial compressive strength of theintact rock, m, s represents the rheological behaviour
parameters whose significance and quantificationdiffer from the dimensionless empirical parameters of
Hoek-Brown reflecting the strength of the intact rock,the natural fractured rock mass and therefore
consideration of a possible scale effect and fracturing
at the large scale. The parameter m quantifies thefrictional strength and s (measuring the induced
cracks) is related to the rock cohesion.
Let (mp, sp) and (mr, sr) be respectively the valuesof parameters (m, s) at the peak and the beginning
residual phase. Assuming a transition between brittle
and ductile behaviour, equation (1) makes it possible
to express a relationship between the peak andresidual strength parameters:
𝑚𝑟 = 𝑚𝑝 + �𝑠𝑝 − 𝑠𝑟 �𝜎𝑐(2)
𝜎3 𝑏−𝑑In the absence of experimental data on theresidual strength, almost null value of sr can beconsidered as a good approximation in relation to79

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

sliding along the macroscopic failure planes or shear
bands. For softening phase, the same yield function(equation 1) is used by introducing the softening
internal variable (ξ). In accordance with the yieldfunction used, (a) the generalized plastic strain ischosen to represent the internal variable, (b) mlinearly varies with ξ between the peak and the
beginning of residual phase (0 < ξ ≤ ξr representing
the shear plastic strain) whereas s varies non linearly(c) m and s remain constant in the residual domain:2𝑑𝜉 = � 𝑑𝑒 𝑝 : 𝑑𝑒 𝑝3

𝑚 = 𝑚𝑝 + �𝑚𝑟 − 𝑚𝑝 �𝑠 = 𝑠𝑝 + �𝑠𝑟 − 𝑠𝑝 � �2 −

𝜉 𝜉
�
𝜉𝑟 𝜉𝑟

𝜉
(3)
𝜉𝑟
(4)

where dep is the increment of deviatoric plastic strain
tensor in post-peak or residual regions.
Assuming for this type of rock materials that theplastic dilatancy occurs only near the peak strengthand cannot exceed a threshold rate (βm) for a certain
value of deformation and by adapting a non
associated flow rule (generally accepted for rockmaterials), we propose the following plastic potential(Gs) which allows to express the constitutive
relationship between the increments of stresses (dσ)
and total strains as follows (dε):
𝐺𝑠 = 𝑞 − 𝛽𝑚 �1 − 𝑒 −𝑏1𝜉 �𝑝
𝜕𝐹
𝜕𝐹�𝐶: 𝑠 � ⨂ �𝐶: 𝑠 �𝜕𝜎𝜕𝜎𝑑𝜎 = �𝐶 −
� 𝑑𝜀
𝜕𝐹𝑠
𝜕𝐺
𝜕𝐹 𝜕𝐺
: 𝐶: 𝑠 − 𝑠 𝑠
𝜕𝜎
𝜕𝜎
𝜕𝜉 𝜕𝑞

(5)

(6)

In addition to the two elastic constants: Youngmodulus and Poisson ratio (E, ν), the neededparameters for the proposed model are: mp, mr, σ3b-d,
sp, sr, σc, ξr, βm and b1. All of these parameters can be
identifiable from triaxial compression tests (3minimum) carried out from low confining pressure(or without) to high confining pressure(characterizing σ3b-d). Finally the proposed model
was implemented in the three-dimensional explicit
finite-difference code, FLAC3D, where a perfectelastoplastic model with the Hoek-Brown criterion inthe (σ1, σ3) plane already exists in the commercial
version.
The most input data used in this paper are fromlaboratory tests, field studies, reports and papers.
More precisely, the Young’s modulus (E), Poisson's
ratio (ν) and the unconfined compressive strength(σc) have been obtained from the point and biaxial
load tests or uniaxial compression loading carried out

on samples (complex ores containing zinc, lead,silver, copper and gold) taken from the measuringholes at -883 m and -967 m levels (Edelbro, 2008;
van Koppen, 2008). These parameters and theempirical constants mp and sp, and dilatancy at failure
were confirmed by many numerical studies aimed tothe calibration of the mechanical characteristics, thedetermination of the in situ stresses (at -880 m leveland from one access gallery at -1155 m level,
respectively carried out by Boliden and INERIS) andthe understanding of the failure mechanism (forinstance spalling, shear failure, slabbing, buckling orother types of compressive failure) as well as the
back-evaluation of fallout extent observed in thefield.
It is known that it is often very difficult to get thefull stress-strain curves of the post-peak behaviour
particularly for hard rock masses exhibiting brittle
behaviour. As first approach, we retained the valuesof additional parameters (sr, σ3b-d, ξr, βm and b1)
summarized in Table 1: a sensitivity analysis on theseparameters will be conducted in parallel to theinterpretation of the in situ stress measurements at
1155 m coming in the future and whose deformation
measurement systems have already been installedfrom an access gallery at -1155 m level (Figure 1c).
Table 1: Numerical values of input model parameters.
Parameter
Value
Parameter
Value
E (MPa)80000
sr (-)
10-5 sp0.2
σ3b-d (MPa)σc√s≈63ν
mp (-)
10
0.0025ξr (-)
sp (-)
0.112
tan(15°)
βm(-)
188
b1(-)
750
σc (MPa)

3. NUMERICAL IMPLEMENTATION AND
MODEL VERIFICATIONSIn order to verify the implemented model, seven
triaxial compression tests with confining pressures
ranged from 0.01 to 75 MPa have been simulated.
The input parameters used for this exercise aresummarized in Table 1.
Figure 2 presents the deviatoric stress versus
axial and lateral strains curves for different confiningpressure (σ3). We note that the post-peak behaviour isconfining pressure dependent: the transition stressbetween brittle failure and ductile behaviour isclearly marked and the numerical transition stress,
σ3b-d, occurs for a confining pressure of 63 MPa in
accordance with the input numerical value.
Figure 3 shows a comparison in terms of thepeak and residual strengths between the predictions
and theoretical expression in equation (1) (withθ = 30° for triaxial compression loading path). The
match is very good as may be seen in this figure,where numerical and analytical solutions coincide.

80

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The relative error for peak and residual strengths isless than 0.3 % and 0.7 % respectively for peak andresidual strengths. This validates the numerical
implementation of the proposed elastoplastic modelin FLAC3D.
Deviatoric stress
400 σ 1 - σ 3 (MPa)σ 3 = 75 MPa

350

σ 3 = 60 MPa

300

σ 3 = 50 MPa

250

σ 3 = 25 MPa

200
150

σ 3 = 10 MPa

100

σ 3 = 5 MPa

50

σ 3 = 1 MPa
σ 3 = 0.01 MPa

0-0,0020Lateral strain (-)

0,002

0,004

0,006
Axial strain (-)

Figure 2: Numerical results of triaxial compression tests.
Deviator σ 1 - σ 3 (MPa)
Theoretical peak
400
Theoretical residual
Model (peak)
350
Model (residual)
300
450

Deviator σ 1 - σ 3 (MPa)
150

250
200

100

150

50

100

0
-2,5
0
2,5
5
7,5
10
Confining pressure σ 3 (MPa)

50
0
-10

0

10

20 30 40 50 60 70
Confining pressure σ 3 (MPa)

80

90

100

Figure 3: Peak and residual strengths: numerical andanalytical solutions.

4. APPLICATION TO GARPENBERG MINE
The aim of this section is to provide averification of the implementation for non-triaxial
stress paths and to show numerically the ability of themodel to evaluate the extent of potential damaged
zones in relation to the excavation of one or morestopes.
In the Garpenberg mine, polymetallic ore is
extracted which contains zinc, silver, lead, copperand gold. The ore has fold axis and the depth is 5001300 m below the surface. During the mining
operations of the upper level (-883 m and-967 m levels), several field studies and numericalmodellings were performed with the aim to calibrate
certain mechanical characteristics, back-determine
the initial and induced in situ stresses and tounderstand the potential failure mechanisms. The
results of these observations and measurements werealso used as input data for the preliminary 3Dmodelling of the initial stress field prevailing at thelower level around 1155 m deep before the future
excavation of stopes and for which stressmeasurements are available using CSIRO cells(Figure 4).
To retrieve the initial stress state (at 1155 m), a
3D numerical model has been carried out withseveral assumptions. A specific methodology forverifying the correlation of measured stresses (where
locations are illustrated in Figure 4) with computed
stresses (after mining operations of the upper level) isdeveloped: it consists of creating a stress data bankwith the numerical model according to the range ofmeasured stress tensors. Because the dependence
between initial and induced stresses is strongly nonlinear, it is very difficult to find what is the initialstress tensor that produces the correct measured
stresses after the excavation of many galleries andstopes and after a partial backfilling of the stopes(chambers). Nevertheless, it was possible to estimate
the initial stress tensor corresponding to level-1155 m. The horizontal and vertical directions are
principal with the following principal values
47.5 MPa (x-horizontal direction), 55 MPa (yhorizontal direction) and 20.5 MPa (vertically). This
stress state was used to uniformly load the numerical
2D-model shown in Figure 4.
As illustrated in Figure 1c, to model the minegeometry in 2D as first stage, we can consider adouble symmetry in the vertical and horizontal
directions. The geometrical model for 2D-modellingwith FLAC3D assuming plane strain conditions isshown in Figure 4. Null normal displacements are
imposed at the boundary limits (symmetry). The
access galleries are 10 m wide and 6 m high. Finally,
typical primary stope sizes are: 80 m long (along Ydirection), 10 m wide, and 19 m high.
The modelling sequences were performed asfollows: (a) model without excavations was
consolidated under the previous initial in situ
stresses, using roller boundaries to the model sides
respectively parallel to x- and z-axis for seeking
symmetry (step 0); (b) four galleries are
simultaneously excavated, numerical model is
stepped until equilibrium (step 1) and (c) stopes 1 and
2 are simultaneously deleted and the numerical modelis stepped until equilibrium.
The plastic zones corresponding to the galleries
excavation (phase 1) (or failed with behaviour inresidual or transition between peak and residual) arelimited to the galleries skin. This is consistent withthe observed fallouts (whose extension is around 0.05m) or predicted by numerical analysis conducted at-880 m level. This is also consistent with the strengthof the rock masses (σc√s≈63 MPa) and the magnitudeof induced stresses. In considering for example thecase of the gallery sides and assuming the linear
elasticity behaviour and neglecting variations of axial
stress, the expected orthoradial, radial, and axial

81

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

stresses are globally 16, 0, and 50 MPa. Thisconfirms the failure at the walls. Moreover, awayfrom the wall, the presence of a non null radial stresssignificantly increases the rock mass strength by theterm (mpσrσc), which explains the limited character offailed area around the galleries.

values: (-20.5, -17.5, 0.75 MPa) and (-48, -35.5,
0.85 MPa) respectively for #1 and #2 (compressive
stresses < 0). Finally, Figure 6b clearly shows asignificant increase in vertical stress (σzz) near thechanges of orientations of failure plane locations,indicating some eventual seats of potential risks of
instability.

z= -113020.5 MPa
Histories(displacements)

55
MPa

Histories(stresses)

47.5
MPa

P2
P1 P3
P4
z= -1180
x= 0

(a)

x= 50

Figure 4: Geometrical model with position of history
points.

After excavating the two stopes in a 2D model,
the extent of plastic zones is concentrated in the pillar(Figure 5), in the compressive region where themaximum deviatoric stress is located (at the heart ofpillars between stopes along the symmetry axis).
Figure 5a shows the distribution of plastic zones in
the pillars (and therefore strain localization). In fact,
the most compressive stresses are located at the
singularity levels (corners of galleries), but as themean stress also increases in magnitude, it is thesame for the failure strength. Excavation of stopes
results in complete release of the horizontal stress,
causing predominantly tensile stresses over the wholewidth and substantially all the height of pillars.
Therefore, the failures can be initiated at the center ofpillars and propagate along an inclined plane at first
and then sub-vertically following the localization of
the plastic zones. As a consequence of stressprojections on the current yield envelop, we observed
decreases in the vertical and axial stresses. This iswell illustrated in Figure 6, which shows the
distribution of horizontal and vertical stresses at theend of step 2.
For comparison purpose and in order to capture
the contribution of the proposed rheological model(#1), another simulation is performed with a basic
perfectly plastic model with Hoek-Brown’s criterion(model #2). In this case, the plastic zones are also
developed in the heart of the pillars but in a very
limited area compared to the results of the model #1(previously presented) without plastic strain
localization(Figure5b).
Specifically,theexamination of the principal stresses (σ1, σ2, σ3) atthe pillar center delimited by the two stopes for thetwo models 1 and 2 provides the following stress(b)

Figure 5: Extent of plastic zones around the stopes: (a)model #1 (b) model #2.

The quantitative comparison between the twomodels was conducted on the stress values at the endof step 2 (points 1 to 4 illustrated in Figure 4) andreported in Table 1 in terms of stress ratios withrespect to the initial stress state before the
excavations of galleries and stopes.
One can note that in both cases, the four points
are outside the plastic domain induced by galleries
and stopes. The points P1, P2, and P3 are located in
the pillar between the two lower galleries and point
P4 is located at the floor of a stope. Table 2 reveals aslight difference between the models on therelaxation at P1, P2, and P3 and compression at P4 of
the horizontal stresses (along x and perpendicular to
the model cross section). Conversely, over-stresses
develop in the vertical direction at P1, P2, and P3
positions with more magnitude (15 to 35%) for #1
compared to #2, resulting from the failure occurred alittle earlier in the pillar of stopes, and then a newstresses redistribution.

82

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

(MPa)

(a)

particular, the importance of considering the postpeak behaviour to predict strains and failure zones
localization, and consequently the advantage over theapproaches without strain softening is shown.
It is often difficult to characterize the post-peak
behaviour parameters from laboratory tests on such
hard rocks in relation to the brittle nature of their
behaviour. These parameters can be viewed as
calibration parameters, which can be backdetermined on the base of the in situ observations.
The prospect of this work after a full 3D modellingback-analysis would complete this numericaldevelopment by implementing the energy balance inview of assessing the proneness to rockbursts or
strain bursts.

6. REFERENCES

(MPa)

(b)

Figure 6: Horizontal (top) and vertical (down) stresses:
model #1.
Table 2: Ratio of horizontal (σxx), vertical (σzz) and axial(σyy) stresses.
σxx* P1
σzz* P1
σyy* P1
Model
#1
0.38
1.45
0.93
#2
0.41
1.59
0.94
σxx* P2
σzz* P2
σyy* P2
Model
#1
0.39
1.31
0.92
#2
0.42
1.57
0.94
σxx* P3
σzz* P3
σyy* P3
Model
#1
0.41
1.22
0.91
#2
0.41
1.58
0.94
σxx* P4
σzz* P4
σyy* P4
Model
#1
1.04
0.96
1
#2
1.05
0.87
1

5. CONCLUSION
This paper presents the development of aconstitutive model for brittle hard rock masses, its
numerical implementation in the three-dimensional
code FLAC3D, as well as its verification. Simulationof triaxial compression tests at different levels ofconfining pressure provides a verification of theimplemented model. The resulting curves display
three regions (elastic, softening in post-peak, andresidual phase) as well as a transition between brittle
failure and ductile behaviour as generally observedon hard and brittle rocks. The ability of the proposedmodel to predict the potential failure regions(damaged zones) around deep undergroundexcavations in hard rocks is successfully tested. In

Edelbro C. (2008). Strength, fallouts andnumerical modeling of hard rock masses. Doctoral
thesis 2008:56, Lulea University of Technology, 80p.
Haimson B. (2006). True triaxial stresses and thebrittle fracture of rock. Pure Applied Geophysics.
Volume 163(5–6), pp. 1101–1130.
Hoek E. and Brown ET. (1980). Undergroundexcavations in rock. The Institution of Mining andMetallurgy, London.
Horii H. and Nemat-Nasser S. (1986). Brittle
failure in compression: splitting, faulting and brittleductile transition. Philos. Trans. R. Soc. (London),Series A, Vol. 319, pp. 337-374.
Priest S.D. (2005). Determination of shear
strength and three-dimensional yield strength for the
Hoek–Brown criterion. Rock Mechanics and RockEngineering. Vol. 38(4), pp. 299–327.
Souley M., Armand G., Su K. and GhoreychiM., (2011). Modelling of the viscoplastic behaviour
including damage for deep argillaceous rocks,
Physics and Chemistry of the Earth, 36, pp. 1949–
1959.
Steif P.S. (1984). Crack extension undercompressive
loading.
Engineering
Fracture
Mechanics. Volume 20(3), pp. 463-473.
van Koppen M.J.G. (2008). Estimation of the
Risk for Mine Induced Seismicity in Large Scale
Mining in the Garpenberg Mine. Master of Science,
Delft University of Technology, Netherlands.
Zhang L. (2008). A generalized threedimensional Hoek–Brown strength criterion. RockMechanics and Rock Engineering. Vol.41(6), pp.
893–915.
Zhu Q.Z., Kondo D. and Shao J.F. (2009).
Homogenization-based analysis of anisotropic
damage in brittle materials with unilateral effect andinteractions between microcracks. Int J of Num andAnal Methods in Geomech. Vol. 33, pp. 749–72.

83

ISMS 2016

Paper No. 230

Estimating the probability of unsatisfactory performance associated with the
instability of mine developments
Wael Abdellaha, Hani Mitriba,*bDepartment of Mining and Metallurgical Engineering, Assiut University, Assiut, Egypt, 71516

Department of Mining and Materials Engineering, McGill University, Montreal, Canada H3A0E8

ABSTRACT
Mine developments are the main access to extract tabular ore deposits in deep underground mines. Therefore, theirstability is considered the principal priority during the mine production plan. The success of ore extraction mainly
depends on the stability and serviceability of mine developments. Mine development instability is expensive and is
a risk to personnel and equipment and in turn, it raises operational costs (e.g, repair costs, slashing, rehabilitation
costs, costs of adding secondary support, miners wages and delay of production) (Ellefmo, and Eidsvik, 2009;
Abdellah et al. 2014a; 2014b; 2014c). This paper aims to develop a hybrid approach in which deterministic
numerical modelling is integrated with probabilistic methods to estimate the probability of unsatisfactory
performance (e.g. rating and ranking) associated with the instability of mine developments with respect to mining
sequences adopting Rosenblueth’s Point-Estimate Method (RPEM). A three-dimensional, elastoplastic, finite
difference model (FLAC3D) is created (Itasca, 2009). The results are presented and categorized with respect to theprobability of instability and the mining stage.
KEYWORDS: Mine developments; numerical modelling; Rosenblueth’s Point-Estimate Method (RPEM);
probability of unsatisfactory performance

1. INTRODUCTION
Many Canadian metal mines adopt a sublevelstoping mining method with delayed backfill, as
shown in Figure 1. In this method, ore is mined out
into stopes (blocks), which are drilled and blasted.
The blasted ore from each stope is mucked out withloaders and transported from a draw point to a nearby
ore pass or dumping point. Mine developments (e.g.,haulage drifts, cross-cuts and their intersections) are
the only access where loaders and/or trucks travel
through on multiple levels. Therefore, theirserviceability must remain active for a few years(e.g., production plan of the mine) (Wei et al., 2012;
Zhang and Mitri, 2008). The following fiveparameters should be considered in the design
process: safety, serviceability (e.g., quality oftechnical solution), economics (e.g., cost),
environment, and rockmass properties. For example
rockmass properties alone are complex and areassociated with uncertainty in deep undergroundmines. These five factors should be maintained andcombined together in the decision-making process.
Consequently, wrong decision may lead tounwanted risks. In order to facilitate decisionmaking, probabilistic analysis should be adopted(Einstein, 1996; Sturk et al., 1996; Abdellah et al.,*Corresponding author – email: wre544@gmail.com

Figure 1: Section view shows sublevel stoping mining
method2014c). The stability performance of minedevelopments could be evaluated by adopting
analytical, empirical, and numerical modelling
techniques. The analytical methods such as those
provided by Kirsch (1898), Bray (1977), Bray and
Lorig (1988), and Ladanyi (1974) cannot provide
adequate solutions for complex mining problems.
Empirical methods such as the stability graphmethod, have become widely used in Canadianunderground mines. These methods are based on thepast experiences and rockmass classification systems.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

They employ certain geomechanical characteristics ofthe rockmass to provide guidelines on stability
performance and to determine the rock support
requirements. However, these methods cannot takeall the important influence factors into account.
Therefore, numerical methods have become widely
accepted in mine design and feasibility studies.
Numerical methods have the potential not only
to solve complex mining problems, but also to help
engineers and researchers better understand andassess failure mechanisms, estimate geotechnicalrisks, and design rock reinforcement systems more
effectively. Numerical analyses can be performed
deterministicallyorprobabilistically.
Inadeterministic analysis, the average values of the
rockmass properties are used as input parameters, anda unique model result is obtained. However, no
information can be obtained about the likelihood of
failure due to the inherent variability of model input
parameters. Thus, probabilistic methods are
employed to carry out stochastic analyses toovercome this shortcoming. The uncertainty
associated with the estimation of rockmass properties
has a significant impact on the design of undergroundexcavations. Thus, a reliable estimate of the strengthand deformation characteristics of rockmass isrequired for the stability analysis. Therefore,
probabilistic analysis is adopted in this investigation
using Rosenblueth’s point-estimate method (RPEM).

Also, the unsatisfactory performance isdetermined when the extent of the strength-to-stressratio contours, corresponding to Mohr-Coulomb
strength-to-stress ratio <1.40 exceeds the anchorage
limit of the rockbolt from the excavation surface. For
a 2.40 m bolt, the minimum support limit fromexcavation surface is 2.10 m. Thus, the stability ofminedevelopment
intersection
becomes
unsatisfactory if the following two conditions are met
together: Mohr-Coulomb strength-to-stress ratio
based yielding <1.40.
 Extent of the strength-to-stress ratio
contours >2.10 m.

3. CASE STUDY
To examine the stability of mine development
intersections, a plan view of the 1540 level is shownin Figure 2. The study zone is divided into thefollowing three zones; hanging wall (HW), orebody,and footwall (FW).
Haulage drifts, minedevelopments and their cross-cuts are driven into thefootwall rockmass. The stope dimensions are
12×15×30 m (L×W×H). The stopes are extracted andthen tight filled with a mixture of pastefill and wasterock.

2. FAILURE EVALUATION CRITERION
In order to assess the stability of the minedevelopment intersection, a performance criterionmust first be selected. This may be one of numerous
conditions such as maximum permissible floor heave
ratio or roof sag ratio, or allowable stressconcentration factor (normally associated with linear
elastic analyses), or a yielding condition such as
Mohr-Coulomb or Hoek-Brown (Zhang and Mitri,
2008; Abdellah et al., 2012). The choice of aperformance criterion is dependent on the applicationand field observations. In this current study, a yieldbased criterion has been selected in which MohrCoulomb is used as the failure condition. The
strength-to-stress ratio is a readily available
parameter in FLAC3D (ITASCA, 2009) and a formof a safety factor. For mining applications, it isrecognized that the factor of safety of permanentmine openings such as mine shaft and mine
infrastructure should be higher than that used formine developments, which are required to be opened
and functional for the life of a mine (production)plan. Therefore, in this study, a strength-to-stressratio of 1.4 was deemed an appropriate safety factor,
given the fact that the required service life of thedevelopments in the study area is only a few years.

Figure 2: Level plan shows the mine development
intersection#6 under the study.

The orebody has a strike length of approximately
220 m. To maintain better ground conditions, thestoping sequence from one level to another and along
the ore strike should follow a pyramid shape asshown in Figure 3. Such sequence helps mitigate
stress concentration and facilitate secondary stopemining thus increasing safety and mining recovery
rate. The stability analysis is conducted for theorebody, whereby a planned sequence of 72 stopes

85

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

over six production levels (1600, 1570, 1540, 1510,
1480 and 1450) is simulated in the form of 18 mineand-fill numerical model steps. While doing so, thestrength-to-stress ratio is monitored on level 1540 at
the intersection of the haulage drift with the cross cut#6 location.

numerical modelling
becomes necessary.

(deterministic

techniques)

4.1 Deterministic analysis
Deterministic analysis is performed to investigate
the effect of mining sequence on the stability of theintersection #6 on level 1540. The physical andgeomechanical properties of rockmasses used in thedeterministic analysis are listed in Table 1 (Abdellah
et al., 2013).
Table 1: Physical and geomechanical properties ofrockmass properties used in the model (Abdellah et al.,2013).
Rock

Figure 3: Pyramidal shape stoping sequence along theorebody strike.

4. NUMERICAL ANALYSIS
Rockmass properties are significant geotechnicaldesign input parameters. These parameters are neverknown precisely. There are always uncertainties
associated with them. Some of these uncertainties are
due to lack of knowledge or limited collected dataand some are intrinsic. Furthermore, some may arise
from errors in testing (e.g. estimating strength of
intact rocks, mapping the joint spacing, assessing thejoint surface condition), and random data collection.
All these uncertainties are attributed to the inherent
nature of the rockmass characterization (Glaser andDoolin, 2000). Therefore, it is important to address
the effect of these parameters on the design using
probabilistic methods of analysis. Well assessment of
uncertainty in rockmass characterization can assist to
better understand how the decision of rock support
design systems is affected by it.
In this investigation, the focus is the uncertainty
arising from the rockmass properties (e.g. rockmassof footwall) and their effect on the stability of minedevelopment intersections (e.g. which are driven in
the footwall). Probabilistic methods provide arational and efficient means of characterizing theinherent uncertainty that is common in geotechnicalengineering. Because of the inherent uncertainty
associated with parameters such as the rockmass
properties around the openings, there is also
uncertainty as to when and where additional rock
support is required. Thus, predicting the probabilityof unsatisfactory performance using probabilistic
analysis approaches together with the developed

HW
ORE
FW
BF

Rockmass properties
C
MPa
5.1
4.3
5.7
1

𝜑
(0)
52
46.7
54.9
30

σt
MPa
0.53
0.56
0.51
0.01

E
GPa
45.5
43.8
65.0
0.01

υ
0.24
0.30
0.23
0.30

γ
Kg/m3
2780
4530
3170
2000

Ψ
(0)
13.0
11.68
13.73
7.50

The deterministic results show that the values ofstrength-to-stress ratio deteriorates as mining
progresses in the roof, wall, pillar corner left, andpillar corner right. However, the two conditions offailure evaluation criterion are met in the roof aftermining step 6 until the end of mining activity (e.g.,
from step 6 to step 18), whilst the conditions are not
met in the wall of the intersection #6 during thewhole mining steps. The two evaluation conditions
are achieved in the pillar corner left after mining step
9 and in the pillar corner right after mining step 10.
The complete deterministic analysis results ofstrength-to-stress ratio with respect to all 18 mining
steps modelled are plotted in Figure 4. As can beseen, the wall the strength-to-stress ratio is well
above the threshold of 1.4 thus suggestingsatisfactory performance (e.g., the depth of theboundary limit is zero along all mining steps). For
the roof at the intersection #6, the strength-to-stressratio drops below the 1.4 limit after mining step 6.
For the pillar corner left and pillar corner right, theratio drops after mining steps 9 and 10, respectively.

86

Extent of strength-to-stress contours (m) atratio ≤ 1.40

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

18
16
14

Based on the parametric study (sensitivity
analyses) that has been conducted by Musunuri(Musunuri et al., 2009), the most influential model
input parameters on the stability of mine haulage
drift are Young Modulus (E), cohesion (C), and angle
of internal friction (φ).

Roof
Wall
Pillar corner left
Pillar corner right

12
10
8

Table 2: Stochastic properties of footwall rockmass.

6

Rockmass
property

Mean,µStandard
deviation,σ

Coefficientof variance,δ1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Cohesion (MPa)

5.70

1.14

0.20

Mining step

Friction angle, (º)

54.90

10.98

0.20

Figure 4: Extent of strength-to-stress contours at ratio of ≤1.4 at various mining step (deterministic analysis).

Young’s Modulus,
(GPa)

65.0

13.0

0.20

In light of these results, it can be said that
secondary support may be recommended after mining
step 6 in the roof (i.e. after 30 stopes have been
extracted). For pillar corner left and pillar cornerright, the secondary support may be recommended
after mining step 9 (i.e., after 40 stopes have been
extracted) and step 10 (i.e., after 44 stopes have been
extracted), respectively. While these results areuseful, the effect of the inherent uncertainty inrockmass properties is still unknown; hence theprobabilistic analysis is necessary. This is presented
in the following section.

4.2.1 Probabilistic results
The stochastic material properties of the footwall
are assigned as listed in Table 2 above. The mean andstandard deviations of these values are selected fromanormaldistribution.
The
Rosenblueth’s(Rosenblueth, 1975) point-estimate method (RPEM)
of 2n (i.e., where n is number of stochastic input
parameters) is adopted in this investigation for theabove three input variables. The stochastic analysis
results are plotted in Figure 5 for an average of 8
simulations (i.e., 23 = 8).

4

Threshold = 2.1m

2

4.2 Probabilistic analysis
Due to the heterogeneity of the rockmass, datafrom underground excavations are limited. Therefore,a great deal of uncertainty is inherent in the design ofunderground excavations. In order to develop a
reliable design approach, one must use methods thatincorporate the statistical variation of the numericalmodel input parameters representing the rockmass
properties, i.e. mean, variance and standard deviation,
as well as the design of rock failure criteria(Kwangho et al., 2005). Probabilistic material
properties of the footwall are assigned (see Table 2).
The means and standard deviations of these values
are picked from the assumed normal distribution.
The sensitivity analysis can be carried out by
varying a single parameter (random variable) at eachrun based on a specified coefficient of variation(COV) and monitoring the effect of this variation on
the applied performance criterion. The variable ateach run has one value of (µ − σ), or (µ + σ) while
keeping all other parameters constant (no change intheir average values). Sensitivity analysis gives agood understanding of the effect of certain
parameters on the overall model behaviour. However,no distribution is obtained for the output parameters(random variables).

Average extent of strength-tostress contours, m (at ratio <1.4)

0

22
20
18
16
14
12
10
8
6
4
2
0

Roof
Wall
Pillar corner left
Pillar corner rightThreshold = 2.1m

1 2 3 4 5 6 7 8 9 101112131415161718
Mining step
Figure 5: Average extent of strength-to-stress contours atratio of ≤ 1.4 at various mining steps (stochastic analysis).

As depicted in Figure 5, the stochastic analysis
agrees with the deterministic analysis in terms ofshowing that the strength-to-stress ratio deteriorates
as mining progresses. In the roof of intersection #6 at1540 level, the strength-to-stress ratio falls below
threshold (i.e., ratio <1.4 and length >2.1 m) aftermining step 1, versus step 6 with deterministic
analysis. In the wall, the ratio does not fall below the87

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

threshold in the deterministic analysis, whereas withstochastic analysis, it falls below threshold aftermining step 15.
For the pillar corner left, theperformance criterion becomes unsatisfactory aftermining step 5 with stochastic analysis where it
deteriorates after mining step 9 with deterministic
analysis. For pillar corner right, the failure also
occurs after mining step 5 with stochastic analysis
whereas its instability occurs after mining step 10
with deterministic analysis.
Comparing these two methods of analysis,
stochastic results call earlier for secondary supports
than with deterministic analysis (i.e., roof calls forsecondary support after mining step 1 comparing
with the deterministic analysis (after mining step 6)).
Wall in deterministic analysis seems to be morestable and no support is required during the whole
mining step comparing with probabilistic analysis(i.e., support may be required after mining step 15).
Pillar corner left and right require support aftermining step 5 with probabilistic analysis, comparedwith mining steps 9 and 10 with deterministic
analysis. Thus, stochastic results appear to be moreconservative than the deterministic analysis. The
reason behind this is that the stochastic method takes
into account the inherent uncertainty associated with
input variables (i.e., rockmass properties). The
deterministic analysis only uses the average values ofrockmass properties as input parameters and gives
only a single value as an output. However, theprobability of unsatisfactory performance should be
estimated to decide when and where secondary
support is needed.
4.3 Probability of unsatisfactory performance
The probability of unsatisfactory performance isestimated for the roof, wall, pillar corner left andpillar corner right of intersection #6 at 1540 level,with respect to mining step. The suggested rating andranking of likelihood of failure are given in Table 3.
Standard normal distribution tables (Z-tables) areused to estimate the probability of failure, Pf. The Pf
isobtainedbysubtracting
theshadedarea�Threshold (X)−average value(µ)
standard deviation (σ)∗

�shaded area, Z =��; under the probability

density function (PDF) curve from the unity which
represents the total area�𝑃𝑓 = 1 − 𝑍 ∗ �. The results
for the probability of unsatisfactory performance areplotted and categorized in Figure 6. As can be seen,
the probability of unsatisfactory performance at theroof of the intersection #6 is certain after mining step
4 (i.e., Pf >85%). Thus, the need for secondary
support is necessary at this early stage (i.e., before

step 4). On the other hand, the wall calls forsecondary support at latest stages (i.e., after mining
step 16) as the probability of unsatisfactory
performance becomes likely (i.e., 60<Pf <85%). The
pillar corner right and left call for secondary support
at middle stages (i. e., after steps 10 and 11,
respectively) as the probability of instability becomescertain (i. e., Pf >85%).
Table 3: Suggested rating and ranking of probability ofunsatisfactory performance (Abdellah et al., 2012).
RatingRanking

1

Rare

2

Unlikely

3

Possible4

Likely5

Certain

Probability of Unsatisfactory
Performance, Pf
< 5%
May
occur
in
exceptional
circumstances
5%-20%
Could occur at sometime
20%-60% Might occur at sometime
60%-85% Will probably occur inmost circumstances>85%
Expected to occur inmost circumstances

Figure 6: Probability of unsatisfactory performance at roof,
wall, and pillar corner left and right of intersection #6 atlevel 1540 at various mining step.

5. CONCLUSION
Mine developments, such as haulage drifts,
cross-cuts and their intersections, play a vital role inproviding access to ore extraction areas for mine
production. The stability of mine developments isthus of crucial importance during the life of a mineplan. This paper examines the stability of minedevelopment access intersection #6 with respect toplanned mining sequence. A 3D elastoplastic finite
difference model is created using FLAC3D and
employed in conjunction with the probabilistic
method of analysis (RPEM) of 2n, for a development
intersection situated 1.5 km below the groundsurface. The stability or performance of the88

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

intersection is evaluated in terms of the strength-tostress ratio. The stability performance of mineintersection is evaluated on the basis of the primaryrock support length comprising 2.4 m resin grouted
rebars in the roof and wall. The stability performanceof the intersection is considered unsatisfactory if thestrength-to-stress contours correspond to ratio <1.4
and extends beyond the anchorage limit of the
rockbolt (i.e., >2.1 m).
The results are presented and categorized withrespect to probability, instability, and mining stage.
The probability of unsatisfactory performance, Pf, of
the intersection #6 is certain (Pf >85%) in the roof
after mining step 4, and is likely (i.e., 60<Pf <85%)in the wall after mining step 16 (i.e., at the end of themining step). The pillar corners right and left call forsecondary support at the mid of mining step (i.e.,
steps 10 and 11, respectively) as the probability of
instability is certain (i.e., Pf >85%). Therefore, theseresults shed light on the requirement for the
installation of enhanced support at the intersection
during the planned mining step.

6. REFERENCES
Abdellah, W., Raju, D., Mitri, H. S., andThibodeau, D. (2014a). "Stability of undergroundmine development intersections during the life of amine plan". International Journal of Rock Mechanics& Mining Sciences (IJRMMS): 72 (2014) 173–181.
Abdellah, W., Mitri, H. S., Thibodeau, D. andMoreau-Verlaan, L., (2014b). “Risk indexing tool
for mine planning", Journal of the Southern African
Institute of Mining and Metallurgy (SAIMM).
Volume 114, June 2014. Pp. 1-9.
Abdellah, W., Mitri, H. S., Thibodeau, D. andMoreau-Verlaan, L., (2014c). “Geotechnical Risk
Assessment of Mine Development Intersections withrespect to Mining Sequence”. Journal of
Geotechnical and Geological Engineering (JGGE).
June 2014. Volume 32, Issue 3, pp. 657-671.
Abdellah, W., Mitri, H. S., Thibodeau, D. andMoreau-Verlaan, L., (2013). “Stability of Mine
Development Intersections – A Probabilistic Analysis
Approach ". Canadian Geotechnical Journal (CGJ),
2014, Vol. 51, No. 2. Pp. 184-195. Doi: 10.1139/cgj2013-0123
Bray, B. ( 1977). "An analysis of rockbehaviour in an experimental stoping block at
the Mount Isa Mine. Geomech Abstr." Int. J RockMech Min Sci 14: 59-66.
Bray, B. and L. Lorig (1988). "Analysis of rockreinforcement using finite difference
methods." Comp Geotech 5(2): 123-149.
Ellefmo, S. L., and Eidsvik, Jo. Local andSpatial Joint Frequency Uncertainty and Its

Application to Rock Mass Characterisation. RockMechanics Rock Engineering 42 (2009), 667-88.
Glaser, S. D., and Doolin, D. M., New
directions in rock mechanics - report on a forum
sponsored by the American Rock Mechanics
Association. International Journal of Rock Mechanics
and Mining Sciences 37 (2000) 683-698.
ITASCA, Fast Lagrangian Analysis of Continua
in 3 Dimensions (FLAC3D),User's Manual Ver. 4.0,
Itasca Consulting Group Inc., Minneapolis,
Minnesota 55401 USA, 2009.
Kirsch, G. (1898). "Die theorie der elastizitat
und die bedϋrfnisse der festigkcitslchre" Veit Ver Deut Ing 42: 797-807.
Ladanyi, B. (1974). Use of the long-term
strength concept in the determination of groundpressure on tunnel linings. Advances in rockmechanics, proceedings of the third congress,
International Society of Rock Mechanics, Denver:
National Academy of Sciences.
Musunuri, A., W. Wei, et al. ( 2009).
Assessment of drift stability using probability of
failure. . In Proc Eighteenth International Symposiumon Mine Planning and Equipment Selection. A.
Mehrotra, F. K. and H. G. eds. Singhal, R.K. Banff,
AB: 987-996.
Rosenblueth, E. (1975). "Point estimates forprobability moments" Proc. Nat. Acad.
Sci. Vol. 72, No. 10: 3812-3814.
Wei, W., Mitri, H. S. & Kelly, C. May 5-9,
2012. 'Evaluating Immediate Mining Induced Ground
Movement the Performance of the Primary Support
System.' Paper presented at In Proceedings of 21st
Canadian Rock Mechanics Symposium, RockEng12.
Zhang, Y. & Mitri, H. S. 2008. 'Elastoplastic
stability analysis of mine haulage drift in the vicinityof mined stopes.' International Journal of
RockMechanics and Mining Sciences (IJRMMS),
45, 574-93.

89

ISMS 2016

Paper No. 154

Numerical modelling of time-dependent skin degradation of an isolated pillar
Atsushi Sainoki *, Hani S. Mitri
Department of Mining and Materials Engineering, McGill University, Montreal, Canada, H3S1R7

ABSTRACTThis study focuses on the instability mechanism of an isolated pillar, caused by time-dependent skin degradation andstrength heterogeneity. The time-dependent skin degradation is simulated with a non-linear rheological model
capable of simulating tertiary creep. The inherent strength heterogeneity is realized with Weibull’s distribution. The
results obtained from the analysis show that pillar degradation is limited to the regions near the surface or the skinuntil two months after ore extraction, but afterwards degradation starts to extend deeper into the pillar, eventuallyleaving a highly stressed pillar core due to stress transfer from the failed rock regions. Rockburst potential indicesshow that the risk increases exponentially at the core as time goes by. It is then demonstrated that the progressive
skin degradation cannot be simulated with the conventional strain-softening model assuming brittle failure. The
parametric study with respect to the degree of heterogeneity reveals that heterogeneity is key to the occurrence ofprogressive skin degradation. Although the average UCS in the model with a high degree of heterogeneity is almost
the same as that in the model with a low degree of heterogeneity, degradation of the rockmass extends deep into thepillar only when the pillar material is highly heterogeneous.
KEYWORDS: pillar stability; underground mine; skin degradation; rheological model; time-dependent failure

1. INTRODUCTION
A pillar is a rockmass that remains to increase
the stability of underground openings. The stabilityof isolated pillars is crucial because the failure ofpillars can lead to fatal accidents and might cause thecollapse of rockmass in an extensive area (Cording etal., 2015). Furthermore, pillars can be the cause forrockburst in the case of deep hard rock mines becauseof the high strain energy stored within the pillar andcharacteristics of rockmass exhibiting extremely
brittle behaviour. Hence, the stability of isolated
pillars needs to be evaluated and assessed in an
appropriate manner.
A number of studies have been undertaken to
estimate the stability of pillars (Martin et al., 2000).
In addition, various empirical equations have been
proposed for the estimation of a factor of safety(FOS) (Potvin et al., 1989; Sjöberg, 1992; Van der
Merwe, 2003). Notwithstanding the significant
efforts, pillars with a high FOS occasionally fail andcollapse, which would be attributed to unknown
uncertainties.
As such uncertainties, the strength heterogeneityof rockmass and time-dependent degradation of apillar skin would be considered. Indeed, thedegradation of a pillar skin, which is represented byspalling, scaling, or strength decay, has been studied
by many researchers (Cording et al., 2015; Napier etal., 2012). The schematic illustration of spalling thattakes place in a deep hard rock mine is delineated in
Figure 1. As can be seen in the figure, due to the*Atsushi Sainoki – email : atsushi.sainoki@mail.mcgill.ca

spalling, the side wall of the pillar is loosened andloses load-bearing capacity, consequently inducing
additional loads to the core of the pillar. When theregion undergoing strength degradation is sufficiently
large, FOS of the pillar can decrease to a criticalvalue due to the increase in stress acting in the pillar
and the decrease in the cross section of an intact
region. In previous studies, the typical simulation
technique to simulate the degradation of a pillar sidewall is to employ an exponential function to estimate
the time-dependent strength decay of rockmass or todecrease rockmass strength in a loosened region
under low confining stress near a pillar surface.
Importantly, both of the simulation techniques are
based on field observations or unverified assumptions
The present study focuses on the time-dependentskin degradation of an isolated pillar due to theoccurrence of creep behaviour that eventually leads
to the critical failure of rockmass whilst considering
the strength heterogeneity with Weibull’s distribution(Weibull, 1951). The mechanism and process ofstress transfer from loosened near-surface regions to
the intact area of the pillar are investigated with the
non-linear rheological constitutive model with input
parameters derived from laboratory experiments. The
comparison of the rheological model with theclassical Mohr-Coulomb model taking into accountbrittle failure (strain-softening) is made in order toemphasize the importance of considering the timedependent degradation of a pillar skin.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
where σ1 and σ3 are the maximum and minimum
principal stresses, respectively; σmax is the maximum
stress calculated from a failure criterion. Note thatcompression is a positive quantity in the equations.
The severity for tensile failure is calculated asfollows:
σ* =Figure 1: Schematic illustration of skin degradation of an
isolated pillar due to spalling.

2. METHODOLOGY
2.1 Constitutive model
As indicated by Scholz (1968), the creep
behaviour of rockmass is essentially the progressive
development of microcracks, which pertains to thedegradation of rockmass. Thus, the present study
employs a creep model. To date, a number of
constitutive models have been proposed andemployed to simulate the creep behaviour ofrockmass (Barla et al., 2012). Importantly, few of themodels are capable of simulating tertiary creep thatcauses rockmass to fail. In order to take tertiary creep
into consideration, the present study employs the
non-linear rheological model proposed by Okubo etal. (2006). The advantage of the constitutive modelover the other models considering tertiary creep(Barla et al. 2012) is that the analytical solution of
creep lifetime, i.e., time to final rupture, is provided(Okubo et al., 2006).
The non-linear rheological model is expressed asfollows:mdλ* 1 m n − m +1 * m * n)(λ ) (σ )= ((1)
dt t 0 n + 1
where λ* is compliance normalized by its initial value,
λ0; σ* is called severity; n and m represent the degreeof time dependency and ductility of rock,respectively; t is time; t0 is time that it takes for theaxial stress applied to a rock specimen to reach its
peak axial value during an unconfined compression
test. In the present study, t0 is determined whilst
assuming a uniaxial test with a typical axial strain
rate. The constants, n and m, for granite are takenfrom the database (Okubo et al., 2006). The constant,n, is derived from uniaxial compressive strengths
obtained from unconfined compression tests under
different axial strain rates, while the constant, m, isestimated from the shape of a post-peak behaviour
curve (Okubo et al., 2006).
The severity, σ*, is given using deviatoric stressas follows:
σ −σ3
(2)
σ* = 1σ max − σ 3

σ3
σt

(3)

where σt is the tensile strength of rock. The larger oneof the severities determined by Equations (2) and (3)is adopted as σ* and substituted into Equation (1). As
Poission’s ratio, v, is expected to increase with theprogression of rock degradation, Okubo et al. (1993)
use the following equation to relate v with λ*:ν = 0.5 −0.5 − ν oλ*(4)where vo is an initial Poison's ratio. The modulus ofelasticity is calculated with λ* as follows:
E=

Eo

λ*

(5)

where Eo is an initial value of modulus ofelasticity. Regarding the failure criterion to calculate
the severity, the classical Mohr-Coulomb failure
criterion is employed because of its simplicity. As
this study does not aim at calibrating analysis
conditions and mechanical properties of rock basedon actual field measurements, the use of the MohrCoulomb failure criterion is deemed sufficient. In
addition to that, it is noteworthy that although
Equations (1) to (5) indicate that compliance might
increase even under initial stress conditions before
mining activity starts, it has been confirmed that theincrease in compliance is extremely small even whenseveral hundred million years passed if there is nomining activity.
2.2 Generalized simulation procedure
When the non-linear rheological model is
employed, an iterative analysis is carried out, ofwhich the generalized procedure is shown in Figure 2.
As can be seen in the figure, after the numericalmodel construction, in-situ stresses are applied if
necessary. This means that when the time dependent
behaviour of in-situ rockmass in an undergroundmine is examined, in-situ stress conditions need to be
simulated. On the other hand, when the timedependent behaviour of a rock specimen during alaboratory test is simulated, there is no need to apply
such in-situ conditions to the model. As the present
study applies the rheological model to two different
numerical models representing a room-and-pillar
mine and an unconfined compression test under aconstant strain rate, the difference in the initialboundary conditions between the two numericalmodels is described for clarification. At the third step,91

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the conditions that cause creep behaviour are applied.
In the case of room-and-pillar mining, the condition
is ore extraction and the generation of an isolated
pillar, while in the case of laboratory test, axial strain
that increases with time, is applied to the top
boundary of the rock specimen. Subsequently, a static
analysis is carried out and if the elapsed time, t, has
not yet reached the pre-determined tmax, themaximum and minimum stresses are computed foreach zone. The, the mechanical properties are
updated according to Equations (1) to (5).
Model construction
Apply mechanical properties
and simulate in-situ stresses if
required
Apply conditions related tothe occurrence of creep
behaviour

Update E and ν

Perform static analysis

Update λ*Not >tmax?

t = t + dt

Calcualte stress for each
zone

Yes
End

Figure 2: Procedure of iterative analysis.

2.3 Numerical model description
Figure 3 shows a 3D numerical model analyzed
in the present study, which is constructed with
FLAC3D (Itasca, 2009). The symmetry of the pillar
is taken into account, that is, the pillar in the figure
represents one-fourth of the actual pillar with thewidth of 10 m. The green-coloured region is
extracted during analysis, and the dimension isdetermined so that the FOS of the pillar falls between
1.0 and 1.4. The FOS is evaluated with empiricalequations (Potvin et al., 1989; Sjöberg, 1992). The
stability of pillars with FOS in the range is uncertain(Martin, 2000) and assumed to be affected by anumber of factors such as the time-dependentdegradation. Thus, it is worth examining.
Pre-mining stress state is based on the equations
proposed by Diederichs (1999). The mining depth isassumed to be 1500 m. The stresses computed fromthe equations are applied to each zone in the model.
Note that the maximum horizontal stress is applied in
the x-direction. Fixed boundary conditions are
employed, that is, the displacements on the modelouter boundaries are fixed in the direction
perpendicular to the boundaries.

Figure 3: Numerical model analyzed.

2.4 Mechanical properties
Granite is assumed as the main type of rockmasscomposing the pillar. In order to convert mechanicalproperties obtained from laboratory experiments to
those for the rockmass, RMR = 92 is assumed, whichis the upper limit of rockmass encountered in the
Canadian Shield (Martin, 2000). Herein, RMR is the
rockmass rating system proposed by Bieniawski(1989). The mechanical properties of intact granite
are derived from the study (Yun, 2008). Using the
RMR, the deformation modulus, E, in Table 1 isobtained with the equation (Mitri et al., 1994). The
uniaxial compressive strength is calculated with the
Hoek-Brown failure criterion while substituting σ3 =0. The tensile strength is assumed to be one-tenth of
the uniaxial compressive strength (Tesarik et al,2003). For the constants in Equation (1), n = 51 andm = 51 are derived for granite (Okubo et al., 2006).
Table 1: Mechanical properties of granite for rockmass.
E
ν
σc
C
σT
Densityφ(GPa)(MPa) (MPa) (˚ (MPa) (kg/m3)
)
59
0.26
116
14.8
63
11.6
2600

2.5 Strength heterogeneity of rockmass
The inherent strength heterogeneity of rockmass
is taken into account with the Weibull’s distribution,
which is expressed as:f (u ) =α −1α u  
u0  u0   u α 
exp −     u0  



(6)

where u and u0 are a mechanical property and a scaleparameter related to the average value of themechanical property, respectively; α represents thedegree of heterogeneity. In a base model, α = 5 is92

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

taken. Figure 4 shows the heterogeneity of UCS forthe case.

Figure 4: Heterogeneity of UCS simulated with the
Weibull’s distribution (α = 5).

2.5 Determination of upper limit of λ*Although the rheological model assumes that λ*increases infinitely, its upper limit needs to be
determined to ensure computational stability. To doso, a uniaxial test is simulated with a cylindricalmodel under a constant strain rate. When the upper
limit is low, the strain softening during post-peak
behaviour is not sufficiently simulated. During thesimulation, displacements are applied to the top
boundary at the third step in Figure 2. Analyses are
performed while changing the upper limit from 50 to1000. It is then found that when the upper limit is1000, brittle behaviour is adequately replicated. It
should be noted, however, that when the brittle
failure takes place, λ* does not reach 1000 in all thezones because failure takes place locally. Thus, it is
not appropriate to apply the upper limit to the pillar
model, directly. In light of the result, the averagevalue of λ* in the cylindrical model at the failure iscomputed. The computed average is near 285. Thus,
after rounding up, the upper limit is set to 300 for thepillar model.

the failed regions. This indicates that the pillar
becomes extremely burst-prone.
In order to investigate the burst proneness of thepillar, brittle shear ratio (BSR) proposed by Castro etal. (2012) and burst prone index (BPI) proposed by
Mitri (1999) are computed at the center of the pillar.
As can be seen from Figure 6, both of the indices do
not show a noticeable increase until 72 days,
whereas, after that, the indices increase
exponentially, indicating that the failure propagation
becomes uncontrolled. Eventually, after 226 days
have passed, BPI and BSR increase to 222% and1.33, respectively. As expected, both the values
indicate extremely high possibility of a rockburst
taking place.

Figure 5: Maximum compressive stress in the pillar.

3. RESULTS
3.1 Time-dependent skin degradation
Figure 5 shows change in the maximum
compressive stress within the pillar with time. It isfound from the figure that the pillar surface can carrystress immediately after the extraction. The low stressregions are limited to the zones with particularly low
initial strength. There is no noticeable change in the
stress state until 33 days after the extraction.
However, when 72 days have passed, low stressregions extend to almost entire the surface, indicatingthat the rockmass near the surface lost load-bearing
capacity due to the time-dependent degradation. After
187 days, the degradation of rockmass extends
deeper into the pillar, and the pillar core carries
extremely high stresses due to the stress transfer from

Figure 6: Burst proneness at the center of the pillar.

3.2 Comparison with strain-softening model
In order to make the difference between the nonlinear rheological model and the conventional strainsoftening model clearer, the comparison between themodels is made. The strain-softening model employs
the conventional Mohr-Coulomb criterion with the93

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

consideration to strain-softening behaviour, that is,when failure takes place, the cohesion is decreased tozero. A static analysis is conducted with the samemodel as shown in Figure 4.
Figure 7 shows the maximum compressive stressobtained from the analysis. Remarkably, there is aclear difference in the stress state within the pillar
between the models. When the strain-softening model
is employed, the region with low stresses occurs only
near the surface. The considerably high stresses at thepillar core shown in Figure 5(d) are not found in
Figure 7, implying that the use of the conventionalmodel might underestimate the possibility of failure
when there is the heterogeneity of strength.
Conversely, when the rockmass is completely
homogeneous, there will be no large difference
between the two models.

When α is low, the possibility that zones with low
UCS are present in the vicinity of each zone is clearlyhigher. From the figure, it can be deduced that theintensive skin degradation shown in Figure 5(d)occurs due to the chain effect of failure through zones
with low UCS, i.e., stress transferred from a failed
zone causes failure in adjacent zones, which
eventually escalates into the chain effect. Zones withextremely low UCS exist even when α = 6. However,in order for the failure to propagate to adjacent zones,
zones with low UCS must exist in the vicinity of thefailed zone. When α = 5, it is assumed that theconditions are satisfied, so that the failure becomes
uncontrolled after sufficient time has elapsed.
Importantly, the chain effect cannot be adequately
simulated with the strain-softening model as shownin Figure 7 because the non-linear rheological model
simulates strength degradation with tertiary creep
even if the maximum stress is less than the maximum
strength.

Figure 7: Maximum compressive stress obtained fromstrain-softening model.

3.3 Effect of degree of strength heterogeneity
In addition to the model shown in Figure 4,
another model is constructed with α = 6 in Equation(6). The model is shown in Figure 8. The larger α, themore homogeneous the model becomes. Except forthe parameter, the same procedure is taken.
Interestingly, the analysis reveals that the progressive
skin degradation does not occur even after 7 years
when α = 6. It should be noted that, in terms of an
average UCS in the pillar, there is no large difference
between the two models. Indeed, the average UCS is
107 MPa and 108 MPa for the models with α = 5 and
6, respectively. It is thus unlikely that the occurrenceof the intensive degradation of rockmass shown in
Figure 5 is determined by the slight difference in the
average UCS.
In light of the results and with respect to eachzone in the pillar, the minimum UCS in adjacentzones is investigated. Figure 8 shows the results. For
instance, when α = 5, the number of zones that haveadjacent zones with UCS between 30 MPa and 50
MPa is approximately 240. The figure obviously
displays the difference between the two models.

Figure 8: Heterogeneity of UCS simulated with the
Weibull’s distribution (α = 6).

Figure 9: Relation between minimum UCS of adjacentzones and the total number of zones with the adjacent zones
within the pillar.

4. CONCLUSIONSThe time-dependent skin degradation of an
isolated pillar in a deep hard rock mine is simulatedwith a non-linear rheological model whilst taking into94

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016account the inherent strength heterogeneity of the
rockmass. Analysis results show that the skindegradation extends deep into the pillar whensufficient time has elapsed, resulting in a highly
stressed pillar core due to the stress transfer from thefailed region. Rockburst potential indices calculated
at the core show extremely high risk for rockburst.
The analysis conducted with the conventional strainsoftening model demonstrates that the propagation ofskin degradation into the inside of the pillar cannot be
replicated with the strain-softening model,
emphasizing the importance of the time-dependentskin degradation. The propagation of failure into theinside of the pillar is not simulated in the model withlesser strength heterogeneity, although an average
UCS within the pillar is almost the same for the twomodels. It is then deduced that the presence ofadjacent zones with low UCS is a key to theprogressive skin failure because it gives rise to thechain effect of failure with stress transfer from thefailed zone to the adjacent zones.

5. ACKNOWLEDGEMENT
This work is financially supported by a grant by
the Natural Science and Engineering ResearchCouncil of Canada (NSERC) in partnership with ValeLtd – Sudbury Operations, Canada, under the
Collaborative Research and Development Program.
The authors are grateful for their support.

6. REFERENCES
Barla, G., Debernardi, D., & Sterpi, D. (2012).
Time-dependent modeling of tunnels in squeezing
conditions. International Journal of Geomechanics,
Volume 12(6), pp. 697-710
Bieniawski, Z. T. (1989). Engineering rock massclassifications. Wiley, New York
Castro, L.A.M., Bewick, R.P., & Carter, T.G.
(2012). An overview of numerical modelling applied
to deep mining. Innovative Numerical Modelling inGeomechanics, pp. 393-414.
Cording, E.J., Hashash, Y.M.A., & Oh, J.
(2015). Analysis of pillar stability of mined gas
storage caverns in shale formations. Engineering
Geology, Volume 184, pp. 71-80
Diederichs, M.S. (1999). Instability of hard
rockmass: the role of tensile damage and relaxation(PhD), University of Waterloo, Waterloo, Canada.
Itasca. (2009). FLAC3D - fast Lagrangian
analysis of continua (Version 4.0). U.S.A.: Itasca
Consulting Group Inc. .
Martin, C.C., & Maybee, W.G. (2000). The
strength of hard-rock pillars. International Journal ofRock Mechanics and Mining Science, 37, 1239-1246.

Mitri, H.S., Edrissi, R., & Henning, J. (1994).
Finite element modelling of cable-bolted stopes in
hardrock ground mines. Paper presented at the SME
Annual Meeting, Albuquerque, New Mexico.
Mitri, H.S., Tang, B., & Simon, R. (1999). FE
modelling of mining-induced energy release andstorage rates. Journal South African Institute of
Mining and Metallurgy, 99(2), 103-110.
Napier, J.A.L., & Malan, D.F. (2012).
Simulation of time-dependent crush pillar behaviour
in tabuluar platinum mines. The Journal of The South
African Institute of Mining and Metallurgy, 112, 711719.
Okubo, S., & Fukui, K. (2006). An analyticalinvestigationofavariable-compliance-type
constitutive equation. Rock Mech. Rock Eng., 39(3),233-253.
Okubo, S., & Jin, F. (1993). Simulation of rockbehaviour around circular roadway by non-linear
rheological model. Journal of the Mining andMaterials Processing Institution of Japan, 109, 209214.
Potvin, Y., Hudyma, M.R., & Miller, H.D.S.
(1989). Design guidelines for open stope support.
Paper presented at the Bull Can Min Metall.
Scholz, C.H. (1968). Mechanism of creep inbrittle rock. Journal of Geophysical Research, 73(10),3295-3302.
Sjöberg, J. (1992). Failure modes and pillar
behaviour in the Zinkgruvan mine. Paper presented atthe 33rd U.S. Rock Mechanics Symposium, Sante Fe.
Rotterdam.
Tesarik, D.R., Seymour, J.B., & Yanske, T.R.
(2003). Post-failure behaviour of two mine pillars
confined with backfill. International Journal of RockMechanics and Mining Science, 40(2), 221.
Van der Merwe, J.N. (2003). New pillar strength
formula for South African Coal. The Journal of The
South African Institute of Mining and Metallurgy,103(5), 281-292.
Weibull, W.A. (1951). Statistical distributionfunction of wide applicability. Journal of appliedmechanics, 18, 293-297.
Yun, Xiaoyou. (2008). Geomechanical behaviourof biaxially loaded rock. (PhD), McGill University,
Montreal, Canada.

95

ISMS 2016

Paper No. 236

Quantitative analysis of haulage system instability in deep hard rock mines
using numerical modelling
Shahé Shnorhokian a,*, Bryce MacNeil a, Hani Mitri aaDepartment of Mining and Materials Engineering, McGill University, Montreal (QC), Canada, H3A 0E8

ABSTRACT
Haulage drifts and related infrastructure are crucial to the success of underground mining operations. In the sublevelstoping mining method, they are developed well before any extraction commences in a given section of the orebody.
One of the more complex design parameters is the relative distance of a haulage drift from the orebody as it runs
parallel to its strike. Opposing considerations from operational and ground control teams need to be balanced, withthe former preferring a shorter distance for increased productivity and the latter requesting a further distance forsafety and stability. Numerical codes are one of the analytical tools used frequently in making these decisions byproviding mining-induced stress and displacement magnitudes using a properly calibrated model. In this study, asimplified model is constructed of a typical tabular orebody within the geological settings of the Canadian Shield,
striking East-West and dipping steeply to the south. Three other formations with the same strike and dip are added tothe model, along with two intrusive dykes at variable distances from the orebody and the drift. The rockmass
properties for all formations are obtained from a previous work on a case study mine in the Canadian Shield, and themodel is calibrated based on in-situ stress measurements there. Two stope sequences comprising two simultaneousmining fronts are implemented and analyzed for the orebody; a diminishing pillar one that moves from both east andwest to the middle, and a center-out option that moves from its center to the sides. In both cases, 24 mine-andbackfill stages – comprising 6 stopes each – are needed to completely extract the orebody. A quantitative assessmentof instability around the drifts, crosscuts, and stopes is conducted at each stage for a level at a depth of 1490 m. Two
instability parameters – the brittle shear ratio (BSR) and a low compressive-tensile stress state – are combined withvolumetric analysis to obtain the quantity of potentially unstable rockmass. The relative proximity of the drift andstopes to the dykes is evaluated and observed to have an impact on the results. A combined numerical-volumetricapproach is found to provide a useful tool for comparing different sequences and obtaining information on the type,location, volume, and timing of rockmass instability.
KEYWORDS: drift instability; modelling; stope sequence; brittle shear ratio; low compressive-tensile stress

1. INTRODUCTION
Haulage drifts, crosscuts, and the intersections
they form constitute a vital component of operationsin underground hard rock mines. They are especiallycrucial for certain mining methods such as sublevel
open stoping where considerable resources need to beallocated at the onset of operations to develop them
(Hamrin, 1998; Bullock, 2011). Hence, it is crucial
that they remain stable for an extended period of time
while mining is conducted in a certain area. The
distance of the haulage drift from the stopes requires
an informed and experienced decision able to satisfy
two opposing requirements. On one hand, it needs tobe as close to the orebody as possible to optimize ore
haulage activities. On the other hand, it needs to be
far enough from the stopes so as not to be influenced
by stress redistributions resulting from ore extraction.
The literature is rich with studies that have examined
drift stability using a number of techniques such as
instrumentation and monitoring (Kendorski, 1993;

Kaiser et al., 2001; Diederichs et al., 2004), andnumerical approaches (Martin et al., 1999; Zhang and
Mitri, 2008; Cai and Kaiser, 2014). Empiricalmethods used for drift stability and support design
constitute the basis of several rockmass classification
schemes (Bieniawski, 1989; Grimstad and Barton,
1993; Hoek et al., 2002). Kaiser et al. (2000) provide
an extensive summary of the different approaches
available for drift stability analysis. One of thefundamental concerns in deep hard rock mines is theoccurrence of rockbursts that pose safety concerns topersonnel and cause severe damage to the network ofdrifts and crosscuts. A number of recommendations
on different mitigation and support measures havebeen presented over the years (Gay et al., 1995;
Kaiser et al., 1996; Cai, 2013).
Numerical modelling provides a useful analytical
tool for determining design parameters such as the
optimum distance of the drift from the stopes whilesatisfying the criteria mentioned above. In addition to*Corresponding author – email : shahe.shnorhokian@mail.mcgill.ca

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

calculating induced stresses and displacements, it cancompare the merits of several stope sequences basedon the location and relative timing of any potential
instability. Starting with the geometry and rockmass
properties of the formations, an instability criterion
can be combined with simple volumetric analysis fora quantitative assessment of stope extraction options.
In this study, a conceptual model is constructedwith the finite difference code FLAC3D (Itasca, 2006)
to represent a typical underground hard rock metalmine in the Canadian Shield. A combination of
volumetric analysis and two instability indicators –the brittle shear ratio (BSR) and a low compressivetensile stress state – are used to quantitatively assess
potential ground control issues in drifts, crosscuts,
and intersections for a level at a depth of 1490 m.

with extensions in all three axis directions to have themodel boundaries far from any openings created bymining activities. Each level includes 32 stopes withindividual L × W × H dimensions of 20 × 15 × 30 m
for a volume of 9000 m3 per stope.
The final model dimensions of are 840 m (E-W),
390 m (N-S), and 300 m in depth. A total of 862000
zones are generated with the mesh density increasingin the areas of study. Figure 1 presents the generallayout of the mine and the geological formations.

2. MODEL SETUP
The model is constructed in FLAC3D to replicate
typical geological conditions in the Canadian Shield,
comprising several formations with east-west strikes
and dips of approximately 80° to the south. A central
greenstone formation hosts the orebody and typicaligneous intrusions in the area are represented by two
dykes trending WNW-ESE and running sub-parallelto the orebody. Based on its geometry and strike, thenorth dyke is at a further distance from the haulage
drift in the western part of the mine. Inversely, thesouth dyke is closer to the orebody in the westernpart and moves away from it in the east. The variable
proximity of the dykes to the drifts and orebody isused to examine their impact on mining-induced
stresses and associated potential instability.

Figure 1: 3D view of numerical model with geologicalformations and drift-crosscut system on active levels.

The orebody is tabular in shape, and extends 360
m in the E-W direction with a thickness of 30 m in
the N-S direction. Four active levels – L 1550, L
1520, L 1490, and L 1460 – are set up at depths
between 1430 m to 1550 m (120 m in height), along

Figure 2: Close-up view of drift-crosscut system on L
1490.

Haulage drifts are constructed in the footwall ofeach of the four active levels at a constant distance of
30 m from – and parallel to – the orebody. From thedrift, three perpendicular crosscuts 60 m in length areextended to the orebody, with the initial 30 m within
the greenstone footwall and the remaining segment
cutting into the stopes. These are 120 m apart along
the strike and similar to the drifts, they measure 5 × 5
m in cross-section with an arch of 1 m at the center ofthe roof. A drift-crosscut intersection is presented in
Figure 2 along with a typical cross-sectional view.
The input rockmass properties for the model are
based on previous publications by the authors for acase study mine in the Canadian Shield (Shnorhokian
et al 2015). They are presented in Table 1 for all theformations in this study.
Table 1: Input rockmass properties for numerical model.
Geological
Density
Bulk K
Shear G
UCS
formation(kg/m3)
(GPa)
(GPa)
(MPa)
Norite
2919
31.1
22.3
190
Dyke
3001
46.3
29.1
224
Greenstone
2989
27.9
21.8
277
Ore
4531
125.6
18.5
91
Metasediments
2768
11.0
7.9
146
Backfill
2000
0.2
0.1
2

Pre-mining stresses in the model are generatedusing boundary tractions, a method first developed by97

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

McKinnon (2001) for a homogeneous rockmass,
which was expanded subsequently for heterogeneous
cases (Shnorhokian et al., 2014). Model calibration isconducted by comparing magnitudes of pre-mining
stresses in the north dyke and norite formations withreadings at comparable depth in the Canadian Shield.

3. STOPE SEQUENCE ALTERNATIVES
After pre-mining stress calibration is conducted,
haulage drift-crosscut networks on all active levels
are excavated simultaneously. Two stope sequences
are then implemented between L 1550 and L 1430,
comprising two simultaneous mining fronts. In thefirst one, operations commence from the eastern andwestern sides of the orebody and move towards thecenter and this is called the diminishing pillar option.
In the second sequence, ore extraction starts from the
middle and moves towards the sides and this is called
the center-out approach. In both sequences, 6 stopes
are extracted and backfilled per stage for a total of 24
stages to mine the orebody on all the active levels.

Figure 3 presents the locations of potentially unstablerockmass at Stage 8 in the diminishing pillar option,and they are seen to coincide with the two advancing
mining fronts. While its rockmass properties indicatethat the orebody is stiff, its relatively low UCS value
also contributes to elevated BSR readings. Similarly,
regions of unstable rockmass are confined to mining
fronts in the center-out sequence, advancing from thecenter to the sides.
Table 2a: Diminishing pillar: volume (m3) > BSR 0.7.
Geology Drift Stage Stage Stage Stage Stage
4
8
12
16
20
GS
0
0
0
0
0
0
Dyke
0
0
0
0
0
0
Ore
0 1875 11305 10397 18206 20323
Table 2b: Center-out: volume (m3) > BSR 0.7.
Geology Drift Stage Stage Stage Stage
4
8
12
16
GS
0
0
0
0
0
Dyke
0
0
0
0
0
Ore
0 2268 13988 15634 21608

Stage
20
0
0
15259

4. INSTABILITY CRITERIA
In order to examine potential instability aroundthe drifts and crosscuts, two criteria are used from theliterature related to failure mechanisms and mininginduced seismicity generation (McCreary et al., 1993;
Trifu and Shumila, 2002). The brittle shear ratio(BSR) was developed by several authors (Castro etal., 1997; Martin et al., 1999) as an indicator for
potential strainbursts. It compares the differential
stress (σ1 - σ3) around an opening to the unconfinedcompressive strength (UCS) of intact rock. A ratio
above 0.7 is indicative of major strainburst anddamage potential (Castro et al., 2012). A second
criterion used is the low compressive-tensile stressstate (Diederichs and Kaiser, 1999; Diederichs,
2003), and values below 0.5 MPa are considered torepresent rockmass failure for this study. The
analysis focuses on a single active level – from L
1490 to L 1460 – for a quantitative comparison of theinstability criteria for all 24 stages.

Table 2c: Volume of total ore mined at each stage ('000m3).
Geology Stage Stage Stage Stage Stage Stage
4
8
12
16
20
24
Ore
324
270
216
162
54
0
Backfill
0
54
108
162
270
324
Total
324
324
324
324
324
324

5. RESULTS AND DISCUSSIONS
5.1 Brittle shear ratio (BSR)
Table 2 presents the volume of rockmass above
BSR 0.7 for the central formations between L 1490
and L 1460 in the diminishing pillar and center-out
sequences. It also provides the volume of mined-andbackfilled stopes between these levels at Stages 4, 8,
12, 16, and 20, with all the ore having been extracted
at Stage 24.
From the results, it can be observed that only the
orebody exhibits BSR values above the 0.7 threshold.

Figure 3: Stage 8 – diminishing pillar: BSR > 0.7.

While volumes of rockmass above a BSR of 0.7
indicate zones of potential mining-induced seismicity
for the mining operation, the only development
segments adjacent to them are those crosscuts that
extend into the stopes. As the mining fronts advance,
the eastern and western crosscuts on L 1490 are
engulfed with potentially unstable rockmass at Stage
8 in the diminishing pillar sequence and at Stage 12
in the center-out one as shown in Figure 4.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

difference is that the volumes with a potential low
compression or tensile stress instability mechanism
extend to the greenstone unit that forms the footwall
and immediate hanging wall on either side of theorebody. Hence, they are no longer restricted to themining fronts only as can be observed in Figure 5. In
addition, the unstable rockmass volumes within thegreenstone formation continuously rise with eachmining stage until the end.

Figure 4: Stage 12 – center-out: BSR > 0.7.

When mining is confined to L 1550 and L 1520
in the initial stages, a relatively small volume of BSR
instability (~ 1875 m3) is detected on the study level
between L 1490 and L 1460 in the diminishing pillar
sequence. This value increases to almost 11300 m3 at
Stage 8 as the mining front reaches L 1490 andremains within the same range at Stage 12 (~ 10400
m3). In the center-out option, larger volumes of
unstable rockmass with elevated BSR conditions
persist at all times except towards the end at Stage
20. In both mining sequences, regions of instability
always coincide with the locations of the mining
fronts. Hence, the center-out option exhibits moreunstable rockmass at the onset of mining when thefronts are close to each other in the middle of theorebody, and registers a significant drop at Stage 20
when they have moved to its sides. In a reverse trend,
the diminishing pillar sequence shows a slightly
lower volume of unstable rockmass at the onset whenthe mining fronts are at the sides, and the volume of
instability increases to a maximum at Stage 20 whenthe mining fronts form a pillar of minimum width in
the center.
The expected effect of unstable rockmass withelevated BSR values is an increase in mining-induced
seismicity. There is a general potential for rockbursts
in the crosscuts at all times but a more specific risk ofpotential failure appears once the zone of influence of
unstable rockmass reaches the excavation (Figures 3
and 4).
5.2 Low compressive and tensile stress
Table 3 presents the volumes of potentiallyunstable rockmass under low compressive and tensilestress conditions. When compared to the previous
one, the extent is observed to be more widespread.
The volumes of unstable rockmass in the orebody arecomparable to the ones with the BSR criterion, andfluctuate with mining operations until Stage 24. The

Table 3a: Diminishing pillar: volume (m3) of σ3 < 0.5 MPa.
Geology Stage Stage Stage Stage Stage Stage
4
8
12
16
20
24
GS
0
3987 13614 19493 32484 16629
Dyke
0
0
0
0
0
0
Ore
1369 13127
6299 11055 11020
0Table 3b: Center-out: volume (m3) of σ3 < 0.5 MPa.
Geology Stage Stage Stage Stage Stage
4
8
12
16
20
GS
0
5349 14738 17289 23099
Dyke
0
0
0
0
0
Ore
2392 11254
5716 12262
9919

Stage
24
16551
0
0

Figure 5: Stage 8 – diminishing pillar: σ3 < 0.5 MPa.

In the hanging wall, these regions constitutepotential volumes of unplanned dilution that could
move into the stope once it is mined out. In the
footwall, unplanned dilution is still a possibility at the
top of the study level near L 1460. However, sections
near the bottom that are close to crosscuts represent
potential instability and fall-of-ground, especially inthe roofs. It is not only the temporary section of acrosscut within a given stope that is at potential risk,
as was the case with the BSR criterion. Rather, theremaining section within the greenstone footwall isalso affected by the volume of unstable rockmass.
The western crosscut on L 1490 is shown in Figure 6
with an outline of rockmass under low compressive
and tensile stress above it. Important quantitative
parameters such as the volume of potential failure, its

99

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

location in the roof of the crosscut, and distance fromthe orebody can be calculated easily based on thisanalysis, as shown in Figure 5 and 6. Similarly, theextent of potential unplanned dilution that may affectthe hanging wall on the level below is seen in thesame figures.

Figure 6: Stage 16 – diminishing pillar: σ3 < 0.5 MPa.

One of the advantages of a quantitative analysis
is that volumes of unstable rockmass in different
locations can be assessed regarding their impact on
mining operations. The volume in the greenstone unit
can be subdivided into its footwall and hanging wallcomponents with the latter representing between 43
and 48% of the total unstable rockmass during all
mining stages in the diminishing pillar sequence(Table 4a). Thus, it quantifies the unplanned ore
dilution that can potentially be expected from thehanging wall. It follows that between 52 and 57% of
the unstable rockmass is located in the footwall, andthese volumes can act as sources of potential dilution
and crosscut instability.
Table 4a: Diminishing pillar: volume (m3) of σ3 < 0.5 MPa.
Geology Stage Stage Stage Stage Stage Stage
4
8
12
16
20
24
GS
0 3987 13614 19493 32484 16629
HW
0 19065908
8797 14092
5514
FW
0 20817706 10696 18392 11114
Table 4b: Center-out: volume (m3) of σ3 < 0.5 MPa.
Geology Stage Stage Stage Stage Stage
4
8
12
16
20
GS
0 5349 14738 17289 23099
HW
0 2393
5625
7323
7921
FW
0 29579114
9965 15178

Stage
24
16551
6864
9687

Table 4b presents the same data for the centerout sequence and a simple comparison between thetwo indicates important trends. In terms of hanging
wall instability, the volumes are consistently smallerin the center-out option from Stage 12 onward but
higher at Stage 8. The footwall side shows smaller
volumes for this sequence from Stage 16 onward but
higher numbers before. This phenomenon has a valid
explanation related to the location of mining fronts.
In the diminishing pillar approach, mining proceedsfrom the sides to the center and instability increases
in volume as the pillar develops there. In the centerout option, operations commence from the center andthe largest volumes of instability can be observed at
the beginning (Stages 8 and 12) when both mining
fronts are in close proximity in the center.
Another trend observed is the relative volumes of
unstable rockmass in the greenstone formation once
mining operations end. While the total numbers arecomparable, the diminishing pillar option ends with amuch more voluminous instability in the footwall(67%) than in the hanging wall (33%). Although the
footwall has a higher volume of unstable rockmass inthe center-out option as well at 59%, compared to the
41% in the hanging wall, the distribution is a morebalanced one.
6.

CONCLUSIONS

A conceptual model is constructed in FLAC3D
for a typical tabular, steeply dipping orebody in the
Canadian Shield that uses the sublevel open stoping
method. A series of drifts and crosscuts are replicatedon four active levels and two stope sequences with
two simultaneous mining fronts are implemented. In
the first case, ore extraction moves from the sides tothe center while the reverse takes place in the second
one. The brittle shear ratio and low compressivetensile stress state are used as instability criteria, andare coupled with volumetric analysis for quantitative
comparisons. It is observed that in both sequences,the potential BSR instability zones are restricted tothe orebody and mining fronts. However, zones under
low compressive and tensile stress conditions can befound in the greenstone footwall and hanging wall, in
addition to the stopes, and pose a risk to crosscuts.
Their relative distribution between the footwall andhanging wall is observed to be a more balanced one
in the center-out option than in the diminishing pillar
sequence.
7.

REFERENCES

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engineering. Wiley-Interscience, New York, 272 p.
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Engineering Handbook, Darling P. (ed.), SME, pp.
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Cai, M. (2013). Principles of rock support inburst-prone ground. Tunnelling and UndergroundSpace Technology, Volume 36, pp. 46-56.
Cai, M. and Kaiser, P.K. (2014). In-situ rockspalling strength near excavation boundaries. RockMechanics and Rock Engineering, Volume 47, pp.
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Castro, L.A.M., Grabinsky, M.W., McCreath,
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Diederichs, M.S. (2003). Rock fracture andcollapse under low confinement conditions. RockMechanics and Rock Engineering, Volume 36, No. 5,
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Diederichs, M.S., Kaiser, P.K., and Eberhardt, E.
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Itasca (2006). Itasca Software Products –FLAC3D. Itasca Consulting Group Inc., Minneapolis.
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(1996). Drift support in burst-prone ground. CIM
Bulletin, Voume 89, No. 998, pp. 131-138.
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Sharpe, J. and Steiner, W. (2000). Undergroundworks in hard rock tunnelling and mining. In:
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(1999). Hoek-Brown parameters for predicting thedepth of brittle failure around tunnels. Canadian
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(1993). Source mechanisms, three-dimensionalboundary-element modelling, and undergroundobservations at Ansil Mine. In: Proceedings of the 3rdInternational Symposium on Rockburst andSeismicity in Mines, Young, R.P. (ed.), pp. 227-232.
McKinnon, S.D. (2001). Analysis of stressmeasurements
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microseismicity at Kidd Mine, Ontario. Pure andApplied Geophysics, Vol. 159, pp. 145-164.
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101

Paper No. 149

ISMS 2016

Minimum strength required for resisting cyclic softening/failure of cemented
paste backfill at early age
Tikou Belem*, Mamert Mbonimpa
Research Institute in Mining and Environment (RIME), Université du Québec en Abitibi-Témiscamingue (UQAT), RouynNoranda, Canada, J9X 5E4

ABSTRACTThis paper attempts to assess empirically the liquefaction susceptibility of cemented paste backfill (CPB) at earlyage (≤ 7 days). Early age CPB can be categorized as a “clay-like” material because their plasticity index, PI ≥ 5 (PI= Liquid Limit, LL – Plastic Limit, PL). For clay-like material such as CPB, the liquefaction susceptibility can becharacterized by the “cyclic softening” or “cyclic failure” which is assessed using an empirical method developed
for clays and clay-like materials. This analysis allowed the determination of the minimum undrained shear strength
required to resist cyclic softening (failure) of cemented paste backfills which is directly related to the unconfinedcompressive strength (UCS).
KEYWORDS: Mine tailings; cemented paste backfill, Binder; undrained shear strength; cyclic softening

1. INTRODUCTION
The mining industry generates significant socioeconomic benefits, but also generates huge amounts
of solid wastes such as mill tailings and waste rock.
These solid wastes can generate environmental
pollution due to their inadequate containment. Due tomore stringent environmental regulations, cemented
paste backfill (CPB) allow to return a large part ofmill tailings (up to 50%) for underground open stopes
filling, hence improving ground support and ore
recovery (Potvin et al., 2005; Belem and Benzaazoua,2008). CPB is a mixture of mill tailings with abinding agent and mixing water. The purpose ofbinder addition is to generate typical unconfinedcompressive strength (UCS) ranging from 500 kPa up
to 4.5 MPa, depending on the type of backfill (slurry
backfill, cemented rockfill, or cemented paste
backfill).
CPB cost generally accounts for between 10%
and 20% of the total operating cost of a mine fromwhich hydraulic binder represents up to 75-80% ofthat cost (Grice, 1998). That is why mining
companies seek to reduce the binder cost by reducing
the amount of binder in the CPB mixtures. One of thepromising options to reduce backfilling operation
costs is a partial replacement of typical cement (i.e.,
general use Portland cement) by industrial byproducts and or other supplementary cementitious
materials (Belem and Benzaazoua, 2008).
Unfortunately, a reduction in the amount of binder
could lead to a substantial decrease in the mechanicalproperties of CPB, particularly at early age (from 0 to*Corresponding author – email : Tikou.Belem@UQAT.ca

7 days of curing). Such a reduction in the mechanicalproperties
of
CPB
may
trigger
cyclicsoftening/failure at early age due to several sources(consecutive sequences of blasting, rock burst,
seismic events, ground vibration, etc.). In common
usage, liquefaction refers to the loss of strength insaturated, cohesionless material due to the build-up
of pore water pressures during dynamic loading(Sladen et al., 1985).
The cyclic actions of an earthquake or blast
detonation have the effect of increasing the potential
for paste backfill softening, causing compression,
which reduces the volume of voids by increasing
pore water pressure as well. This implies a loss or asignificant reduction of undrained shear strength due
to pore pressure in the backfill, which means shear
strain under constant volume. This is essentially due
to rapid shaking, too short because the dissipation ofpore pressure accumulated in the fluid may havestarted (Seed and Idriss, 1971).
The main objective of this paper is to assess
empirically the cyclic softening (liquefaction
susceptibility) of cemented paste backfill at early age(curing time ≤ 7 days) by providing preliminary
results. The liquefaction susceptibility will beassessed through the “cyclic softening or failure”
analysis (for clay-like materials such as CPB) basedon empirical method. The specific aim is to verify
experimentally whether the cost of binder can be
reduced by lowering the CPB binder content while
keeping sufficient undrained shear strength to resist
cyclic softening. Hence, the empirical method should
allow determining the minimum undrained shear

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

strength related to the unconfined compressive
strength (UCS) for resisting cyclic softening (orfailure) of CPB.

2. SIMPLIFIED PROCEDURE FOR CYCLICSOFTENING ASSESSMENT
2.1 Susceptibility to dynamic loading
For cohesive materials such as CPB, the cyclic
action of an earthquake or blast detonation is deeply
influenced by the number of cycles N of theearthquake, the relative density Dr (density index)
and the grain size of the matrial. The response of soil
to seismic loading varies with soil type and state(void ratio, effective confining stress, stress history,etc.). Seed et al. (2003) and Boulanger and Idriss(2005) distinguished between “sand-like” and “claylike” behaviour. According to Seed et al. (2003),
sand-like soils are susceptible to cyclic liquefaction
when their behavior is characterized by Plasticity
Index (PI = LL – PL) < 12 and Liquid Limit (LL) <37 and natural water content (wn) > 0.8(LL). Claylike soils are generally not susceptible to cyclicliquefaction when their behaviour is characterized by
PI > 12 but they can experience “cyclic softening”.
These criteria are generally conservative. Boulanger
and Idriss (2005) suggested that sand-like behaviour
is limited to PI < 7, while clay-like behavior can be
expected for fine-grained soils that have PI ≥ 7,
although a slightly lower transition point for soils
with a CL-ML classification (perhaps PI ≥ 5 or 6)
would be equally consistent with the available data.
Based on this soil classification, CPBs can be
categorized as clay-like materials. Also, it wasobserved in the literature that the plasticity index, PIof uncemented mine tailings from hard rock varies
between 1 and 10.
2.2 Empirical assessment of cyclic softening
Most of the existing work on cyclic liquefaction
has been primarily for earthquakes. Seed et al. (2003)
developed a comprehensive methodology to estimate
the potential for cyclic liquefaction due to earthquake
loading, originally developed by Seed and Idriss(1971). The evaluation procedure used worldwide istermed the “simplified procedure” (U.S. National
Center for Earthquake Engineering Research,
NCEER, 1998) as described by Youd (2001), whichuses generally conservative assumptions. The
simplified approach to evaluate the triggering ofseismic liquefaction involves comparing the Cyclic
Stress Ratio (CSRM) caused by the design earthquakeof magnitude Mw with the Cyclic Resistance Ratio(CRRM) of the soil pertaining to an earthquake ofmagnitude Mw = 7.5. A factor of safety againstliquefaction FSLiq is defined as the ratio of CRRM=7.5
to CSRM:=
FS Liq

CRRM=7.5 CRR=σ 1,=α 0 Kσ Kα=MSF
CSRM=7.5
CSRM(1)

where CRRM=7.5 = cyclic resistance ratio pertaining toa magnitude 7.5 earthquake = CRRσ=1,α=0 = CRR forlevel ground conditions and an effective overburden
stress (σ’v0) of one atmosphere (≈ 100 kPa); Kσ =correction factor for the effects of σ’v0 on CRR; Kα =correction factor for the effects of static initial shear
stress on CRR; α = static horizontal shear stress ratio(α = τs/σ’v0); τs = static horizontal shear stress (kPa);
MSF = Magnitude Scaling Factor (also called
magnitude-correlated duration weighting DWFM) for
adjusting the induced CSR during earthquake ofmagnitude Mw to an equivalent CSR for anearthquake magnitude, Mw = 7.5. If α = 0, i.e. τs = 0(no sloping), then Kα = 1.
The recommended MSF by the NCEER
Workshop in 1998 (Youd, 2001) is given as follows:
MSF =

174
M 2.56

Eq.(2)

where Mw = moment magnitude of the earthquake.
More recently, Idriss and Boulanger (2006) proposed
an updated version given as follows: −M 
=MSF 6.9 exp  − 0.058 ≤ 1.8
 4 

(3)

A simplified method to estimate CSRM was also
developed by Seed and Idriss (1971) based on the
maximum (or peak) ground horizontal acceleration(PGA or amax) at the site. The cyclic stress ratio
proposed by Seed and Idriss (1971) is given as
follows:
 a  σ 
CSRM = 0.65  max   v0  rd
 g   σ 'v0 (4)where amax (= PGA) is in g (1g = 9.81 m/s2); σv0 =total vertical stress (kPa) and σ’v0 = effective verticalstress (kPa) at depth z (m). The parameter rd in Eq. 4
is a stress reduction coefficient that accounts for theflexibility of the soil column. Youd (2001) proposed
the following relations suggested by the NCEER(1998):
rd 1.174 − 0.0267 z== rd 0.744 − 0.008 z

9.15m < z ≤ 23m
23.0m < z ≤ 30m

(5)

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

For depth z > 34 m, Idriss (1999) also proposed
the following relationship:rd =0.12 ⋅ exp ( 0.22 ⋅ M )(6)

Because of the cohesive nature of clay-likematerials, they tend to develop smaller pore pressures
under undrained cyclic loading than sand-likematerials. Therefore, clay-like materials do not reachzero effective stress with resulting large deformations
under cyclic loading (not susceptible to cyclicliquefaction). However, when the cyclic stress ratio(CSR) is large relative to the undrained shear strength
ratio (Su/σ’vc; where Su = undrained shear strength,
σ’vc = effective vertical confining stress) of clay-likematerials, cyclic strain or softening can develop.
However, post-earthquake volumetric strains tend tobe small. Boulanger and Idriss (2005) used the term
“cyclic failure” (instead of liquefaction) to describe
this build-up of strain under cyclic loading in claylike soils. Boulanger and Idriss (2004) showed that
the CRR for cyclic failure in clay-like materials is
controlled by the undrained shear strength ratio.
These authors recommended the following relation
for CRRM=7.5 (for a moment magnitude 7.5
earthquake) of clay-like soils: S 
CRRM=7.5α= 0.80  u  K
 σ 'vc 
and
0.344
=
K α 1.344 −0.638
 τs 
1
−

Su 


(7a)

(7b)

where Kα was previously defined in Eq. (1); (τs/Su) =ratio of static initial shear stress and undrained shear
strength. Boulanger and Idriss (2004) also suggested
that there is no need for overburden correction factor
Kσ which is taken implicitly into account in the
undrained shear strength ratio.

3. PROCEDURE FOR CYCLIC FAILURE
ASSESSMENT OF CPB
Knowing that Su = UCS/2 for saturated CPB
sample and that the most common parameter inbackfill engineering is UCS, equation 7 along withequations 1 – 6 can be combined in the following
forms, for a given total vertical stress σv0 (= γwetz) ata given depth:
 0.8 ⋅ UCS   g  Kα ⋅ MSF
FS Failure = 2  amax  ( 0.65 ⋅ σ v0 ⋅ rd )(8)
 g   UCS ⋅ Kα 
= 0.6154  MSF
 amax   σ v0 ⋅ rd 

where UCS = Unconfined Compressive Strength(kPa) of CPB; σv0 = initial total vertical stress (kPa)at a given depth z (m); Kα = correction factor for
static shear stress (always = 1 for vertical stopes but
should be around 0.8-0.9 for sub-vertical stopes);amax, rd and MSF are previously defined.
Vibration amplitude in the CPB is weaker thanthat in the rock. The magnitude of vibration (or peak
particle velocity PPV) recorded in CPB was in therange 25 – 65 mm/s (0.025 – 0.065 m/s). Signal
frequencies are about 20 – 120 Hz (Liu, 2004). The
PPV can be converted to peak ground horizontal
acceleration (PGA or amax) for sine waves using thefollowing relation (e.g., Dowding, 1985):
amax ( g ) =2π ⋅ PPV (m ⋅ s-1 ) ⋅ f ( Hz )9.81 (m ⋅ s-2 )(9)where PPV = peak particle velocity (m.s-1); f =frequency or number of oscillations per second (Hz);9.81 m/s2 correspond to 1g.
The calculated amax corresponding to blasts
ranged from 0.3g to 5.0g compared to a minimum
amax value of 0.1g necessary to trigger cyclicliquefaction of soils. These values may seem too
high, but it is for a very short period of time (0.07 −0.13 sec). For comparison, the range of frequency
band for strong motion (usually causing structural
damage during strong ground shaking of about 5 − 30
seconds) is ~0.05 Hz to ~10 Hz (Berkley
Seismological Laboratory).
A blast vibration can be compared to a strong
motion (1 − 10 Hz) through the calculation of kinetic
energy Ek released [Ek = MassCPB*PPV2/(2*amax)].
The calculated Ek is in the range 10-3*MassCPB −4*10-4*MassCPB for the observed magnitude of blast
vibration PPV in the range of 25 − 65 mm/s (20 −120 Hz). This corresponds to a range of equivalent
moment magnitude Mw of 4.4 − 6.1 earthquakes witha maximum duration of 0.13 sec. The corresponding
amax will be in the range 0.009g to 0.08g. Whenconsidering that a real earthquake of magnitude 6 canlast about 8 seconds compared to 0.13 seconds for the
blast, a simple rule of three gives an equivalent actualenergy released by the blast that should be(1/8)*(1.3/10) lower (approximately 62 times smaller
than an actual earthquake).

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

From equation (8), the UCS values can be directly
used, for the first time, to assess the cyclic failure (orsoftening) of CPB materials. Furthermore, equation(8) can be rearranged to provide the minimum
compressive strength (UCSmin) required for resisting
against cyclic failure or softening of CPBs due tostrong motion. The minimum compressive strength
ratio (UCSmin/σv0) is given as follows:
UCS minσ v0 a 
rd= 1.625  max   FSmin g   Kα ⋅ MSF (10)

where FSmin = minimum factor or safety against
cyclic failure of CPB (≥ 1.0); σv0 = γwet * z (total unit
weight of CPB (kN/m3) x depth of concern in abackfilled stope (m)).
If FSmin = 1.0, the Cyclic Resistance Ratio(CRRM=7.5) is equal to the Cyclic Stress Ratio
generated by a magnitude Mw earthquake(CSRM/MSF). It is believed that this condition is notconservative enough to resist to cyclic failure
triggering. Based on slope stability analysis
principles, it may be recommended that the minimum
factor of safety against cyclic failure should be FSmin= 1.1. Putting this value along with Kα = 1.0 into
equation (10) yields:
UCS min

σ v0

a
r 
= 1.7875  max d 
g
MSF



(11)

Equation (11) shows that the minimum
compressive strength ratio (UCSmin/σv0) depends on
the stress reduction coefficient rd (see equation 5) that
accounts for the flexibility of the CPB Mass.
It should be noted that UCSmin or UCSmin/σv0 canbe represented as a function of backfilled standalone
stope depth z (or the total or overburden stress σv0),
the maximum or peak ground horizontal acceleration(amax or PGA) or Magnitude Mw earthquake.

2.47 wt%, respectively). For all the mixtures theaverage solid mass concentration Cw% was about 83%
which correspond to standard slump height ranging
between 140 and 165 mm (5½ and 6½ inches). The
CPB mixtures were poured into 76 mm diameter and
152 mm height capped plastic molds (3 in x 6 in) andleft to cure in a humidity chamber at ambient
temperature (25°C) and > 90% relative humidity. The
strength development is assessed for undrained noted
UD (non-perforated molds) and drained noted FD(perforated molds). The curing times were 3, 7, 28
and 56 days.
4.2 Unconfined compression tests
The cyclic failure potential will be assessed onsaturated CPB specimens at early age (≤ 7 days)
curing times, through the unconfined compression
tests in order to determine the UCS values whichcorresponds two time the undrained shear strength(UCS = 2*Su), assuming Tresca criterion. The
compression tests were performed using a MTS
10/GL universal hydraulic press of 50 kN loading
capacity (compression rate of 1 mm/min).

5. RESULTS
5.1 UCS and Su data
Figure 1 shows the relationship between binder
content and UCS values. It can be observed thatwater drainage induces an increase in UCS due toself-weight consolidation. This figure can be usedmainly to determine how the cement content can be
reduced while maintaining the same strength
performance of the CPB.

4. SAMPLE APPLICATION
4.1 Cemented paste backfill mixtures preparation
The backfill specimens were prepared using
tailings sampled from Brunswick’s mine (BM). The
CPB batch of mixtures were prepared by adding
progressively the appropriate mass of tailings, binderand mixing water to a Hobart mixer and mixed forabout 10 minutes. The binder type used was the highsulphate resistant Portland cement HS. Four different
CPB mix recipes were considered with five binder
contents (= mass of binder/mass of CPB): 1, 1.5, 1.75
and 2% (corresponding to binder ratio Bw% = mass ofbinder/mass of dry tailings = 1.22, 1.84, 2.15 andFigure 1: Relationship between binder content and UCS for
drained and undrained CPB specimens

Table 1 contains the UCS data from Figure 1 andthe corresponding calculated undrained shear strength
Su. The undrained strength Su can be obtained
directly from the UU triaxial test, direct simple shear(DSS) test, direct shear test (fast shear rate) or
uniaxial compression test (saturated specimens). The
simplest way is to calculate Su from the UCS data (Su105

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

= UCS/2) assuming or ensuring that the CPB
specimens are saturated (Belem and Benzaazoua,
2008 showed that when the CPB specimens areunsaturated, Su ≠ UCS/2).
Table 1: UCS and corresponding undrained shear strength
Su values of the Brunswick’s Mine CPB
Su =BinderCuring
UCS
Relative
UCS/2
(%)
(day)
(kPa)
consistency
(kPa)
1
3
15
7.5
Very soft
1
7
25
12.5
Soft
1.5
3
23
11.5
Very soft
1.5
7
66
33
Medium
1.75
3
51
25.5
Medium
1.75
7
162
81
Stiff
2
3
69
34.5
Medium2
7
218
109
Very stiff

5.2 Cyclic failure potential of CPB
For this evaluation, 30 m stope height isconsidered. As the CPB is assumed fully saturated,
the water table level is supposed to be on top of any
stope (depth z = 0 m). It is assumed that theminimum pore water pressure before any shaking is
the hydrostatic pressure (u0 = γw*z = 9.81z kPa).
Table 2 presents the total (σv0 = γwet*z) and effective(σ’v0 = [γwet - γw]z) stresses calculated at backfilled
stope depths of 15, 20 and 30 m (with tailings
specific gravity of 4.03 and Cw% = 83%, thecalculated γwet = 26 kN/m3).
Table 2: Total and effective vertical stresses
Depth z
σv0
u0
(m)
(kPa)
(kPa)
15
390
147
20
520
196
30
780
294

σ'v0
(kPa)
243
324
486

Table 3 presents the results of calculated factorof safety against cyclic failure FSFailure with amax =0.074g (earthquake moment magnitude Mw = 6),
MSF = 1.482, rd = 0.458, and Kα = 1 (no sloping of
the backfill mass).
Table 3: Calculated factor of safety against cyclic failure or
deformation for BM’s CPB
Su =
CSR
CRR
FSFailurebinder Curing
UCS/2(M=6) (M=7.5) (M=6)
(%)
(day)
(kPa)
1
3
7.5
0.024
0.0124
0.52
1
7
12.5
0.024
0.0206
0.86
1.5
3
11.5
0.024
0.0189
0.79
1.5
7
33
0.024
0.0544
2.28
1.75
3
25.5
0.024
0.0420
1.76
1.75
7
81
0.024
0.1334
5.59
2
3
34.5
0.024
0.0568
2.38
2
7
109
0.024
0.1795
7.52

If FSFailure > 1.0, the CPB will not fail cyclically;
if FSFailure ≤ 1, the CPB is likely to undergo cyclic
failure. From Table 3 it is clear that the CPB preparedwith only 1% of binder (Bw% = 1.22%) will probably
undergo cyclic failure or large softening (FSFailure <1.0). The same observation is made for CPB with
1.5% of binder (Bw% = 1.84%) cured after 3 days
only. Nevertheless, after 7 days of curing this CPB
develops sufficient undrained shear strength to resist
cyclic failure. Therefore, Table 3 suggests that therecommendable minimum binder proportion for the
CPB to resist cyclic failure is 1.75% (Bw% = 2.15%).
The binder proportion can however be lowered to
1.5% (Bw% = 1.84%) if the minimum allowed curing
time is 7 days, but this is not safe.
Figure 2 shows the relationship between
UCSmin/σv0 required to resist cyclic failure as afunction of backfilled stope depth z and for FSmin of
1.0 (critical case) and 1.1. These curves can beconsidered as “cyclic softening or failure curves” andare compared to the actual UCS data of the preparedcemented paste backfill. The shape of these curves isdictated by the stress reduction factor rd.

Figure 2: Relationship between UCSmin/σv0 required forresisting cyclic failure as a function of stope depth z

6. DISCUSSION
The minimum compressive strength UCSminrequired for resisting against cyclic failure of CPB
specimens in this study at the bottom of 30 m height
stope (σv0 = 780 kPa) is 32 kPa only, for a moment
magnitude Mw = 6 earthquake (amax = 0.074g). The
Japanese Port and Harbour Research Institute (1996)
have observed similar low values for cemented sands.
Their test results showed that when UCS was in therange 49 – 98 kPa, the cemented sand could notundergo liquefaction. Based on shaking table tests(amax = 0.25g), they also found that by adding 1% (bydry mass of sand) of cement and after 7 days ofcuring the cemented sand (with an average UCS of
29 kPa) didn’t liquefied. It was concluded that thepercent of cement addition required for treatment toproduce a material that will not undergo liquefaction
differs according to the soil type. It should be noted106

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016that there are very few studies on the evaluation ofliquefaction potential of cemented paste backfill(Blight, 1990; Belem et al., 2013). Blight (1990)
suggests that, even very severe lateral accelerations(up to 10g!), will induce only moderate shear stresses(about 100 kPa) in the backfill contained in a narrow,tabular stope. Since then, it is customary to assume
that a CPB having a UCS of about 100 kPa will neverundergo liquefaction.

7. CONCLUSION
This paper presents the evaluation of thepossibility to lower CPB binder content used forstope filling without causing liquefaction (or “cyclic
failure”). The cyclic failure or softening (equivalent
to liquefaction for clay-like materials such as CPB)
was assessed based on empirical method proposed byleading world experts on liquefaction, namely
Boulanger and Idriss (2005). This method is based oncomparing the Cyclic Resistance Ratio of a soil
subjected to shaking by an earthquake of Mw = 7.5(CRRM=7.5) to the Cyclic Stress Ratio imposed to thesoil by a shaking due to an earthquake of Mw (CSRM).
A Magnitude Scaling Factor (MSF) is used for the
calculation of the Factor of Safety against the cyclic
failure FSFailure which must be higher than 1.0 to resist
cyclic failure or softening. Sample application of thismethod shows that CPBs prepared with 1% of
cement (at 3 and 7 days of curing) and 1.5% of
cement at 3 days of curing will undergo cyclic failure
or softening for an earthquake of magnitude Mw = 6(amax = 0.074g).
Based on the Boulanger and Idriss (2005)
empirical model, a procedure using the UCS values is
proposed for the assessment of cyclic failure of CPB
in general. For the first time it is possible to connect
the cyclic failure (softening) potential with theminimum required strength value (UCSmin) and theheight of the backfilled stope. However, further study
is needed for validating and refining the proposed
method by performing cyclic direct simple shear(DSS) testing or direct shear test at fast shear rate on
different CPB mixture recipes at early ages.

8. ACKNOWLEDGEMENT
This research was financially supported by
NSERC discovery grant. The authors would like toacknowledge their helpful support.

9. REFERENCES
Belem T., Effenguet H., Mbonimpa M. (2013).
Estimation of required minimum binder content byassessing the liquefaction potential of early age
cemented mine backfill. Proc. of 66th Canadian
Geotechnical Conference, Montreal, Quebec,
Canada, September 29 - October 3, 2013, 8p.

Belem, T. and Benzaazoua, M. (2008).
Underground mine paste backfill technology:
applications and design methods. Geotechnical andGeological Engineering. Vol. 26(2): 147-174.
Blight, G.E. (1990). The effect of dynamic
loading on underground fill in South African gold
mines. Victor de Mello tribute volume. Editorial
Edgard Bluücher, Sao Paulo, Brasil, pp. 37-44.
Boulanger, R. W., and Idriss, I. M. (2005). New
criteria for distinguishing between silts and clays thatare susceptible to liquefaction versus cyclic failure.
Proc., Technologies to Enhance Dam Safety and theEnvironment, 25th Annual United States Society on
Dams Conf., USSD, Denver, 357–366.
Grice T. (1998). Underground mining withbackfill. Proceedings of the 2nd Annual Summit on
Mine Tailings Disposal Systems, 1998, Brisban, 14 p.
Idriss I.M. (1999). An update to the Seed-Idriss
simplified procedure for evaluating liquefaction
potential, Proc., TRB Workshop on New Approaches
to Liquefaction, January, Publication No. FHWARD-99-165, Federal Highway Administration.
Idriss, I.M., and Boulanger, R.W. (2006). Semiempirical procedures for evaluating liquefaction
potential during earthquakes. Soil Dynamics andEarthquake Engineering, 26: 115–130.
Liu, K. (2004). Blast vibration monitoring andBlast damage evaluation. 1st Noranda/Falconbridge
Blasting Workshop, September 27-28, 2004. 12 p.
Potvin, Y., Thomas, E., and Fourie, A.B. (eds)(2004). Handbook on mine fill, Australian Centre forGeomechanics, Perth, Australia, ISBN 0-9756756-21.
Seed, H. B., and Idriss, I. M. (1971). Simplified
procedure for evaluation soil liquefaction potential.
Journal of the Soil Mechanics and Foundations
Division, ASCE, 97(SM9): 1249-1273.
Seed R. B., Cetin K. O., Moss R. E. S.,
Kammerer A. M., Wu J., Pestana J. M.,Riemer M. F.,
Sancio R.B., Bray J.D., Kayen R. E., and Faris A.
(2003). Recent advances in soil liquefactionengineering: A unified and consistent framework.
Keynote presentation, 26th Annual ASCE Los
Angeles Geotechnical Spring Seminar, Long Beach,
Calif.
Sladen, J. A., D’Hollander, R. D., and Krahn, J.
(1985). The liquefaction of sands, a collapse surface
approach. Canadian Geotechnical Journal, 22(4),564–578.
Youd, T.L. (2001). Liquefaction resistance ofsoils: summary report from the 1996 NCEER and1998 NCEER/NSF Workshops on evaluation ofliquefaction resistance of soils. Journal of
Geotechnical and Geoenvironmental Engineering,
127(4): 297 – 313.

107

ISMS 2016

Paper No. 166
Analysis of failure in a salt room and pillar mine
Farid Laouafa, Mehdi Ghoreychi

Institut National de l'Environnement Industriel et des Risques- INERIS, F-60550 Verneuil-en-Halate, France

ABSTRACT
Failure mechanisms have been investigated in a salt mine (Alsace Potash mines, Esat of France) excavated by theroom and pillar method, a part of which is under study for chemical waste storage. This part is located at a depth ofabout 550 meters. Some singular failure modes appear in the roof mine. These modes are perpendicular to the axisof the gallery and are created by tensile stresses. Such a failure mode is rarely observed in classical mines (coal,construction stones, etc.). 3D modelling of the site has been required for accurate description of the physicalmechanisms. The results show that the failures and more generally the roof behaviour are controlled by the
deformation of the pillars inducing tensile forces in the roof. The results also show that the creep or the viscoplastic
behaviour of the salt is a key element that explains the existence of such failure and their evolution over time. A
parametric analysis of the properties of overburden, geometrical pillar features slenderness, confirm the conclusion.
Namely, time-dependent deformation of large salt pillars generates their lateral extension and induces roof
deformation and failure in tension. The numerical results are in full agreement with in-situ observations.
KEYWORDS: Salt mine; modelling; failure; creep

1. INTRODUCTION
Part of the salt mine belonging to Alsace
Potassium Mines (MDPA) excavated by the roomand-pillar method has been used as a storage area forindustrial waste (Figure 1).

Figure 1: Example of waste storage.

Storage began in 1999, in a specifically designed
area (rooms and pillars) with a configuration
comprising galleries 2.8 to 3 m high and 5.5 m wide,with pillars 20 m wide per side. Convergencemeasurements were taken at regular intervals andobservations were also recorded regarding themechanical behaviour of the structures. The storage
project was stopped in 2002 and several options arebeing considered regarding the future of the site.
Cracks in the mine roof and bed separations wereobserved. In particular, transverse cracks relative tothe axis of a gallery appeared in 2015 in addition tolongitudinal cracks of the roof and bed separations. In*Corresponding author – email: farid.laouafa@ineris.fr

order to determine the mechanical strength of themine, INERIS was asked by the MDPA to identify
the origin and consequences of these cracks.
The present study focuses in particular on the
network of cracks due to mechanical failure (causedby the stress levels) observed in the roof and facingsof some galleries running perpendicular to their axis.
These more or less open cracks intersect alongitudinal fracture. The aim of this article is toanalyse the mechanisms that led to this mode of
failure in the roof.
Numerical modelling shows that the origin of the“transverse” cracks perpendicular to the axis of thegalleries is linked to the creep of the salt pillars. In
other words, the mechanism of deformation of theroof in the immediate vicinity is controlled mainly bythat of the pillars. As these pillars are extremely
massive (20 m wide), during their vertical andtransverse deformation (continuous deformations
related to salt creep), they pull down the roof in theimmediate vicinity.
Although fracturing phenomenon along the axis
galleries is often encountered in underground minesand quarries (coal, building stone...), transverse
cracking is much more rare. Indeed it is strongly
related to the intrinsic nature of salt, which deforms
as there are stress deviators within it. It is on thismechanism that the paper will focus.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2. DESCRIPTION OF THE SITE
The site examined by this study covers an area of
about 4 hectares, 700 m x 600 m. It is located at a
depth of approximately 550 m and exploited by theclassical abandoned room and pillar method. The
pillars are 20 m x 20 m square. The chambers are 5.5m wide and 2.8 m high (Figures 2 and 3). The
worked proportion (ratio of excavated surface to total
surface) is 38%. Storage is accessible through aisles
called double tracks, 4m wide, separated by 3m-wide
pillars.

cuts before caving in the roof (by removing the
support structure).
Thus, significant subsidence of a maximum of
5.5 m was measured at the surface. The storage area
is more or less affected by mechanical disturbances,induced caving, and stot.

Cracks
Roof
Waste
bag
PillarFigure 4: View of a transverse crack in the roof (MDPA2015).

Figure 2: Section through Storage Area and location of
cracks (blue) (MDPA, 2015) (Key: Bloc – Block).

Figure 3 is a zoomed-in image showing the design of
the access tracks.

A visual inspection of the site revealed theexistence of Mode 1 open cracks (Figure 4). One ofthe vertical cracks runs longitudinally in the directionof the track, practically in the middle of it (classic“flexion” mechanisms) resulting in horizontal
traction.
It is however intersected by cracks perpendicular(transversal) to the track (Figure 4). These cracks aremainly at mid-width of the (20 m wide) pillars. It wasobserved that the transverse cracks are more or lessopen. They cross the roof and facings of the track.

Figure 3: Zoomed-in image of pillars, aisles andintersections and location of cracks (blue) (MDPA, 2015).
Key : Voie d’accès latérale - Side access route; Voie d’accès
médiane - Middle access route; allées - aisles; recoupe intersection; R1, R2... - I1, I2...

The site is located in the Alsace Potassium Mines
which have been exploited throughout the lastcentury. The formerly exploited level is about twenty
meters above the level of storage. A very large pillar
called stot was left for the overlying exploitation.

Figure 5: Example of separation of roof(source, MDPA 2015).

This is an unworked part, and includes two
Potash layers worked by the method of making long

As for bed separation (Figure 5), this affects the
bed of rock salt in the roof immediately above the109

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

tracks at the marly-anhydrite insoluble interlayersthat are frequent at MDPA site.
In order to analyse the mechanical response ofthis structure, we must correctly define the intrinsic
characteristics of its constituent material, namely salt,
which will be the subject of the next section.

3. MECHANICAL BEHAVIOUR OF SALTThe main aspects of the rheological behaviour ofrock salt are generally the same, whatever the variety.
They can be summarised as follows:
1- a more or less marked aptitude for creep.
2- the absence of any viscoplasticity.
3- the rates of deferred deformations increase, in a
non-linear manner, with deviatoric stress.
4- the rate of creep also increases exponentially withtemperature. This dependency is expressed by the
Arrhenius Law.
5- salt creep is accelerated after a crack occurs(resulting in so-called called “tertiary” creep
observed in the laboratory, which results in thesample being ruined).
6- salt creep is accelerated in the presence ofhumidity and brine.
7- Above a certain level of stress, salt will crack.
Unlike creep, the damage threshold of salt depends
both on the mean stress and the deviator (like mostrocks).
8- the damage thresholds (microcracking) andmacroscopic breaking (maximum resistance)
thresholds of salt fall in the presence of brine.
In light of these main traits of the thermomechanicalbehaviour of rock salt, two main rheological models
have been proposed for the viscoplastic behaviour(creep) of this material: i) The Lemaitre model.
According to this model, salt creep slows down overtime and its development is expressed by a time
power law, ii) the Norton (also called Norton-Hoff)model, widely used for salt throughout the world.
This model considers that beyond a short transientphase, creep reaches a stationary state (linear
evolution). We would also point out that the Nortonand Lemaitre models are designed for the viscoplastic
behaviour of rock salt and are not aimed at modellingthe damage and rupture of this material. We used inthis study the Norton model, on the basis of ourfindings on the results obtained during a previous
study (Laouafa, 2010) focussing on the in situ
convergence measurements (Figure 6).

Figure 6: Rate of vertical closure, at different points of themine (MDPA 2015).

Figure 6 clearly shows the linearity of
convergence as a function of time, hence the use of
the Norton model described below. For this model,
the rate of viscoplastic strain εvp

is expressed asfollows (in tensor form):ε vp A exp(− B / T )(Q / Q0 ) n
=

∂Q
∂σ

(1)

Q is the von Mises effective stress (MPa) and A ,B , n : model parameters ; Q0 = 1 MPa
Table 1: Creep model used by INERIS, adjusted against in
situ measurements (Laouafa, 2010).

Elastic Parameters
E (MPa)25000

ν( - )
0.25

Viscoplastic Parameters(Norton model)
A (j-1)B(K)n( - )
0.022
4700
4.0

4. NUMERICAL MODELLING
4.1 Numerical Model and Assumptions
Although the storage area has no particularsymmetry (Figure 3), a quasi-periodic “unit cell” canbe seen, consisting spatially of pillars, aisles andintersections.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 7: Plan and 3D view of the pillars, galleries andplanes of symmetry.

In order to optimise the calculations without
reducing their accuracy, a unit cell (Figures 7 and 8)
composed of a 20 m x 20 m pillar 2.80 m high, aisles
and intersections 5.5 m wide and the roof of thestorage area positioned at -550 m (depth) was used.

4.2 Numerical results
This sub-section is dedicated to numericalresults. We will focus only on the tensile stresses
generated in the gallery roof, the main subject of thispaper. Figure 9 shows the spatial extent of the zones
under horizontal traction (Syy, stress component)(blue) affecting the roof and pillars after 10 years of
creep. Note that Syy (orthogonal to the gallery axis)
tractions develop on facets perpendicular to the axisof the gallery. Note also that the edge of the pillars
and part of the roof is also affected by tractions.

Figure 8: 3D view of pillar, galleries and unit cell andzoom-in view of the galleries.
Key: Modèle… - Mesh Model

The idealized geological medium is composed
entirely of salt (Table 1), without taking into accountthe few marly seams in the roof. The dimensions of
the model, the state of initial stress and the set
boundary conditions are described below.
The dimensions of the model (Figure 8) are as
follows:- Width 25.5 m- Length 25.5 m- Height 42.80 m (wall 20 m and roof 20 m and pillar
2.80 m)The boundary conditions are as follows:- Plane of symmetry for the four vertical sides- Plane of symmetry at the base of the model- Pressure of 11.45 MPa (weight of the overburden).
The initial conditions are as follows:- Range of initial lithostatic and isotropic stresses(hypothesis supported for evaporites):

σ xx ( z )= σ yy ( z )= σ z z ( z )= γ × z(2)In regards to the chronology and time span of thestudy, aisles and intersections were simulated
numerically in about ten days. It does not follow thereal chronology but allowed the stabilization of theevolving problem over time. The period of time
considered since the voids were created is from 10 to
15 years.

Figure 9: Positive horizontal Syy Stress (traction): Side
view (left) and bottom view of the roof 10 years after
excavation (obtained using the reference model).

Figure 10 shows (wireframe view) the 3D spatial
distribution of the zones subjected to Syy traction .

Line LA

B

Figure 10: 3D view of the zones affected only by traction in
direction y (Syy > 0) in the roof and pillar after 15 years(obtained using the reference model). The aisle,intersection, roof and pillars are shown.

From a more quantitative viewpoint, the paper isinterested in what follows the time evolution of these
tractions induced by creep of the pillars. For thisLine L (parallel to the gallery axis), in direction y,located at mid-span of the roof, and segment AB,

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

located along the edge of the model (Figure 11)(perpendicular to the gallery) is considered.

Figure 11: Definition of Line L under analysis passing
through the roof of the storage area and parallel to the yaxis and Transverse segment AB (perpendicular to the axisof an aisle), located on the roof at mid-width of the pillar.

Figure 12 shows the distribution of horizontal
stress Syy along Line L at two moments: 5 and 10
years. Initially (all structures in virgin state), Syyequals around -13 MPa (negative due tocompression).
The redistribution of the stresses due to theworks (here modelled with no phasing and virtually
instantaneous) at t=0 changes continually over time.
Note, for example, that 5 years after the works, Syy
stress is still under compression but gradually comesunder traction domain.

horizontal stress Syy at point B and for different
configurations (hard or soft roof, slenderness, orexcess-load roof).

Figure 13: Distribution of Syy stress along segment AB(Figure 10) after 5, 10 and 15 years. For two pillar heights(H).
Key: - Abscisse - distance-axis

A reduction in Syy stress was observed, passing
gradually from compression to traction and reach
failure state within 10 and 15 years.
This
corresponds exactly to the period when the cracks
appeared in the roof.

Figure 14: Temporal evolution of horizontal Syy stress atpoint B, as a function of time, since excavations began andfor the different configurations.

Figure 12: Distribution of horizontal stress Syy along line
L at 5 and 10 years (computed using the reference model).
The horizontal-axis represents the distance in m and thevertical-axis the stress in MPa. The sign convention is thatof continuum mechanics (stress positive in traction andnegative in compression).

These results show that the creep of the salt
pillars is the main factor responsible for thesesignificant variations in stress in the immediate roof
area of gallery. The combined effect of this mode of
failure and cracking occurred in two perpendicular
directions (longitudinal and related roof separation)
threatens the security of the site.

This result is confirmed in Figures 13 and 14,
which focus solely on the time evolution of the112

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

5. CONCLUSION
The 3D models (finite elements) clearly showthat the creep of the salt mine is the primary cause of
the cracking observed in situ. In particular, thetransverse cracking affecting the galleries is causedby the gradual horizontal expansion of the pillars
whose height continuously decreases (and leads tothe expansion of the pillar, salt creep occurring withno variation in volume) due to the effect of salt creep.
This expansion of the pillars forces the roof tostretch, which causes horizontal tensile stresses
increasing over time. These stresses, on exceeding
the salt’s tensile strength (very low, 1 to 2 MPa
maximum, in the short term and practically negligible
in the long term) give rise to transverse cracks, which
manifest themselves sooner or later in the pillars of
all of the tracks.

6. ACKNOWLEDGEMENT
The authors wish to warmly thank the MDPA
(Mines de Potasse d’Alasce) for their support andtheir active contribution to the work which allowed
carry out the study.

7. REFERENCES
Cristescu N., Hunsche U. 1991. A constitutive
equation for salt, 7th Int. Cong. Rock Mech., Aachen,
Sept. 16-20, Balkema
Cristescu N., Hunsche U. (1998). Time effects in
Rock Mechanics, Wiley.
Ghoreychi M. (1990). Conséquences ducomportement thermomécanique du sel pour laconception et la sûreté d'un enfouissement de déchets
radioactifs. Stockage en Souterrain, Presses des Ponts
et Chaussées, 229-243.
Laouafa, F. (2010). Etude géomécanique dustockage de StocaMine. Rapport INERIS–DRS10108130-14273A.
Laouafa, F. (2010). Analyse critique des études
géomécaniques du stockage de StocaMine, Rapportd’étude INERIS-DRS-10-108130-04240A, 2 avril.
Mogenier, C. (2015). Rapport d’étude
géophysique -Wittelsheim Bloc 21 / Allée 3 –00029074. SOLDATA Geophysic.
Roman, J. (2015). Stockage de déchets
StocaMine. Note de synthèse suite à la « visited’inspection du 6 novembre 2014 ». MDPA.

113

ISMS 2016

Paper No. 15

Lessons in slope stability management from Kinross’ Tasiast mine,
Mauritania
Korhan Tasoren a, *, Gillian Gardhouse, P.Eng. b, Dr. Jerry Ran, P.Eng. caSenior Geotechnical Engineer, Kinross Tasiast Mauritanie Limited SA, Nouakchott, Mauritania, BP 5051
Senior Geotechnical Engineer, Kinross Gold Corporation, Toronto, Canada, ON M5J 2V5
c
Geotechnical Services Director, Kinross Gold Corporation, Toronto, Canada, ON M5J 2V5b

ABSTRACTThe continued monitoring and optimization of a mining operation are essential extensions of a feasibility study.
While the ultimate goal is to mine to the planned design in a safe and economic fashion, such efforts are challenged
on a daily basis by changing ground conditions. Success in a dynamic mining environment requires a strong
understanding of historical instabilities and wall control blasting, along with well-defined near wall excavation andclean-up procedures, and an advanced slope monitoring system. This paper presents several cases describing
different modes of slope failure experienced at Kinross’ Tasiast mine site, and the operational and design measures
implemented to manage and monitor these instabilities. Routine data collection practices and blasting designs thathave been introduced to minimize wall damage and steepen slope angles are also discussed.

1. INTRODUCTION
The Tasiast mine (Tasiast) is an open pit gold
mining operation that is owned and operated by
Kinross Gold Corporation. The mine is located innorthwestern Mauritania, approximately 300 km
north of the capital city of Nouakchott (Figure 1).

(Figure 2). The Piment Zone hosts eight small,narrow pits. The largest of these pits is known as
Piment Central and is 0.9 km long and 0.5 km wide,with a depth of 0.2 km. Mining commenced at
Piment in 2007 and commercial production wasreached in 2008. To the south of the Piment zone is
the West Branch Zone. The West Branch pit is thelargest of the four pits located in this area. In 2009,
the mineralized Greenschist Zone was discovered atWest Branch, prompting additional exploration andstudy to support an expanded project. A feasibility
study was subsequently completed in 2014. The final
pit shell in the current design measures 1.8 km longby 1.4 km wide and is approximately 0.5 km deep.
The pit is now in the first phase of operation.
Since extraction began in 2007, a number ofminor slope failures have occurred at Tasiast. Backanalyses were performed in some cases, and slope
designs and implementation procedures were
optimized to minimize blasting damage and monitor
slope movements.
This paper presents typical slope failure modes
observed at Tasiast, results of the corresponding backanalyses, and lessons learned in slope stability
management.

2. MINE GEOLOGY
Figure 1: Location of the Tasiast mine site.

Today there are two active mining zones at
Tasiast: the Piment Zone and the West Branch Zone

At Tasiast, gold mineralization at the regional
scale occurs in two parallel trends: the Piment Zone,
with a strike length of 4.5 km, and the Greenschist
Zone, with a strike length of approximately 1.5 km.

*Corresponding author – korhan.tasoren@kinross.com : 00 (222) 44441573

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Both zones are characterized by oxidized andtransition materials to a depth of 50 m to 100 m,
which are then underlain by fresh rock. The dominantand controlling structure of the eight to ten sets ofidentified geological discontinuities and features isthe foliation, which dips toward the hanging wall of
the deposits (east).
Groundwater flow occurs in the oxidized zone
and into the transition zone. Following the start-up ofmining, local scale flow shifted the hydraulicgradient toward and into the pits. Below the transition
zone, there is virtually no groundwater movement
due to the low hydraulic conductivity of the fresh
bedrock. There is no regional-scale groundwater flowin the Tasiast area (SWS, 2014).

Slope stability analyses completed for West
Branch were based on the developed geological,
structural, rockmass quality, and hydrogeologicalmodels. Two numerical modeling methods (Limit
Equilibrium and Finite Element) were used toestablish slope angles and obtain the corresponding
Factor of Safety values for the slopes. Recommended
slope design parameters are shown in Table 1.

Figure 2: Mining area layout showing studied pits.

3. GEOTECHNICALDESIGN

DATA

AND

PIT

The latest geotechnical study and pit design forWest Branch were completed in 2014. In addition toprevious geotechnical investigation programs, the2013 drilling campaign consisted of eight dual
purpose geotechnical and hydrogeological holes
totaling 4,609 m. Oriented core logging, field andlaboratory testing, borehole televiewer surveying, andpit mapping methods were also used to collectgeotechnical data. Golder Associates, the consulting
firm behind the 2014 geotechnical investigation,
selected Cai’s Geological Strength Index (GSI) for
rock mass classification purposes.
The West Branch pit is divided into four
geotechnical domains based on geological, structuraland rockmass similarities, as well as wall orientation
due to the nature of the foliated/bedded host rock
(Figure 3). Each domain is sub-divided into oxide,
transition, and fresh categories based on the intensityof weathering. Two different rockmass qualities havebeen identified within the transition zone andsubsequently categorized as the upper and lower
transition zones for geotechnical slope design
purposes.

Figure 3: West Branch open pit geotechnical sectors.
Modified from Golder (2014).
Table 1: West Branch slope design recommendations.
Bench
Bench
Berm
Face
Height Width
Depth
Angle
Sector
(m)
(m)
(m)
(°)
HW oxide
0-30
60
10
6.5
HW transition 30-10065
10/20 6.5/8.5
HW fresh
>100
75
30
10.5
FW oxide
0-30
45
10
6.5
FW transition 30-10045
10/20 6.5/8.5
FW fresh
>100
45
30
10.5

4. HISTORICAL SLOPE FAILURES AND
DESIGN IMPLEMENTATIONS
Pit slope stability is an important aspect ofproviding a safe and productive working environment
at a mine site. Slope failures have historicallyoccurred in the upper zones of operating pits at
Tasiast. Circular, planar, wedge, and toppling failuremodes have been observed and are generally115

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016attributed to the weak rockmass and excessive
blasting damage. Although none of these failures
were large in scale, the insights gained can be used tomake operational and design improvements.
4.1 Piment Central Pit Rockfall Incident
A loose rock fell 50 m from a bench crest to thepit floor on the hanging wall side of the PimentCentral Pit during a night shift. The slope monitoringradar was able to detect the movement, which wascaused by crest damage, but was unable to send an
alarm to the site geotechnical team because themovement was sudden rather than progressive(Figure 4). The radar data indicated that the loose
rock had a mean displacement of 1.10 mm and avelocity of 2.5 mm/h (Figure 5).

Figure 4: Slope monitoring system screen shot of the
movement area during the event.

Figure 6: Back analysis of the rockfall incident using
RocFall software.

The root cause of the failure was the presence ofloose rocks on the broken crest due to blastingdamage, excessive sub-drilling, and poor face cleanup practices. The geological characteristics of theregion adjacent to the blast and further up the slope
dictate the potential for blast-induced damage (Read& Stacey, 2008). The hazard area was identified, ahigh windrow was built along the ramp 10 m awayfrom the toe, and a 15 m standoff distance procedure
was put in place for the rest of the pit to prevent
similar incidents. A 20 m vertical mid-bench presplit
blasting design was applied to the pit hanging wall to
reduce production blast damage to the face, since a
proper trim blast could not be implemented in such anarrow and small scale mining environment.
Significant improvements have been observed in thecondition of the face and in pit design compliancesince implementing the pre-split design (Figure 7).

Figure 5: Displacement graph of the event.

RocFall software (Rocscience) was used to backanalyze the rockfall event and calculate thedisplacement. The weight of the rock mass wasestimated to be 200 kg. A face profile was createdusing AdamTech photogrammetry software. The
actual distance from the toe at the pit bottom to thefinal resting location of the spilled rock wasmeasured at 10.75 m in the field and calculated at
10.015 m by the RocFall model, demonstrating thatthe model is an adequate representation of the event(Figure 6).

Figure 7: a) Actual pit wall design after implementing presplitting procedures; b) Predicted pit wall without wall
control blasting.

4.2 Planar Failure at West Branch Footwall
The West Branch footwall design bench faceangle (BFA) was limited to 45° to avoid undercutting
the foliation, which dips at 42° to 46°. The foliation116

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

strikes 350° and has an average spacing of 2.5 m.
Previous blast designs used in the early stage of the
project did not consider these design limitations,which led to excessive damage in the oxide andtransition zones on the footwall. This was
exacerbated by the use of standard full depth verticalblast holes near the wall.
Several small, bench scale planar failures wereexperienced as a result of damaged or narrow catchberms, and broken toes. The typical failure dimension
was limited to 20 m long by 2 m wide by 30 m highdue to the condition of the rockmass and theintersection of joint sets.
To prevent blast damage, a modified trim blast
design was applied to the area near the footwall(Figure 8). Two stepped holes were introduced tobreak the rock along the foliation surface and achieve
the pit design. This approach resulted in smooth faceconditions along the foliation plane and improved pit
design compliance on the footwall.

SLIDE v5.0 software (Rocscience) was used toback analyze the failure. Inputs included a highresolution photogrammetry face profile (Figure 9),
steep transient water table profile behind the face,and density, cohesion, and friction angle values.
Different combinations of the input parameters
shown in Table 2 were analyzed to simulateconditions similar to those of the failure. The SLIDE
v.5.0 results are shown in Figure 10. All of thecondition combinations suggest a Factor of Safety(FOS) of 1.0 (Table 3).

Figure 9: Photogrammetric surface of the failure area.

4.3 Turek 2 Pit Rockmass Failure
The Turek 2 pit is one of the oxide satellite pitsthat will eventually become part of the West Branch
pit as mining progresses. The Turek 2 pit has 10 mhigh benches with 6.5 m wide catch berms and a 65°
BFA. It is 45 m deep. Approximately 400 tons ofmaterial fell several benches to the bottom of the pit,
resulting in a failure area 25 m long, 3 m deep and 25
m high. A 75° foliation angle was measured on thepit face where the failure occurred.
Back break was observed on the catch berm
parallel to the strike of the foliation after production
blasting. No consideration for wall control had been
included in the blast design, such that a high energy
charge was used in soft rock, causing damage to thefinal wall. Rainfall flow marks were found on the topof the pit in the failure area during the incident
investigation. Over-digging was observed on theface, resulting in a very narrow catch bench berm.
Together these factors contributed to the failure.

Frictionangle(degree)

Cohesion(kPa)
Wet

Cohesion(kPa)
Half Dry

Cohesion
(kPa)
Dry

FOS

Figure 8: An example of a modified footwall trim blast
design.

Unit Weight(kN/m3)

Table 2: Back analysis results using different combinationsof conditions.

23
23
23
23
23

30
32
34
36
37

31
27
24
20
17

25
20
15
11
8

19
14
9
3
0

1.0
1.0
1.0
1.0
1.0

Figure 10: SLIDE v5.0 section of the hanging wall.

The pit design was reviewed and modified after
the failure. A 15 m wide catch berm was left on the
hanging wall, and a radar system was set-up to detect
any further movement. A similar type of movement
was observed by the slope monitoring system on thenorthern side of the failure (Figure 11). Blasted

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

material was left as a buttress to prevent excessive
movement along the face. Only a toe charge wasapplied to the first row of the production blast to
further reduce vibrations and related damage.
Turek 2

Problem& CauseAnalysis

Solution

ResultFigure 11: Movement at the northern side of the failure.

The following rockmass characteristics were
determined as a result of the back analysis: thecohesion is 19 kPa, the friction angle is 30° and theunit weight is 25 kN/m3 for similar types of material.
The effect of weathering in the oxide zone wasgreater in the hanging wall of the Turek 2 pit than in
the West Branch area. Based on this, the Turek 2 pit
geometry was modified to 10 m high benches with 7
m wide catch berms and a 55° bench face angle.
4.4 Summary of Failures
Table 3 summarizes the different failures, actions
and outcomes discussed in this section.

West Branch

Piment Central

Table 3: Summary of the failures and the actions taken in
response.
Pit
Area
Summary
Rockfall due to broken crest resulting
Problemfrom excessive sub-drilling and poor
& Causeface clean-up practices
Review of monitoring data
Analysis Back analysis to calculate
displacement
Implemented mid-bench pre-splitting
Built windrow appropriate distance
Solution away
Implemented standoff distanceprocedure
Improved face condition
ResultIncreased compliance to design
Problem Planar failure due to incompliance& Cause with pit design dimensions
Blasting design review
Analysis
Pit design review
Two stepped blast hole design
Solution
appliedResultSmooth face conditions along thefoliation plane
Improved pit design compliance

Rockmass failure due to excessive
blasting damage and rainfall
infiltration
Field investigation
Photogrammetry survey
Back analysis
Review of monitoring data
Revised pit design based on the backanalysis results
Enlarged catch berm
Modified blasting design
Planned pit production completed
without safety issues or ore loss

5. ONGOING DATA COLLECTION AND
MONITORING
Ongoing geotechnical data collection at Tasiast
consists of face mapping, application ofphotogrammetry techniques for measuring structures(Figure 12) and bench configurations, pore pressure
measurements from twelve vibrating wire
piezometers around West Branch, and wet blast holeand grade control hole mapping, where available, tosupport pit inspection and operation.
Recently, data from face mapping and structural
measurements were used to update the structural andgeotechnical models. The geotechnical model was
subsequently used in a fragmentation study to better
understand the effects of energy distribution acrossmajor and minor joint sets. This is significant because
blasting loosens existing structures to liberate rockblocks and create new fractures within the intact
material (Kanchibotla et al., 1999). Rockmass
elasticity parameters and the intensity of structures(in-situ block size) are known to have significant
influence on the efficiency of blasting at Tasiast. As aresult of the study, fragmentation was improved in
the ore zone, and the cost of drilling and blasting was
reduced while maintaining the quality offragmentation in the two main rock types.

Figure 12: Structural measurements obtained along theWest Branch footwall using photogrammetry.

The control and management of water is afundamental component of most successful large
open pit mining operations (Beale & Read, 2013).
Pore pressure data obtained from vibrating wire
piezometer holes and mapping of wet blasting or
grade control holes assist groundwater studies and118

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016provide guidelines for pit dewatering activities on adaily basis (Figures 13 and 14).

Figure 15: IBIS-FMT slope monitoring radar in action.

Figure 13: Cross section of vibrating wire piezometer hole.

Figure 16: Summary of the slope movement action plan.

6. CONCLUSIONS

Figure 14: Plan view of West Branch major structure andwet drill hole mapping correlation.

The Tasiast mine currently has two synthetic
aperture slope monitoring radar systems. Thesesystems have been used for tactical and strategic
monitoring in different pits since 2013 (Figure 15).
Parameters for alarm set-up include area (m2),velocity (mm/hour), and time interval (hour or day).
These parameters must be low enough to provide an
early warning when a slope is starting to move, butalso high enough to prevent false alarms. The systemcollects continuous data in three minute scanintervals and backs up historical files to an external
storage unit for further analysis. Interpreted data aretransmitted to the Guardian slope monitoring
software in the office to be filtered based on site
thresholds. Any type of movement above the set
thresholds triggers the alarm, prompting the software
to send email and SMS alerts to relevant personnel.
The site slope movement action plan is summarized
in Figure 16.

Bench excavation at the Tasiast mine site iscontrolled through a variety of measures, including
the use of appropriate equipment, standard operatingprocedures, and marked lines or pegs, in order tominimize face damage and crest loss. When there are
localized failures, wider catch benches and safety
berms are commonly used to protect personnel andequipment. Areas of concern related to slope
movement or restricted operating space aremonitored by one of two ground-based synthetic
aperture radar units. These units provide real timemeasurements and send out alert messages based onpreset threshold values.
Exposed benches are routinely mapped forgeological and geotechnical features using manualand photogrammetric techniques. The collected data,
together with the existing database, feed the mine’s
geotechnical model and permit both predictive
analyses and back analyses of slope stability.
Blasting against pit walls in particular has
significant impact on slope stability and achievementof the design configuration, as well as implications
for safety, productivity and mining costs. Various
blasting designs have been applied to both footwall
and hanging wall slopes. In general, hanging wall
slopes are protected from excessive damage by preshearing prior to trim shots or modified production
blasts, while trim shots and modified production
blasts with two stepped stab holes are used when119

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

blasting against footwall slopes. These modifications
to the blast design support a safe and economic
mining operation.

7. ACKNOWLEDGEMENT
The authors would like to thank Rahadian
Widiadi and Moulay Ahmed Hamoudy for theirsupport, and Kinross Gold Corporation for
permission to share these lessons by publishing thispaper.

8. REFERENCES
Beale, G. and Read, J. (2013) Guidelines for
Evaluating Water in Pit Slope Stability. 49 p.
Cai, M., Kaiser, P. K., Uno, H., Tasaka, Y., &Minami, M. (2004). Estimation of rock mass
deformation modulus and strength of jointed hardrock masses using the GSI system. International
Journal of Rock Mechanics and Mining Sciences, 41:
3-19.
Golder Associates. (2014). Tasiast West BranchOpen Pit Slope Design Recommendations – Revision
1, Technical Memorandum. Buckinghamshire:
Golder Associates UK Ltd.
Kanchibotla, S. S., Valery, W. and Morrell, S.
(1999). Modelling fines in blast fragmentation and its
impact on crushing and grinding. In Explo’99: A
Conference on Rock Breaking, Kalgoorlie, WA,
November 7-11, AusIMM, Vol. 99, pp. 137-144.
Read, J. and Stacey, P. (2008) Guidelines forOpen Pit Slope Design. 275 p.
Schlumberger
Water
Services.
(2014).
Hydrogeological characterization of the West BranchPit, Tasiast, Mauritania. Shrewsbury: Schlumberger
Water Services.

120

ISMS 2016

Paper No. 20

Effect of buttress on reduction of rock slope sliding along geological boundary
Ryota MORIYA*, Daisuke FUKUDA, Jun-ichi KODAMA, Yoshiaki FUJII
Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan, 060-0808

ABSTRACTIn open-cut limestone mines in Japan, huge rock slopes with a geological boundary between limestone and bedrock
have been formed by mining activities. In addition, latent sliding plane near the toe of the slopes may be formed
through the development of damaged zones with an increase in size of the rock slope. It has been reported thatinelastic time-dependent sliding deformation of rock slopes along both the geological boundary and the latent sliding
plane can occur. In this case, one of the countermeasures to suppress sliding deformation is an application of rockbuttress to the slope surface where the sliding is taking place. However, the effect of rock buttress on reduction of
the rock slope sliding has not yet been clarified. In this paper, the effect of rock buttress on reduction of the rockslope sliding is discussed based on a 2-dimensional finite element analysis using a non-linear visco-elastic model.
The results indicate that (i) the degree of deterioration of sliding plane at the time of the application of rock buttresssignificantly affects the expected life of rock slope, (ii) there is an optimum height for rock buttress,, (iii) larger
Young's modulus of rock buttress results in a longer expected life of rock slope, and (iv) the balance of increase anddecrease of normal and shear stresses on the sliding plane by buttress is important and the obtained results can bechanged by the difference of friction angle and the geometry of the sliding plane.

1. INTRODUCTION
In open-cut limestone mines in Japan, huge rockslopes have been formed by mining activities (Obaraet al., 2000). In Japan, limestone deposit is often
found on inclined bedrock and a part of the limestone
deposit is left on the bedrock, such as schalstein toprevent the bedrock from weathering (Nakamura etal., 2003). Thus, the rock slopes include a geologicalboundary between limestone and bedrock. In
addition, with increases in size of the rock slope, thestress state near the toe of slope can be severe and adamaged zone can develop. Therefore, it is necessary
to pay attention to the deformation behaviour at thegeological boundary and the toe of slope for theestimation of slope stability. Moreover, it isimportant to consider effective countermeasures incase dangerous signs such as sliding deformation atthese parts are observed. One of the countermeasures
to suppress the sliding deformation is application ofrock buttress to the slope surface where the sliding istaking place. However, the effect of rock buttress on
reduction of the sliding has not yet been clarified.
In this paper, the effect of rock buttress on
reduction of inelastic time-dependent rock slope
sliding, for example, how the height and stiffness ofrock buttress affects slope deformation is discussed
based on self-developed 2-dimensional (2-D) finite
element code using a non-linear visco-elastic model.

2. MODELLING SLIDING DEFORMATIONOF ROCK SLOPE
The aforementioned inelastic time-dependent
sliding deformation of rock slope was modelled first
to investigate the effect of rock buttress on the
reduction of the sliding. Figure 1 shows the 2-D
model of rock slope with geological boundary (blueline) and latent sliding plane (red line). Hereafter theterm “sliding plane” is used to indicate both
geological boundary and latent sliding plane. It was
assumed that the rock slope was already formed bypartially excavating the left side of a mountain. The
height and angle of slope were set at 270 m and 45°,
respectively. The geological boundary was set
parallel to the slope surface and latent sliding planefrom the slope surface, with an angle of 18° from thehorizon, and intersected with geological boundary
near the toe of slope. The intact rock mass was
represented by 6-node and 8-node solid elements andassumed to be isotropic linear elastic body, while the

Figure 1: Schematic of 2–D FE model.

*Corresponding author – email : r_moriya102@frontier.hokudai.ac.jp

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

sliding deformations along the sliding plane wererepresented by 6-node joint elements (Pande et al.,1979) and assumed to be a non–linear visco-elastic
body. The nodal displacements perpendicular to theright and bottom boundaries of the model were fixedat zero. All the analyses were conducted under planestrain conditions.
By applying downward gravitational force to theentire model, linear elastic analysis was conducted
and the initial stress state of both the solid and joint
elements was simulated. This state was regarded astime t = 0 for the non-linear viscous sliding
deformation analysis along the joint elements, i.e.
sliding plane. This viscous sliding deformation was
expressed by decreasing shear stiffness, Ks(t), of joint
elements with time. For the way in which Ks(t)decreased, we extended the constitutive equation ofvariable compliance type proposed by Okubo (1992)
as follows:mmndλ* (t ) 1  m  n − m +1 *= λ (t ) σ * (t ) .........(1)dtt0  n + 1
where λ*(t)(= Ks(0)/Ks(t)) is normalized complianceand monotonically increasing function with time; t0 is
a time constant; m and n are degree of ductility andtime-dependency of rock, respectively (Okubo,1992); σ*(t) is severity representing how close thepresent stress state of a joint element is to a failureenvelope expressed by Mohr−Coulomb failure
criterion. To make the following discussion simpler,it was assumed that rock mass was homogeneous andonly Ks(t) changes with time while other physicalproperties are constants, as shown in Table 1. The
upper limit of λ*(t), λ*lim, was set at 10000 and joint
elements whose λ*(t) reached λ*lim were regarded ascompletely fractured.

(

)(

)

respectively, and λ*(t) of only latent sliding planeincreased according to equation (1).
Table 1: Physical properties used in the analysis.
Solid element
Joint element
Values(Rock mass)(Sliding plane)
Young's
Initial Shear
1.0 GPa
modulus, E
stress, Ks0
Poisson's ratio,
0.25
Normal stress, Knν
27.0
Unit weight, γ
Cohesion, ckN/m3
Friction angle, φValues
3.4
MPa
1.0
MPa
0.7
MPa
50°

To demonstrate that the inelastic time-dependent
sliding deformation of rock slopes can be
successfully simulated by the proposed approach, an
example of the analytical results for case A is shownin Figure 2. This figure shows the distribution ofviscous displacement around the rock slope between t= 0 and 1 year. It was found that rock mass above theentire sliding plane showed obliquely downward
sliding relative to the sliding plane. Case B was also
found to show the same tendency.

(a) Case A

Figure 2: Distribution of viscous displacement aroundthe rock slope at t = 1 year (case A).

It is also important to consider the degree ofdeterioration of the sliding plane at the stage of
construction of buttress. In this study, the following
two cases were considered:− Case A: λ*(0) of the entire sliding plane was set at
1.1 and λ*(t) increased according to equation (1).
− Case B: λ*(0) of the geological boundary and latentsliding plane were set at λ*lim and 1.1,(b) Case B
Figures 3 : Temporal change of horizontal viscousdisplacement at point P in Figure 2. Time at “×”represents tlife.

Figures 3(a) and (b) show the results of thetemporal change of horizontal viscous displacement
at the top of the mountain (point P in Figure 2) for122

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

cases A and B. It is clear that both cases first showeda gradual increase of displacement followed by asudden increase. In cases A and B, the entire sliding
plane was regarded as collapsed when λ* of all joint
elements reached λ*lim in about 4.5 years and 3.8
years, respectively.
From the above results, because the non-linear
time-dependent sliding deformation of rock slopes
along the sliding plane was successfully expressed, it
is possible to discuss whether the application of rockbuttress can extend the time when λ* of all joint
elements reaches λ*lim, i.e. expected life of rockslope, tlife, by suppressing the sliding deformation
along the sliding plane.

3. EFFECT OF ROCK BUTTRESS ON
REDUCTION OF ROCK SLOPE SLIDING
3.1 Effect of height of rock buttress
In order to investigate the effect of rock buttresson tlife, the model shown in Figure 4 was analyzed inwhich various heights of buttress, hbut = 30 m - 130
m, with the fixed width were considered. The rockbuttress was expressed by 6-node and 8-node linear
elastic solid elements with Young's modulus Ebut,
Poisson's ratio νbut and unit weight γbut. In thefollowing analyses, solid elements corresponding to
the rock buttress were deactivated until t = 50 s, andthen activated at t = 50 s. The aforementioned twocases of degree of deterioration of the sliding plane,cases A and B, were analyzed.
Figure 5 compares temporal changes of horizontal
viscous displacement at the top of the slope at point P
in Figure 2 with/without rock buttress for cases A and
B. The physical properties of buttress were fixed at
Ebut = 0.01 GPa, νbut = 0.25 and γbut = 2.7 kN/m³. Bothcases A and B show that tlife with buttress is more orless long than that without buttress in the range of hbut
investigated in this study. Especially, tlife in cases A
and B became the longest when hbut was 90 m and
110 m, respectively. Table 2 shows tlife with rockbuttress of various heights normalized by that withoutrock buttress. From the results of Figure 5 and Table
2, it is suggested that the degree of deterioration ofsliding plane at the time of the application of rockbuttress significantly affects tlife and that optimum hbut
should exist depending on the degree of deteriorationof the sliding plane. In other words, the ability ofrock buttress to extend tlife will be compromised once
hbut exceeds the optimum value.

Table 2: tlife with rock buttress of various hbut normalized
by tlife without rock buttress.

Figures 6 and 7 show the stress state on sliding
hbut

30 m

50 m

70 m

90 m

110 m

130 m

Case A
Case B

1.1
1.0

1.2
1.2

1.6
2.0

1.7
6.4

1.3
6.6

1.1
4.2

(a) Case A(b) Case B
Figure 5: Temporal changes of horizontal viscousdisplacement at the top of the slope (Point P in Figure 2)
with/without rock buttress. Time at “×” represents tlife.

plane just before and after the application of rockbuttress in case where hbut was 90 m and 110 m,
which showed the longest tlife in cases A and B,
respectively (See Table 2). In these figures, black andred lines represent the stress state of joint elements
Figure 4: Various heights of buttress, hbut, analyzed inthis paper.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

before and after the application of rock buttress,
respectively. Horizontal axes in these figures
represent the position on sliding plane in which latentsliding plane is in from 0 m (slope surface near thetoe) to 63 m (the intersection of latent sliding planeand geological boundary) and is in from 63 m to 353
m (top of slope); Compressive normal stress, σn, andshear stress, τ, causing normal fault are expressed bynegative values; absolute value of severity, |σ*|, closer
to 1 indicates that the stress state is closer to failureenvelope.

(a) Normal stress(b) Shear stress(c) Severity

These results show that the application of rockbuttress mainly affects the zone of latent sliding
plane. Especially, when σn pressing the latent sliding
plane increased, the result was a decreasing effect of|σ*| in both cases A and B. τ promoting sliding
deformation along the entire sliding plane in case A
and latent sliding plane in case B increased, resulting
in the increasing effect of |σ*|. For hbut investigated inthis study, the increasing effect of |σ*| due to increaseof τ along the entire sliding plane was smaller thanthe decreasing effect of |σ*| due to an increase of σn oflatent sliding plane. Thus, the application of rockbuttress results in extending tlife. However, it is alsosuggested that the application of rock buttress withmuch larger height than those investigated in thispaper should enhance τ promoting sliding
deformation along the entire sliding plane and tlife
could be shorter than tlife without the rock buttress.
The process of sliding plane failure was found toprogress from the toe of slope to the top of the slope.
3.2 Effect of Young's modulus of rock buttress
The effect of Young's modulus of rock buttress,
Ebut, on reduction of rock slope sliding was also
investigated. Three cases, Ebut = 0.01 GPa, 0.1 GPaand 1 GPa, were analyzed only for hbut = 90 m and
110 m in cases A and B, respectively. It is worth
mentioning that the effect of Poisson's ratio, νbut, wasalso investigated in the preliminary analysis,
however, the effect of the change of νbut was
negligible therefore this paper only discusses theeffect of Ebut.
Figure 8 shows temporal changes of horizontal
viscous displacement at the top of the slope (Point P
in Figure 2) for each Ebut in cases A (hbut = 90 m) andB (hbut =110 m). Table 4 shows tlife with rock buttressfor each Ebut, normalized by tlife without rock buttress.
These results clearly show that the larger Ebut resulted
in longer tlife. In particular, the condition of Ebut = 1.0
GPa resulted in about 18−times longer tlife than tlife
without rock buttress and the smallest viscoushorizontal displacement.

Figure 6: Change of stress states on sliding plane before
and after applying buttress (Case A).

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figures 9 and 10 compare the stress state on
sliding plane just after the application of rock buttressfor each Ebut in cases A and B. The meaning ofvertical and horizontal axes of these figures is thesame as those of Figures 6 and 7. Because a relatively
clear difference of the tendency between each Ebut
was found only near the slope surface on the latentsliding plane, these figures only show the results forthe latent sliding plane near the slope surface.
Regardless of cases A and B, larger Ebut resulted insmaller σn and smaller τ. In case A, although only the
results at latent sliding plane near the slope surface
are shown in the figure, larger Ebut reduced τpromoting sliding deformation for the entire sliding
plane, which significantly decreased |σ*|. On the other
hand, change of Ebut locally affected σn (as in Figure9(a)) and caused little difference for the remaining
sliding plane, resulting in a local increase of |σ*| only
near the slope surface. |σ*| for entire sliding plane

Table 4: Expected life of rock slope with buttressnormalized by that without buttress for various Ebut in
Cases A (hbut = 90 m) and B (hbut = 110 m)).
Ebut
Case A(hbut=90m)
Case B(hbut=110m)

0.01

0.1

1.0

1.7

2.5

4.4

6.6

12.5

17.9

(a) Normal stress(a) Case A(b) Shear stress(b) Case B
Figure 8: Effect of Ebut on temporal changes ofhorizontal viscous displacement at the top of theslope (Point P in Figure 2). Time at “×” represents
tlife.

(c) Severity
Figure 9: Comparison of stress state on sliding
plane after applying buttress with different
Ebut (Case A).

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016(a) Normal stress

The obtained knowledge is summarized below:- The deterioration of sliding plane at the time
when rock buttress was applied significantly affected
the expected life of rock slope.
- The optimum height of rock buttress was found
to exist.
- Stiffer rock buttress with larger Young's
modulus resulted in the longer expected life of therock slope.
- The balance of increase and decrease of normal
and shear stresses on sliding plane by buttress isimportant, and the obtained results can be changed by
the difference of friction angle and the geometry of
the sliding plane.

5. REFERENCES(b) Shear stress

Nakamura, N., Tsukayama, Y., Hirata, A. andKaneko, K., (2003), Displacement Measurement ofRock Slope with Cover Rock and its Interpretation, J.
MMIJ, Vol. 119, pp. 547-552 (in Japanese withEnglish abstract)
Obara, Y., Nakamura, N., Kang, S. S. andKaneko, K. (2000), Measurement of local stress andestimation of regional stress associated with stability
assessment of an open-pit rock slope, Int. J. Rock.
Mech. Min. Sci., 37, pp. 1211-1221
Okubo, S. (1992), Analytical Consideration ofConstitutive Equation of Variable Compliance Type,J. MMIJ, Vol. 108, pp. 601-606 (in Japanese withEnglish abstract)
Pande, G. N. and Sharma, K. G. (1979), On
joint/interface elements and associated problems ofnumerical ill−conditioning Int. J. Numer. Anal. Meth.
Geomech, Vol. 3, pp. 293-300(c) Severity
Figure 10: Comparison of stress state on
sliding plane after applying buttress withdifferent Ebut (Case B).

decreased and tlife extended. A similar explanation
can be made for the results of case B.
From the above discussion, in the case of fixed
hbut, it is preferable to apply stiffer rock buttress using
such cement in order to effectively extend tlife.

4. CONCLUSIONSIn this study, non-linear time-dependent sliding
deformation of rock slope along the sliding plane wasanalyzed by 2-D FEM, and the effect of rock buttresson reduction of the rock slope sliding was discussed.

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ISMS 2016

Paper No. 184

Validation of empirical rock mass classification systems for rock slopes
Hassan Basahel*, Hani Mitri
Department of Mining and Material Engineering, McGill University, Montreal, Canada, H3A 0E8.

ABSTRACT
Many classification systems have been proposed in the literature to identify the state of stability of rock slopes. Mostof these classification systems involve factors relevant to the general condition of the rock mass, for example, intact
rock strength (UCS), geometry and condition of discontinuities, and groundwater condition. Such factors represent
the basic part of most of the classification systems, which refer to the well-known Bieniawski’s Rock Mass Rating
or RMR system. However, these factors were initially developed for underground excavations. Therefore, theseclassification systems have been subjected to many criticisms and were questioned for their suitability for rockslopes.
In this paper, some of the common classification systems for rock slopes are used to identify their suitability for rockcuts. Twenty two sites of rock cuts in mountainous roads affected by heavy rainfall in the southwestern part of Saudi
Arabia have been selected as case studies, and four empirical methods are examined for these case studies. The
selected methods are Slope Mass Rating or SMR (Romana, 1985), continuous SMR (Tomás, 2007), Chinese SMR(Chen, 1995), and a graphical SMR (Romana, 2012). The stability conditions for each site have been determined byeach of these methods and a comparison between the results is made for the case of plane failure mode. It is shownthat some of the empirical methods are not applicable such as Chinese SMR (for slopes less than 80 m high), and thegraphical SMR method when the slope angle is more than 80°.
KEYWORDS: Empirical methods; SMR; graphical SMR; continuous SMR

1. INTRODUCTION
Rock slope failure is one of the most common
problems in roads, highways, and railways
constructed in mountainous and rugged areas. Thishas the potential to cause road infrastructure andproperty damage, injuries, and even fatalities.
Different techniques have been proposed toaddress rock slope instability. One of these methods
is rock mass classification systems (empiricalmethods) representing an important tool to assess theengineering behaviour of the rock mass. Empirical
relations between rock mass properties and the
behaviour of the rock mass in relation to a particularengineering application are combined to give amethod of designing the rock structure. Over the lastfew decades the rock mass classification systems
have been commonly used to assess the stability ofrock slopes and identify those of high risk of
instability (Pantelidis, 2009).
Rock mass classification procedures (empiricalmethods) were initially developed for undergroundexcavations as a means to evaluate discontinuousrock mass. The classification systems were developed
primarily empirically by establishing the parametersof importance, giving each parameter a numericalvalue and a weighting factor. This led, via empiricalformulae, to final rating for a rock mass. The final
rating is related to the stability of the underground*Corresponding author – hassan.basahel@mail.mcgill.ca

excavation used for the development of theclassification system (Hack et al., 2003).
In this paper, rock mass classification systems
are discussed in terms of their suitability and validity
for the analysis of rock slope stability. Some of thesesystems are addressed in this study. These are: Slope
Mass Rating or SMR (Romana, 1985), Chinese Slope
Mass Rating (Chen, 1995), Continuous Slope Mass
Rating (Tomás, 2007), Graphical Slope Mass Rating(Tomás, 2012).
Twenty two sites have been selected in thesouthern-west of Saudi Arabia (Figure 1), in order toexamine these four classification systems for theirsuitability and applicability to rock slope stability
assessment. These empirical methods are discussed in
the following section.
2.

CLASSIFICATION SYSTEMS FOR ROCKSLOPE ASSESSMENT
A number of classification systems have been
adopted for assessing the rock mass and the stability
conditions of rock slopes. These classification
systems are described below. The Rock Mass Rating(RMR) system developed by Bieniawski (1973-1989)
is considered the basis of all empirical systems. RMR
system was first developed to analyze the rock masscondition in tunnels; it was later modified to analyze
slopes and foundations. The RMR value is computed

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

by adding ratings values of five parameters according
to Bieniawski (1989). These are: 1) Strength of intact
rock, 2) Rock quality designation (RQD), 3) Spacingof discontinuities, 4) Condition of discontinuities,
and 5) Water inflow through discontinuities. These
five parameters represent the basic RMR. Bieniawski
added a parameter in 1979 to the basic RMR system
as an adjustment for discontinuity orientation (Aksoy,2008). The adjustment parameter for discontinuity
orientation was derived for tunnels and dam
foundations but not for slopes. Bieniawski (1989)
recommended the use of Slope Mass Rating(Romana, 1985), for determining the value of the
discontinuity orientation. The RMR system gives avalue which ranges between 0 and 100.
2.1 Slope Mass Rating (SMR)
Slope Mass Rating system was proposed by
Romana in 1985 as a tool for the preliminary
assessment of slope stability. SMR system provides anumber of simple rules about the instability modes
and required support measures. SMR classification isbased on the Rock Mass Rating by Bieniawski(1979). Two kinds of structural failure modes are
considered in this classification. These are planar andtoppling failures.
The SMR value is obtained from the basic RMRscore (ignoring the discontinuity orientation factor
from RMR) by subtracting a factorial adjustment
factors depending on the joint-slope relationship andadding a factor depending on the method of
excavation as expressed in the following equation:
𝑆𝑀𝑅 = 𝑅𝑀𝑅𝑏𝑎𝑠𝑖𝑐 + (𝐹1 × 𝐹2 × 𝐹3 ) + 𝐹4 . (1)In the above, RMR is the basic score of the rockmass rating. F1 is an adjustment factor, which
depends on parallelism between joints and slope facestrike. It ranges from 1 when near parallel, to 0.15
when angle between strikes is 30 degree (Table 1).
F2 is an adjustment factor that refers to joint dip
angle in the planar mode of failure. It varies from 1
for joints dipping more than 45° to 0.15 for joints
dipping less than 20°. F3 is an adjustment factor thatreflects the relationship between the slope face andjoint dip. F3 ranges from 0 when the angle is morethan 10 degree “Very favorable”, to -60 when theangle is less than -10 degree “Very Unfavorable”. F4
is an adjustment factor that depends on the method of
excavation. The values are selected empirically as
follows:
1) Natural slope “more stable” F4=+15, 2) Presplitting F4=+10, 3) Smooth blasting F4= +8, 4)
Normal blasting F4=0. 5. Deficient blasting “damage
stability” F4= -8.
The SMR classification was modified by
Anbalagan et al. (1992), where the wedge failure wasadded to the system. Both planar and wedge failures

are considered as different cases in the modified
SMR, but in this paper this modified SMR will not be
discussed and only the plane failure will be
addressed.
2.2 Chinese Slope Mass Rating (CSMR)
The Chinese slope mass rating (CSMR) was
proposed by Chen in 1995, where two coefficientswere added to the Romana’s system (SMR). These
two coefficients are the slope height factor (ζ), andthe discontinuity factor (λ), as shown in the following
equation.
𝐶𝑆𝑀𝑅 = (ζ × 𝑅𝑀𝑅𝑏𝑎𝑠𝑖𝑐 ) + [λ × 𝐹1 × 𝐹2 × 𝐹3 +𝐹4 ]..(2)ζ can be defined from the following relationshipζ = 0.57 + 0.43 × 80�𝐻 ..(3)H is the slope height in meter
λ is based on the discontinuity type as follows:
λ=1 for faults, long weak seams filled with clay
= 0.8 to 0.9 for bedding planes, large scale joints
with gauge, and= 0.7 for joints, tightly interlocked bedding planes.
Regarding the slope height the Chinese slope mass
rating is applicable for slope height more than 80m
and any slope equal to 80m or below the equation
will be used without the factor of slope height.
2.3 Continuous Slope Mass Rating (CoSMR)This system uses a continuous function for SMR
adjustment factors. It was proposed by Tomás et al.
(2007). In this system continuous functions for F1,
F2, and F3 correction parameters have beendeveloped.
The proposed F1, F2, and F3 continuousfunctions that best fit discrete values of Romana’ssystem are expressed as:
F1 =

16
25

−

3

500

1

arctan � (|A| − 17)� ..(4)10|𝐴|= �𝛼𝑗 − 𝛼𝑠 � 𝑓𝑜𝑟 𝑝𝑙𝑎𝑛𝑎𝑟 𝑓𝑎𝑖𝑙𝑢𝑟𝑒= �𝛼𝑗 − 𝛼𝑠 − 180� 𝑓𝑜𝑟 𝑡𝑜𝑝𝑝𝑙𝑖𝑛𝑔 𝑓𝑎𝑖𝑙𝑢𝑟𝑒= |𝛼𝑖 − 𝛼𝑠 | 𝑓𝑜𝑟 𝑤𝑒𝑑𝑔𝑒 𝑓𝑎𝑖𝑙𝑢𝑟𝑒
Where𝛼𝑗 , 𝛼𝑠 and 𝛼𝑖 are the joint dip direction,slope dip direction, and the trend of the line ofintersection of two planes.
9

1

17

F2 = +
arctan � B − 5�..(5)
16
195
100
Where B is the dip angle of the joint for planar andtoppling failure modes�𝛽𝑗 �, and the plunge of the lineof intersection of two planes for wedge failuremode(𝛽𝑖 ).
B is arctangent function expressed in degree.
1F3 = −30 + arctan C ..(6)3The relationship (6) is used for slopes with planar andwedge failures.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
1

F3 = −13 − arctan(C − 120)..(7)7The relationship (7) is used for slopes with toppling
failure.
Where C is the absolute difference in angle between
the joint dip and slope dip in case of planar failuremode�𝛽𝑗 − 𝛽𝑠 � , and between the plunge of the line ofintersection of two planes and the dip of the slope|𝛽𝑖 − 𝛽𝑠 | for the wedge failure mode, and the sum of
the two dip angles of the joint and slope for the modeof toppling failure�𝛽𝑗 + 𝛽𝑠 �.

2.4 Graphical Slope Mass Rating (GSMR)
A graphical method was proposed by Tomás etal. (2012), where he designed new Stereo plots basedon the planar, wedge, and toppling failures todetermine the rating values of the slope mass ratingcorrection factors. The two correction factors forjoint direction and dip; F1 and F2, respectively, aregrouped in one term (ψ). The projection of great
circles for main joint sets, as well as the slope face
are laid on these proposed stereo plots in accordancewith the type of failure. Subsequently, the rating
values of FI, F2, and F3 are determined for each kindof failure. Then the equation of the SMR is asfollows:

3.

LOCATION OF THE STUDY AREA
The study area is located in Jazan region in thesouth-western part of Saudi Arabia (Figure 1). It is
located between Lat. 16° and 18° N, and longbetween 42° and 44° E.
Twenty-two sites of rock cuts along themountainous roads in the study area have been
selected. These case studies were chosen on the basisof slopes with structurally controlled failure (Figure2), slopes with stress-controlled failure (Figure 3),
and stable slopes. A field trip has been done toidentify these sites and collect necessary geologicaland geotechnical data from each site.
These sites are distributed as follows: Five sites
along road 12, seven sites on road 8, four sites on Al
Hasher road and five sites along Al Raith road and 1site on Al ‘Aydabi road (Figure 1).

𝑆𝑀𝑅 = 𝑅𝑀𝑅𝑏𝑎𝑠𝑖𝑐 + (ψ × 𝐹3 ) + 𝐹4 ..(8)Figure 2: Site #1 along road 12 represents an example ofstructurally controlled failure.

Figure 3: Site # 21 on Al-Raith road exposed to failure due
to stress controlled factor (completely weathered).

4. DISCUSSION OF RESULTS

Figure 1: Locations of case studies in Saudi Arabia.

The results of the RMR-system indicate that therock cuts sites (1, 2, 3, 4, 5, 6, 10, 14, 16, 17, and 18)
have RMR values between 41 and 57 and areclassified as fair. While, four locations (7, 11 12 13)
have RMR values between 63 and 79 and are

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016classified as good. One site which is 18 gave poorrock quality with RMR value of 37.
The RMR system was not applied in some sites
such as 8, 9, 15, 20 and 21 because the degree of
weathering is high (completely weathered), so thediscontinuities are not well-defined and theirproperties could not be assigned. Also, the failure
behaviour of these locations is most likely to be nonstructurally controlled; discontinuities do notcontribute to the occurrence of the failure, thus, theslope’s instability could be affected by water and/or
seismic forces (stress controlled failure).
The four rock mass classification systems areapplied for only the structurally controlled sites. In
this paper, planar failure mode has only beenaddressed for all these classification systems
analyses. SMR (Romana, 1985) results for rock cuts
indicate that all scores are below 50 and categorizedfrom partially stable to unstable in conservative case(no limit range between the strike direction of slope
face and joints). While, the SMR values will bedecreased until less than 15 when the strikes
difference between the slope face and the joint bearound ±20, and the rock cuts will be categorized
completely unstable (Table 1).
The Chinese SMR system is applied to the casestudies without slope height factor as the heights ofall sites are less than 50 m, and only the discontinuity
factor (λ) has remained in the Chinese SMR equation.
However, the results of this method show asignificant increase in the SMR values than in
Romana’s system (Table 1). The reason for thisincrease is likely due to the low values of the
discontinuity factor for most rock cuts with averagevalue of 0.7. This means tight joints (high cohesion),
which leads to increased SMR values and thus anincrease in the degree of the stability condition.
The results of the continuous SMR (Table 1)
indicated that the range of SMR values are between
29 to 46, and it can be observed that the results of thismethod are in a reasonable range, where there are noabnormal values as found in the discrete SMR by
Romana, where some values are below 10 as in sites
1, 4, 10.1 and 22. Therefore, the continuous functions
for the corrections F1, F2 and F3 gave some kind ofreality to SMR scores.
The graphical SMR method results (Table 1)
indicate that there are no differences between thissystem and Romana’s system results. The reason forthese similarities in the results probably due to theconcept used in the graphical system was the same ofthe original SMR (Romana, 1985), which is thediscreet rating for the correction factors of F1, F2,
and F3, but the difference was in the method of
application by using the stereo plots to determine
these correction factors.

There are some difficulties in application of thegraphical method especially in adjustment factor(F3), when the slope face angle is equal to or morethan 80°, which makes the application of graphicalmethod impossible, such as in sites 6, 7.2, and 10.2.

5. CONCLUSION
Four empirical methods, SMR (Romana, 1985),
Chinese SMR (Chen, 1995), Continuous SMR(Tomas, 2007) and Graphical SMR (Tomas, 2012)
are applied to twenty-two sites of rock cuts located ina rugged area along mountainous roads in thesouthwestern part of Kingdom of Saudi Arabia.
The main purpose of this study is to validate
these classification methods, and compare theirresults for assessment the stability conditions of therock cuts.
All these methods take into account condition of
the rock mass presented by RMR system, and therelationship between the dip and the direction ofslope face and joints which presented by thecorrection factors of F1, F2, and F3, as well as theeffect of the method of excavation (F4).
The results of discrete SMR (Romana, 1985)
give varying scores for SMR and not in tight range
where in some locations the values areunderestimated.
Chinese SMR adds two factors to the original
SMR formula, slope height factor ad discontinuity
factor, but in this study the factor for slope height has
been eliminated, as the slope height for all casestudies is below 80m. Although, the discontinuity
factor has enhanced the SMR values, but the factor ofslope height makes this method not applicable in acorrect manner in rock cuts below 80m, as the height
will be ineffective.
The continuous SMR system results showed nolarge difference among the scores unlike the discrete
SMR by Romana because new continuous functions
have been proposed in this method for adjustment
factors F1, F2, F3 calculations rather than the discrete
function in Romana’s system.
The graphical SMR system has also been used inthis analysis, and it has been observed that the resultsof this method have almost the same results of
Romana’s system as both of them using the discrete
method to determine the correction factors of therelation between the slope face and the joints.
In conclusion, the continuous SMR that is
proposed by Tomas (2007) is closest to the reality
from the other methods. Also if the continuous RMR(Sen and Sadagah, 2002) used rather than the discrete
RMR (Bieniawski, 1989), this may lead to enhance130

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Results of the four empirical methods in case of plane failure mode for structural failure sites.
Site No.
1
2
3
4
5
6
1

70/1902

80/010Joint
51/04046/341
40/09555/283
No (P)No (P)
62/19558/24470/050Site No.
91
102

Slope faceJoint

70/28511
12

76/32070/25040/27540/27577/239No (P)No (P)
66/01534/08066/01534/08044/059

7

Slope face60/04069/01477/05560/26978/02080/0268

88/2851

67/0302

74/023

13
14
15
16

66/09517

76/15470/130

1
2
3

18
19
20
21
22

65/07066/05774/00874/19065/14040/07444/10264/186
No (P)No (P)
70/00855/20960/22550/154

SMR (1985)
CSMR (1995)
CoSMR (2007)
7
22
46
31
34
29
35
38
32
9
12
33
13
26
45
47
50
46
48
51
45
Soil-rock slope (completely weathered)
Table 1: Continued.
SMR (1985) CSMR (1995)
CoSMR (2007)
Soil-rock slope (completely weathered)
4
4
36
38
4
36
38
38
36
20
30
45
47
50
45
12
25
46
48
51
44
38
41
22
Soil-rock slope (completely weathered)
36
38
33
44
47
41
43
46
42
41
44
38
3
16
34
36
39
34
Soil-rock slope (completely weathered)
Soil-rock slope (completely weathered)
8
20
39

GSMR (2012)
7
31
35
9
N/A
13
47
N/A

Field observations
MW, slope height 18m
MW, slope height 19m
MW, slope height 15m
MW, slope height 8m
MW, slope height 19m
MW, slope height 11m

GSMR (2012)

Field observations
Slope height 13m

11
N/A
N/A
20
48
12
48
38
36
44
43
41
3
36

8

SW, slope height 18m
SW, slope height 31m
Slope height 13m

MW, slope height 30m
MW, slope height 10m
MW, slope height 8m
MW, slope height 18m
MW, slope height 22m
Slope height 26m
MW, slope height 33m
MW, slope height 23m
HW, slope height 15m
HW, slope height 36m
Slope height 11m
Slope height 28m
MW, slope height 29m(P) Planar failure. (SW) Slightly weathered. (MW) Moderately weathered. (HW) Highly weathered.

the SMR values and unique scores for SMR will beassigned to the rock cuts (Tomás et al. 2007).
These empirical methods are suitable only withstructurally controlled slopes, and for nonstructurally controlled slopes (highly weatheredslopes) will be difficult to apply as the structuresfeatures are not well-defined, and the stress control
factors will be unknown (i.e. water pressure andseismic force).

6. ACKNOWLEDGMENT
The authors are very grateful to Saudi Geological
Survey for their technical support by provided thefield data and all technical information and unlimited
support throughout the progress of this work.

7. REFERENCES
Anbalagan, R., Sharma, S., Raghuvanshi, T.K..
(1992). Rock mass stability evaluation using
modified SMR approach. In: Jha, P.C. (Ed.), RockMechanics Proceedings of the Sixth National
Symposium on Rock Mechanics, pp. 258–268.
Aksoy,C. (2008). Review of Rock Mass Rating
Classification:
Historical
Developmentsm
Applicationsm and Restrictions. Journal of Mining
Science, Vol. 44, No. 1.
Bieniawski ZT. (1979). The GeomechanicalClassification in Rock Engineering Applications,
Proceedings of 4th In-ternational Congress on RockMechanics, International Society for RockMechanics, Salzburg, Vol. 2, pp. 41-48.
Bieniawski ZT. (1989). Engineering rock massclassifications. New York:Wiley, 251pp.

131

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Chen, Z. (1995). Recent developments in slope
stability analysis. In: Fujii, T. (Ed.), Keynote Lecture:
Proc. 8th Int. Cong. Rock Mech, vol. 3, pp. 1041–
1048.
Hack R, Price D, Rengers N. (2003). A new
approach to rock slope stability-a probability
classification (SSPC). Bull Eng Geol Environ
62:167-84.
Pantelidis, L. (2009). Rock slope stability
assessment through rock mass classification systems.
Int J Rock Mech Min Sci 46(2):315–325.
Romana, M. (1985). New adjustment ratings forapplication of Bieniawski classification to slopes. In
Proc. Int. Symp. On the Role of Rock Mech., pp 4953. Zacatecas.
Tomás, R., Delgado, J., Serón, J.B. (2007).
Modification of slope mass rating (SMR) by
continuous functions. International Journal of RockMechanics and Mining Sciences 44,1062–1069.
Tomás,R., Cuenca,M., Cano,J., Garc
ίa -Barbra.
A. (2012). A graphical Approach for Slope Mass
Rating (SMR). Engineering Geology, vol.124.67-76.

132

Paper No. 73

ISMS 2016

Application of InSAR for monitoring deformations at the Kiirunavaara Mine
Karola Mäkitaavola a, Britt-Mari Stöckel a, Jonny Sjöberg b,*, Stephen Hobbs c, Jonas Ekman d,Michael Henschel e, Anura Wickramanayake f
aLuossavaara Kiirunavaara Aktiebolag, LKAB, Kiruna, Sweden, SE-981 86
Itasca Consultants AB, Luleå, Sweden, SE-977 75c
Cranfield Space Research Centre, Cranfield University, Cranfield, United Kingdom, MK43 0ALdDepartment of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Sweden, SE-971 87e
MDA Geospatial Services, Ottawa, Canada, K2E 8B2
f
Self-employedb

ABSTRACTAn integral part of sublevel cave underground mining is the associated caving of the surrounding host rock. This
causes mining-induced ground surface deformations on both the hangingwall and footwall side of the orebody. The
municipality of Kiruna, in northern Sweden, is located in close proximity to the LKAB Kiirunavaara mine and isthus unavoidably affected by the mining activities. To be able to plan for an urban transformation, as the effects ofmining approach the city infrastructure, it is necessary to monitor the ground deformations on a regular basis.
Historically, GPS-monitoring has been used, with an extensive network of measurement hubs in place. New
techniques for monitoring ground deformations are, however, constantly evaluated. As part of this process, LKAB
has conducted a five-year research and development project on deformation measurements using radar satellites andthe InSAR technology. The project has included a monitoring component and a research- and technology transfer
component. The overall findings of the monitoring program, and the associated research and development work arepresented. Particular emphasis is put on achieved accuracy and the implications for the ability to reliably monitor the
progressing deformations toward the municipality and existing infrastructure. Lessons learnt from the conducted
work are presented, followed by recommendations on future use of InSAR for this type of application.
KEYWORDS: Sublevel caving; mining-induced deformations; DInSAR; CTM; CR

1. INTRODUCTION
1.1 Background
It is an undisputable fact that sublevel cavemining results in ground deformations, in particularon the hangingwall side of the orebody, but to someextent also on the footwall side. The deformations are
categorized into continuous deformations, notcausing fracturing and/or damage, and discontinuous
deformations, in which fracturing and caving
develops (Figure 1). In the long-term perspective, it
is not possible to have any residential buildings orinfrastructure within the fracture zone and cave zone.
The Kiirunavaara mine, in northern Sweden, is
an iron ore mine owned and operated by the
Luossavaara-Kiirunavaara
Aktiebolag(LKAB)
mining company. The mine is currently exclusively
mined underground using large-scale sublevelcaving. Annual production amounts to 28 million
metric tons of crude ore.
The municipality of Kiruna is located in close
proximity to the mine and thus subject to a process of"urban transformation", as the effects of mining*Corresponding author – email : jonny@itasca.se

approach the city infrastructure. Monitoring ofground deformations on a regular basis is necessary
to be able to plan for this urban transformationaccordingly.

Figure 1: Mine-induced fracturing and deformations on the
hangingwall and footwall in sublevel cave mining(schematic, not to scale).

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

GPS-monitoring is used in Kiruna for thispurpose, with a measurement network presently (fallof 2015) comprising 372 hubs. Readings are taken
four times per year. The allowable mining-induced
ground deformations in Kiruna are regulated througha ruling in the Environmental Court in Sweden. The"environmental criterion" states that the groundoutside the mining industrial area cannot be affectedby more 0.3 % strain (horizontally) and 0.2 % tilt(vertically), illustrated schematically in Figure 2.

Example: 50 m
distance

M1

Maximum
15 cm

M2 M2

Maximum
10 cm

Figure 2: The environmental criterion for allowable
mining-induced ground deformations, illustrated for a hubto-hub distance of 50 m.

Results from the GPS measurements are
generally satisfactory and used for establishing thelimits of the environmental criterion per the above.
However, the work load associated with thesemeasurements is fairly extensive. Moreover, GPSmeasurements require installations of measurement
hubs, with additional hubs required as the area ofmining-induced ground deformation increases as aresult of mining at larger depths. New and alternativetechniques for ground deformation monitoring arethus constantly being evaluated to fulfill the needs of
LKAB.
1.2 Work Description
In 2009, LKAB initiated a five-year research anddevelopment project on deformation measurements
using radar satellite techniques, so-called InSAR
technology. The aim of the project was to investigate
the application of InSAR for measuring mininginduced ground deformations, to possibly reach thesame, or better, measurement precision as in GPS
measurements. The project objectives were to:––Assess the use InSAR technology for LKAB's
purposes  as a replacement and/or complement
to current GPS measurements.
Further develop the InSAR technology for winterconditions in high latitudes, aiming at improving
precision.

–

Conduct a technology transfer to LKAB with thegoal of LKAB being able to produce results(deformation maps) in-house from satellite data.

The project was divided into two major
components: (i) monitoring, and (ii) research andtechnology transfer, as shown in Figure 3. The
monitoring work was carried out by MDA Geospatial
Services, using data from the RADARSAT-2
satellite. MDA also provided technology transferfrom MDA to LKAB. The supplementary research
work involved Cranfield University and Luleå
University of Technology as research partners. The
work was conducted in the form of a doctoral thesis
project. In addition, supplementary graduate student
projects were carried out at both universities.
The overall research objective was to seek toimprove the precision in InSAR-measurements forthe conditions at the Kiruna site, i.e., at high latitudes
and with snow cover during a large portion of theyear. The research work was monitored through areference- and steering group with representatives
from both universities and from LKAB.

SAR Project

Monitoring
Semi-annual
deformation maps

Technology
Transfer

Software &procedure
training

Basic theory
and research

Supervision(PhD & MSc)

Figure 3: Components of the LKAB InSAR project.

2. MONITORING PROGRAM AND
RESEARCH RESULTS
2.1 Historical Analysis
Initially, a historic analysis of InSAR datacollected over the time period of 1992 to 2009, wasconducted. The data analyzed was from the ERS and
ENVISAT satellites, collected from three separate
tracks in 74 images. The study was aimed atquantifying the historical ground deformation in thevicinity of the Kiruna mine operations.
A total of 30 deformation maps were created.
The recorded deformation pattern was generally as
expected, and with the best results obtained for thewaste rock dump areas, which provided highcoherence between image pairs. The large gaps in thetime series of data, and the (relatively) low number ofusable image pairs precluded an analysis of so-called134

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

"hard targets", or CTM (Coherent Target Monitoring)from these satellites. The work showed, however,that CTM analysis using RADARSAT-2 using acontinuous time series during the reminder of the
project would likely be successful. The existing
infrastructure in the town of Kiruna and the industrial
area would provide excellent sources of persistent
scatterers year round. Thus, data from 2008 and 2009
from RADARSAT-2 were included in the firstdeliverable from the monitoring program.

Satellite data is collected for different beammodes, with different incident and aspect angles.
Early on, it was found that accuracy in the northsouth direction was not satisfactory, primarily due tothe polar orbit of (all) satellites (traveling in a nearly
north/south orientation). Thus, "line-of-sight",
measurements and decompositions into east-west andvertical deformations were more reliable. The final
beam combination used for the larger part of the
project was U6D, U25A, and U70D.

2.2 Monitoring Program
Monitoring of ground deformations was
conducted during the period of 2009 to 2014, by
MDA Geospatial Services, Inc. Data was obtained
from the RADARSAT-2 satellite, with a return
period of 24 days. The monitoring program involved
using differential InSAR (DInSAR), coherent target
monitoring (CTM), persistent InSAR technique(PSInSAR), and supplementary Corner Reflectors(CR) in areas where there were little or no natural or
artificial backscatters. A total of 60 corner reflectors(two at each installation point) were initially installedin the Kiruna area, with 6 more reflectors added later,
see Figure 4.

2.3 Accuracy Assessment
By
comparingtwo
independent
3D
decompositions, uncertainties in the east/west,
vertical, and north/south deformation motion of CRs
were found to be 2 mm, 14 mm, and 91 mm,
respectively. For the CTM targets, these uncertainties
were found to increase slightly to 4 mm, 17 mm, and
113 mm. Uncertainties are minimized for directions
with a close to orthogonal basis but the north/south
deformation measurement remain poorly constrained.
By considering a 2D decomposition for motionin the east/west (horizontal) and vertical directions,the precision could be further improved, see also
Henschel et al. (2015). For a preferred set of 2D
decompositions (among a large number tested), theuncertainty in the CR measurements was found to beapproximately 2 mm in both the east/west andvertical directions. For the CTM, these uncertainties
increase slightly to 4 mm and 3 mm in the east/west
and vertical directions respectively.
Thus, by using dual beam coverage, thehorizontal east-west and vertical deformation is
captured with good precision. The method wasapplied to all data for the Kiruna site, with previously
collected data re-analyzed in the final deliverable.

Figure 4: Corner reflectors (CR; see inset) installed in the
Kiruna area.

2.4 Monitoring Data
The data were compiled, analyzed andinterpreted, and results then delivered to LKAB every
six months, covering the time period from November
2009 to October 2014. The deliverables included: (i)RADARSAT-2 imagery for each beam mode used,(ii) conventional deformation maps, and (iii) timeseries profiles of individual point targets (including
both CR and CTM). Continuous improvements weremade for the deliverables during the project.
The CTM results were based on 250,000 points(between the individual beams), and the data wasthen subsampled to 25 x 25 m cells before the beamcombinations were performed. The collocation ofavailable points in each beam resulted in a total of
23,850 points for the motion estimation.
The delivered deformation maps were used toassess overall trends in the data. Moreover, timeseries plots were created for selected CTM points that135

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

were deemed of particular interest for LKAB, andthus subject to more detailed interpretation.
2.5 Comparison with GPS Data
An example of a time series plot for CR targets
is shown in Figure 5. Ground deformations from GPS
measurements are plotted for comparison, also for theE-W deformation. The GPS data are accumulated
deformations from a starting date as close as possible
to the start data of the InSAR measurements. The
precision in the GPS measurements has been
estimated to 7 mm in the horizontal direction(through a repeatability test).
These examples indicate that both the trends andmagnitudes of ground deformation are similar for the
InSAR and GPS measurements, which lend somereliability to the InSAR data. Additional work should,
nevertheless, be undertaken to confirm these findingsfor other areas and other CRs.

deformation measurements, the so-called "small
baseline subset" (SBS) technique was also used. With
this technique, different subsets of interferograms arelinked together to extract the complete deformation
time series. Two sets of SBS techniques were
employed  one in which all interferograms wereused, and one in which only interferograms with ahigh average coherence (threshold set at 0.25) were
utilized, essentially meaning that several winterimage pairs were discarded.
An example of the results is shown in Figure 6.
The difference between GPS and InSAR CR data islarge for two of the applied analysis techniques,
whereas a relatively good agreement is found whenthe InSAR data was extracted using only highaverage coherence interferograms (CR-InSARSBAS-COR). The mean error compared to the GPS
measurements is 1.1 mm with 10.7 mm standard
deviation, and the correlation coefficient is 0.88.

0.00
InSAR CR03

-0.05

GPS C8E-W Deformation (m)

-0.10
-0.15
-0.20
-0.25
-0.30
-0.35
-0.40
-0.45

-0.50
2009-09-03 2010-09-03 2011-09-03 2012-09-02 2013-09-02 2014-09-02
Date

0.00
-0.02

E-W Deformation (m)

-0.04
-0.06

Figure 6: Time series plots of double difference CRInSAR
measurements (CR6) and double difference Static-GPS
measurements (L10) for different InSAR analysis
techniques.

-0.08
-0.10
-0.12

InSAR CR08

GPS M8-0.14
2010-03-23 2011-03-23 2012-03-22 2013-03-22 2014-03-22
Date

Figure 5: Cumulative deformation measurement for CR03
and CR08, compared with GPS data from nearby points C8
and M8, in the east-west direction.

A different methodology was used by
Wickramanayake et al. (2015), in which the GPSdata were first re-calculated to line-of-sight direction
to enable more accurate comparison. All calculations
were done for the U6D beam model. In addition tousing sequential interferograms (interferograms thathave the shortest temporal baseline) to extract the CR

The large difference between the CR-InSARSBAS-COR and CR-InSAR-SBAS in Figure 6 may
be because the InSAR winter measurements (due tosnow) appear to have larger phase errors than thesummer measurements. This additional phase can be
reduced by using only those interferograms withhigher average spatial coherence values and the
SBAS techniques, as described above. There is,however, the risk of losing entire sets ofinterferograms related to a particular (winter) image
when interferograms with low coherence areremoved. It should also be pointed out that errors
resulting from the ground snow layer and from the136

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

snow layer on top of the corner reflector shield havenot been separated. The next step would be toquantify the error contribution from each component.
2.6 Strain Calculations
An important potential application of the InSAR
measurements is the ability to assess the location ofwhere the environmental criterion (cf. Section 1.1) issatisfied. The same methodology as used for GPS
measurements was applied to the InSAR data, using
CR measurements. An example of the calculated
strains is shown in Figure 7, together with thecorresponding location of the strain limit calculated
from GPS measurements.
The agreement between InSAR-derived strains
and GPS-derived strains is reasonably good, with the
InSAR data generally slightly larger strains. It
appears likely that InSAR data can be used forassessing the "environmental criterion". However,more work is required to come up with a robust
method for strain calculation, possibly also requiring
additional CRs and/or including CTM targets toincrease coverage.
2.7 Seasonal Coherence Variation
In the work by Wickramanayake et al. (2016),
the degree of spatial coherence was studied to
identify the seasonal variation in interferograms. A
total of 561 differential interferograms were used,
and arranged in three different ways for the analysis,
with the first including common masterinterferograms (with the summer master image), thesecond including the sequential interferograms thathave the shortest temporal baseline, and the third
accounting for all possible combinations of theinterferograms (full network of interferograms).
As expected, seasonal variation in spatial
coherence due to the ground snow layer in winter was
found. Only less than 50% of the available
RADARSAT-2 images were suitable for DInSAR
deformation measurements. However, there wassignificant summer-to-summer coherence for someregions even over the course of a few years. The
master image should thus be a summer image toachieve high coherence. Even with a longer temporalbaseline, the summer-to-summer interferograms forthe barren and flat waste rock areas provide almost
the same coherence. Forest areas, on the other hand,lose coherence with an increase in the temporalbaseline and do not regain it seasonally. A next stepwould be to study the seasonal variation in coherencein natural or man-made targets/persistent scatterers.
2.8 Technology Transfer
The purpose of the technology transfer was tobuild up knowledge and know-how within LKAB
regarding InSAR-technology. MDA provided LKAB
with high-level training for a larger group and moretargeted training to a smaller group, including
software and hardware tools to be able produce
deformation maps independently.

137

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 7: Spatial distribution of CR strain measurements in the east-west direction for the period of March 2010 to April
2014, with green representing low strain and red representing high strain. The environmental criterion limit determined from GPS
measurements, corresponding to 0.3 % strain, is shown with a red line.

An "in-house" technology transfer was also
accomplished, through regular meetings and training
sessions on InSAR processing with LKAB staff.
During the course of the project, it became clear thatthe goal of producing deformation maps
independently by LKAB was probably too ambitious.
However, the technology transfer ensured that LKAB
staff acquired a deeper understanding on InSAR
technology, and thus can critically assess results andassumptions made in the analysis.

3. DISCUSSION AND CONCLUSIONSInSAR-technology allows measurements overlarge areas, with fewer measurement hubs (CRs)compared to GPS measurements. DInSAR
measurements providing deformation maps worked
well for identifying trends and patterns in grounddeformations. The technique is, however, dependent
on achieving high coherence between image pairs,
which has proven challenging at the Kiruna site.
Measurements on Corner Reflectors (CR) and"hard targets" (CTM) provided high-precision data
for specific points. The CTM measurements are
particularly appealing since they do not require
installation of reflectors, and were found to work
very well in urban environments. A potential problem
is the ambiguous phase unwrapping that can arise incases where deformations between successive
satellite passes are large. The project work has shownthat by including a large number of measurement
points in the analysis, it is possible to reduce theeffects of this potential error source, although it
cannot be completely eliminated. However, in areas
where infrastructure is, or is planned to be removed,
due to mining effects, CTM coverage is poor andmust likely be supplemented with CR installations.
While the east-west and vertical deformation
components can be satisfactorily analyzed, resolving
deformations in the north-south direction with anacceptable accuracy was not possible. The improved
accuracy obtained through a dual beam acquisition ispromising for future work, implying that higher
precision can be obtained with fewer beam modes,
for east-west and vertical deformations.
Comparison between GPS and InSAR data areimportant since this provides a tool to "ground truth"
the InSAR data at this site. This constitutes animportant next stage to further the application of
InSAR for the specific tasks of interest for LKAB,
particularly for determining the limits to theenvironmental criterion for allowable deformations.

Coherence effects and whether e.g., certain
winter images should be discarded or not from theanalysis also warrant further work. A robust
methodology must be in place for the data analysis,
without risking the loss of important information.

4. RECOMMENDATIONS
The requirements on the possible future use of
InSAR in Kiruna should be further defined, including
what monitoring and interpretation techniques thatare most applicable for these conditions. More workon comparing CR/CTM InSAR data with GPS
measurement data should be conducted, to further"ground truth" the InSAR data. The long series ofGPS data at Kiruna provide excellent opportunities to"calibrate" InSAR results and minimize e.g., phaseand unwrapping errors. This step is also important todetermine what methodology should be used for
InSAR processing and to what extent images withlow coherence can be discarded.
Additional Corner Reflectors should be installed
in areas with poor CTM coverage and poor backscatter. These are relatively inexpensive and would
supplement the DInSAR and CTM data. The locationof CRs should be based on the results from GPSmeasurements, and a geomechanical perspective, toincrease understanding of the mining-induced grounddeformations. Additional CRs would also help in
better delineating the location of the environmental
criterion strain limit from InSAR data.

5. ACKNOWLEDGEMENTS
The work presented in this paper has been fully
funded by LKAB. The authors would like to thank
LKAB for permission to publish this paper. We
would also like to thank Jimmy Töyrä and Carlos
Quinteiro of LKAB for paper review; Wendy
Branson (project leader) and Brad Lehrbass of MDA
Geospatial Services for excellent cooperation; Stefan
Buehler and Tore Lindgren of Luleå University ofTechnology for academic supervision; Dr. Priya
Fernando of EADS Astrium for project support; andBo Fjällborg and Anders Berg of LKAB.

6. REFERENCES
Henschel, M., Dudley, J., Lehrbass, B., Sato, S.
and Stöckel, B-M. (2015). Monitoring slope
movements from space with Robust Accuracy
Assessment. In Proc. Slope Stability 2015, CapeTown, October 12-14, The Southern African Instituteof Mining and Metallurgy, pp. 151-160.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Wickramanayake, A.A.B, Mahapatra, P.,
Buehler, S.A., Ekman, J., Hobbs, S. and Mendrok, J.
(2015). Comparison between Static-GPS and cornerreflector InSAR (CR-InSAR) measurements at a highlatitude site. Submitted for publication.
Wickramanayake, A.A.B, Henschel, M.D.,
Hobbs, S., Buehler, S.A., Ekman, J. and Lehrbass, B.
(2016). Seasonal variation of coherence in SARinterferograms in Kiruna, Northern Sweden.
International Journal of Remote Sensing, 37:2, pp.
370-387, DOI: 10.1080/01431161.2014.915435.

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ISMS 2016

Paper No. 210

Modelling the impact of particle flow on rigid structures: experimental and numericalinvestigations
M.A. Meguida, Ge Gaob, M.M. Abouelkairc and M.Z. AbdelrahmancaAssociate Professor, Civil Engineering and Applied Mechanics, McGill University, Montreal, Canada, H3A 0C3
Graduate student, Civil Engineering and Applied Mechanics, McGill University, Montreal, Canada, H3A 0C3
c
Undergraduate Research Trainee, Civil Engineering and Applied Mechanics, McGill University, Montreal, Canada, H3A 0C3b

ABSTRACT
Gravity-driven debris flow of granular particles down an inclined slope is a problem of growing concern inmountainous regions and poses a significant risk to people, roads, and other infrastructure. Different aspects of the
problem have been previously investigated using physical modelling and numerical analysis. However, three
dimensional pressure distribution on a barrier wall resulting from debris flow over a rough slope is scarce in theliterature. In this study, a series of experiments are conducted to track the movement of granular particles down aslope and measure the impact pressure imposed by the flowing particles on a nearby vertical wall. The particles are
released from a container located at the top of the slope and the velocity profiles are recorded using marked pebbles
and a high-speed camera. The effect of the debris volume, slope angle, and distance to the wall on the velocity
profiles and impact forces are investigated. Validated using the experimental results, discrete element simulations
are performed using PFC3D to evaluate the effect of particle sizes on the flow characteristics and final impact
pressure on the structure. Analysis showed that impact energy is highly affected by the slope inclination, particle
velocity, and runout distance.

1. INTRODUCTION
The numerical modelling of granular mass
movement under the influence of gravity (e.g. debris
flows, avalanches, etc.) has received significant
research attention over the past decade. Various
methods have been used to investigate the flow-likemass runout behaviour including finite element
analysis (Crosta et al., 2002; 2003) and discontinuous
deformation analysis (DDA) (Wu, 2010; 2011). The
DDA method represents debris flow using sliding
blocks and therefore, this method may not be suitable
to model the rapid movement of loose particles.
Discrete element method (DEM) was first
proposed by Cundall and Strack (1979) and because
the method naturally takes discontinuity into account,it has been successfully used to simulate debris flow
problems (Li et al., 2012; Liu and Koyi, 2013; Zhao
et al., 2015). However, very few studies focused on
the three-dimensional analysis of gravel movement
over a rough inclined surface considering the
dynamic impact of the moving particles on nearby
structures. McDowell et al. (2011) and Li et al.
(2012) studied the dynamic behaviour of flowing
particles using different sizes of four-ball clumps
validated using velocity profiles measured in thelaboratory. Lo et al. (2010) decomposed fluctuating
particle flow velocity filed on rough inclines into
best-fit and fluctuating components using three-*Corresponding author – email: mohamed.meguid@mcgill.ca

dimensional DEM. These studies provided someinsight into the effect of surface roughness on the
dynamic behaviour of flowing particles, however, theimpact of particle flow on nearby protective
structures is yet to be fully understood.
In this study, an experimental investigation isconducted to understand the mechanics of debris flow
over rough inclines in a controlled laboratoryenvironment. High-speed camera and tactile pressure
sensors are used to track particle movement andmeasure the impact force on a barrier wall,
respectively. Discrete element analysis is also
performed using walls and spheres to model thelaboratory experiment for three different slope
angles. Preliminary results are presented andconclusions are made regarding the recorded velocity
profile for each slope inclination and the associateddisplacements as well as stress distribution resulting
from the impact of particles on the vertical wall.
2.

EXPERIMENTAL PROGRAM

The experiments were performed using river
pebbles with an average particle diameter of 5 cm, as
shown in Figure 1.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

(26 mmdiameter coin)

Figure 1: The river pebbles used in the experiments.

The surface of the slope and the horizontal
runout section are designed and built using smoothaluminum plates, lined with perforated sheets tocreate a bumpy (rough) surface. A stiff rubber sheetof 2 mm in thickness is used to simulate the roughsurface. The sheet is punched with round holes 5 cm
in diameter arranged in a hexagonal pattern at 8 cm
center spacing (See Figure 2).

Figure2:Particle

size

distribution.

Figure 3: Experimental setup.

2.1 Test Setup
The slope, 1.82 m long and 0.62 m wide has the
0.03 m high Perspex sides so that all activity within it
is visible. The slope inclination can be adjusted tocover a range of angles between 0 and 90º to thehorizontal. The setup is equipped with a Perspex
release box with a hinged door at the top of the slope.
During the test, the river pebbles are released throughthe hinged door and allowed to travel freely down theslope and runout onto a flat base. A high-speed
camera (Canon T3i) that can take 30 frames per
second at a maximum resolution of 1280 x 720 pixels
was used to track the position of the marked pebble.
Two tactile sensing pads with pressure capacityof 20 psi were fixed at the particle landing locationand similar pads were fixed directly on the verticalwall. These pads were connected to a data acquisition
system to monitor the impact forces on the ground(horizontal plane) and on the wall (vertical plane) asa result particle movement. The layout of thesesensors can be seen in Figure 3.
3.

DEM SIMULATIONThe Discrete element method is known toconsider the interaction among distinct particles attheir contact points. It is generally a dynamic processthat reaches static equilibrium when the internal andexternal forces are balanced (Tran et al., 2014). The
numerical simulations are performed in this study
using the discrete element program, PFC3D. A
detailed description of the code can be found in therelevant manual (ICG, 2014).
The numerical simulations are carried out as
depicted in Figure 4. A discrete element sample thatconsists of 53 spherical particles is generated tofollow the particle size distribution of the material
used in the experiment, as shown in Figure 2.
Spherical particles are used in this preliminary
analysis to reduce computational cost and at the sametime capture the mechanical response associated withparticle flow. The micromechanical parameters usedin the analysis are listed in the Table 1.
The sloped section is simulated using bonded
particles arranged in a hexagonal pattern with anaverage particle diameter of 5.5 cm (see Figure 2).
This procedure captures to a reasonable extent thecharacteristics of the perforated sheet used in theexperiment, and reproduces a bumpy surface thatallows for the rolling resistance to be automaticallyconsidered.
Once the generated particles have reached anequilibrium state in the release box, particle flow is
initiated by removing the wall facets of the releasebox allowing the particles to freely flow down theslope.

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A total of 12 particle flow simulations are
performed in this study using various slope
inclination angles (30º, 45º and 60º) and wall location
with respect to the toe of the slope (0 cm, 25 cm, 40
cm, and 60 cm).
The particle friction coefficient was determinedusing the repose angle test. It is worth noting thatfriction coefficients that range from 0.37 to 0.5 wereused by other authors (e.g. The reference paper
written by the McDowell et al., 2011 & Lo et al.,2010).

θ = 45 º, x = 1.3 m, y = 1.3 m

Table 1: Particle properties used in DEM tests.
Property
Unit
Value
Contact modelLinear (no-tension)
Densitykg/m³
2620
Effective Modulus
(Pa)
20E8
Stiffness ratio
1.5
Friction coefficient
0.45
Viscous damping ratio
Normal
0.5
Shear
0.5
Number of particles
53

θ = 60 º, x = 0.9 m, y = 1.6 m
Figure 4: DEM setups of particle flow for different
inclination angles and separation distance from the wall.

4. RESULTS

θ = 30 º, x = 1.6 m, y = 0.9 m

4.1 Particle mobility
The recorded and calculated results for the three
investigated slope inclination angles (30º, 45º and60º) are summarized in this section.
Displacement profiles with time are shown in
Figure 5. Results reveal that for a given elapsed timefrom the beginning of the test, particle displacement
increased with the increase in slope inclination. For
example, when the elapsed time reached 0.6 sec.
particles had moved 0.7 m, 1.2 m, and 1.5 m forslope angles 30º, 45º, and 60º, respectively. In allinvestigated cases, the rate of change in displacement
was found to increase up to a maximum maintained
value. The flowing particles started to slow down as
they approach the toe of the slope. Calculated
displacements are generally found to be in good
agreement with the measured values for different
inclination angles.
The velocity profiles obtained from theexperiments and the DEM simulations are presented
in Figure 6. Results show that, the maximum
measured velocity increased from 3 m/s to 6 m/s
when the slope angle increased from 30° to 60°. The

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

time required to reach the maximum velocity
decreased from about 0.7 seconds to 0.3 seconds
when the slope angle increased from 30° to 60°. It
was also found that the maximum calculated velocity
is slightly smaller compared with the measured one,particularly for a slope angle of 60°. On the other
hand, particle acceleration (defined by the slope ofthe velocity-time relationship) calculated using DE
analysis is slightly higher compared with the values
measured in the experiments. In addition, asignificant deceleration response was calculated (seeFigure 6) after the maximum velocity was reached.
The difference in acceleration responses between thecalculated and measured values can be attributed tothe simplified spherical shaped particles used in theanalysis.

Figure 5: Displacement profiles for different inclination
angles with the wall located at the toe of the slope.

Figure 7: Impact stress onto the vertical wall considering
the different conditions.

Figure 7 shows the relationship between the
maximum impact stress measured on the vertical walland the inclination angle of the slope. It can be seenthat the location of the vertical wall has a significant
impact on the impact pressure. The largest impact
pressure was reached at an inclination of 60º and wasfound to be approximately 35% higher than thatmeasured for 30º and 45º slope angles. Figure 6 also
shows that, at wall distances of 25 cm and 40 cm,
higher impact pressure was recorded for slope angleof 45º as compared to those measured at angles of
60º. It is also evident from the results that with theincrease in vertical wall distance from the toe of theslope, the impact pressure for inclination angle of60º, significantly dropped to a very small value. Thiscan be attributed to the fast dissipation of energy inthe moving particles for such a steep slope.

Figure 6: Velocity profiles for different inclination angles
with wall located at the toe of the slope.
Figure 8: Contour of impact pressure on the vertical wallconsidering different inclination angles.

4.2 Impact pressure onto the vertical wall
Figure 8 illustrates contours of the impact
pressure on the vertical wall when placed right at thetoe of the slope. It is apparent that the distribution of143

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

impact pressure on the vertical wall was irregular as
observed in the experiments and as confirmed using
the numerical simulations. It has been found that for
the investigated slope inclination angles, thecalculated pressure was consistently larger than thatmeasured in the experiments. Additional numericalsimulations are needed to investigate the role ofparticle shape on particle movement pattern and theimpact forces on the barrier wall.
5.

DISCUSSION
The above results suggest that a simplified DEM
simulation using spherical shaped particles was able
to capture some of the important features of particle
flow on different inclined slopes. Reasonableagreement was found between the measured andcalculated particle velocities as well as the impact
pressure on a vertical wall located near toe of theslope. The numerical simulation provided slightly
higher impact pressure in most of the investigatedcases as compared to those measured in theexperiments with a difference of about 10%.
The maximum velocity calculated from theDEM analysis was found to be slightly higher thanthe measured value. It was also found that observed
pebble movement during the experiments is sensitive
to the particle geometry. Further analyses will beneeded to explore the role of particle geometry on the
micro-scale response and the sensitivity of thesolution to the contact model used in the DEM
simulations.
6.

SUMMARY AND CONCLUSIONS
Laboratory experiments were conducted toinvestigate particle flow on a rough incline for threedifferent slope angles. Particle velocity anddisplacement patterns are measured and the results
are used to validate a discrete element model. Impact
pressure induced by the flowing particles on a
vertical wall located at some distance from the toe isalso measured. The suitability of discrete element
methods to realistically simulate the observed
behaviour is evaluated. Despite the complexity ofparticle flow behaviour observed in each test, DEM
was able to reasonably produce a response that is
consistent with that found in the experiments. The
model was to some extent able to capture theinteraction between particles and the perforated sheet
as well as the vertical wall where particle flow isdominated by coupled sliding and rolling movement.
7.

ACKNOWLEDGEMENT
This research is supported by the Natural
Sciences and Engineering Research Council of
Canada (NSERC) under Grant No. 311971-11.

8.

REFERENCES
Crosta, G., Imposimato, S., and Roddeman, D.
(2002). Numerical modelling of large landslide
stability and rouout, EGS 27th General Assembly,
Geophysical Research Abstracts, European
Geophysicalal Society, 4, EGS02-A-0224.
Crosta.G., Imposimato, S., and Roddeman,D.
(2003). Numerical modelling of large landslides
stability and runout. Natural hazards and earth systemsciences 3, pp. 523-538.
Cundall, P. A. & Strack, O. D.L. (1979). A
discrete numerical model for granular assemblies.
Géotechnique 29, No.1, pp. 47-65.
Giani, G. P., Giacomini, A. , Migliazza, M. , andSegalini,A. (2004) Experimental and theoreticalstudies to improve rock fall analysis and protection
work design. Rock Mech. Rock Engng. 37(5), pp.
369-389.
ICG (Itasca Consulting Group,Inc.) (2014)
PFC3D, v5.0 Minneapolis, MN:ICG.
Jiang, J.C., Kazuyoshi, Y., and Takuo, Y. (2008).
Identification of DEM parameters for Rockfall
Simulation Analysis. Chinese Journal of RockMechanics and Engineering. 12, pp. 2418–13
Li. H., McDowell, G.R., and Lowndes, I.S.
(2012). A laboratory investigation and discreteelement modelling of rock flow in a chute. Powder
Technology 229, pp.199-205
Liu, Z.N. and Koyi, H.A. (2013). Kinematics andinternal deformation of granular slopes: insights fromdiscrete element modelling. Landlisdes 10, pp.129160.
Lo, C.Y., Bolton, M.D., and Cheng, Y.P. (2010).
“Velocity fields of granular flows down a roughincline: a DEM investigation.” Granular Matter, 12,477 – 482.
McDowell, G.R., Li, H. and Lowndes, I. S.
(2011). The importance of particle shape in discreteelement modelling of paticle flow in a chute.
Géotechnique Letters 1, pp. 59-64.
Tran, V.D.H., Meguid, M.A., Chouinard, L.E.
(2014). Discrete element and experiemntal
investigations of the earth pressure distribution on
cylindrical shafts. Int J.Geomech., 10.1061/(ACSE)
GM.1943-5622.0000277. pp. 80-91.
Wu, H.J. and Chen, C.H. (2011). Application of
DDA to simulate characteristics of Tsaoling landslide.
Computers and Geotechnics 38, pp. 741-750.
Wu, H.J. (2010). Seismic landslide simulations in
discontinuous deformation analysis. Computers andGeotechnics 37, pp. 594-601.
Zhao. T., Utili, S., and Crosta, G. (2015).
Rockslides and impulse wave modelling in the
Vajont Resoivor by DEM-CFD analyses. Rock
Mech. Rock Engng: 1–20. doi:10.1007/s00603-0150731-0.

144

ISMS 2016

Paper No. 207

A versatile model for the evaluation of subsidence hazards above
underground extractionsPeter Cain, Ph.D., P.Eng. a*, Dr. Ing. Karsten Zimmerman ba

Director of Engineering, DMT Geosciences Ltd., Calgary, Alberta, Canada, T2R 0E4

bHead, Expert Body for Ground Movement, DMT GmbH & Co. KG, Essen, Germany

ABSTRACTAll underground extraction – oil, gas, water and minerals – results in subsidence of the surface to some degree.
Subsidence can cause damage to infrastructure – roads, powerlines, gas and oil pipelines, buildings – and to thenatural surface, with the development of cracking, potholes, changes in hydrogeology and destabilization of slopes.
Pre-extraction estimates of the amount of subsidence and the hazards it might produce are difficult to determine withaccuracy, and the most frequent approach is to model the surface movements in response to extraction using
empirically based models.
There are a number of large underground coal mine projects on the drawing board in British Columbia and Alberta
despite the current prolonged episode of reduced coal prices. Fortunately, almost all of these projects target
metallurgical coal, for which windmills, hydro and nuclear “clean” power sources provide no substitute and in fact,
on which they depend for their construction. Each of these projects will have to demonstrate satisfactory mitigationof hazards arising from potential subsidence before they will be allowed to proceed.
DMT Geosciences Ltd of Calgary, AB has recently worked with an underground mine proponent to model
subsidence over an entire mine layout, in native coordinates and for multiple seam extraction, using a proprietaryinfluence function model. Currently calibrated using a best estimate of western coal subsidence characteristics, themodel itself will undergo additional calibration as monitoring data above the actual mine is obtained.
The model itself is fairly easy to use, quick to run and provides results in an easily managed format for graphicaldisplay. As well as mining subsidence, it has in the past been shown to predict surface movements due to oil andwater extraction at depth. For the current project, the results obtained in the initial subsidence prediction phase haveallowed areas of potentially hazardous or damaging surface movements to be determined.
KEYWORDS: subsidence; modelling; surface safety; environmental management

1. INTRODUCTION
North East British Columbia has a long historyof large scale open pit coal mining targeting
metallurgical coal for overseas markets. As in most
coalfields, the easy coal has gone, but there remains
substantial resources of good quality coal accessible
by underground methods. The Wapiti Project, owned
by Canadian Dehua, reported a resource in excess of
1 billion tonnes, and Glencore is proceeding with the
Sukunka Project which has underground resources tobe mined after an initial open pit.
All of these are major projects in an establishedmining area, but they will attract considerably moreenvironmental scrutiny than they might have done in
the past. The environmental issues associated withsurface mines – waste rock disposal, selenium
leaching, dust and habitat destruction – are wellknown to the local regulators. Underground mines,
however, are largely a mystery to them.
Although underground mining has a number ofenvironmental advantages, mitigating many of the*Corresponding author – email : peter.cain@dmt-group.com

disadvantages of surface mines, a significant concern
is the effect of subsidence and the hazards it mightpresent on the surface. This concern has become
apparent during the environmental assessment
process for another major underground coal mining
project in NE BC.
This paper describes methods used to estimate
the surface subsidence, their shortcomings andadvantages, and to present some of the results that
demonstrate how the output can be used to identify
potential areas of surface hazard after undermining.

2. PROPOSED MURRAY RIVER PROJECTThe Murray River Project in the Peace River
Coalfield of British Columbia is joint venture
between three Chinese companies, operated by HD
Mining International Ltd of Vancouver, BC. Figure 1
shows the locations of the coalfields of British
Columbia. Figure 2 shows the principal property
owners within the Peace River Coalfield.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 1: Coalfields of British Columbia.

Figure 3: Typical Strata Column at the Murray River
Property.
The proposed underground mine extends about
10 km along strike (NNW-SSE) and about 5 km to
the dip. There are five target seams, identified as D
through J from the top down (Table 1), with a total
extraction of about 25 m, all of it from superimposed
longwalls, many of them using the longwall top coalcaving method. The proposed layout is shown in
Figure 4.
Table 1: Target Coal Seams.
Thickness
Lithology

Figure 2: Principal Property Holders in the Peace River
Coal Field.

The Murray River Project property lies centrally
in the Peace River Coalfield between the historic
open pit properties of Quintette and Bullmoose.
Anglo American and Walker Energy have also
operated open pit mines in the immediate area, now
mothballed due to low prices.
The coal is found in the Gates Formation of theUpper Cretaceous period and sits at depths ofbetween 500 m and 1300 m (Figure 3).

70-80 mMudstone, siltstone and coal.
The lower part of the group is athick layer siltstone. Contains
A, B and C seams, none ofwhich are mineable.

> 55 mSandy mudstone, mudstone andcoal, including three minablecoal seams:
D; 0.4 – 5.71 m, 2.12 m avg.
E; 0.05 – 6.52 m, 2.32 m avg.
F; 0.67 – 7.51 m, 3.46 m avg.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

>40 m

Mudstone, sandy mudstone andcoal, including two workableseams:
G/I; 0.4 – 3.52 m, 1.6 m avg.
J; 2.6 – 9.2 m, 6.19 m avg.

100 m

The lithology consists of thicklayer sandstone, included withthin-layer mudstone. Mainly
medium sandstone, followed by
gritstone, included with
mudstone.

Figure 4: Layout of the Proposed Mine Panels
showing planned and current infrastructure.
The mine extends beneath boreal forest as wellas oil and gas exploration and production
infrastructure – pipelines, well-heads and compressor
stations. The terrain itself is a valued environmental
component, as it is home to a number of species
including caribou and some valued fish species.
Disturbance to rivers and streams including thepotential for slope instability in some of the deeply
incised valleys, is a major concern.
Almost the entire oil and gas industry
infrastructure is protected in the mine plan by pillars
left in the coal underground. However, service roads
and power lines criss-cross the area and the effects ofsubsidence must be assessed

3. SUBSIDENCE ASSESSMENT
The project proponents were asked to provide anassessment of the effects of subsidence on surface
features which included some deeply incised rivervalleys, and specifically on valued environmental
components. Regulators were concerned that large
amounts of subsidence could occur as a result ofmultiple superimposed panels with extracted
thicknesses of up to 25 m and that subsidence might

result in stream reversals, wetland destruction andslope instability in sensitive areas.
The initial subsidence estimates were made by
consultants with experience of subsidence estimation
in western North America. The estimates were madeusing a proprietary influence function model.
Because there was no local data to use to calibrate themodel, subsidence parameters known to provide
reasonably accurate estimates of subsidence undersimilar conditions in the western United States wereused.
The subsidence estimation model used required
the translation of the panel coordinates into a
Cartesian coordinate system with the panels parallel
to either the x- or y-axis and the size of the model
limited subsidence estimation to a single mining
district, although all five seam extractions weremodelled. The simplification of the panel layouts
resulted in the elimination of the pillars between thepanels.
Although there was no concern over the resulting
estimates, the model used for the initial assessment
was limited to 3,000 data points which results ineither long distances between estimation points or thesegmentation of the mine plan. It was thus not able toprovide coverage of the entire mine area without
segmenting the mine layout and converting
coordinates, and analysis of linear features was thus
made very difficult.
On reviewing the initial set of results, theregulators asked for a mine-wide subsidence estimate
as well as subsidence estimates along the courses ofthe major streams. The additional information
required from the environmental reviewers dictated achange in approach to the subsidence modelling. The
modelling software originally selected would require
too much time and post processing and anotheroption was sought.

4. SPS 4D SOFTWARE
DMT’s SPS 4D subsidence prediction software
based on the stochastic prediction model of
Sroka (1978). The software is designed to predict
multi-panel and multi-seam subsidence influences
both on objects at surface and on objects within therock mass. The software is especially suited for
calculating subsidence effects of inclined seams andinclined overburden strata with respect tounsymmetrical rock mass behaviour. In addition topredicting subsidence by longwall coal mining, thesoftware has been successfully used to estimate
subsidence caused by oil, gas and water production.
4.1 Theory
The process of subsidence starts with theextraction of material (oil, gas, water or coal and147

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

other minerals) from underground. The shape of theoccurring subsidence trough depends on various,
often hardly known parameters. For a model
description of mining effects a relation between cause(material extraction) and effect (ground movements)
is necessary. This relation can be set up by atransformation function describing the rock mass
behaviour (Figure 5a).
The main influences in the case of longwall coalmining are the thickness of the mined seam, the depthof the mining works, the inclination of the seam andthe dimensions and shape of the panel. Also
important is a time factor, describing the delay intime between the extracted coal volume and theoccurrence of the corresponding subsidence trough.
However in this study only final subsidence values
were sought, so the time factor model was not
implemented.
For calculating the subsidence of a longwall
operation with the computer program the mined area
can be divided into small mining elements (Figure
5b).
The subsidence potential of one mining element
is calculated within the program by using theGaussian distribution as influence function. Usingsuper-positioning of all mining elements, thesoftware is able to calculate the final subsidence
trough induced by mining of the whole longwall(Figure 5c). Consequentially it is also possible toestimate subsidence in every stage of face advance.
Final surface subsidence induced by mining asingle mining element can be calculated using
equation 1.
𝑠(𝑥, 𝑦, 𝑧) =𝑘 𝑎𝑉𝑑2
∙ 𝑒𝑥𝑝 �−𝑘 2 �
2
𝑅
𝜋 𝑅

(1)

where: 𝑘 = −ln (0,01) , the fixed parameterization
value of Ruhrkohle method
𝑎 = mining factor (𝑎 ∈ [0,1]) , volume ofsubsidence trough divided by extracted volume
𝑉 = volume of mining element depending
on element area and mining height
𝑅 = radius of in�luence, 𝐻 ∙ 𝑐𝑜𝑡𝛾
𝐻 = mining depth𝛾 = angle of influence𝑑 = �(𝑥 − 𝑥𝐴 )2 + (𝑦 − 𝑦𝐴 )2 distance between
mining element �𝑥𝐴, 𝑦𝐴, � and calculation point (𝑥, 𝑦)
The parameter k is necessary because theGaussian function used to determine verticalsubsidence is asymptotic. The value of k forces avertical subsidence value of zero at the edge of thesubsidence trough although it reduces the estimate of
subsidence very slightly at the maximum subsidence
point.

The volume and location of every mining
element is known and depends on the specific layout
and dimension of the longwall panel. The only
parameters that depend on the mining site specificgeology characters are the mining factor and angle ofinfluence. These parameters have to be determinedfrom in-situ observations or estimated based on
similar locations. In this case, the initial modelling
used parameters selected by consultants withexperience in similar conditions, and these values
were used in the SPS 4D computations.
The derivation of equation 1 yields the tilt in xand y-direction of the calculation point.
𝑇𝑥 (𝑥, 𝑦, 𝑧) =𝑇𝑦 (𝑥, 𝑦, 𝑧) =𝜕𝑆(𝑥, 𝑦, 𝑧)𝜕𝑥𝜕
𝑆(𝑥, 𝑦, 𝑧)
𝜕𝑦

(2)
(3)

When calculating horizontal displacement it isassumed that horizontal displacement is proportional
to tilt. In this way it is possible to calculate grounddeformations. Equations 4 to 6 show the calculationof horizontal displacement in x- and y-direction andfor a point at surface.
Ux = −B ∙ Tx (x, y, z)

Uy = −B ∙ Ty (x, y, z)
with: B =

R

√2k

(4)

(5)

(6)

Field measurements of subsidence in North
America and elsewhere show that maximum tilt does
not occur directly above the edge of the panel but isinstead located in a distance d towards the minedpanel (the so-called edge effect). The edge effect is
integrated in the model by applying a specific roof
convergence model which is parameterized by valued – the edge effect distance.
For full details of the model theory anddevelopment, refer to Zimmermann (2011).
4.2 Implementation
In significant contrast to the modelling software
originally selected, SPS 4D applies a finite element
based processing approach, which enables nonrectangular panel processing directly using the native
coordinate system. This makes a comprehensive
prediction for a multi-panel and multi-seam minelayout, presented in this article, very easy. For
example, the initial software deployed could only
process 3,000 points of data, so the larger the area
being modeled, the lower the resolution of the output
data. SPS 4D allowed up to 100,000 data points, innative coordinates, and has recently been expanded to400,000 points. If a data point spacing of 1/20th of thedepth is followed (NCB, 1975), this would allow
single pass subsidence estimation of a 1,000 m deep148

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 5: Illustration of the subsidence modelling principals and method (after Sroka et al, 1988 andZimmermann, 2011).

coal mine over an area of about 900 km2 This islarge enough for most practical purposes.
SPS 4D is implemented in conjunction with aproprietary data manipulation package, SurferTM.
Using a front-end and back end processing package
already on the market greatly simplified
implementation. SurferTM is relatively inexpensive,
easy to learn and widely used, making it an ideal
partner in this process.
Outline coordinates of 84 individual longwall
panels in 5 seams at depths ranging from 500 to
1400 m were entered in BC Provincial gridcoordinates. Panel outlines, depths and seam
thicknesses are entered as individual text files. The
seam model can be displayed before processing
begins (Figure 6).

Figure 6: Illustration of model parameters; Left – 3D plotof surface and mine panels with depth referring to zerolevel [m], Right – Plan plot of seam thickness [m].

4.3 Calibration
Subsidence models are “calibrated” to produce
estimates which match, as closely as possible, thesubsidence experience of the area by adjusting threemajor model parameters: the influence angle, thesubsidence or mining factor and the edge effectdistance. The most accurate estimates fromsubsidence models are obtained when there issufficient data from actual subsidence profiles toestimate the values of these parameters. Even then,parameters are chosen which err on the conservativeside and model estimates tend to overpredict.
When no site specific in-situ data is available,
data from sites with similar structure, rock properties
and conditions are used to determine initial parametervalues for initial subsidence estimates while therequired data is collected and aggregated into themodel to improve the accuracy of estimates.
There is no observed data for the Murray River
coalfield. The original subsidence estimates usedmodel parameters were based on past experience andknowledge of subsidence in the western part of the
USA (the closest similar mining conditions for which
subsidence measurements were available). This is acommon approach to subsidence estimation in newmining areas.
The initial model parameters were reviewed by
DMT and compared to the very limited subsidence
data available in western Canada. The highpercentage of “hard rock” in the overburden was also

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

considered. The parameters used in the initial model
were ultimately accepted as applicable for
implementation in SPS 4D.
There was thus no argument with theassumptions used in the initial model, but it was
important to be able to show the environmental
review panel that the change in model mid-process
was irrelevant. A comparison of the two models
using the same parameters was performed.
Figures 7 and 8 show the subsidence profile
results of the two models after one, two and four
panels extracted. The only significant difference
between the models is the appearance of reduced
subsidence over pillars in the SPS 4D results. The
SPS 4D model could accurately resolve pillars
between panels, whereas the initial model could not,so they were omitted.

Figure 7: Subsidence Profile from the First Model.
0,5
0
-0,5

Subsidence [ft]

-1
-1,5
-2
-2,5
-3

D1101-05

-3,5
-4
-1000

D1101
D1101-02

-500

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Distance from D1105 South Edge [ft]Figure 8: SPS 4D Subsidence Profiles.

The similarity of the results, and the additional
resolution of the DMT model, convinced thereviewers to accept the new model.
Although neither of the models has had thebenefit of observed subsidence data with which tocalibrate it, every effort has been made to use
representative subsidence parameters which will givea conservative estimate of the subsidence effects.
Both the project proponent and the regulators
understand that the results obtained are estimates,

even though they have been designed to err on theconservative side. Both the project proponent and theregulators understand the importance of gathering
accurate subsidence measurements to refine themodel and allow accurate site specific calibration for
future assessments.

5. MODELLINGThe first stage of the model was to obtain adigital elevation model (DEM) of the topography
above the mining area. The DEM was constrained toa distance of 900 m beyond the mining limits to
reduce the number of data points for which
subsidence was to be predicted. Even so, the Lidar
data was too dense to allow timely modelling, so a
subset of the elevations at 15 m northings andeastings was produced. This resulted in slightly lessthan 200,000 data points. The end of mine life
subsidence was subsequently calculated for each ofthese points.
The spacing of the points, 15 m, was acompromise between the accepted “bay length” overwhich strains associated with subsidence areconventionally calculated and the data density
required to properly describe changes in topography.
The“baylength”(distance
betweenmeasurement points) is usually recommended as 0.05
times the depth (NCB, 1975).Any less, andcalculations become too time consuming; any more,
and the strain estimates are affected. The range of
depths of working at Murray River is 500 m to 900
m, resulting in bay lengths of 25 m to 45 m
respectively.
Terrain changes are quite substantial over shortdistances over much of the mine area, and DMT feltthat a 25 m DEM would not be effective, hence the
15 m discretization chosen.
Once the surface DEM had been prepared as asimple x,y,z data file, the mine layout was digitizedin AutoCAD and the coordinates of each of the 84
panels were prepared as another simple data file. At
this point, the data files could have been preparedwith elevations and seam thicknesses for each corner
point, and the software would have interpolated thesevalues across each panel at 10 m intervals. This
interpolation interval is user selectable, but 10 m
seems to produce adequate results.
Instead of interpolating between panel corners,
AutoCAD 3D-polyline files of base of seam elevationand seam thickness were prepared as simple x,y,z
strings. The software accepts these files andinterpolates both depth and thickness more accurately
than if corner points alone were used. By way of
example the base of seam elevations for the
lowermost J seam derived for each panel and150

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

contoured using the integrated “Surfer package, areshown in Figure 9.

Figure 10: Contoured Surface Elevations and the Major
Creek.

Figure 9: Contoured Seam Elevations from Data.

The effect of subsidence on a fish-bearing creek
in the area was of particular interest. To assess
potential hazards, elevations along the creek bed
were interpolated from the GIS system at roughly
5 m intervals, resulting in about 14,000 points.
Once the data sets were completed, the model
was allowed to run.
Total subsidence after
completion of mining was determined for each of theDEM surface points and for each of the M20 Creek
bed data points. Despite the capacity of the model,
the surface DEM exceed the number of points that it
could handle, and the mine layout model wascompleted in two sections, although the model has
subsequently been modified to allow up to 400,000
points to be modelled

Figure 11 shows the contoured total subsidence,
which reaches close to 10 m under shallow, multiple
thick seam workings. This area was identified ashaving potential for hazardous crack or surface
fracture development. Fortunately it is largely
wilderness and the risk to people and infrastructure
was assessed as low.

6. RESULTS
Figure 10 shows the surface elevations contoured
from the DEM subset. The dark line is the creek ofinterest. Towards the east end of the creek it runs
through a deeply incised valley and the stability ofthe slopes was in question.

Figure 11: Contoured Total Subsidence.

Figure 12, showing areas of concentrated tensileand compressive strain, matches the areas of major
subsidence as expected.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

erosion and possible destruction of spawning beds.
Flattening will result in deposition and silting up
potential.

Figure 12: Contoured Strain.

Figure 13 shows a unique feature of the SPS 4D
model, its ability to estimate subsidence along nonlinear features in significant detail. The stream trace
is represented by 14,000 points which, and the results
indicate the areas of greatest potential surface hazard.
This allows the project proponent to plan mitigation
for habitat loss based on a realistic assessment of thephysical requirements. Figure 14 shows the stream
bed profile from which possible flow reversals orchanges to stream bed morphology can be
determined. Steepening will result in increased

Figure 13: Subsidence along the Stream Bed.

Figure 14: Subsidence along the Stream Bed Illustrated as a Stream Bed Profile.

7. CONCLUSIONS

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The modelling work demonstrated firstly that the
SPS 4D model could produce results in North
America similar to North American models. In areas
where large amounts of subsidence data exists thisisn’t a problem – models can be calibrated to local
conditions. However, in a new mining field with noexisting data it is important to be able to have adegree of confidence that the results are meaningful.
Secondly, the formulation of the model and theuse of a proprietary front and back end made data
input and visualization and more importantly, results
visualization, very easy. The identification of zones
of significant subsidence and the potential for surface
hazards, and the effects of subsidence on stream
courses and wetlands was made significantly easierusing the proprietary visualization software.
The presentation of the results, albeit with anumber of caveats regarding the nature of theestimates and the need for extensive subsidence
monitoring and observation to verify the results andconfirm the mitigation strategies, was successful.
Subsidence estimation is a tricky field. Model
results are only estimates, approximations of theactual result. The only sure way to increase thereliability of the model outputs and hence theassessment of the hazards, is to calibrate the modelwith as much field data as possible. The proponent inthis case has committed to a multi-year Lidar andsurface survey monitoring program to ensure that thesubsidence estimates become increasingly moreaccurate and hence the potential hazards are moreaccurately identified for mitigation.

Lagerstätten unter Berücksichtigung anisotroper
Gebirgseigenschaften, des Durchbauungsgrades unddeszeitlichen
Konvergenzund
Verzögerungsverhaltens
desGebirges;
Abschlussbericht des Forschungsvorhabens” Ha
526/15-1 am Institut für Markscheidewesen;Technische Universität Clausthal (Deutschland),1988 (in German language)
Tandanand, S, and Powell, LR. (1984)“Influence of Lithology on Longwall Mining
Subsidence” Mining Engineering, December pp
1666-1670.
Zimmermann, K and Fritschen, R. (2007) “Study
about the dynamic influences of longwall mining in
the US on surface objects” Proceedings of the 26th
International Conference on Ground Control in
Mining, Morgantown, WV., 2007
Zimmermann, K. (2011) “Prediction andAnalysis of Dynamic Ground Movements induced by
Near-Surface Coal Mining in the USA” PhD Thesis,
University of Freiberg, 2011 (in German language)

8. ACKNOWLEDGEMENTS
The authors would like to acknowledge thesupport of HD Mining International Ltd., of
Vancouver, BC, for whom this work was undertaken
and who have supported the presentation of theresults at this conference.
The views expressed are those of the authors
alone and may not represent the views of HD Mining
International or their employers.

9. REFERENCES
NCB (1975) “Subsidence Engineers Handbook”
National Coal Board Production Department,
London, UK, 1975
Shadbolt, C. (1987) “A Study of the Effects ofGeology on Mining Subsidence in the East Pennine
Coalfield” PhD Thesis, University of Nottingham,
March, 1987.
Sroka, A. (1978) “Teoria S. Knothego w ujęciu
czasoprzestrzennym”, Geodezja 24, S. 73-85,
Kraków, 1978 (in Polish language)
Sroka, A. et al. (1988) “Vorausberechnung vonGebirgsbewegungen bei geneigten flözartigen

153

ISMS 2016

Paper No. 99

Slope stability analysis and prediction based on the limit equilibrium methodof Luming Molybdenum Mine's West-I and North Region
HUANG Zhi-an, LIU Fang-zhe, WANG Hui*, GAO Yu-kun
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing, China, 100083

ABSTRACT
Slope stability is directly related to the safety of mine production, which is one of the key factors influencing themining production benefit. The present study used China Railway Resources Group Co., LTD Luming Molybdenum
Mine’s west-I and north area as the main research background and established a numerical simulation model for theselected profile according to the slope engineering geological conditions and mining design of Luming Molybdenum
Mine. The profiles included three profiles from the West-Ⅰregion and three profiles from the North region. The
safety factor was calculated and analyzed by the limit equilibrium method and Geo-Slope software. Slope stability
was evaluated. An optimization design was carried out on the sections not meeting the requirements, and afterwards
the safety factor met the requirements, with the slope being generally stable.
KEYWORDS: surface mining; slope stability; limit equilibrium method; Geo-Slope
1.

INTRODUCTION

The proportion of coal mining at home andabroad has increased in the last century. In recent
years, with the continuous development andutilization of resources, there has been an overall
trend towards deep sunken open pit mining. The deepmining process has led to increases in slope heightand mining depth, resulting in poor slope stability
and safety. In addition, for large open-pit mines, theoptimization of slope angle is one of the importantmeans to make full use of resources, and could
reduce production costs and increase mining benefit.
According to Sun (1988), with the increase of theslope angle, billions or trillions could be saved instripping rock costs. Therefore, in the process of deepmining in open-pit mines, there is a prominentcontradiction between ensuring the slope safety andimproving the economic benefit.
Luming Molybdenum Mine is an open-pit minethat was designed with steep slope mining and relief
for the stripping process, with the stripping direction
going from the plate to the footwall of the ore body.
Luming Molybdenum Mine is a typical high andsteep slope strip mine, therefore it is of greatsignificance to China to ensure safe and efficient
production to meet demands for molybdenum
resources.
Based on the above requirements, the early fieldengineering geological investigation and field data
gained by the rock physics mechanics test are
analyzed, and the impact exerted on the slope
stability by the geological conditions of Luming*Corresponding author – email : wanghuiustb@live.cn.

Molybdenum Mine West-I area and North area arestudied using the limit equilibrium analysis method,slope stability analysis, and the numerical simulation
software Geo-Slope. Finally, optimization measures
are put forward.
2.

LIMIT
EQUILIBRIUM
THEORYANALYSIS

The limit equilibrium method design procedures
are an important and most commonly used method
for the analysis of slope stability. Broadly speaking,the method also belongs to a kind of numericalanalysis method, but due to its generality andpracticability, it is often listed as a separate class of
methods. The limit equilibrium method is comprisedof cutting the soil along a slip surface within thescope of the sliding trend into a bar or oblique,establishing the equilibrium equation of all thesliding soil based on the analysis of the stress of theblocks, and on this basis, determining the safety
factor of slope stability (Li, 2010). These methods
assume that soil rigid sliding or rotating occurredalong a potential slip surface, and sliding soil mass isthe ideal rigid-plastic body (Zhou, 2004). The method
does not consider the soil stress-strain relationship. It
assumes that the safety factor of the degree of shear
strength mobilization and the shear strength of thevarious points along the sliding surface are the same,and assumes its safety factor expression with thedeformation characteristics of the landslide area in
addition to the landslides regional geologicalconditions and stress conditions. The differences

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

between the Fellenious, the Bishop, and the Janbu are
only the assumptions for interslice force or sliding
surface interaction force to eliminate the staticindeterminateness and the method of deriving thesafety factor. Limit equilibrium methods are widelyused in engineering due to their advantages such as
the easy model and the convenient and easy tounderstand formula.
An early limit equilibrium method was presented
in 1916 by Peterson, and followed by many scholars
such as Fellenius, Taylor, Bishop, Janbu,
Morgenstern and Price, Spencer, Sarma (Sarma, 1979;
Chen and Mogenstern, 1983) who were devoted to
improving the method. At present, the rigid-bodylimit equilibrium method has been developed fromtwo-dimensional to three-dimensional. The greatest
benefit of this solution is the constitutive relation
expression in engineering, and thus it has a clear
physical concept, giving it the advantage of a simple
and rigorous solution. There are several methods tocalculate slope stability based on the principle oflimit equilibrium method. The present study mainly
uses the Swedish article points method, Janbu
method, Bishop method, Spencer method, Sarma
method, and Morgenstern - Price method

3.1 GEO-Slope software introduction
The SLOPE/W module of Geo-Slope software
was used for the calculations. SLOPE/W has become
the most widely used software in geotechnicalengineering professional slope analysis. It includes avariety of methods (Morgenstern-Price, GLE,
Spencer, Bishop, Ordinary, Janbu, Sarma, Corps ofEngineering, and Lowe-Karafiath) to analyze
geotechnical engineering problems, such as shapechange of the slip plane, condition of pore waterpressure, soil properties, and different loading ways.
Finite element method can be combined with thetheory of limit equilibrium to calculate and analyze
the slope stability. It can also use the parameters toanalyze the stability. SLOPE/W software can analyze
almost all of the SLOPE problems in geologicalstructures, such as civil engineering and mining
engineering
3.2 Selection of study section
Preliminary was completed concerning the
Luming Molybdenum Mine engineering geologicalconditions, rock mass structure characteristics, thephysical and mechanical properties and quality of therock, and the rock mass mechanics parameters. Thislaid the foundation for the simulation. For the sake of
convenience, the field engineering geological zoning,
and the early stages of the rock mass quality

stability of the West- Ⅰ and the North area. The
locations are shown in Figure 1, labeled clockwise as
sections 1-1, 2-2, 3-3, 4-4, 5-5, and 6-6.
F3 Fault

3. THE GEO-SLOPE SOFTWARE

evaluation results, three sections of West-Ⅰand three
sections of North were chosen to evaluate the slope
stability. The optimization of design was carried out
for the instability profiles.
According to the actual situation of the field, theprinciples of the selection profile are as follows:(1) Close to or through the drill as far as possible,
to ensure the accuracy of the research.
(2) Set the section vertical to the slope strike inorder to simplify the problem about analyzing theslope stability to plane strain problem, and reduce thecalculation error.
(3) Ensure the selected profile through the F3
and F4 fault, in order to research how the faults affectthe slope stability of the region.
(4) Make the profile through the fracture zones
as far as possible, in order to study how the fracturezones affect the slope stability.
Based on the above principle, six representative
profiles were ultimately chosen to research the slope

4-4Section

5-5Section

3-3Section

6-6Section

F4
Fault

2-2Section
1-1Section

Figure 1: The research section of the west-Ⅰ district and thenorth district.

3.3 Establishment of the calculation model
According to the above theory combined with
Luming Molybdenum Mine's actual situation and theengineering geological zoning information, sections
1-1, 2-2, 3-3 of West-Ⅰand sections 4-4, 5-5, 6-6 ofNorth were selected as the research areas. The slope
stability was analyzed by adopting the method oflimit equilibrium theory. According to the geologicalconditions and actual mining situation, deformationof rock mass in the vertical and profile direction is
negligible. Thereofre by using the plane strain model
assumption, the deformation of the vertical and thecalculating section direction is assumed to be zero.
The calculation model is shown in Figure 2. The
length of the 1-1 and 2-2 sections model is 500 m andthe height is 400 m. The 3-3 section model length is
500 m and the height is 420. Sections 2-2 and 3-3155

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

have fracture zones. Sections 1-1 and 2-2 passthrough the F3 and F4 faults, the 3-3 section passes
through the F4 fault, which should be considered tohave an effect on the slope stability during
calculations. The 4-4 section model of North length is
500 m along the horizontal axis and the height is 420
m. The 5-5 section model length is 800 m and theheight is 540 m. The 6-6 section model length is 700
m and the height is 550. For the 4-4 section, there is a
big range of fracture zone, which should beconsidered when calculating the impact on the slope
stability.

Granite#1
Fracture Zone
Granite#2
Water LineF4 Fault
Granite#3

Granite#1
Granite#2

F3 Fault

Water LineF4 Fault(c): West-Ⅰ 3-3 section calculation model
Granite#1

Granite#3

Fracture Zone

Water Line

Granite#2

Granite#3(a): West-Ⅰ 1-1 section calculation model
Granite#1

Granite#2(d): North 4-4 section calculation model

Fracture Zone
F3 Fault

Water LineF4 Fault

Granite#1

Granite#3
Water Line

Granite#2

Granite#3
Fracture
Zone(b): West-Ⅰ 2-2 section calculation model(e): North 5-5 section calculation model156

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Granite#1

BishopmethodJanbu method

1.365

1.389

1.345

1.408

1.213

1.278

1.202

1.317

M-P method

1.288

1.344

1.289

1.380

Water Line
Granite#2

Fracture
Zone

Granite#3(f): North 6-6 section calculation model
Figure 2: West - I area and North area of Luming
Molybdenum Mine calculation model.

4. NUMERICALSIMULATIONANDANALYZING OPTIMIZATION RESULTS
4.1 Simulation optimization analysis of West-Ⅰ(1)Simulation analysis of West-Ⅰ
The safety factor with different calculation
methods is as shown in Tables 1 and 2. In the 1-1, 22, 3-3 profile of West-Ⅰ, the minimum safety factors
are Fs=1.213, Fs=1.202 and Fs=1.086, respectively.
According to the Bishop method, the safety factor isless than 1.3, so the slope is not stable.
(2)Optimization analysis of the West-Ⅰslope
According to the calculation results for the 1-1
profile, slope overall stability is poor. The reductionof the slope angle between the 180m-210m platform
should be considered. The slope angle should be
optimized from 59° to 57°. The result is as shown in
Table 1.
According to the calculation results for the 2-2
profile, the slope angle should be optimized between
the 270m-300m platform, from 64° to 60°. The result
is as shown in Table 1.
According to the calculation results for the 3-3
profile, the slope angle between 300m~330m
platform should be reduced from 64° to 60°. The
safety factor did not meet the requirement that Fs>1.3,
the slop angle should be optimized between the
330m~360m platform, and reduced from 65° to 63°.
The result is as shown in Table 2.
Table 1: Safety factor summary of 1-1, 2-2 profile.
1-1
1-1
2-2
2-2
profileprofileprofileprofile
59°
57°
64°
60°
Swedish slice
1.247
1.316
1.217
1.333
methodTable 2: Safety factor summary of 3-3 profile.
3-3 profile
3-3 profile
3-3 profile
63°
64°
60°
Swedish
1.326
1.129
1.253
slice method
Bishop
1.367
1.143
1.299
method
Janbu
1.332
1.097
1.274
method1.305
M-P method
1.086
1.238
The slope angle of 300 m~330 m platform to 60°，and
slowing the slope angle of 330m~360 m platform to 63°

4.2 simulation optimization analysis of 4-4 profile ofNorth(1) Simulation analysis of 4-4 profile of North
The safety factor of 4-4 profile was Fs=1.168, so
the slope angle should be optimized.
(2) Optimization analysis of the 4-4 profile
According to the calculation model of 4-4 profile,the slop angle between the 240m~270m platform
should be optimized from 65° to 61°. The safety
factor is as shown in Table 3.
Table 3: Safety factor summary of 4-4 profile.
4-4 profile 65°
4-4 profile 61°
Swedish slice method

1.197

1.313

Bishop method

1.291

1.346

Janbu method

1.168

1.302

M-P method

1.276

1.378

(3) Simulation analysis of 5-5, 6-6 profile ofNorth
According to the calculation results of 5-5 and 66 profile, the minimum safety factors are Fs=1.306
and Fs=1.303, respectively, which meets therequirements of the slope design specification. The
safety factors are as shown in Table 4.
Table 4: Safety factor summary of 5-5, 6-6 profile.
5-5 profile
6-6 profile
Swedish slice method

1.351

1.311

Bishop method

1.368

1.397

Janbu method

1.306

1.303

M-P method

1.359

1.352

5. CONCLUSIONS

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

(1) Six typical profiles of West- Ⅰ and Northzones were selected and studied. The principles of theselection profile are as follows: close to or throughthe drill as far as possible; set the profile vertical to
the slope strike; ensure the selected profile throughthe F3 and F4 fault; make the profile as far as
possible through the fracture zones.
(2) Before optimization, the safety factors of the
1-1, 2-2, 3-3 profile of West-Ⅰ and 4-4 profile ofNorth were Fs=1.213, Fs=1.202, Fs=1.086, and
Fs=1.168, respectively, so the slope is not stable. The
minimum safety factors of 5-5 and 6-6 profiles were1.306 and 1.303, respectively, meeting therequirements of the slope design specification.
(3) After optimization, the minimum safety
factors of the 1-1, 2-2, 3-3, 4-4 profiles wereFs=1.307, Fs=1.317, Fs=1.305, and Fs=1.302,
respectively, meeting the requirements of the slope
design specification. The possibility of slope
instability is very small within the stable state.
According to the above analysis results, theoptimization of the slope angle of the final slope hasa certain effect. If the condition is permitted, the fieldshould strengthen the construction management andmonitoring in the process of mining, and takemeasures to control those sensitive areas using gentle
slope mining and avoiding the placement of heavy
objects on the top of the slope in order to reduce
accidents and ensure safe production.

6. ACKNOWLEDGEMENT
It is with great pleasure that we acknowledge thegenerous financial support of National Natural
Science Foundation of China (project number:
51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).

7. REFERENCES
CHEN, Z. Y., MOGENSTERN, N. R.. (1983).
Extensions of the generalized method of slices ofstability analysis. Canadian Geotechnical Journal.
Volume 20, No. 1, pp. 104-119
Li, S. P.. (2010). Overview on application ofslope stability analysis method. Yangtze River.
Volume 41, No. 20, pp. 12-15, 31
Sun, G. Z.. (1988). Rock texture mechanics.
Science Publishing Company, 381p.
Sarma, S. K.. (1979). Stability analysis ofembankments and slope. Journal of GeotechnicalEngineering. Volume 105, pp. 1511-1524
Zhou, Y.. (2004). The most dangerous sliding
surface search in the slope stability analysis. Dalian
University of Technology, 65p.

158

ISMS 2016

Paper No. 100

Study on the similar materials simulation of the slope stability of the west-Ⅰ
zone in Luming Molybdenum Mine
Huang Zhian, YangFei, Wang Hui*, Zhang Yinghua, GaoYukun
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing 100083, China

ABSTRACT

Based on a study of the geological data and rock mechanics parameters of the Luming Molybdenum Mine andaccording to the slope stability in the excavation process of the weak structure of the mining area, the similarmaterial simulation test was developed. Using the proportion of geometric similarity constant 300, thelaboratory model was set up for a 3-3 profile, and arranged with displacement monitoring points and stressmonitoring points. Then the excavation process of the actual slope was simulated with this model and finallyconclusions were made after collecting relevant data, as follows: in the process of open-pit slope excavation,
the bench slope was affected by a weak structural plane and excavation disturbance. The bench slope wasdestroyed due to deformation failure, especially in the cross area of the weak structure plane and fault and thearea of the bench slope located in weak structural plane.
KEYWORDS: slope; stability; similarmaterial; experimental simulation

1.

INTRODUCTION

Research on stability for slope engineering has
always been one of the core problems in the field ofmining engineering, and the main content of slopeengineering research relates to the mechanisms ofdeformation and failure. Under the comprehensive
effect of various internal and external factors,
stability is characterized by certainty and randomness,making it difficult to adopt the mathematicalanalytical method to solve the problem of stability forslope engineering (Yang, T.H. et al., 2011). Directly
using an experimental study of the actual structure
size is also impossible and has great limitations. With
the principles of similarity theory, using the similar
physical model for slope stability research has been
one of the effective ways to solve the problem ofslope engineering, and the development of slopeengineering research also shows that it is an effective
method.
Based on the experiment method of the similarmaterial simulation, this study simulates the Luming
Molybdenum west-I area slope engineering
deformation and failure process, and studies thedeformation and failure rules. The test of similarmaterial mixture is conducted to get all kinds ofmaterial proportion, then a similar material
simulation experiment is conducted to simulate the
excavation sequence, and finally the stress anddisplacement data are collected for stability analysis(Yin, Z.G. et al., 2011; Zhang, H. et al, 2011).

*Corresponding author – email :wanghuiustb@live.cn.

Combined with the numerical simulation results, thepurpose of this study is to find the 3-3 section of
Luming Molybdenum on the west-I slope potential
damage area through a similar material simulation,and to provide technical support for the safety
production.

2.

THE BASIC PRINCIPLE OF SIMILAR
EXPERIMENTS

The theoretical basis of similar material
simulation experiment are three laws, according to
the theory of similarity, and they are mainly
geometric similarity, kinetic similarity, anddynamical similarity which are to satisfy the single
value geometric conditions, physical conditions andtime conditions, boundary conditions, and initialconditions (Wu, W., 2011). The similarity criteria are
as follows:（1）Geometric similarity
Lm= C l （1）Lp

In the formula: M represents the similar model,
P represents the engineering prototype, C is similarity
ratio, the same below.
（2）Time similarity
C t = C l （2）（3）Bulk density similarity

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016γm
= C γ （3）γp（4）Stress similarity (elastic modulus, strength, etc):σm= C σ = C γ ⋅ C l （4）σp（ C E = Cγ ⋅ Cl ， C R = Cγ ⋅ Cl ）3. MODEL SELECTION AND THE
SELECTION OF SIMILAR MATERIAL

3.1 Selection of similar modelThis study is based on the investigation ofgeological data and mechanical parameters of rockmechanics parameters in the early period of a mining
area, and the area of potential safety hazard is mainlyin the fault area of F4 and F3. In order to confirm
with numerical simulation research, the profile of theselected analog simulation is 3-3 section (as shown in
Figure 1). Rock mechanics parameters are shown in
Table 1.

Table 1: Rock and soil physical and mechanical parameter table of west-Ⅰarea slope engineering of Luming Molybdenum.
Internal
Elasticity
Poisson's
Shear
Cohesive Compressive
Densityfriction
Depth
modulusratio
elasticity
force
strength
Lithology
angle
103kg/m3

GPa

Granite 1

2.526

4.82

Granite 2

2.592

5.34

GPa

°

MPa

MPa

0.28

1.88

29

0.12

0.061

0-93

0.23

2.17

33

0.21

0.457

93-147
147-

Granite 3

2.614

6.52

0.2

2.72

37

0.25

0.512

Crushed zone

2.173

1.44

0.33

0.54

19.01

0.075

0

m

In the same way, the thickness of LM2, LM3, LM4
are 300 mm, 297 mm, 870 mm.
（2）The time similarity constantat = aL=(300)1/2=17.32（3）The bulk density similarity constantαγ = γ H / γ M γ Hγ,-prototype unit weigh, M -γFigure 1: 3-3 Profile geological map.

2.2 Determine similar conditions(1) The geometric similarity constant
Length similarity constant: αL=LH/LM, LH-thethickness of prototype, LM-the thickness of model. In
the choice of geometric similarity constant α L=300(empirical value), due to the fact that the prototype
height is 440 m and the horizontal width is 1260 m,
the simulation size, height, and thickness should be4200 m, 1467 m, 250 m, respectively.
The planestrain conditions are used in theexperiment, and the thickness of each layer in thesimilar model are respectively:

LM 1 = LH 1 / a L =50 m/300=167 mm；

M -generally is13.7-17.68
model bulkdensity.
3
kN/m , after considering comprehensively the option
is 16.5 kN/m3.
With the granite 1 unit weight as the prototype
unit weight, the unit weight similar constant iscalculated as follows:
2.526 × 9.8== 1.5
α γ γ=
H /γM
16.5（4）The intensity of similar constant

αC=CH/CM，CH-the intensity of the prototype，CM-the model intensity. The intensity similarity
constant is equal to the density of similar strength.
（5）Stress similarity constant=ασ

σ H γ H HH
γ== αL Hσ M γ M HM
γ M （5）So, ασ=αL·γH/γM≈450
Type: σH—the original rock stress or strength; theunit is kN/m3，same below.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
σM —the stress or strength of model; σp—prototype average density
2.3 The selection of similar material, strength
calculation and material ratio
River sand was chosen as the raw material,
where the density is 1.35-1.45 g/cm3, lime andgypsum as cement, and the density is 2.60-2.75 g/cm3
and 0.936 g/cm3.
The model strength is calculated, according to
the similarity calculation formula:

σM =

σp

α Lα γ（6）
Type: σM- simulation strength of the rock (ore)in the model, unit for MPa; σp- actual strength of therock(ore) in the prototype, unit for MPa.
α L 、 α γ represent the geometric similarity ratio
and bulk density, respectively. Therefore, thesimulated strength of the corresponding rock is: thecompressive strength and bulk density of the firstlayer of granite model, which are:1
19.37 ×0.043( MPa ) ；σ M1 ==
300 × 1.5

γ
αγ

H
=
γ M 1=

2.526= 1.68 kN/ m3 ；1.5

In the same way, as for the second and thirdlayer of the granite and the fracture zone model, thecompresive strength of σM2, σM3, σM4 are 0.102 MPa,0.114 MPa, 1.78×10-4 MPa and the bulk density for
γM2, γM3, γM4 are 1.728 kN/m3, 1.74 kN/ m3, 1.45
kN/m3.
Based on the literature (Duan, H.G. et. al.,2011), the dosage of aggregate, cement, gypsum andwater are all factors that affect the strength of thespecimens. After many matching tests, a ratio thatsatisfies the requirement is selected (as shown in
Table 2).

Table 2: The matching parameter table of rock mass similar material experiment for Luming north slope engineering.
Simulation of compressive
Simulated bulk
Position
Lithology
The ratio of no.
Proportion material
Strength(MPa)density(kN/m3)
1

Granite1

0.043

1.68

12:01:00

Sand, Lime, Gypsum

2

Granite2

0.102

1.728

873

Sand, Lime, Gypsum

3

Granite3

0.114

1.74

955

Sand, Lime, Gypsum

1.45

-

Mica, Sand Mixture

4

4.

Crushed zone/ Fault

1.78×10-4

THE FABRICATION OF SIMILAR
MODEL AND ARRANGEMENT OF
MEASURING POINTS

4.1 The fabrication of similar model
The building process of the similar model (Figure2) of this project is as follows:

Figure 2: The similar mode of the west 3-3 profile for
Luming Molybdenum.

Firstly set up the subject building of the modeland compound the material, then smoothly place thematerial on the model. After the similar material is alittle dry, remove the template and arrange themonitoring points.

4.2 Arrangement of the stress monitoring points
The strain gauges are arranged near the slope andcrushedzone, in fault, at a total of 48, and the positionof the specific placement is shown in Figure 3. As forthe experiment limit, we mainly research the verticalstrain. Pressure measurement applies to the testing
system of the static strain, and the system includes adata collection box, a microcomputer and the
supporting software.
4.3 The arrangement of the displacement monitoring
pointsIn order to observe the slope surface and theregulation of the movement and deformations ofoverlying strata for the working face, the observation
points of displacement are set up on the surface of theslope, the earth’s surface, and different positions ofoverburden layers for the molybdenum mine,
respectively. The arrangement of designed points for a
3-3 profile similar model is shown in Figure 3.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
continuously, resulting in obvious macro deformation
and reduction.
5.1 Simulating analysis of stress variation about 3-3
sectionThe excavation is divided into 8 levels and themonitoring data of each excavation is acquired. Figure
5 is the stress monitoring data after each step of
excavation.

(a) General view of 3-3 section(b) Partial enlarged detail of 3-3 section
Figure 3: The arrangement of strain gauges, displacementmonitoring points for 3-3 section similar model.

5.

（a）210 m level excavation stress change curve（b）390 m and 360 m level excavation stress change curve

THE EXPERIMENT RESULTS OF
SIMILAR SIMULATION ANALYSISThe experiment results of 3-3 section stresschange and displacement change were researched andanalyzed, and eventually the section stability
conditions were determined.

（c）330 m level excavation stress change curve（a）Damage phenomenon of 360 m level（b）Damage phenomenon of 330 m level（c）Damage phenomenon of 300 m level
Figure 4: Deformation and damage of slope during
excavation of 3-3 profile in the west area.

（d）300 m level excavation stress change curve

The analysis of Figure 4 shows that during the
excavation of western 3-3 profile, 360 m, 330 m, 300
m represent elevation, and the macro deformation andfailure of the slope are mainly embodied in the 360 m
level, 330 m level and 300 m level. With thecontinuous excavation of the adjacent level, theoriginal micro cracks penetrate mutually and expand

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016（e）270 m level excavation stress change curve（f）225 m level excavation stress change curve（g）180 m level excavation stress change curve
Figure 5: The stress change curve of 3-3 profile during
excavation in west area.

In conclusion, 3-3 profile was not stable, thereason being that the slope was in the crushed zone,
which resulted in instability phenomenon due to thevariation of stresses.
5.2 The analog simulation displacement change ruleof 3-3 profile
According to research data (Liu, L.P. et al.; 2000
Zeng, Y.W., 2005), in the slope stability analysis
process, big displacement deformation of the slope
occurrs mainly in poor structural surfaces and benchslope areas. The similar simulation study focused on
the 30 monitoring data analysis in the area near thebench slope and the monitoring results are shown in
Figure 6.

（a）The change curve of the 390 m level excavation
displacement

We can find from Figure 5 that:(1) With the continuous excavation process,stress values from the 390 m-180 m levelexcavation had a rising stage, but overall the rise
kept to a gentle degree.
(2) When excavation approached a certain
level, its stress appeared to increase. After the
exploiting was completed, stress reduced andpressure relieved quickly. Figure 5 shows that as for
the NO.A-1 points (390 m level) and NO.B-1 points(360 m level), the two stress variation curves wereparallel but the difference was relatively larger thanother slopes, indicating that the stability of the 360
m level was poorer than other side slopes.
On the same level, stress change curves of two
different monitoring points have large differences,indicating that the stability of the level is poor. The
differences of the stress variation curve in the 330
m level and 300 m levels indicates that the stability
was poorer than some other side slopes. There weresome differences in stress curves in the 270 m, 225m, 180 m levels nearby, indicating that there was asmall possibility of slope instability during
excavation. The 5# strain monitoring gauge at the
180 m level slope was laid in fault, and the rate of
the stress changes was large, indicating there was
the existence of instability phenomenon due to thefault through 180 m level slope.

（b）The change curve of 360 m level excavation
displacement（c）The change curve of the 330 m level excavation
displacement（d）The change curve of the 300 m level excavation

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016displacement

Foundation of China (project number: 51474017) andNatural Science Foundation of Xinjiang Uygur
Autonomous Region of China (2014211B013).

8.
（e）The change curve of the 270 m level excavation
displacement（f）The change curve of the 225 m level excavation
displacement
Figure 6: 3-3 section displacement monitoring deformation.

As Figure 6 shows about the similar deformationand displacement monitoring figure of slope
excavation, displacement has a certain change in the
29 times simulation of excavation process about the
open pit slope. The negative displacement represents
sink and positive displacement represents bounce. In
Figure 6, from the displacement monitoring anddeformation trend of excavation in the 180 m-390 mlevels, we can find that the overall deformation of theslope is mainly in the sinking trend, with bounced as
the secondary trend. The displacement of deformation
ranges from a few centimeters to more than 20
centimeters. What we can analyze from thedisplacement deformation monitoring diagram and thepicture of damaging during the excavating is that thefracture phenomena mainly appears in zone 360 m,
zone 330 m, zone 300 m, and zone 270 m, which haveF3 fault or are crossed by crushed zones. There ismuch more obvious fracture growing phenomena
especially in the 300 m-360 m levels.

6.

REFERENCES

Duan, H.G., Jiang, Z.Q., Zhu, S.Y., et, al.(2011).
Centrifuge model tests on rock brusting induced bygreat depth highly stressed roof strata of weak
structural plane. Journal of Central South University,
Volume 31, NO. 9, pp: 2774-2782.
Liu, L.P., Jiang, D.Y., Zheng, S.C., et al. (2000).
The recent progress of the slope stability analysis
methods. Journal of Chongqing University(Natural
Science Edition), Volume 15, NO.3, pp: 115-118.
Wu, W. (2011). The slope instability analysis of
the causes and prevention and management. Mining
Technology, Volume 12, NO. 5, pp: 44-46．
Yang, T. H., Zhang, F. C., Yu, Q.L., et al. (2011).
Research situation of open-pit mining high and steep
slope stability and its developing trend. Rock and Soil
Mechanics, Volume 32, NO.5, pp: 1437-1451, 1472.
Yin, Z.G, Li, X.F, Wei, Z.A, et al. (2011).
Similar simulation study of deformation and failure.
Chinese Journal of Rock Mechanics and Engineering,
Volume 14, NO. 1, pp: 2913-2923.
Zeng, Y.W. (2005). Slope Stability Analysis By
Combining Fem With Limit Equilibrium Method.
Chinese Journal of Rock Mechanics and Engineering,
Volume 7, NO. 2, pp: 5355-5359．
Zhang, H., Liu, Q.S., Liao, X.G. (2011). Control
and Support of Open － pit Slope. Mining Researchand Development, Volume7, NO. 4, pp: 34-36, 40.

CONCLUSIONS
Based

on

the

similarmaterial

simulation

experiment, theoretical analysis of west-Ⅰarea Luming
Molybdenum 3-3 section of the slope stability was
analyzed, and the following conclusions were drawn:
In 3-3 section 360 m level, 330 m, 330 m level,the 180 m level stability are poorer, and instability
may exist. The 3-3 section on 360 m level is the most
likely to experience instability. To sum up, because theslopes are located in the fracture zone and the stresschange leads to instability, the 3-3 profile is obviously
not stable.

7.

ACKNOWLEDGEMENT

It is with great pleasure that we acknowledge thegenerous financial support of National Natural Science164

Paper No. 171

ISMS 2016

Stability and access implications of open pit mining through old undergroundmine workings
John G. Henning*
Goldcorp Inc., Vancouver, BC, Canada

ABSTRACT
Increasingly, mining operations are looking at developing large open pits down through old, abandoned
underground workings in order to extract remnant ore left within pillar zones. Maintaining pit wall stability while
mining through major scale underground stoping zones presents both a risk and challenge that can have significant
impact on overall pit economics and viability. Potential operational problems associated with the interactions
between the stopes and the pit walls may occur, necessitating pit wall redesign, ground support installation andoperational rescheduling. In addition, anticipated interactions of the pit shell with underground mine workings must
be closely evaluated to maintain a safe working environment. Using illustrative examples, this paper discusses how
operational hazards and risks to pit wall stability can be assessed and mitigated.
KEYWORDS: Open Pit mine; highwall stability; underground workings; stope interaction; hazard awareness

1. INTRODUCTION
Maintaining pit wall stability while mining
through major scale underground workings presents
both a risk and challenge that can have significant
impact on overall pit economics and viability.
Potential operational problems associated with theinteractions between the stopes and the pit walls,
such as shown in Figures 1 and 2, may occur. These
interactions may require pit wall redesign, groundsupport installation and operational rescheduling.

performed to exploit mineralization left by some ofthese underground mines. While each surface mine
has unique design attributes, the practices initiallyestablished at the Dome Mine, were essential inpermitting safe open pit mining practices.
The Dome Mine began underground productionin 1910. Over the years, more than 900 undergroundstopes have been mined and hundreds of kilometersof drifts, sublevels and raises developed.
Underground mining methods included shrinkage,
cut and fill and longhole. Longhole stope tonnage
may be in excess of 1.0 M tons with vertical heightsof 300 m, widths of 60 m and lengths of 180 m. Not
all stopes were backfilled upon completion.

Figure 1: Example of underground workings within
designed open pit mine (Kliche et al., 2000).

2. CASE EXAMPLE, DOME OPEN PITThe Porcupine Gold Mining Camp, located near
Timmins, Ontario, Canada, has been in continuous
production since 1910. Over that period,
approximately 65 million ounces of gold have been
produced by more than 50 Underground mining
operations. In recent times, Open Pit mining has been

* Corresponding author – email : john.henning@goldcorp.com

Figure 2: Example of a Shrinkage stope daylighting into pit
floor.

Open pit operations began in 1988 to supplement
underground production. When completed in 2006,
the bottom of the Dome pit had reached a depth of

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

335m. The pit was mined with 9 m bench heights,
with 11m-wide catch benches established at 27m
intervals. Inter-ramp wall angles vary with lithology,
ranging from 39° to 54° with average of 49°. Benchface angles were typically between 65° and 75°.
In 2002 the pit began to intersect voids in its
final wall, and re-designs of the pit and alternate
planning had to be undertaken. The intersection ofunderground stopes/voids with the Dome Pit’s
ultimate pit high wall resulted in stability issues that
had safety, design, scheduling, operational, andeconomic impacts.
Much of the planning and design of the pit was
driven by the interaction of large voids with the pit
wall, as illustrated in Figure 3. The success of theDome pit depended on the ability to design aroundthe underground voids, profitably maximize ore
recovery and maintain production, Miller (2003).

Figure 3: Interaction with mined underground stopes
and the Dome pit (yellow colour).

3. INTERACTION
WORKINGS

WITH

MINE

The interaction of the Dome pit with previously
mined underground stopes presented a challenge tostability design in the walls, and pit floor. An
examples of stope exposure in the pit wall is provided
in Figure 4.
Stopes were assessed on a case-by-case basis.
Special attention was directed towards stopes which
may impact the pit ramp or catch bench due tolocation or size, stopes with unknown fill conditions,and stopes with unstable wall conditions. In addition,
since some mine workings adjacent to the pit dated
back more than 75 years, the exact location,geometry and condition of individual stopes andassociated development is not always known.

Figure 4: Pit wall undercut by stope.

3.1 Void Definition
Potential voids are identified and defined using avariety of sources. A geometric model based on the
open pit and underground mine plans, created withsophisticated design software, provides a 3dimensional view of interactions between the pit
excavation and mine workings.
Other data sources available for void definition
include:• Historical sections of underground voids• Stope files and records of backfilling• Underground visual confirmation of voids• Confirmation of voids via diamond drilling• Probe drilling from pit floor andmeasurement of rock, fill and void• 3D survey via borehole scanner ofintercepted voids
Based on the results of void definition,engineering planners design probe holes to verify
underground voids. On the basis of proximity tovoids, the pit floor is subdivided into non-restricted,
cautionary and restricted lanyard areas to ensure
safety of personnel.
3.2 Geotechnical design
Geotechnical information is used for the design
the pit geometry and for ground support design toachieve acceptable factors of safety, quantify failure
mechanisms and assess risk. Available geotechnicaldata includes:• 3-dimensional lithological model for the pit• Bench scale mapping for structure and rockmass quality• Major feature recognition and mapping(fault, slips and joints)• Underground level and stope mapping andhistory• Rock and backfill characteristics andstrength parameters

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Problematic stopes were identified and theirstability assessed using a range of techniques,
including:• Conventional kinematic analyses to examine
potential for wedge, planar and toppling
failure of the designed final wall in thevicinity of the identified stope,• Detailed analyses of potential 3-dimensional
wedge block geometry and necessary
support capacity, and• Numerical analysis (2-dimensional and 3dimensional) to evaluate overall stability
interaction issues and to quantify
geotechnical assumptions.
Examples of stability modelling at the Dome pit
are described in Carter el al. (2009), Henning (2009),
and in Palmer et al. (2003).

4. STABILITY DESIGN TACTICS
Ground support or pit geometry re-design areused to establish stable walls conditions when inclose proximity to mine workings or when regions of
low quality ground are encountered.

•

•

•

quality rock. Screening is draped over thewall or installed as catch fences (see Figure7) to control the descent of small loose rockin sensitive areas or where catch bench
spacing has been modified.
Backfill exposures are stabilized byreplacement of the existing fine grain fill(sand or tailings) with a covering of waste
rock, allowing a steeper angle of repose. In
sensitive areas, fiber reinforced shotcrete has
been used to reduce unraveling risk.
Voids are backfilled in advance of pit
mining. Depending on proximity to theultimate pit wall, unconsolidated andconsolidated backfill are used. On occasion,some voids may be filled with concrete.
Typically a minimum one-to-one pillar ismaintained above voids, otherwise sill
pillars are blasted down. In the case of large
stopes, drop raises may be used to fill thevoids with broken waste muck prior toblasting down the sill.

Figure 6; Cable bolt reinforcement above void in pit wall.

Figure 5: Example of Cable bolt support pattern aroundunderground mine workings (Carter et al, 2009).

4.1 Ground support
Ground support is installed to locally stabilize
the rockmass around mine workings or in sectors of
low quality ground. Ground support measures used
include:• Cable bolting. Bulbed cables, up to 36m
long are installed into the pit wall or floor.
Support patterns, such as that shown in
Figure 5, are designed on a case-by-casebasis. Up to four 25 tonne cables are
installed per hole. On occasion, the cables
may also be plated, as illustrated in Figure 6.
• Rock bolting, strapping and/or screening isused to provide surface confinement in poor

Figure 7: Catch fence installation along bench.

4.2 Pit wall geometry redesign
Pit wall geometry is redesigned to minimize
impact of voids on pit wall stability. An example ofpit re-design around a stope is shown in Figure 8.
Design measures used include:167

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016•••

Increase or decrease bench face angles andberm widths
Alter ramp width or grade
Change location of ramp

4.3 Wall control blasting
Preshear blasting is routinely performed along
the final pit walls in order to create a smooth, stable
face. The goal of the blasting is to create a crack in
the rock along the line of the pit wall, but to not
fragment or displace the rock.
In areas adjacent to voids, a single row of
114mm diameter preshear holes are drilled at anangle of 80°. Spacing between holes (usually 1.2 m)
may be reduced in low quality rock. Elsewhere, 165
mm preshear holes were drilled at 1.8 m spacing.

•

Delineator cones and pickets. The type andseverity of potential hazard can be indicate
by colour coding or delineator size. See
example, Figure 9.
Safety procedures at the mine dictate what areas
can be accessed, and what precautions are required.

Figure 9: Example of visual hazard identification.

6. MONITORING

Figure 8: Pit wall re-design to increase pillar dimension
around a stope.

5. HAZARD AWARENESS
In addition to hazards associated with pit wallstability, a major concern associated with working
around underground workings is that areas of
subsidence, or “sinkholes”, may occur unexpectedly.
Most of the existing mine openings have beenmodeled in 3-D. However, there is always thepossibility of the presence of unknown openings, orthat some openings have failed / caved to a larger
than anticipated dimension.
Subsidence can be defined as “the sudden
collapse of material into a void beneath it”.
Subsidence occurrences can be triggered by the thawof frozen ground (spring time), heavy rains, and by
nearby pit blast vibrations.
5.1 Identification of Hazard Areas
Areas where subsidence may be anticipated,
where near-surface voids are known to exist, andmined areas connecting to surface are all considered
to be Hazard Areas. In the Pit, these areas are
identified by:• Physical barriers (Temporary fencing,
Berms, etc.)

The objective of the instrumentation is toprovide warning of the onset of movement in stope
sidewalls, crown pillars, filled stope openings andfinal pit walls. Of particular importance to themonitoring program are zones of potential instability
encompassing many stopes. Due to the absence ofreinforcement in many of these zones, it is imperativethat deterioration of stope sidewall stability or fillsubsidence be identified promptly.
Monitoring is used to provide an early warningof ground movement to ensure safety of workers. The
instrumentation program at Dome Mine consists ofseveral different types of monitors to provide an early
detection system, including:
Visual inspections
Visual inspections are performed on an on-goingbasis to identify evidence of instability, as indicatedby crack formation, unraveling, falls of ground, lossof fill, damaged ground support, unexpected
breakthrough into void, or subsidence. Unusual
occurrences are reported for further review.
Multi Point Borehole Extensometers
Multi-Point Borehole Extensometer (MPBX)
instruments are used on occasion as a quantitative
early detection system for progressive ground failurein the vicinity of mine workings. Each MPBX
consists of six nodes grouted in place and attached tothe instrument head by a thin flexible rod. These
instruments directly measure displacement of thenodes relative to the head.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Sloughmeters
Sloughmeters are installed into filled stopes tomonitor for potential subsidence. These instruments
are used as a qualitative early detection system forprogressive ground failure. Consisting of ten nodes
grouted in place, each node forms a loop for current
flow. Should a node be lost (or sloughed), this will be
indicated by no current flowing through the loop.
Monitoring of survey prisms
Survey prisms are mounted onto the surface ofthe pit wall at locations of anticipated instability,
such as on potentially unstable wedge intersections.
At locations adjacent to the intersection of the pit
wall with large backfilled voids, prisms may beinstalled systematically on a dense (15 m x 15 m)
pattern to permit close monitoring of a specificregion.
The prisms are monitored several times per day
by an automated Robotic Total Station (RTS) survey
system, used in conjunction with Geodetic
Monitoring software.
Radar
Slope Stability Radar can be used to remotely
monitor pit highwall stability. Advanced analysis
tools allow for long term trending and hazard
identification. Alarms warn of accelerated slope
movement prior to wall failure

Underground Mine Voids. Proc. 3rd International
Symposia on Rock Slope Stability, 9 – 11 Nov 2009,
Santiago, Chile. 13 pg.
Henning, J.G., 2009. Selective highwall mining
at the Dome Open Pit mine. 3rd Canada-US RockMechanics Symposium (RockEng 09), Toronto, May
2009. 8pg.
Kliche, C., Hladysz, Z., and Franzen, V., 2000.
A slope stability analysis for the Trojan Pit expansion
at the Wharf Resources Mine, Black Hills, SD. In
proc. SME Annual Meeting, 28 Feb – 1 Mar 2000,
Salt Lake City, Utah. 18pg.
Miller, P. 2003. Dome Pit Highwall Stability inareas intersected by underground stopes.
3rd
Biennial Placer Dome Mining Engineering
Conference, October 2003, Kalgoorlie, Western
Australia.
Palmer, P.G., Dimock, T., and Cameron, A.R.,
2003. Stability analysis of the 653 stope impacting
the Dome Mine Open Pit. CIM Mine Operators
Conference, Saskatoon, SK, Oct 2003.

7. CONCLUSION
Design and stability of Open Pits developed
through historic underground workings are
influenced by ‘typical’ factors, such as rock masscondition, and by ‘atypical’ factors – in the form ofunderground mine workings.
To anticipate and mitigate risks, voids
intersecting the pit wall and floor are identified,defined, and assessed. Strict hazard awarenessprotocols are required. Pit designs are adjusted
around anticipated and intercepted workings.
Highwall stability is monitored by an ongoingprogram of visual inspections for changing
conditions, coupled with regular tracking of potential
displacements both at the pit surface (survey prisms
and radar) and within the wall (extensometers).

8. ACKNOWLEDGEMENTS
The support of Goldcorp Inc. and of Porcupine
Gold Mines, for permission to publish is gratefully
acknowledged.

9. REFERENCES
Carter, T.G, Rougier, M., Palmer, P., Miller,
P.M, and Henning, J.G., 2009. Wall Stability
Implications of Large Open Pit Mining through169

ISMS 2016

Paper No. 127

Thermomechanical impact of Underground Coal Gasification exploitation
Laouafa Farid
Institut National de l'Environnement Industriel et des Risques- INERIS, F-60550 Verneuil-en-Halate, France

ABSTRACT
Underground mining by coal combustion (Underground Coal Gasification - UCG) raises questions regarding themechanical behavior of the site and the stability of the overburdened rock layers. By studying the underground reactor, its
inlet and outlet, the key roles played by mechanical damage and thermo-mechanical phenomena were confirmed.
Deformation or collapse above the cavity may cause a collapse in the overlying layers or a subsidence at the surface level.
These phenomena highly depend on the thermo-poro-mechanical behaviour of the surrounding rock (host rocks). The
numerical results presented in this paper were derived from models based on different assumptions describing a raw
geological background. Both 3D and 2D nonlinear finite element modelling was conducted based on two different
approaches. Based on the analysis of the numerical results, we were able to highlight the main factors influencing the
behaviour and mechanical stability of the overburden, and consequently the UCG process evolution.
KEYWORDS: Underground; coal; combustion; mining; thermomechanic; modelling

1. INTRODUCTION
Underground Coal Gasification (UCG) is a process inwhich coal is burnt in situ without an explicit extraction of
the matter (Bell 2011; Bhutto et al. 2013; Shafirovich etal. 2009). The efficiency of the process depends on the
combustion properties of coal rock and otherthermodynamic features of the physical phenomenon(temperature, pressure, mass transport related variable)(Williams 1985; Speight 2013).
In terms of cavity shape and its time evolution, theUCG resembles the longwall mining method (Peng et al.
1982, 1984, 2007; Shabanimashcool, 2012).
The UCG process involves high temperatures ofaround 1000°C, which will affect the host rock, changing
its mechanical properties. Based on different tests andresearch of mudstone specimens from coal seams, Luo etal. (2011) shows that high temperatures cause thermal
expansion of mudstone, and that the expansion increases
with temperature, producing expansive stress in thesurrounding rock of underground gasifiers. Brittle cracks
are the main type of deformation. The temperaturedependency of rock behavior has been the subject ofintense research (Bauer 1983; Deng’gina et al. 1994;
Dwivedia et al. 2008; Fjaer et al. 1992; Ide et al. 2010;
Somerton 1992; Wolf 2006).
The UCG process may also have other environmental
impacts in terms of pollution of groundwater and surface
subsidence. The groundwater may be affected by gas orothers chemical species transported through the rock
porous matrix, and the initial or induced cracks and microcracks. At the ground surface, soil subsidence is expected.
The extent of subsidence is dependent on the location of*Corresponding author – farid.laouafa@ineris.fr

the coal seam, its thickness, and the mechanical propertiesof the overburden.
The purpose of our article is related to the thermomechanical effects induced by the UCG process.
In this framework we performed finite element
analyses of a case study coal site that could be exploitedby this method. The numerical results presented in thispaper were derived from models based on different
assumptions describing a raw geological background.
Both 3D and 2D nonlinear finite element modelling was
conducted based on two approaches. The first one
assumed the rock media as a perfect thermo-elastoplastic
continuum. In the second one, and in order to simulate
explicitly large space scale crack propagation, a method
based on finite element deactivation was developed,
which is built on a finite element mesh refinement anduses two failure criteria.
On the basis of the analysis of the numerical results,
we were able to highlight two main factors that influence
the behavior and mechanical stability of overburden, andconsequently the sustainability of the UCG process.

2. UCG PROCESSIn the case of UCG, the shape of the cavity (first
factor) and its evolution with time can be strongly
modified by the thermo-mechanical behaviour of the hostrocks. The second factor is the presence of a heat source
whose location and intensity evolve with time. The
thermal properties of rocks depend strongly on theirmineralogical composition, porosity (φ), saturation, etc(Fjaer et al. 1992). Table 1 below gives values of porosity(φ), thermal conductivity (λ) and specific heat capacity (ρ3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016cp), where ρ is the material density. Somerton (1992) has
shown that for different rock materials, the thermal
properties are not constant but temperature dependent.

0.3 mm/min (after Total Company). The temperature
within the cavity can reach several hundred degrees
Celsius.

Table 1: Thermal properties of some materials (Jaeger et al.
2007).

In Figure 1, we describe the Underground Coal
Gasification (UCG) process. The injection of air isperformed by a vertical well, while syngas (synthetic gas)
resulting from coal combustion is extracted by the other
well. The coal seams are made to react underground withinsufficient oxygen for complete combustion to create
syngas. Air is usually used as an oxidant. The oxygen andwater within the coal seam react with the coal to produce
syngas, which is withdrawn through a production well.
Figure 1 depicts the so called CRIP (Controlled,
Retractable Injection Point) method, in which the injection
point is gradually withdrawn as coal is consumed. This
specific UCG industrial process uses two parallel wells
also called Knife-edge CRIP. In this case the distance
between the two wells axes is taken to be 20 m. The
thickness of the coal seam is equal to 17.3 m. It is
assumed that the total width of the burning front is equal
to 30 m.

Figure 2: Stratigraphy and location of coal seam (on the left) and3D numerical model (on the right). A 2D plane passing throughthe middle of exploitation used in plane strain numericalanalyses. V stand for the burning front velocity.

In the case of a cavity (or gallery) having a geometricconfiguration such as that shown above, the deformation
mechanism is mainly plane strain (plane perpendicular to
the axis of the cavity). The plane strain analyses are basedon a cavity width of 30 m. These dimensions assume that
combustion extends 5 m transversely from two casings
installed 20 m away from each other.
The reader can refer to Fjaer et al. (1992) for themechanical and thermal properties of some of the rocks.
Among all these properties that have been identified,some representative averaged values were extracted. The
properties used in these models are as follows): Thermal
conductivity: 2 W/m/K, Heat capacity: 800 J/kg/ K,
density: 2500 kg/m3.
The Young's Modulus of the coal is taken as 2.5 GPa
and Poisson's ratio as 0.3. The Young's modulus ofoverburden is assumed to vary from 5 GPa to 25 GPa andthe Poisson's ratio is equal to 0.3. Several computations
have been performed by varying these parameters withinrealistic value ranges, and they do not change ourconclusions based on our modeling work. Low values for
the Young's Modulus are assigned to the layers close to
the surface in order to consider them as dead load. The
thermal expansion coefficient of rocks is equal to 10-5 °C-1.
3.

Figure 1: Schematic illustration of the adopted UCG industrial
process with two wells.

The temperature at the combustion front is about1000 °C (after Total, a French multinational integrated oil
and gas company). The burning front is assumed to be astraight plane at 1000 °C and its normal velocity is about

2D AND 3D THERMOMECHNICALMODELLING

The objective is to analyze the spatial extent ofplasticity (damage) in the vicinity of the cavity. The
model size is deliberately reduced to the dimensions
defined in Figure 3. Although the model has a verticalplane of symmetry (through the axis of the cavity), thecalculations were carried out on the whole 2D model toanalyze a component of the robustness of the numerical171

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

model (maintaining the symmetry of the mechanicalresponse).

Figure 4: 2D finite elements mesh (left) and effective plasticstrain (right) (L=30 m).
Figure 3: Spatial distribution of the effective plastic strain (in theleft) and schematic of potential movements (failure, rockfalls,
collapse,..) on the right.

Let us recall that the definition of the effective plasticstrain is as follows:t

2 p p
εij εij
30
We observe that plasticity affects a part of the coverand the coal wall. However, the extension is limited but
the coal layer is also affected.
We can assume that the hypotheses of material
continuity and classical thermo-elasticoplastic framework
are too conservative. In other words, if the analysis was
performed in the framework of fracture mechanics, linear
or nonlinear (Broek 1986), we would certainly have founda lower overall stability rather than local rockfall from theroof and major collapse in coal (Figure 3, right). Likewise,
it is reasonable to assume that overburden massive coal
generally consists of calcareous clay layers, sometimes
sandy, is layered, heterogeneous, and marked bydiscontinuities at different scales. The overall strength
properties are quite low. Therefore, the choice of pair ofvalues (cohesion, friction angle) representative of thewhole overburden is critical for the prediction of theextent of the damaged area. We can a priori assume thatthe uniaxial compression strength of the overburden
seldom exceeds 3 to 5 MPa overall. This leads to an
extension of the damage larger than calculated above.
These failure types can affect the combustion process as
the combustion front may break and, due to the failures atthe edge of the cavity, change the kinetics, the size, andshape of the combustion front, and therefore the shape ofthe cavity. They can also affect the direction of the cavity
evolution. It is observed that the greatest displacement
naturally lies in the cavity roof. The effect on the surface(subsidence) will be presented in the section dedicated to
3D models. If it is not explicitly specified, the criterion for
the adaptive mesh refinement is based upon the value ofthe equivalent plastic strain.

=
ε eqp

ε dt with ε
∫=
p
eq

p
eq

The model on which we performed our analysis is
illustrated by its finite element mesh in Figure 4. The
width of the cavity is 30 m. This approach required theuse of another finite element code that allows adaptive
mesh refinement and the possibility of deactivating a
number of elements (MARCTM finite elements code, MSC
Software, 2014). Figure 4 shows also spatial distributionof plasticity and Figure 5 presents the mesh density whenusing finite element refinement and deactivation in order
to simulate crack propagation.
It was observed that the extension of the plasticity
zone for a cavity of 30 m width is limited in space but still
significant.

DamagedInitialFigure 5: Example of result with adaptive mesh refinement andelement deactivation (L = 30 m). The effective plastic
deformation range from 0 to 0.17.

The results in Figure 4 are obtained through aclassical approach and the elastoplastic continuum
medium (i.e., overburden and coal) is assumed to becontinuous and remains so regardless of the degree of"damage". Figures 5, 6, and 7 show the same computation,
but using a deactivation (roughly simulating fracturing) offinite elements based on adaptive mesh refinement. We
observe that with the most intense element concentration(small elements and therefore finer mesh), the damage
zone becomes more detailed. Note also that thecomputation highlight the "failure" in the walls of thecavity and the collapse of part of the roof of the cavity.
On the basis of the spatial distribution of the mesh, it
is easy to foresee the shape and damaged areas. The extent
of mesh refinement is limited only by the power of thecomputer. The refinement is an h-refinement (based on
subdivision of the finite element), which is different thanp-refinement (based on the degree of the finite element).

172

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The effect of the fineness of the mesh is shown in Figures
6 and 7.
The rock properties (reduction of cohesion andfriction angle by 40%) were decreased and the cavity was
widened to 30 m. The initial mesh was regular andrelatively coarse (in size).

and wall being important outcomes. It should be notedthat such mechanisms are those generally observed during
underground mining. In the case of UCG, these failures
can disrupt the function of the reactor, alter the path of the
combustion front, and so on.
4.

Figure 6: Initial mesh (left) and after dynamic computation,using adaptive mesh refinement and finite element deactivation(right). (Cavity width=30 m).

Figure 6 shows the distribution of fracturing in the
overburden, in the coal walls, and the mesh density in theplasticity zones. Figure 7 (right) shows a focus of qualityof mesh refinement required in order to carry out thecalculation. The "triangular" shape of the collapse area inthe roof and high degradation of coal wall are to be noted.
This failure mode, described here in a very simplified
way, is commonly observed in situ in the case ofunderground mines or quarries. The figures represent
results at an instantaneous state (observation at a given
time t) because the elements are allowed to move in the
dynamic analysis. The inertial terms induced by gravity
and the fractures play an important role and this analysis
therefore differs fundamentally from the quasi-static
approach. The cavity extends laterally until the coal zone
is sufficiently undamaged (by failure). The combustion
process which is already a chaotic phenomenon would be
difficult to formalize in such condition. The combinationof burning and fracturing/block falling should influence
the rate of combustion in the cavity.

SUBSIDENCE AND ROOF DEFORMATIONThe 3D computations are performed on thegeometric model shown in Figure 8. The cavity and its
spatio-temporal evolution are not explicitly created. Moreprecisely, the initial cavity, a purely geometrical shape,
has the dimensions of the final “cavity”. However, itapplies to the boundaries of the cavity pressure andtemperature whose laws of spatial and temporal evolution
describe the expansion of the cavity.

Figure 8: 3D mesh and location of the coal seam.

Figure 9: Vertical displacement of the roof of the cavity(segment CD) when it is created (left) and surface subsidence(segment AB) when the whole cavity is created (right) for 4
temperatures fields inside the cavity.

Figure 7: Focus of the coal wall and roof meshes (several
thousand elements).

The modelling results depicted in Figures 6 and 7
present the main failure mechanisms as described by
Whittles et al. (2007). The coal wall, the roof, and part of
the floor are damaged by the cavity creation. This
numerical computation using adaptive mesh refinement
and element deactivation seems relevant for this study as
they contain much information performed even on an
idealized geometry such as failure and damage of the roof

The first remark concerns the vertical displacement of
the roof of the cavity. Asymmetry (with respect to thereference solution T=0) occurs. Note in the modelling the"front" of combustion moves from left to right. The higher
the temperature, the greater the intensity of movement(left increases), and the asymmetry is more pronounced.
This is explained by the fact that by conduction and due tothe intensity of the temperature difference, the part to theleft is longer subjected to a high temperature.
Consequently the extension of the temperature will begreater in the rock matrix. There is also a shift to the rightfor the maximum subsidence. The surface subsidence is
induced not only by the excavation of the cavity, but also
by thermal effects. That the subsidence is negative173

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016indicates that the contribution of the rock mass thermal
expansion in the uprising is lower than the displacement
induced by stress modification due to undergroundexcavation. The following 3D results are given as anillustration and show the burning front evolution.
Elastoplastic models with adaptive refinement and 3D
finite element deactivation were performed in order toassess the consequences of a possible "fracturing".

Figure 12: Vertical displacements field using two methods:
Pseudo fracturing (top) and continuum model (bottom).

One can observe that the intensity of the verticaldisplacement and the final shape is strongly dependent on
the assumption of a perfect continuum. The effect of thepresence of layers with different mechanical parameters isshow in Figure 13.
Figure 10: Example of induced "fracturing" during time and thespace evolution of the cavity.

5.

STRATIFIED ROOF

In this short subsection we analyze briefly the
behavior of a stratified roof composed of marl andsandstone (Figure 11). The elliptical cavity is located in
the coal layer. he remaining rock is sandstones.

Figure 11: Mesh of the elliptical burning cavity and stratified
roof.

After a given extend of the burning cavity (assumed
elliptical in this sub-section), we applied a given
temperature to its boundary (200 °C). After a given time
we obtained the following displacement field as illustrated
in Figure 12.

Figure 13: Effective plastic strain distribution with crack
propagation.

The spatial distribution of the effective plastic strain
is totally different when we take into account a layeredroof. In this configuration that exhibits a stratified roof wehighlight the transient effect of temperature. Indeed,
thermal effects are more important when the medium isstratified and thus heterogeneous. The differential thermal
and/or mechanical properties induce incremental strains
and shear at interfaces layers. The case presented here isan academic and theoretical case. In real environments,
we encounter heterogeneities at the porous matrix level,
where it is well known and demonstrated that they induce
an increase of the Von Mises stress. In addition, theresults for a stratified medium show that solving suchproblems by using continuous media assumptions is far
too conservative.
6.

CONCLUSIONS

Geomechanical evaluations of the rock massproperties remain very important processes during
Underground Coal Gasification. An accurate stability
analysis of the consequence of UCG requires a global
characterization of the rock constituting the overburden.
All of the different factors contribute to instability of the174

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

host rock during and after the gasification process. Unlike
the stresses induced by void creation and theirredistribution (as encountered in conventional mining),
UCG introduced additional thermal stresses in the vicinityof the reactor. Thermal expansion may induce buckling orelastoplastic instability due to the increase of compressive
stresses. The problem, which can be defined as transientbifurcation, is quite complex. The shape of the cavity andits evolution in time remain an important parameter which
influences the stability of the host rock. Nevertheless, theevolution of the cavity in space and time has some randomcharacter due to the non-control of the parameters driving
the combustion process and also due to the effects of hostrock behavior. Caution must be taken when using a
specific technique for UCG simulation.
7.

ACKNOWLEDGEMENT

The work performed in this paper is supported by the
EU project COGAR, Grant Agreement RFCR-CT-201300002.

Peng S.S., Chiang H.S. (1984) Longwall Mining.
Wiley
Peng S.S., Zhang J. (2007). Engineering Geology for
Underground Rocks. Springer-Verlag, Berlin Heidelberg.
Shafirovich E., Varma A. (2009). Underground Coal
Gasification: A Brief Review of Current Status. Ind. Eng.
Chem. Res. 4 : 7865–7875
Somerton W. H. (1992). Thermal properties andtemperature-related behavior of rock/fluid systems.
Elsevier.
Speight J.G. (2013). The Chemistry and Technology
of Coal. Third Edition. CRC Press
Williams F. A. (1985). Combustion Theory The
Fundamental Theory of Chemically Reacting Flow
Systems Second Edition. Princeton University
Wolf K. H. A. A.(2006). The Interaction between
Coal Fires and Their Roof Rocks. Phd thesis, Delft
University of Technology

8. REFERENCES
Bell D.A., Towler B.F., Fan M. (2011). Coal
Gasification And Its Applications. Elsevier
Bhutto A.W., Bazmi A.A., Zahedi G. (2013).
Underground Coal Gasification: From fundamentals toapplications. Progress in Energy and Combustion Science39, pp. 189-214
Broek D. (1986). Elementary Engineering Fracture
Mechanics, 4th ed., Kluwer, Dordrecht
Den’gina N.I., Kazak V.N., Pristash (1994). Changes
in rocks at high temperatures. Geotechnological methods.
Plenum Publishing Corporation, pp. 472-777.
Dwivedia R.D., Goela R. K., Prasada V.V.R., Sinhab(2008). Thermo-mechanical properties of Indian and othergranites. International Journal of Rock Mechanics &Mining Sciences. 45, pp. 303–315
Fjaer E, Holt R M, Horsrud P, Raaen A M , Risnes R(1992) Petroleum related rock mechanics. Elsevier
Ide T.S., Pollard D, Orr F M (2010) Fissure formationand subsurface subsidence in a coalbed fire. International
Journal of Rock Mechanics and Mining Sciences. Vol.7:
81–93
Jaeger J.C., Cook N.G.W., Zimmerman R.W. (2007).
Fundamentals of Rock Mechanics. Fourth Edition.
Blackwell
Luo J., Wang L. (2011). High-Temperature
Mechanical Properties of Mudstone in the Process ofUnderground Coal Gasification. Rock Mech Rock Eng
44:749–754
Marc Software (2014). Marc user manual.
Peng S.S., Chiang H. S. (1982) Roof Stability inlongwall coal face. in Stability in Underground Mining,
Brawner C O ed. American Institut of mining,
Metallurgical and petroleum Engineers, Inc.

175

ISMS 2016

Paper No. 218
Escapeway Solutions
Allison Deadmana, Steven Durkinb, Vincent LawrencecaGeneral Manager, Safescape, Bendigo, Australia, 3551, allison@safescape.com
Managing Director, Safescape, Forrestfield, Australia, 6058. steve@safescape.comcMining Engineer, MMG Golden Grove, vincent.lawrence@mmg.comb

ABSTRACTThe requirement for secondary egress from underground workings has long been regulated in Australia. Escapeway
systems have evolved from simple airleg rising ladders and timber ladders to steel galvanized ladders and more
recently fully enclosed polyethylene ladders.
The polyethylene ladder - Safescape Laddertube - was introduced to the underground mining industry in 2010. It isa cylindrical, enclosed, modular plastic ladder designed for use in underground escapeways and access ways. The
design of Safescape Laddertube has many advantages, one of those being that it is enclosed therefore minimizing therisk to climbers of exposure to fretting rock. In ‘standard’ installations there have occionally been changes in the
ground conditions which have resulted in significant fretting or rock burst causing deformation in the Laddertube. In
addition there is on occasion a requirement to position an escapeway in ground that has highly stressed or squeezing
ground conditions, presenting mines with potential for failure of ground resulting in serious damage to theseescapeways.
As a result, Safescape have developed a number of proactive solutions that can be used at the time of installation
which will eliminate or minimize the effects of ground that is not ‘competent’. These solutions address the need forground support and eliminate the need for the traditional methods of ground support in a rise such as bolt and mesh,which also means we no longer need to put people in unsupported ground to complete this high risk work.
Despite being a recent development in escapeway systems, Laddertube is effectively being used in a variety of
applications, meeting the specific needs of underground mines worldwide.
KEYWORDS: Perlite; Laddertube; Ground support; Polyliner; Raiseliner

1. DEVELOPMENT OF LADDERTUBE
ESCAPEWAY LADDER
Legislation exists in all developed mining
countries covering the requirement for producing
mines to ensure miners working underground haveaccess to an alternative exit from working areas. The
primary reason for this is for insurance against asignificant ground collapse in the main travelway,
which would otherwise result in the entrapment of
personnel for an extended period.
In many mines with sub-horizontal orebodies ormines with excessive ventilation requirements suchas uranium mines, secondary egress is taken care of
by mining multiple primary accesses, multiple shaftsor declines accessible from all working areas. Where
sub-vertical mines exist with limited strike extent, themost common methods of providing secondary
egress include ladderways, raise climbers andheadframes with rope hoists.
Ladderways have historically been the preferredchoice where the length is limited. Compared to thealternatives, ladderways are more popular because
they are simple, self-escape systems and do not*Corresponding author – email : allison@safescape.com

require support from personnel on the surface. They
are relatively cheap to install and maintain and they
are reliable provided that they are maintained in goodcondition.
Up until recently the most common ladderways
found in Australian mines consisted of timber stiles
with 20 mm black steel rungs or a simple steel design(Figure 1a). Steel modular caged ladders (Figure 1b)offered additional support to the user in terms ofmesh cages and inclusion of rest platforms. One ofthe problems with these systems is that over time
when exposed to ground water they tend to
deteriorate. In 2010 Laddertube (Figure 1c) fully
enclosed polyethylene ladders were developed as analternative to conventional steel and timber ladders.
This style of ladderway has proven very popular
due to the speed and safety of its installation as wellas the fact that it does not corrode when exposed tothe highly saline and acidic ground water often foundin Australian mines.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016(a) Simple steel design (b) Steel cage (c) Laddertube
Figure 1: The evolution of escapeway ladders.

2. PASSIVE GROUND SUPPORT – A NEW
APPROACH
To date Safescape have installed as well as
trained site personnel in the installation of laddertube
in 9 countries, all of which have a variety of groundconditions.
The methodology and solution for
dealing with the ground conditions are each dealt
with individually to ensure the best possible outcome.
The two main methods of ground support used
where the rise is not already supported are Perlite fill
and Polyliner support.
2.1 Perlite
Perlite is used as a loose filled surface support
medium. It does not add strength to the excavation,
but merely stops any scats that become loose frommoving. This system is ideally suited to rock that is
subject to fretting over time or unravelling due tostress shadow changes. If the issue is low strengthrock with a high stress field there are better options
including the use of thick poly liners with concrete
fill in the annulus.
2.2 A case study – Xanthos Escapeway
Golden Grove Mine site is located in the MidWest region of Western Australia and has twocopper, lead and zinc producing underground mines.
It is owned by MMG Pty Ltd. and has been in
production since 1990. The mining method used inboth underground mines is a combination of verticalcrater retreat (VCR) mining and sub-level stopemining. On average, the underground operations
extract between 1.2-1.7 mtpa of both copper andzinc/lead based ore. The present mine life of six years
is expected to be extended based on the current
exploration program.
Gossan Hill, one of the two underground mines atGolden Grove has been in operation since 1998.
Over this period a ladder way system has beendeveloped as a second means of egress. Currently thisladder way system extends from the lowest levels of
the mine to the surface, a total of 1100m vertical. To
begin with the mine developed air-leg raises between
levels which were furbished with narrow wooden
ladders with steel rungs. As handheld mining becameless prevalent there was a shift to raisebore holes,
which were furbished with steel caged ladders. Steelcaged ladders had been installed in Gossan Hill since2000 up until 2010. During 2010, as a businessdevelopment program, Safescape Laddertube wasconsidered as a possible substitute for the steel caged
ladders. Cost, time and safety were all taken into
consideration when comparing the two.
Based on the comparison it was decided that
Safescape would be trialed, with the first ladder way
being delivered to site in December 2010 andinstalled in January 2011. Despite some challenges
when installing this initial Laddertube, it was decided
to continue using the Safescape product and sincethat time 11 separate Laddertube escapeways totaling
570m have been installed at Golden Grove.
Like most underground mines, Gossan Hill is everextending in a downward direction. The challenge
associated with this depth is the increased stresses
acting on mine openings. One of the inherent
advantages of using Laddertube was that the laddercould be installed in a smaller, more stable raisebore
hole which would not require any form of groundsupport. The second round of Laddertube installed at
Gossan Hill was in the lowest reaches of the mine inclose proximity to impending stoping activities. Even
with this smaller more stable raisebore hole,
problems were still encountered during the
installation phase of the Laddertube. The raise bore
hole was fretting, causing scat sized material todislodge and fall from the walls of the raisebore hole.
This was the first time Laddertube had been exposed
to such severe ground conditions.
Recommendations were made by Safescape to fill
between the outside of the Laddertube and raisebore
hole to limit the amount of rock material that could
continue to dislodge. The decision was made tocontinue with the install. Some months after theladderway had been installed, the Laddertube
experienced minor deformation. This was due tosmall scat sized material falling and accumulating
between the raisebore and the outside of theLaddertube. Stoping in the area had alreadycommenced and an acceptable material to fill thevoid had not been decided upon. This particularescapeway was never filled and shortly after stoping
was completed in the area the ladderway was
decommissioned as a result of substantial
deformation.
The next round of Laddertube installed at Gossan
Hill was in the upper region of the mine which had
more favourable ground conditions. This allowed
time to develop a means to fill the void which would
reduce the chance of the Laddertube deforming inother high stressed regions of the mine. Over a sixmonth period numerous types of material were177

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

trialed, ranging from washed aggregate to aerated
concrete. The final product which was decided upon
was a light weight, free flowing material called
Perlite. The material was relatively cheap and easy todeliver and install.
While Safescape had had success with concreteand cemented sandfill in the past, the downfall of thismethod is that Laddertube can only handle a static
hydraulic head pressure of 2 m of water. This meansthat concrete can only be poured in 1 m lifts, whichmakes for a slow and repetitive process to fill longer
escapeways.
The Xanthos ore body is a high grade region ofore located between 1000 m to 1600 m below thesurface. Mining of this ore body was set tocommence late 2013. Prior to any stoping activities
the installation of a 200 m long ladderway extending
from a neighbouring decline was required. A 1.5 m
diameter raisebore hole had been developed between
the Ethel and Xanthos declines in 2011. For a 12month period this hole was used to supply secondary
ventilation from the Ethel decline in order to top up
the low ventilation flows experienced in the Xanthosarea. This system was then later decommissioned
when the Xanthos primary ventilation (Figure 2)
upgrade was completed. Plans were then set in place
to furbish the 200m long raisebore hole in order tocreate a secondary means of egress for this region of
the mine.
Two options were presented to management at thetime. The first option was to go with the conventional
steel ladder with a mesh protective cage. This option
also required the raise to have ground supportconsisting of steel mesh and bolts. The second option
was to continue using the Laddertube product withthe additional protection of filling the void with
Perlite. The cost comparisons between the two
options were similar with the Safescape option
representing a 10% saving compared to steel and thetime frame available meant that the longer durationof the steel installation was not critical.
As a result, both cost and time were consideredminor benefits of the Safescape option. The next
consideration was whether the raise could be used tohouse additional services such as a rising main
dewatering pipe. The steel caged ladders had this as
an advantage over the Laddertube product as while it
could be installed outside of the Laddertube, it would
not be accessible for repairs in the future.This
requirement was later discarded and this factor was
made redundant and accordingly the final anddeciding factor was safety. When comparing thesafety of the two options the Laddertube product hasa clear advantage over the steel cage ladderway,
specifically as management considered the process ofbolting and meshing the 200m long raise as high risk.

Therefore Laddertube was decided upon as thepreferred option.
Perlite is the generic name for naturally occurring
siliceous volcanic rock. Perlite ore is crushed andscreened to various size ranges and then exposed to a
rapid heating process taking it up to 850oc at which
point the water inside the material vaporizes andcauses the softened rock to expand. Tiny glass likebubbles are produced which account for thelightweight and exceptional physical properties of
expanded perlite. The resultant lightweight productis a white granular material that handles and pours
easily. It provides a quick, inexpensive andpermanent method for filling vertical spaces.
Perlite has been the subject of numerous healthstudies conducted by scientific and governmental
research organizations. Significantly, no test result or
information indicates that Perlite poses any healthrisk. Indeed, the uniform result of all health studies
points to the conclusion that Perlite and perlite
products are safe for consumer use. As with all
workplace dusts, Perlite can function as a nuisancedust, so exposure limits are set at those levels. For
some workers, exposure can result in temporary
physical irritation, discomfort, impaired visibility andenhancement of accident potential. This nuisancedust was encountered during the filling process atGolden Grove and while the irritation caused could
be easily resolved by using dust masks or respirators,
the installers took the extra step to build a water
spray mist to help reduce the dust generated.
2.3 Project performance at Xanthos Escapeway
Installation of the Xanthos escapeway began in
the first half of 2013. Due to the additional
complexity of installing a 200 m ladder it was
decided to use Safescape technicians to complete theentire install as opposed to MMG personnel who had
previously been trained in the installation
methodology. The technicians arrived on site andcompleted a three day induction before any work wasundertaken. Setting up the site to commence theinstall required a full day. The time to install theentire 200 m was an additional two days. It then took
another days work to anchor and fit out the inside of
the Laddertube with rest platforms and a static line
fall arrest system. The entire install of the Laddertube
itself was completed in less than five days.
The placement of Perlite was undertaken by
MMG personnel. This required 230 cubic metres ofPerlite to fill the annulus between the raisebore andthe Laddertube. The first 100 m section and middle
46m section were undertaken without any issues but
during the placement of the bottom 46 m section rockmaterial was dislodged from the walls of theraisebore hole. This caused damaged to the178

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Laddertube which required remedial work to beundertaken by MMG personnel.
A jumbo was used to chip out the shotcrete seal
and bleed the slabs of rock that had fallen andsqueezed the Laddertube. Once this rock wasremoved, the Laddertube was pushed back to its
original shape and the seal was replaced before
completing the perlite fill process.

Figure 2: Xanthos primary ventilation network.

While Perlite fill provides mines with a passive
ground support solution, in some instances theground conditions require a more robust solution.
2.4 Polyliner ground support
Highly stressed or squeezing ground conditions
or rock bursts, present mines with potential for
failure of ground support and can result in serious
damage to escapeways. In the mining context, apractical definition for squeezing ground conditions
is when the total displacement of an excavation ormore specifically, the drive closure reaches at least
tens of centimetres within the life expectancy of a
supported drive. In general, mine drives are designed
to be in operation up to two years (ACG, 2015).
Installing conventional mesh and bolted groundsupport in escapeway rises is both costly anddangerous, while steel cans installed is a costly andtime-consuming process. An alternative to placing
individuals in unsupported ground to install groundsupport which would be quicker and more costeffective than existing solutions was the desired
outcome.
Faced with a number of sites which had
conditions that were resulting in ground failure andsubsequent damage to their escapeway ladders,

Safescape made the decision to investigate further asystem used in a client’s mine in Idaho, USA. Thissystem involves the installation of a thick poly liner
followed by a fill around of concrete in a single passwith the escapeway ladder then installed inside theliner (Figure 3).
The liner used by Australian clients is a productproduced by Enviropipes. The Enviropipe is dual
wall HDPE (PE100) or Polypropylene pipe that arecorrugated on the exterior and are smooth on theinterior. The standard dimensions are 1050 mm ID,
1216 mm OD, and weigh approx. 215 kg per 3 mlength. A larger dimension is available for sites that
required them. The modules are high performanceand very durable. The pipes do not rust, corrode,crack, shatter or degrade.
The liners are installed by lowering it down theraise and adding pieces, much the same as
installation of the Laddertube (Figure 4). Concrete isused to secure the liner in place and support the wallrock. The bottom of the raise is sealed and an initialpour is made to a height of 1m. The concrete is thenallowed to cure before pouring the rest inincrements. In an installation with a void space of
0.5 m the maximum concrete lift heights allowable
to avoid overstressing the pipe are as follows:- 1050 mm SN8 Enviroculvert – maximum
2.4 m concrete lift
- 1200 mm SN8 Enviroculvert – maximum
2.6 m concrete lift
A safety factor of 1.5 has been used indetermining the allowable fill heights. The following
assumptions have been used in the design
calculations;i.
The maximum differential concreteheight around the pipes perimeter is tobe no more than 200 mm
ii.
The allowable lift heights shall bemeasured parallel to the pipelineiii.
The concrete is assumed to have adensity of 2400 kg per cubic metreiv.
Due to the variable nature of the initial
set times of concrete and dependency
on admixtures, the initial set time fromthe time of concrete pour should berequested from the supplierv.
Consecutive concrete pours shall thenoccur at a minimum of 60 minutes after
initial set of the previous pour.

179

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

increases efficiency and safety hand in hand.
Safescape’s polyethylene escapeway ladders areproving a versatile and welcome addition tounderground mines in Australia and abroad.

4. ACKNOWLEDGEMENT
MMG site management
Safescape Administration and Operations personnel
Hecla Lucky Friday Mine

5. REFERENCES
Australian Centre of Geometrics 2015, Australia,
May
2016,
accessedon
24th
http://www.acg.uwa.edu.au/research/squeezing_task_force)Figure 3: Installation using Polyliner.

Figure 4: Installation setup for Polyliner.

The installation of polyliners has been successful
in providing sites with a cost effective, time efficientsolution and importantly, a safe installation process
to sites.

3. CONCLUSION
The Australian mining industry is known forleading the world in terms of productivity and safetyin underground mining. These escapeway projects
are examples of mine operators discarding the statusquo and finding a new way to work that both180

ISMS 2016

Paper No. 211

Estimating stope vein footwall stability using various constitutive modelling
techniques
Andrew Pyon, Atsushi Sainoki, Hani S. Mitri
Department of Mining and Materials Engineering, McGill University, Montreal, Canada, H3A 0E8

ABSTRACT
Operating in weak narrow vein mines presents many issues in terms of ore productivity. Maintaining stable mining
excavations and limiting unplanned overbreak are some of the main concerns in narrow vein mining. The use ofnumerical modelling has become a popular method because it is capable of examining stress patterns and identifying
rockmass failure. This paper will focus on creating a 3-dimensional constitutive numerical model for narrow veinmines that incorporate weak rockmass properties. The selected Case Study Mine is an underground narrow veinmine joining a weak material known as talc-chlorite-schist. The construction of this model will be associated withthe unplanned ore dilution determined by surveyed profiles from the mine site.
KEYWORDS: Numerical modelling; ore dilution; rock mechanics; underground mining; footwall stability; failure
criterion

1. INTRODUCTION
The selected Case Study Mine, located 50 km
west of Val d’Or, Quebec, Canada, was chosen forthis study as it held a weak rockmass known as talc
chlorite schist that presented important stability
issues in the stopes. Over the course of its operations,the existence of schist material represented 70% ofore dilution from planned stopes and over 1 metre ofwall displacements from drifts due to squeezing
ground. Such difficulties are not to be overlooked andare worth investigating.

2. ORE DILUTION IN NARROW VEIN
MININGOre dilution is defined as the unsolicited waste
rock caused by overbreak of stopes. A poor control ofdilution will induce the extraction of excess wastematerials, which will present more handling of therock as well as unnecessary additional costs. Rockoverbreak comes from several causes such as thequality of geology, ore continuity, planarity of thewalls and dip of the orebody (McCarthy, 1993).
There are a number of approaches to establish
overbreak benchmarks in stopes. The most common
ones are related to the relaxation of stope surfaces.
Relaxation typically occurs when tensile stresses are
created through opening of existing joints or thecreation of new cracks formed by induced stresses(Potvin, 1988). It is therefore projected that once therockmass exhibits mining-induced tensile stresses,
unplanned dilution occurs. This is stated as σ3≤0, i.e.
when σ3 is tensile. Other dilution criteria related torelaxation are: 1) -σ3≤ σt, i.e. when σ3 is tensile and islower than the tensile strength, and 2) when the*Pyon, A. – email: andrew.pyon@mail.mcgill.ca

rockmass yields (Zniber, et. al., 2009). However,dilution can take many other forms of failure such as
spalling, bending, wedge failure, crushing, etc. A
combination of these failure modes is also possible
leading to complex dilution occurrences. During theprocess of applying various numerical constitutive
models, failure conditions will be examined to get abetter grasp of rock behaviour.
3.

CASE STUDY MODEL

The Case Study Mine is located within the
Cadillac-Larder Lake Fault Zone. This zone contains
the Archean-age Piché Volcanic rock in which manyof the gold-mineralized structures are inside thehinges of the folds. There are 2 central groups ofrockmasses where mining will be detained. One is the
Piché group containing mafic to ultra-mafic talkchlorite schist combined with intrusive volcanic
rocks such as basalt. This group is known to behighly anisotropic in which the rockmass isextremely foliated.
The second group is called the Cadillac group
comprised mostly of fine grained sedimentary
Greywacke. The orebody is situated between these
two rockmasses with widths varying between 3 to 8
metres and 85° dip.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 1: Foliated schistose rockmass in footwall buckling
towards the drift (Case Study Mine).

4. METHODOLOGY

The stope of interest for this study is at a depthof 1040 metres from ground level. A Cavity
Monitoring System (CMS) was used to survey theoverbreak approximately one week after blasting.
Figure 2a shows a section view of the mined stope
profile. As can be seen, significant footwall dilution
and little hangingwall dilution took place. This ismainly because of the strong volcanic hangingwall
basalt rock. Cablebolts were installed in the drift
sidewalls. It is worth noting that other influencessuch as stope undercut, blasting and drilling were notaccounted for in this model. The model contains sill
drifts in between openings. Stopes are locatedmidpoint of the Orebody Zone in which it dips at anangle of 85° south. Figure 2b shows the final
isotropic view of the model along with its
dimensions.

a)
4.1 NUMERICAL MODELLING SOFTWARE:
FLAC3DTo perform an in depth dilution analysis in a 3dimensional medium, FLAC3D (Fast Lagrangian
Analysis of Continua) was selected. This software isa 3-D finite-difference program that uses well defined
numerical formulations between geotechnicalmaterials (Itasca, 2012). Geometric models arearranged by polyhedral elements in which failurelaws are given based on elastic or plastic behaviours.
The main advantage of using this tool is its ability toaccurately represent the effect of plasticity in a 3-D
medium. This is most suitable for ductile materials
similar to the case of the Piché group at the Case
Study Mine.
4.2 MODEL SETUP
Since the rockmass structures are fairly
continuous at steep dips, it is best to construct themodel into layers. 4 sections have been assigned to
distinguish the main alterations within theheterogeneous nature of the rockmass. These are
Volcanic Zone, Orebody Zone, Weak Schist Zone andSediment Zone. Each of these layers consists ofdifferent rock compositions based on geologicalmapping of the Case Study Mine. The extents ofthese zones are defined when there are prominentchanges in the arrangements of the rock. The model
is designed as a brick and each boundary is widened
to at least 5 times the size of one stope allowing
calibration for far field stresses. Smaller meshes wereapplied in the area of interest and were graduallyenlarged towards the boundaries. Meshes were
adjusted until displacements and stresses converged
to a stable state. The final model contains 1,234,800
elements.

Green: Planned
Pink/Purple: CMS profile

b)
610 m

650 m

NORTH OR X DIRECTION

c)
VOLCANIC

OREBODY/
STOPESSEDIMENTWEAK SCHIST

Figure 2: Case Study Mine Model a) Surveyed profile ofthe stope b) Perspective view c) Side view against the xaxis.

4.3 ROCKMASS CLASSIFICATION OF CASESTUDY MINE
Based on laboratory tests and field observations,
rockmass parameters have been compiled into a
database. Uniaxial compressive strength tests (UCS)
were performed on intact core samples to acquire
UCS values, the intact Young’s Modulus of Elasticity(Ei), poisson’s ratio (ν) and intact Hoek & Brown fit
parameter (mi). The Damage Factor (D) was also
obtained from underground field observations.
Rock samples were classified as Sedimentary
Wacke rocks, Intrusive Volcanic rocks and Schistose182

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

rocks. Once compiled into a database, Hoek &Brown parameters are calculated to translate into
equivalent rockmass values (Hoek & Brown, 2002).
These were further converted into Mohr-Coulomb
parameters with a best-fit linear relationship between
major and minor principal stresses. Doing so,
attaining equivalent equations for the angle of friction(ϕ’), cohesive strength (c’) and tensile strength (σt’)
for each rockmass are made possible.
FLAC3D also requires using elastic constants
such as Bulk Modulus (K) and Shear Modulus (G) to
specify volumetric change and shear resistance ofrocks. These are found by incorporating the Young’s
Modulus of Elasticity for the rockmass (Erm) andPoisson’s ratio (ν):
𝐸
𝐾 = 𝑟𝑚(1)3(1−2ν)𝐺=

𝐸𝑟𝑚

2(1+ν)(2)

5.

NUMERICAL STRESS RESULTS

Before moving on, it was necessary to examine
the stress fields before selecting a representative
constitutive model. FLAC3D’s Ubiquitous Joint
Model was selected for the weak material since it
accounts for plasticity and anisotropic behaviour of
the rockmass. All other rock zones will be evaluatedas isotropic elastic models due to its brittleness.
When excavating the first primary stope, lower
stresses (-2 to 25 MPa) are observed in the Weak
Schist Zone while high stresses (20 to 50MPa) are in
the host rocks. Note that in FLAC3D, negative
numbers refer to compressive stresses and positive
numbers refer to tensile stresses. The major (σ1) andintermediate (σ2) principal stresses have relatively
similar values in the schistose zone (0 to 25 MPa).
As for the minor principal stresses (σ3), few pocketsof negative stresses are observed on the footwall face.
This shows the presence of relaxation occurring in
the abutment’s surface.

The dilation angle ( 𝜓) , a function of volumetric𝜙′change, is measured as 𝜓 = .
4
The final rockmass properties are given in Table 1.
4.4 IN-SITU STRESSESIn order to reach a more realistic approach,stresses were applied on the boundaries of thenumerical model. Doing so, an uneven distributionof internal stresses will travel through the different
layers of rock. Stresses will be re-adjusted dependingon the properties of each material before moving onto the next (R.P. Bewick, 2009). The applied stresses
were adapted to stress tensor results that werepreviously measured (Arjang, 1996). The bottom
boundary is fixed with rollers and vertical stress (σv)
was applied on top with the following equation:
𝜎𝑉 = 𝛾𝐻(3)

Where γ is the average unit weight of the rockmass in
MN/m3 and H is the depth of the mine. Additionally,
stresses were applied on the x and y axes until thetensor values were achieved. The tensor is at a depthof 900 metres below surface with σmaximum=51.8 MPa,
σintermediate=35.8 MPa and σminimum=19.0MPa. This was
assumed to be positioned at coordinates x=300,
y=305 and z=350 in the Sedimentary Zone of themodel. It was also ensured that this tensor was
within 300 metres of model boundaries to account for
far field stresses. The final stresses that were appliedon the boundaries were determined to be σxx=50MPa,
σyy=21 MPa and σzz=18 MPa.

Figure 3: Post-mining section view of minimum principal
stresses (σ3).

The directions of these stresses were also
perceived by looking at the σxx, σyy and σzz contoursof the model. The stress contours in the y-axis (σyy)
of the model displays the highest values which
depicts the maximum principal stresses. The stresses
in vertical direction (σzz) correlate with theintermediate principal stresses. The stress contours
in the x-axis (σxx) shows the lowest, hence, minimum
principal stresses.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Selected rockmass parameters for numerical modelling study.
Young's M odulus (Erm ) GPa

HW Basalt

Orebody

FW Weak Schist

Sediment Wacke

18.9

7.29

2.17

23.3

Bulk M odulus (Krm ) GPa

9.27

3.8

1.13

1.14

Shear M odulus (Grm ) GPa

8.15

3.09

0.92

10

Cohesion (c) M Pa

4.9

2.7

2.2

4.3

Friction Angle (ϕ)°

44.2

31.5

27

42.7

Dilation (ψ)°

11

7.88

6.8

10.68

Tensile Strength (σt)

-0.3

-0.05

-0.05

-0.2

Poisson's Ratio (ν)

0.16

0.18

0.18

0.16

6. DILUTION FAILURE MODES AT CASESTUDY MINE
6.1 RELAXATION (TENSILE) FAILURE
As previously mentioned, relaxation of rockoccurs when the expansion of joints loosens the rockand falls off due to gravity pull. In this model, thefailure criterion is expressed as σ3<0. FLAC3D’s
Elastic Transversally Isotropic (Anisotropic) model
was chosen for the Weak Schist Zone. A Young’s
modulus ratio of 1 to 7 was chosen in direction
perpendicular to the planes of weakness. Figure 4
shows the areas of relaxation (in red) and the CMS
profile of the first excavated primary stope (in white).
A fine layer of tensile failure is observed in the
footwall which is underestimating CMS results. Thismethod is thus not recommended to analyze ore
dilution in weak rock properties. Although tension isclearly shown in field observation, the rock’s ductile
behaviour renders the no-tension model ineffective.

6.2 BIAXIAL FAILURE
Biaxial failure occurs when poly-axial loadingnear rock surface causes an accumulation of mininginduced planar stresses (Yun et. al., 2010). This inturn can cause a wide variety of failures such as
spalling, slabbing, buckling and crushing. An Elastic
Transversally Isotropic (Anisotropic) constitutive
model was selected in order to account for highstresses and disregarding the effect of material’s peakstrength. σ1 and σ2 results show that the tensor values
in the Weak Schist Zone range from 0 to 90 MPa.
These values were then plotted in order to see if a
failure pattern exist. Figure 5 illustrates a σ1/σc versus
σ2/σc plot where σc represents the UCS of intact rock.
Tensors were grouped by their σ3 values and divided
by σc for normalization purposes.
3.5
3
2.5

σ3(10MPa)

Figure 4: No-tension (σ3<0) analysis in elastic transversally
isotropic (anisotropic) model.

CMS
σ3(20MPa)1

σ3(30MPa)
Poly. (CMS)

0.5
0
0
-0.5

CMS

σ3(5MPa)

1.5

-0.5

Red=σ3<0
Blue=σ3>0

Surface2

σ1/σcFrom these observations, the highest stresses
occur in the y and z directions, both parallel to thefootwall abutment. This suggests that a spalling or aslabbing type failure might arise.

0.5

1

1.5

2

2.5

3

σ2/σc

Figure 5: σ1/σc vs σ2/σc tensors along footwall width.

An increase in biaxial stresses was observed as it
went deeper into the footwall. With an increase in σ2,σ1 rises until it reached equilibrium of 90 MPa. A
best fit polynomial was then conducted for tensors
along the CMS overbreak profile which showed thatσ3 ranges from 10 MPa to 30 MPa. Given that theranges of biaxial stresses along the overbreak outline
are 2.19 < σ1/σc < 3.07 and 1.04 < σ2/σc < 2.02, it canbe made possible to evaluate dilution profiles in184

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

foliated talc-chlorite-schist as a result of biaxial
loading. However, further models are needed tovalidate these results.
6.3 SHEAR AND TENSILE YIELDING
Shear or tensile yielding was analyzed byconducting a Ubiquitous Joint Model. This
constitutive model takes into consideration planes of
weakness on a perfectly elasto-plastic MohrCoulomb model. Failure criteria are designated by its
Mohr-Coulomb envelopes as well as the weak-planeof failure. Additional joint properties were employedwhich were dramatically reduced from the rockmass
properties (0.5 MPa for joint cohesion and 12° forjoint friction angle). This was done to reflect theutmost critical joint conditions. Figure 6 shows theyielding states on the model before excavation.

𝜀𝜀 = �

2
922

��𝜀𝑥 − 𝜀𝑦 � + �𝜀𝑦 − 𝜀𝑧 � + (𝜀𝑧 − 𝜀𝑥 )2 �
12
2
2
+ (𝛾𝑥𝑦
+ 𝛾𝑦𝑧
+ 𝛾𝑧𝑥
)

(4)

3

Where:
ɛx, ɛy and ɛz = total principal strain in the x, y and zaxis, respectively.
γxy, γyz and γzx = total shear strain in xy plane, yz
plane and zx plane respectively.
For this analysis, the Ubiquitous Joint model was
selected to account for the plasticity of the rockmass
and planes of failure. Given that the material behaves
as a perfectly-elasto plastic model, it is essential todetermine at what strain amount will be affected bydilution. Since failure occurs when there ispermanent or irreversible strain in the material, it isrequired to measure the amount of strain from thepoint of yield stress to the point of dilution as shownin Figure 7, which is also known as the Equivalent
Plastic Strain or E.P.S.
Yield Stress

Point of dilution

E.P.S.

Figure 6: Yielded states of Case Study Mine model before
excavation with directions of applied loads.

The weak material undergoes shear and tensile
yielding in its entirety as indicated by the green, red,
purple, cyan and pink colors (the “-n” in the legend
signifies failure now and “-p” signifies failure in pastiterations). This is primarily due to the effect of
having weak material constrained within stronger
materials. The arrangement of rocks will cause highloads on the weaker material, which results inyielding. Evaluating shear or tensile yield in response
to dilution is therefore not desirable since yielding
has occurred prior to excavations.
6.4 EFFECTIVE PLASTIC STRAIN FAILURE
The Effective Strain is defined as the amount ofbody rotation and distortion due to deviatoricprincipal strains. Uneven amounts of strains in theprincipal directions can cause the material to change
its shape and volume. This behaviour can ultimately
obstruct the rockmass and result in dilution. The
Equivalent Total Strain (ɛɛ) is calculated according to
the following equation (Xia and Wang, 2001):

Figure 7: Illustration of perfectly elasto-plastic curve andapplied E.P.S.

The Effective Plastic Strain generated amounted to
15% to achieve the CMS overbreak profile as shownin Figure 8.
Although the use of Effective Plastic Strain gives
fair results in identifying ore dilution, more studies
are needed for validation; especially since thegeological and mining conditions fluctuate at varying
depths.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 8: Comparison of CMS profile with 15% Effective
Plastic Strain (midpoint).

7. CONCLUSIONSThe no-tension model proves to be ineffective
due to the minimal tensile in the footwall. However,
failure under biaxial loading condition is noticeable
due to the stresses applied on the stope footwall face.
This needs to be validated with other stope models
for future studies. From the Ubiquitous Joint Model,
the shear and tensile yields cannot be implemented
since yielding states occur at pre-mining stages. This
event is primarily caused from the application of highloads of the stronger rockmasses into the Weak Schist
Zone. Finally, the Effective Plastic Strain has been
examined. The actual (measured) overbreak of thestope corresponds to 15% Effective Plastic Strain.
Although these results are encouraging, further
studies are needed to validate this method.

International Journal of Rock Mechanics and Mining
Sciences. Res. 44: 5, pp. 692-703
Hoek, E., C.T. Carranza-Torres and B. Corkum.
(2002). Hoek-Brown failure criterion - 2002 edition.
In Proceedings of the Fifth North American RockMechanics Symposium and 17th Tunneling
Association of Canada Conference, Toronto, 7-10
July 2002, pp. 267-273
ITASCA (2012). FLAC3D - Fast Lagrangian
Analysis of Continua. 5.0 ed. U.S.A.: Itasca
Consulting Group Inc.
McCarthy, P. (1993). Economics of Narrow
Vein Mining, Narrow Vein Mining Seminar, The
Australasian Institute of Mining and Metallurgy,
pp.89-97
Miller, F., Potvin, Y. and Jacob, D. (1992). Laser
measurement for open stope dilution. CIM Bulletin
1992, pp.85:96-102
Potvin, Y., (1988). Empirical open stope designin Canada. PhD. Thesis, University of British
Columbia, Vancouver
Xia, K. and Wang, J. (2001). Shear, Principal,
and Equivalent Strains in Equal-Channel Angular
Deformation, Metallurgical and Materials
Transactions A, Volume 32A, pp.2639-2647
Yun et. al., (2010). Experimental Investigation
into Biaxial Compressive Strength of Granite.
International Journal of Rock Mechanics & Mining
Sciences. 47. pp.334-341
Zniber, E. M., et. al. (2009). Effect of stope
undercutting on its wall overbreak. Proceedings 43rd
US Rock Mechanics Symposium, held in Asheville,
NC June 28th – July 1, Paper No. ARMA 09-200

8. ACKNOWLEDGEMENT
This research paper was made possible throughthe help and support from the members of the McGill
Mine Design Lab team.
9.

REFERENCES

Arjang, B., (1996). In situ ground stresses in the
Abitibi Mining District. CIM Bulletin, 89, no. 996,
p.65-71.
Bewick, R.P., Valley, B. and Runnalls, S.
(2009). Global Approach to Managing Deep Mining
Hazards, Proceedings of the 3rd CANUS RockMechanics Symposium, Toronto, May 2009, Paper
3994
Brewis, T. (1995). Narrow Vein Mining 1 –Steep Veins. Mining Magazine. Vol.173, No.3,
pp.116-130
Henning, J. and H.S. Mitri (2007). Numericalmodeling of ore dilution in blasthole stoping.

186

ISMS 2016

Paper No. 197

Redesigning the geometry of the Makala Coal Mine to improve safety andproductivity
Jean-Pierre Tshibangu*, Fanny Descamps
Department of Mining Engineering, University of Mons (UMONS), Mons, Belgium, 7000

ABSTRACT
Makala is a room-and-pillar coal mine situated in the Katanga Province (DR Congo), close to the city of Kalemie(eastern part of the country). It exploits the so-named Lukuga Coal Basin, which is composed of four coal seams
numbered 1 to 4. The economically mineable are 1 (about 2m thickness) and 2 (1 to 1.5m thickness). This coal basinshows some similarities with south-African deposits (Cahen 1961, in Carte Géologique du Zaïre). From the West thedeposit plunges towards the East with an average dip of 8°. Mining operations using room-and-pillar method started
in 1914 on the northwestern part of the deposit, following the outcrops of coal seams. Currently only seam 1 is being
mined out and the workings are being developed southwards to avoid the higher overburden towards the East.
Despite the increasing thickness of the overburden, the geometry of the method does not vary, and consists of rooms
4m wide and pillars of 8x6m, leading to a recovery of about 60%. The main gallery lays from North to South formore than a kilometer. Panels situated on the western part of the main gallery are composed with stable pillars,
while on the eastern part one can observe some typical problems like pillar fracturing, ground heave and roof falls.
In this last case we noticed that the roof of seam 1 is of poor mechanical quality.
In order to understand the geomechanical problems, we first built a 3D geometrical model, updating the mine layout
and incorporating both geological and topographical data. This modelling has been achieved using the GEOVIAGEMS software. The approach helped in assessing as accurately as possible the overburden to be taken into accountwhen calculating the weight to be supported by pillars. From the defined geometry, we used the modified tributaryarea method (Brady and Brown 1999) to redesign the pillars accordingly. 2D numerical modelling has been used aswell to assess the stability of the roof and dimension timber support used in the mine.
KEYWORDS: room-and-pillar mining, mine design, tributary area

1. INTRODUCTION
Makala is a room-and-pillar coal mine situated in
the Katanga Province (DRC), close to the city ofKalemie. This coal basin was discovered in 1911 andmining started in 1914 on the northwestern part of thedeposit, following the outcrops of coal seams.
Currently, only seam 1 is being mined out and theworkings are being developed southwards to avoid
the higher overburden towards the East.
Despite the increasing thickness of theoverburden, the geometry of the method does notvary: it consists in 4m wide rooms and 8x6m pillars,leading to a recovery of about 60%. Whereas panels
situated on the western part of the main gallery arecomposed of stable pillars, typical problems areencountered on the eastern part: pillar fracturing,ground heave, and roof falls. In addition, the roof ofseam 1 is of poor mechanical quality.
This study intends to understand thegeomechanical problems and propose a new designfor the pillars accounting for the increasing depth ofthe orebody. Meanwhile, a 2D numerical simulationis conducted to assess the stability of the roof anddimension of the timber support used in the mine.

2. GEOLOGICAL CONTEXTThe Katanga coalfields (Luena, Lukuga…) aresimilar to southern African ones (Cahen 1961, in
Carte Géologique du Zaïre). The coal deposits wereformed during Permian and Carboniferous ages andresulted in lenticular coal seams with a high ash
content and highly volatile matter content. Different
explorative works have been undergone in the area
(1930, 1953 to 1954, early 2000…) but the mostcomplete geological description is the one from
Jamotte (1931) which is based on 15 core drillings(total length 1800 m), trenches and outcrops
observation. Table 1 gives a typical succession ofgeological formations as observed in drillholes S1and S4.
The Makala mine is located in the Lukuga Basin(Figure 1). The orebody has been affected by faults
during the formation of the Tanganyka graben.

*Corresponding author – email : jean-pierre.tshibangu@umons.ac.be3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Geological formations in the seam 1
neighborhood.
Thickness
S1 (m)

Thickness
S4 (m)

H3: feldspathic sandstone

4

3.72

Seam 2 with a footwall of
psammitic sandstone

0.9

1.15

H2: zone Psammites, sandy
sometimes

1.8

3.33

H1: coarse sandstone,
feldspathic, conglomeratesometimes

4.13

7.3

Seam 1 with a footwall ingrey argillaceous shale

2.4

1.81

Psammites and black shales
with coal

2.85

2.29

Geological formation

The mined area is situated to the East of the
Hôpital Fault and to the South of the Lukuga River,where the thickest outcrops of seam 1 have beenfound in the Nikuha Valley. The orebody strikes in a
N-S or NE-SW direction, with an 8° dip to the E-SE.
Figure 2 gives a typical cross-section of the orebody
showing the increase of the overburden towards theEast.
According to the available data (Woitrin andDelvaux), if we consider the panel defined by the
200m barrier pillar separating the mined area fromthe Lukuga River, the Hôpital Fault to the West, theKaniki Fault to the South-West and the Kandeke
Fault to the East, the coal in seam 1 may represent 7
642 250 mineable tons. This assessment is based on a
2 m thickness of the seam 1 and a recovery of about
60% by the room-and-pillar mining. Mining seams 2
and 3 could also represent another 7 642 250 tons.
For the whole basin, Cailteux (2006) assesses thecoal reserves to more than 75 million tons, meaningthat this area has interesting potential.

Figure 1: Geological map of the Lukuga coalfield (modified from EGMF, after Jamotte 1931.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 2: Typical cross-section of the orebody through drillholes I, II, V, VI, VII, XI (Jamotte 1931). A, Mikamba Fault. B,
Kaniki Fault. C, Fault. D, Mulumba Fault.

Figure 3: Mining map at Makala. In red, the main access from surface to the face.

3. MINING METHOD
Generally, only the seam 1 is mined even if insome areas the seam 2 has been also mined. Since
1914, the deposit has been mined by a room-andpillar method with abandoned pillars. The mining
operations started on the northern part and evolved
towards the South. An abutment pillar with a widthof 200 m has been left to the North to prevent water
income from the Lukuga River (Figure 3). The main
access is an inclined shaft that follows the seam andoriented according to the dipping. It crossed the
Nikuha Fault and, due to the slip of this fault (8 m),
the seam 2 has partly been mined in this area before
the shaft joins again seam 1.

The inclined shaft is used for coal extraction tosurface by means of a conveyor belt. It joins a
directional gallery (or main gallery) with a N-S
direction. This gallery is surrounded by a row oflarge pillars (20 x 6 m) for stability purposes. The
longest part of the conveyor belt is installed in thisdirectional gallery (more than a kilometer). A
parallel way situated westerly with respect to thedirectional gallery is dedicated to workers.
When developing the layout, panels are createdevery 100 m along the directional gallery, leaving a
row of barrier pillars (40 x 20 m) between panels.
When the main gallery is mined out for a panel, 4m-wide raises and declines are mined on dip before
cross-cutting the long pillars. Residual pillars in the1893rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.2 3D geometrical model of the overburden
A geological model needed to be built andcoupled to the topography and the geometry of theworkings in order to assess the thickness of theoverburden. 13 drillholes described by Jamotte(1931) and a recent topography were used for thispurpose. Mining data included an Autocad filedelivered by EGMF for older workings, an up-to-date
paper mine map (1/1000) and a recent file withsurvey data dealing with the access ways. We built
the model using the GEOVIA-GEMS software.
The seam 1 is known to cross some faults but theirposition is not precisely documented. Therefore, theseam has been modelled as a monocline and its
extension is limited to the surroundings of the minedarea.
Based on available data, the geometry of themining works has been modeled. Several verticalcross sections (W-E) have been plotted through the
3D geometrical model. Figure 4 shows the verticalcross-section 800N on which one can observe the

Figure 4: The 800N vertical cross-section showing the trace ofseam 1, surface topography, and a description of a borehole.
820
800
780
760
740
720
Top
Bottom

700

1400

1300

1200

1100

900

1000

800

700

600

500

400

300

200

680

0

4.1 Rock mass qualification and mechanicalproperties of the rocks
The roof is made of an argillaceous material, withvery bad mechanical behavior. In some places, mainly
at crossings, roof falls are observed, leading to 50 cm
to 1 m depth holes in the roof. A new pilot-gallery to
be enlarged for a decline has been dug in 2011 toaccess the southern part of current mining operations.
It is intended to improve ventilation. During theauthors’ visit on site, bad quality rocks were observed
along its side walls.
A more detailed evaluation of the quality of therock mass has been performed, using the Rock Mass
Rating (RMR, Bieniawski 1973, 1984) and the
Geological Strength Index (GSI, after Hoek and
Brown 1998). Following the rock description along
the new decline, the RMR is estimated between 20
and 40, corresponding to a poor quality rock mass.
The
GSI
parametersareconsideredas“blocky/disturbed” and “poor” to “very poor”,
leading to GSI values of 25-30 for the coal seam 1
and the hanging wall.
In terms of mechanical properties, noexperimental data were available for the coal, thehanging and the foot wall. The properties wereassessed using bibliographic data (Vutukuri andLama 1974, Hoek and Brown 1998) and byconsidering the low RMR value. The pillar strength isestimated to 5 MPa.

100

4. NEW DESIGN FOR THE MAKALA MINE

dipping of seam 1 from left to right, the waving
topography, and the description of a core drillhole.
In order to assess the overburden, Figure 5 gives
the minimum (bottom) and maximum (top)elevations measured on each vertical section. The
deepest works are found in the 800N cross-section
but in this case an assumption was made on the
topography due to missing data.

Elevation (m)panel have dimensions of about 8 x 6 m, giving atheoretical recovery of about 60%.

Vertical cross-section (m to the North)Figure 5: Measured elevations (top and bottom) in thevertical cross-sections from the 3D model.

4.3 New pillar design based on modified the tributaryarea method
The tributary area method (Brady and Brown
1999) is widely used in room-and-pillar mining
design. The approach is accepted when the panel
width is larger than the depth of the mined area. In
the Makala mine case, this method can be considered
as valid since the depth is about 50-60 m for 100 m
panels.
The method for pillar design is rather simple but,due to the quality of the available data, it seems
sufficient in comparison to more sophisticatedmethods like numerical simulations. The pillar
strength is given as:(1)
R p = R0 h α w βwith Rp, the pillar strength, R0, the rock strength, h, thepillar height, w, the pillar width. Parameters α and β190

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.4 2D numerical simulation for assessing thestability of the roof and timber support
This approach is intended to better understandthe mechanical behavior of the roof and adjacentpillar, and then assess the loading on support.
We assume a plane strain geometry (longcontinuous pillars) for a typical case occurring at
60m depth, and for two sets of mechanical properties
corresponding to rock mass of either medium or poor
quality. Computations were performed using theFLAC2D software.

Figure 7: Yielding around a pillar in the case of a poor
quality rock mass.
3

H-10

2,5

Safety factor

are assessed to -0.8 and 0.5 respectively, following
values from the literature (Brady and Brown 1999). In
the Makala mine, we obtain a pillar strength of 6.36
MPa.
The safety factor is defined as the ratio between
the pillar strength to the mean vertical stress.
Considering a mining depth of 60m and a specificgravity of 25 kN/m³, the vertical stress before miningis 1.5 MPa. The ratio between the surface of the area
supported by the pillar and the section of the pillar is
2.5 and the stress on the top of pillars is 3.75 MPa.
The safety factor equals 1.7.
The assessment of safety factors is based on
empiricism. Salamon (Brady and Brown 1999)
studied the performance of South-African coal mines
pillars. From his analysis, one can see that intact
pillars generally correspond to safety factors between
1.3 and 1.9. A reasonable approach for the Makala
mine would be to suggest a safety factor of 1.6.
Due to the dipping of the seam, the pillar
dimensions should change with the depth. In
particular, the pillar size could be reduced inshallower panels resulting in an increased recovery.
However, for deeper areas, the pillar size should
increase and additional support may be necessary.
We computed the variation of the safety factor
with the pillar width for various mining depths(Figure 6). The abacus indicates that for a depth of
90m, with the current assumptions,, a 1.6 safety
factor cannot be reached even with 10 m wide pillars.
Based on the abacus, the pillar width iscomputed for a given depth in order to reach a safety
factor of at least 1.6. The recovery ranges from 85%
at a depth of 10 m to 52% for a depth of 70 m.

H-30
H-50

2

H-70

1,5

H-90
H-110

1

H-130

0,5

H-150

0
0

2

4
6
Pillar width (m)810Figure 6: Safety factor as a function of pillar width forvarious mining depths.

Figure 7 corresponds to a case of poor qualityrock mass when no support is installed. It shows atypical result gathered in terms of failure andplasticity and one can observe that both side walls,
roof and ground are severely affected. In this casesome support is to be envisaged, for instance byusing roof bolts, or reduce the size of the rooms assuggested in section 4.3.
Depending on the technology and the distance atwhich the support is placed with respect to thecurrent face, the extension of the damaged (or failed)zone can be limited. Different techniques can beenvisaged: roof bolts, shotcrete, steel arches, etc. but
the region of Makala is difficult to access for usual
supplies. For roadways (4 m width), we thenrecommended mainly the use of either timber support
or steel sets because the components can be accessed
locally. For timber, we assessed the diameter of 15 to
17 cm, while for steel sets a H19 type was191

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

recommended. The normal spacing is 1 m from a set
to the next but this can be reduced when geologicalconditions are very poor. A shotcrete can also be
used for long duration roadways and galleries.

5. CONCLUSIONSThe Makala mine in DR Congo has been minedsince the early 20th century using a room-and-pillar
method. Despite an 8° dipping deposit, thedimensions of pillars and rooms do not change withthe depth of operations, involving a low recovery at
low depth and potential stability problems at higher
depth. Geological studies have emphasized theremaining resources in the coalfield and a new designof the mine was necessary to improve recovery andensure stability of future works.
During a visit undergone in 2011, the authors
observed typical stability problems consisting in roof
fall and ground heave for most of stopes situated on
the eastern part of the main gallery. In order tounderstand the mechanical behavior of pillars, a 3Dmodel was built including geological data gatheredfrom drillholes, an updated general layout of theworkings (mine map), and the surface topography.
Analyzing the built model allowed an assessment of
the variation of thickness of the overburden above thedeveloped mine.
In a second step, the modified tributary area
method is applied in order to assess the safety factor
and also propose, for a given safety factor that wechose to be about 1.6, pillar dimensions depending on
the mining depth.
Finally, a numerical simulation using the finite
difference method is undergone in order to assess thestability of the working based on different sets ofmechanical properties of the rock mass. To enforce
safety, some recommendations have been made forsupport, especially for roadways and main galleries.

Hoek, E., Brown, E. (1998) Practical estimatesof rock mass strength. International Journal of RockMechanics and Mining Sciences, 34 (8), pp. 11651186. Elsevier.
Jamotte, A. (1931) Contribution à l’Etude
Géologique du Bassin Charbonnier de la Lukuga ;Comité Spécial du Katanga, Annales du Service desMines.
République du Zaïre, Département des mines –Direction de la Géologie, 1974. Notice Explicative dela carte géologique du Zaïre au 1/2 000 000.
Vutukuri, V. S., Lama, R. D., Saluja, S. S.
(1974) Handbook on mechanical properties of rocks:
testing techniques and results, Volume 1, Trans Tech
Publications.
Woitrin, M., Delvaux, B. (1984) Charbonnages
du Tanganyika, informations générales ; internalreport.

6. ACKNOWLEDGEMENT
The authors acknowledge HeidelbergCement for
funding this research.

7. REFERENCES
Bieniawski,
Z.T.
(1973).
Engineeringclassification of jointed rock masses. Trans S. Afr.
Inst. Civ. Engrs 15, pp. 335-344.
Bieniawski, Z. (1984) Rock mechanics design inmining and tunneling. Balkema, Rotterdam.
Brady, B.H.G., Brown, E.T. (1999) RockMechanics for underground mining. Chapman &Hall, Kluwer Academic Publishers – London.
Cailteux, J. (2006) Le charbon de Makala,synthèse géologique et de son exploitation. Rapport
interne EGMF/DRD numéro RT031.

192

ISMS 2016

Paper No. 69

Shear behaviour of regular and irregular rock joints under cyclic conditions
S. M. Mahdi Niktabara,*, K. Seshagiri Raoa, Amit Kumar Shrivastavabab

Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi, India, 110016
Department of Civil Engineering, Delhi Technology University, New Delhi, India , 110042

ABSTRACTRock masses often have sets of joints or fractures and almost all failures are due to the presence of these
discontinuities. Natural joints have irregular surfaces, and the correct evaluation of shear strength and deformationof these irregular joints is very important for the analysis and engineering design of rock structures. These joints areoften subjected to dynamic loads because of earthquake and blasting during mining and rock cutting. Hence, it isimportant to correctly evaluate the shear behaviour of regular and irregular rock joints under dynamic conditions. In
the present study, synthetic rock joints are prepared with plaster of Paris and regular joints are replicated by keeping
regular asperities with asperity angles 15°-15° and 30°-30°. Irregular rock joints are prepared by keeping theasperity angles 15°-30° and 15°-45°. The sample size and amplitude of roughness are kept constant for both regularand irregular joints, at 298×298×125 mm and 5 mm respectively. Shear tests have been performed on these joints
with a large scale direct shear testing machine by keeping the frequency and amplitude of shear loads constant undercyclic load conditions and varying the normal stress. The shear strength of rock joints increases with increase in theasperity angle and normal load during the first cycle of shearing. With the increase in the number of shear cycles,
the shear strength reduces for all the asperity angles, but the rate of reduction is greater in the case of high asperity
angles. Test results indicate that the shear strength of irregular joints is higher than regular joints at different cyclesof shearing at low normal stresses. The mechanism of the shearing for regular and irregular joints is different under
the cyclic conditions at low normal stresses. Shearing and degradation of joint asperities on regular joints between
loading and unloading are the same, but for irregular joints they are different at low normal stresses. Shear strengthand joint degradation are more significant on the slope of asperity with higher angles on the irregular joint, until two
angles of asperities become equal during the cycle of shearing and it starts to behave like a regular joint.
KEYWORDS: Cyclic shear behaviour; shear strength; regular joint; irregular joint; joint dilation

1. INTRODUCTION
Shear stress and deformation behaviour of rockjoints play an important role for design and analysis
of underground structures, foundation, slope stability
and risk assessment of underground disposal. Many
researchers in the field of rock mechanics and rockengineering have presented the shear behaviour ofjointed rock, based on peak stress-strain along thejoint under unidirectional or monotonic (static) shear
loads. However, joints are subjected to dynamic loads
due to earthquake, blasting, and vibration, which canbe simulated as shear along the joint under cyclicloads. In this condition, load direction is reversed on
the shearing plane repeatedly. In the present work, aphysical model is prepared in order to examine theshear behaviour of a natural jointed rock mass. In thepast shear behaviour of regular joints under cyclic
conditions was studied by many researchers (Huang
et al.,1993; Hutson & Dowding, 1990; Homand et al.,
2001; Jafari et al., 2003; Indraratna et al., 2012;
Mirzaghorbanali et al., 2013; Niktabar et al., 2015).
However, joints in the rock mass are irregular andhave different roughness. In the present study regular*S. M. Mahdi Niktabar – email : cez128284@civil.iitd.ac.in

and irregular joints with asperity angles 15°-15° and
30°-30° and 15°-30° and 15°-45° are preparedaccordingly. Joints with irregular asperities are more
representative and closer to natural joints. Each cycle
is divided into four stages as described by Lee et al.
(2001), such as forward advance (FA), forward return(FR), backward advance (BA), and backward return(BR); for better understanding, the four stages areillustrated in Figure 1. The FA movement at firstshear cycle is similar to static or monotonic shear
loads.
To study the effect of irregular asperities on theshear behaviour of rock joints under cyclic
conditions, a series of tests were performed on
regular and irregular jointed samples.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

and 4, respectively. The uniaxial compressive
strength of model material at 0.60 water cement(POP) ratio and after 14 days of air curing was 6
MPa.

3. LARGE-SCALEAPPARATUESDIRECT

SHEAR

A servo controlled large-scale direct shear
system designed by Shrivastava and Rao (2012) was
modified to be able to carry out tests under cyclic
shear conditions. This system is illustrated in Figure
5, which consists of three main units, namely the 1)

Figure 1: Load direction and joint movement under shear
cyclic condition.

2. SAMPLE PREPARATION
Similar sample preparation methodology isadopted for preparing both regular and irregular
joints, except for the use of different asperity plates
to create different asperity angles. A model material
is found in such a way that it can easily be handled
and reproducibility of the sample can be ensured. To
achieve this, different brands of plaster of Paris anddental plasters at different moisture content andcuring period in isolation or combinations wereassessed. Finally, plaster of Paris (POP) was selected
because of its universal availability and its ability tomould into any shape when mixed with water toproduce the desired joints, as well as its long term
strength being independent of time once the chemical
hydration is completed. The prescribed percentage ofwater was decided so as to achieve proper
workability of the paste and required strength tosimulate the soft rock. Different water POP ratios
were tried in order to obtain desired strength andworkability. The ratio which was finally selected was
0.60. Size of samples and amplitude of asperities are
298×298×125 mm and 5 mm respectively for all of
the joints based on moulds and asperity plates. The
asperity plates of different angles like 15°-15° and
30°-30° and 15°-30° and 15°-45° were designed andfabricated to produce desired asperities in the sample.
The POP with 60% of the moisture was mixed in the
mixing tank for 2 minutes and then the material was
poured in the casting mould which was placed on thevibrating table as presented in Figure 2. Vibrations
were given to the sample for a period of 1 minute toremove any entrapped air. The sample wasdemoulded from the mould after 45 minutes and kept
for air curing for 14 days before testing. Pre-test
regular and irregular joints are shown in Figures 3

15˚-15˚ asperity plates

Figure 2: Set up for sample preparation.

Figure 3: Regular joint (15˚-15˚ asperity angle).

Figure 4: Irregular joint (15˚-30˚ asperity angles).

loading unit, 2) data acquisition with controlling unit
and, 3) hydraulic power pack. Maximum capacity of
the normal and horizontal load cell was 500 KN and1000 KN, respectively. The size of each shear box
was 300 mm × 300 mm × 448 mm. This system canwork under both static and cyclic condition.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4. EXPERIMENTATIONThe cyclic shear tests were conducted on regularand irregular joints under different normal stresses.
Normal stresses are 0.1 MPa and 1 MPa as low andhigh, respectively. The frequency and amplitude ofshear loads are set to constant values of 0.01 HZ and+-8 mm, respectively for all cyclic shear tests. Each
type of specimen is tested on thirty shear cycles
under constant normal load conditions. The
orientation of samples with irregular joints isimportant when loaded because of the different
asperity angles. Experimental results are plotted, firstand last shear cycles are shown in black and redcolors in the graphs and from 2-29 shear cycles arepresented in blue color for clarity.

Figure 5: Large scale direct shear testing machine.

4.1 Low normal stress (P=0.1 MPa)
Shear stress versus horizontal displacement on
the joints with asperity angles (a) 15°-15°, (b) 30°30°, (c) 15°-30° and (d) 15°-45° at P=0.1MPa arepresented in Figure 6. Figure 6 (a) indicates that no
significant change is observed on the peak shear
stress from first to last (30) shear cycles on the joint
with 15°-15° asperity angle, whereas it decreases
with increasing number of shear cycles for 30°-30°
asperity angle, as shown in Figure 6 (b). The peak
shear stress at initial cycles for the joint with 30°-30°
asperity angle is more than for the 15°-15° asperity
angle, but it decreases for 30°-30° asperity angle andthe peak shear stress is less than for the 15°-15°
asperity angle after several shear cycles, i.e. peak
shear stress on joint with 30°-30° asperity angle isless than 15°-15° asperity angle at 30 shear cycles.
Normal displacement versus horizontal displacementon the joints with asperity angles (a) 15°-15°, (b) 30°30°, (c) 15°-30° and (d) 15°-45° at P=0.1 MPa ispresented in Figure 7. The dilation angle for 15°-15°
asperity angle is constant during 30 shear cycles asshown in Figure 7(a), but it decreases by increasing
the number of shear cycles for 30°-30° asperity angle

and dilation on the joint after several shear cycles isconverted to compression (positive normal
displacement) as indicated in Figure 7 (b).
Mechanism of the shear is changed from sliding on
the low asperity angle (15°-15°) to shearing on the
joint with the high asperity angle (30°-30°) at thesame normal stress under cyclic shear loads.
Irregular joint shear behaviour is significantly
different from that of the regular joint. Shear strengthof the irregular joint as indicated in Figure 6(c) ismore than that of the regular joint as presented in
Figure 6(b) on the same slope of asperities atdifferent cycles of shearing. With increasing
irregularities (the difference of angles between two
slopes of asperities is increased) or the joint with
15°-45° asperity angle, the peak shear stress isincreased. However, it rapidly decreases withincreasing number of shear cycles, as shown in
Figure 6(d). No significant change is observed onpeak shear stress on the lower slope of asperities orbackward movements. Figures 7(c) and (d) reflectthat dilation and dilation angle is more on the higher
slope of asperities and decreases gradually until it isequal with the lower slope of asperities. However,dilation and dilation angle of the regular joints bothare constant or decrease gradually and equally on
forward and backward movements from first to lastshear cycles, as indicated in Figures 7(a) and (b).
Irregular joints have a tendency to convert to regular
joints at low normal stress under cyclic shear loads.
Degradation of irregular joints is more predominat on
the slopes at higher angles rather than at lower angles
on the asperities.
4.2 High normal stress (P=1 MPa)
Shear stress versus horizontal displacement on
the joints with asperity angles (a) 15°-15°, (b) 30°30°, (c) 15°-30° and (d) 15°-45° at P=1MPa ispresented in Figure 8. Normal displacement versus
horizontal displacement of the same joints at
P=1MPa is indicated in Figure 9. The peak shear
stress increases with the increasing normal stress for
all types of joints. In addition, the peak shear stressincreases with the increasing asperity angle andirregularity of the joint at first shear cycle (in forward
advance). After two or three shear cycles, all types ofjoints reach relatively the same shear stress level andbehaviour of the joints changes from non planar toplanar, due to the complete shearing of asperities of
the joint at high normal stress. This joint behaviour ortransition from nonplanar to planar becomes more
obvious as the normal stress on the joint under cyclicloads increases. With increasing normal stress,
compression is created on the joints. Small dilation isobserved on regular joints only at first cycle at highnormal stress, as presented in Figures 9(a) and (b).

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

a

a

b

b

c

c

d

d

Figure 6 : Shear stress versus horizontal displacement on
the joints with asperity angles, (a) 15°-15°, (b) 30°-30° (c)15°-30° and (d) 15°-45° at P=0.1 MPa.

Figure 7: Normal displacement versus horizontal
displacement on the joints with asperity angles, (a) 15°-15°,(b) 30°-30°, (c) 15°-30° and (d) 15°-45at P=0.1 MPa.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

a

a

b

b

c

c

d

d

Figure 8 : Shear stress versus horizontal displacement on
the joints with asperity angles, (a) 15°-15°, (b) 30°-30°, (c)15°-30° and (d) 15°-45 at P=1 MPa.

Figure 9 : Normal displacement versus horizontal
displacement on the joints with asperity angles, (a) 15°-15°,(b) 30°-30°, (c) 15°-30° and (d) 15°-45 at P=1 MPa.

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In the case of irregular joints, dilation anddilation angles start to increase in the backward
movement with increasing irregularities as shown in
Figure 9 (d). Dilation and dilation angles on the slopeof asperities with lower angles increases in backward
movement with respect to the other joints, and it iseither due to increase in slope angle because of
deformation on another part of slope in firstmovement, or some debris getting deposited on thisslope due to first shearing and joint degradation on
the slope of asperity with higher angle. Horizontal
displacement corresponding to peak shear stressdecreases with increase in asperity angle, whereas itincreases with the increasing irregularity of the joint.

5. CONCLUSION
The test results indicate that the shear strength ofrock joints increases with increase in asperity angles
and normal loads at first cycle of shearing. With theincrease in the number of shear cycles, the shear
strength reduces for all the asperity angles (except a
joint with a low asperity angle at low normal stress).
However, the rate of reduction is greater in the caseof asperities with higher angles. Natural rock joints
are irregular, but most prior studies have been
conducted on regular joints. In the present study,
cyclic shear tests were performed on both regular andirregular joints for comparison. Shear strength ofirregular joints was found to be higher than that ofregular joints at different cycles of shearing at low
normal stress. The analysis of design of structure on
rocks by using the above test results makes the design
safer and more economical. The mechanism ofshearing for regular and irregular joints is different
under cyclic conditions. Shear strength anddegradation of asperities on the regular joints
between loading and unloading are the same at low
normal stress, whereas for irregular joints they are
different. Shear strength and joint degradation are
more on the slope of asperity with higher angles on
the irregular joints, untill two angles of asperities
become equal under shear cycles at low normal stresswhen it starts behaving like the regular joints.

joints. International Journal of Rock Mechanics andMining Sciences. Volume 30, No. 3, pp. 257–269.
Hutson, R. W., & Dowding, C. H. (1990). Joint
asperitydegradation
duringcyclicshear.
International Journal of Rock Mechanics and Mining
Sciences. Volume 27, No. 2, pp. 109-119.
Indraratna, B., Mirzaghorbanali, A, Oliviera ,D,A, F. Premadasa, w (2012). Shear behaviour of rockjoints under cyclic loading. Proceedings of the 11 th,Australia - New Zealand conference onGeomechanics : Ground Engineering in a Changing
World, In G. A. Narsilio, A. Arulrajah & J. Kodikara(eds.), pp. 1256-1261.
Jafari, M. K., Amini Hosseini, K., Pellet, F.,
Boulon, M., & Buzzi, O. (2003). Evaluation of shear
strength of rock joints subjected to cyclic loading.
Journal of Soil Dynamics and Earthquake
Engineering. Volume 23, No. 7, pp. 619-630.
Lee, H. S., Park, Y. J., Cho, T. F., & You, K. H.
(2001). Influence of asperity degradation on themechanical behavior of rough rock joints undercyclic shear loading. International Journal of RockMechanics and Mining Sciences Volume 38, No. 7,
pp. 967-980.
Mirzaghorbanali, A Nemcik, j. & Aziz, N.
(2013). Effects of Shear Rate on Cyclic Loading
Shear Behaviour of Rock Joints Under ConstantNormal Stiffness Conditions. International Journal ofRock
Mechanics
androck
engineering.
Volume 47, No. 5, pp. 1931-1938.
Niktabar. S. M. M. Rao, K.S, & Shrivastava,
A.K . (2015) Shear Behaviour of rock joints undercyclic condition. Special Publication, Journal ofEngineering Geology, October 2015. pp. 277-286.
Shrivastava, A. K, & Rao, K .S. (2013),
Development large scale direct shear testing machinefor unfilled and infilled rock joint under constantnormal stiffness condition, American Society for
Testing and Materials, Volume 36, No. 5, pp. 1-11.

6. ACKNOWLEDGEMENT
The authors wish to thank for the financial support ofthis research from Indian Institute of Thechnology
Delhi. We are thankful to Mr. Jattinder Singh,
Managing Director, of Hydraulic Engineering andInstruments Company, New Delhi, for extending help
during the modification of shear testing machine.

7. REFERENCES
Huang X, Haimson BC, Plesha ME & Qiu X.
(1993). An investigation of the mechanics of rock198

ISMS 2016

Paper No. 34
3D geological modelling method based on hybrid data model
Xue-xi Chen a,*, De-fu Che bab

Department of Safety, North China Institute of Science and Technology, Beijing, China, 101601
Center for RS/GPS/GIS and Digital Mine, Northeastern University, Shenyang, Liaoning, China, 110004

ABSTRACT
Based on a comprehensive analysis of research findings using a 3D geological model made by predecessors, a new
method using a hybrid data model is proposed to construct 3D geological models. This method takes borehole as its
main modelling data source. The modelling process is comprised of the following steps: 1) generate the triangle
irregular network (TIN) adhering to the Delaunay’s law of ground surface according to borehole’s collar data, 2)
down the borehole extend each triangle of TIN into generalized tri-prism (GTP) with knowledge inference rule, 3)
convert GTP model into tetrahedral network (TEN) model or boundary representation (B-reps) model according to acertain conversion algorithm. This mixed modelling method integrates the advantages of TIN, GTP, TEN and Breps model. The model is not convenient for updating data dynamically, but makes it easy to construct 3D
geological models, carry out visualization and spatial analysis, and extend the applicable scope of 3D geologicalmodels. Based on the constructed 3D geological model in Central Business District (CBD), Beijing, someengineering applications including arbitrary cutting, virtual excavation design, virtual wandering, and others aredemonstrated. The flexibility and practicality of this modelling method is tested.
KEYWORDS: borehole data; 3D geological modelling; hybrid data model; knowledge inference rule; engineering
application

1. INTRODUCTION
In recent years there has been an increased
demand for simulating 3D geological information inmine, geology, environment, and geotechnicalengineering. This has promoted research on 3D
geological modelling and its application (Cao andWang, 2004). Many scholars have put forward theirrespective 3D geological models, such as triangle
irregular network (TIN) model (Lemon and Jones,
2003), boundary representation (B-reps) model(Wang, 2003; Cheng et al., 2004), tetrahedral
network (TEN) model (Chen, 1995), tri-prism (TP)model (Gong et al. 2004; Zhang and Bai, 2001; Ruiet al., 2004), and generalized tri-prism (GTP) model(Wu, 2004). Although TIN modelling is mainly used
to describe the interface of geological bodies and isconvenient to show and update data, it cannot
describe the internal properties of geological mass.
B-reps model records all the spatial data that
constitutes a geological entity by complete vector
structure and makes it easy to carry out spatial queryand topology analysis, but it inconvenient for
describing a geological entity accurately with acurved surface. TEN modelling has advantages inquick geometry shows and transformation andvisualization for complex geological entities.
However, it produces a great deal of redundant datawhen describing stratified geological bodies due tothe complex construction algorithm. TP models and*Corresponding author – email: xuexichen1210@163.com

GTP models are easily to build and giveconsideration to both interface and internal
properties. However, section visualization is more
complicated, with a great number of deformation
triangular prisms produced in the process of repeatedfree cutting.
Thus, a new method using a hybrid data model toconstruct 3D geological models is proposed to solve
the problems discussed above. The first step is togenerate ground surface TIN according toDelaunay’s law based on borehole’s collar data andto establish basic topology relationship among
boreholes. The second step is to extend TIN triangle
into GTP down the borehole with certain rules, tobuild the overall described model of the geologicalbody. The third step is to convert GTP into TEN or
B-reps via a corresponding conversion algorithm forvisualization operation and spatial analysis. This
mixed
modellingmethodintegrates
thecorresponding advantages of each model, such as
convenient data updates for TIN, simple construction
algorithm for GTP, convenient visualization
operation for TEN, and spatial query for B-reps,
making up for the defects of each single model.

2. 3D GEOLOGICAL MODEL BASED ON
HYBRID DATA MODEL

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2.1 3D Geological Model
The 3D geological model based on hybrid data
model was designed for practical application, as isshown in Figure 1. This model includes such models
as TIN, GTP, TEN, and B-reps and abstract geometry
elements such as node, edge, arc, triangle, super-face,
GTP, tetrahedron, and super-body. The component
elements of B-reps such as node, arc, super-face, andsuper-body are called boundary geometry elements.
These kinds of elements are mainly used to express
topology relationships between geological entities.
Node, edge, triangle, GTP, and tetrahedron are calledvolume geometry elements. Unlike boundary
geometry elements, they are mainly used to express
geometry topology structure change in the interior ofgeological entities. This model also defines
constraints between geometry modelling elementsthat not only are the theoretical basis for spatial
analysis, 3D visualization, and 3D query in 3Dmodels, but also a guarantee of unity, correctness,and uniqueness for 3D geometry object
reconstruction.
Entity element

3D Geological model

Point entity

Line entity

Volume entity

Surface entity

Complex entity

Node

Arc

Super-face(X, Y, Z)

Edge

Triangle

Simple entity

Compound entity

Super-bodyBoundarygeometry
glement

GTP
Boundary geometry element
Tetrahedron

Figure 1: 3D geological model based on hybrid data model.

Geological entity is usually divided into thefollowing: like point entity, line entity, surface entity,and volume entity. For volume entity, it can bedivided further into three tapes: simple entity,complex entity, and compound entity. Complex
entity is the combination of simple entities thatbelong to the same tape while compound entity is thegathering of simple entities affiliated to different
types. Both complex entity and compound entity aredefined by simple entity. Simple entity is defined bysurface entity. Surface entity is defined by line entity.
Line entity is defined by point entity. Obviously, thisentity description method has a clear hierarchy and isconvenient for organizational management.

2.2 Data Structure
According to object-oriented theory and methods,
entity elements and geometry elements in Figure 1
can be designed to various object classes and be built
to corresponding topology structures combined witha practical application. Their own member variables
are thought of as data structure. In this paper only themain data structures of node, triangle, and GTP
which have a close connection with modelling
inference and algorithm efficiency are discussed.
Data structure of point:class CBoreholePoint: public CObject //point
class{long PointID; // ID mark of pointchar AttributeID; //attribute markdouble x, y, z; // x, y, z coordinate of point
int StratumNO; //number of stratum
CString BoreholeNO; //number of borehole
CBoreholePoint*PrevPoint,*NextPoint;//previou-s point and next point in point chain……}
Data structure of triangle:
class CTriangle: public CObject //triangle class{long TriangleID; //ID mark of triangle
CTriEdge *Edge1, *Edge2, *Edge3; //threeedges of triangle
CGtriprism *UpGtriprism, *DownGtriprism; //GTP of triangle up and down
CTriangle*PrevTriangle,*NextTriangle;//previou-s triangle and next triangle in triangle chain……}
Data structure of the GTP:Class CGtriprism: public CObject // GTP class{long GtriprismID; // ID mark of GTP
CTriangle *UpTriangle, *DownTriangle; //triangle at top and bottom of GTP
long TENDivNO; //code of sectioning the GTP
into tetrahedron……}According to point data structure shown above,
AttributeID is used to mark special points, such as
the fault point. StratumNO is the code of stratum
where the point is located. Its order increases
progressively from ground surface to the lower.
Attribute code of point is the lower adjacent stratumcode. PrePoint and NextPoint are the previous point
and the next point, respectively, on a point double
linked list. On the one hand, point double linked lists
are convenient for the retrieval of logical points ofboreholes for extension. On the other hand, previous
point and next point can be linked together whendrawing under OpenGL driver, automatically solving
deviation problems in a real situation. Therefore thisdouble linked list helps improve modelling efficiency.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

In data structure of triangle, PreTriangle and
NextTriangle are the previous triangle and the next
triangle on a triangle double linked list. Triangles
whose three vertexes are subject to the same borehole
number constitute of triangle double linked list. This
double linked list efficiency can be improved when
triangles extend into GTP along the borehole. In thedata structure of GTP, TENDivNO is the section
code. Based on this, it will section the GTP into
tetrahedron by linking diagonals of quadrilateral at
the side of GTP one by one.

3. 3D
GEOLOGICALMODELLING
METHOD BASED ON HYBRID DATA
MODEL
3.1 The Formation of Ground Surface TIN
The formation of ground surface TIN is the basis
for mixed model construction. The process ofregarding borehole’s collar coordinates as data points
and generating TIN according to Delaunay’s law andestablishing a basic topology relationship between
boreholes is named the formation of ground surface
TIN. The incremental insertion is one of theconstruction algorithms to generate Delaunay
triangulation. The algorithm is suitable for groundsurface modelling based on borehole data because of
its simple principles. The basic steps are as follows(Wu et al., 1999). Firstly, define an initial polygonthat contains all borehole data points. Secondly,
construct an initial triangulation in the defined initial
polygon, and then conduct iteration until all data areprocessed. The iteration should be as follows, toinsert a P data point and to find the T triangle that
contains P in the triangulation, then link P and thethree vertexes of T to form a new triangle. Third,
optimize triangulation using the Local Optimization
Procedure (LOP) to meet Delaunay’s law.
For fault ruptures above the ground, theconstraint relationship between discrete points will beenhanced due to fault when constructing Delaunay
triangulation at the orifice. It can be solved byviewing the fault line as a constraint and adopting analgorithm named constrained Delaunay triangulation.
These kinds of algorithms mainly include constraingraph
methods,
divide-conquer
algorithms,
triangulation growth methods, encryption algorithms,
and two-step methods. The diagonal exchanging
algorithm that forcibly inserts constrained boundary
is simpler, easier to realize, and is more practical thanthe other two-step methods (Li and Tan, 1999).
3.2 3D Geological Model Construction Method
Based on the GTP

After the generation of TIN, the triangle can beextended down the borehole to form GTP. The main
steps to form GTP are as follows.
1) Choose a triangle from TIN and set it to be thetriangle of the first GTP.
2) As shown in Figure 2, a new triangle can beformed by extending three vertexes of previous
triangles down the three boreholes according tostratum ID.
The stratum is formed in a sequence and alwaysof different distribution map, which reflects ordinal
relationship of abnormal stratums pinching out
during geological formations. Besides, stratum can be
broken and be constrained by the fault. Therefore, itis necessary to reflect this geologic structure rule
when triangle extending down. In order to ensure
correctness and uniqueness when reasoning therelationship mentioned above. The reasoning rules
are as follows.
As shown in Figure 2(a), if none of threevertexes of the current extending triangle are the fault
point, the next point of the corresponding borehole
will be vertexes of a new triangle with the same code.
As shown in Figure 2(b), once the code is different,
vertex whose number is less than other’s will be
extended into a new triangle vertex along thecorresponding borehole. Vertex whose number isbigger will be unchanged.
If the current extending triangle has one or two
fault point(s) among the three vertexes, whether theattribute of next point of the rest of vertexes is thesame as the attribute of fault point should be checked.
If attribute is the same, fault point cannot be extended
down regardless of number size until all the rest of
the vertex extend down into the same attribute.
Figure 2(c) shows that triangle 111 is extended down
into triangle 221. The black circle dot represents fault
point while the black triangle represents fault surface.
Otherwise all vertexes can extend down based on
number size. As is shown in Figure 2(c), triangle 222
extends down to form triangle 333.

1

1

1
1

1

1

1

2

2

2

1

1

2

2
2

2

3

(a)

3
3

3

3
3

2

3

3

(b)

(c)

Figure 2: Down expanding rule of triangle.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

In such situation as all current vertexes of theextending triangle are fault points, the way thetriangle extends down to form a new triangle
according to number size can be the same as thesituation without any fault points. In Figure 2(c),triangle 221 is extended down to form triangle 222.
3) Construct GTP according to corresponding
relationship between previous triangle and the next
triangle on the triangle double linked list andborehole point list, then record reflected information
and regard the next triangle as with the previous
triangle.
4) Repeat step 2) and 3) until all vertexes of theprevious triangle lie in the bottom of the borehole.
5) Repeat steps 1) to 4) until all TIN is traversed.
If there are new data about the borehole, only the
local ground surface TIN should be modified and be
extended down to generate new GTP. This method isconvenient for dynamic modification. It can also
automatically reason complex geological structures
such as fault and pinch-out. This method has asimple construction algorithm.
3.3 Tetrahedron Generation and Boundary
Conversion of GTP
After construction of the whole 3D geologicalmodel, it is necessary to transform the GTP model
into a tetrahedron model or the B-reps model for
visualization and engineering application analysis.
The former is realized by the method named thesmallest vertex identifier (Chen et al., 2004). Firstly,
number each vertex of GTP uniformly for
identification. This must meet the two following
conditions. 1) The identification number is invariable
and unique. 2) The identification numbers can becompared with each other. Secondly, the vertexes
that have the smallest identification number are
selected by comparing the identification numbers offour vertexes in each quadrangle at side of GTP, andthen they are linked to the corresponding vertexes in
the opposite face in order to finish tetrahedron
division. To ensure that the geological body is
described completely by GTP and to save memory
space, it is not directly sectioned into a tetrahedron.
Instead it will add tetrahedron division code to its
data structure. Connection code of diagonal of theside face constitutes these codes in order, and each
GTP element includes three mark bits, each of which
has a corresponding connection way about the
diagonal. Thus, tetrahedron division is finished bysearching the identification number of GTP. Thismethod has a certainty and is easy to program.
What’s more, it does not need to store data ofadjacent GTP elements for local operation. Only inthis way, can a global unit be sectioned andcompatible.

Boundary conversion is done through special
data structure of GTP. According to topology
relationship between GTPs, not only adjacent volume
elements are easy to be found, but also boundary
volume elements whose bottom triangle or side
quadrangle is located in the boundary can besearched. For a boundary triangle, it will be added toa triangle-linked list expressed by an entity boundary.
Boundary quadrangles should be sectioned into
triangles by the smallest vertex identifier before
being added to the linked list. The following are theprocedures for boundary conversion. Firstly, initialize
the triangle-linked list expressed by entity boundary
to dynamically store s boundary triangle. Secondly,
extract a GTP from the GTP linked list and search
information as to adjacent volume elements
according to the stored topology relationship among
adjacent volume elements. If the top triangles or thebottom triangles are not the adjacent volume
elements or the adjacent volume elements are of adifferent attribute, it will be added to the linked list.
Side quadrangles in the same situation should besectioned into two triangles by the smallest vertex
identifier before being added to the linked list. Lastly,
the second step should be repeated until the GTP
linked list is fully processed.
Entity boundary expression not only contributes
to analysis on spatial topology relationships between
geological entities, but also simplifies visualization
operations for those geological entities whose
internal information is not needed.

4. ENGINEERING APPLICATION CASE
Based on modelling methods mentioned above,the 3D geological modelling system GeoMo3D wasdeveloped by using VC++6.0 and the 3D graphic
drawing tool OpenGL. An engineering application
experiment was carried out and combined with actual
geological exploration data from the Beijing Central
Business District. The studies area contained a totalof 46 primitive boreholes. The stratum is divided into
10 layers, as is shown in Figure 3(a). Because a 3D
geological model based on a hybrid data model canunify all surfaces of volume elements to be boundary
triangles and can transform all volume elements into
tetrahedrons, it is easier to perform normal analyses
such as a random section plane or layer display.
Above all, it is possible to conduct special
visualization operations, such as virtual excavationand spatial query. Figure 3(b) is a fence diagram thatis found by repeatedly sectioning the tetrahedronmodel. It clearly shows every internal detail of thegeological model, which helps to learn the geologicalstructure. As shown in Figure 3(c), by designing avirtual tunnel in the tetrahedron model andintersecting, we can observe the distribution situation202

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016of exposed geological structures after excavation.
Figure 3(d) shows that we can study the spatial
relationships between tunnel and stratum using the Breps model. It can provide reference information for
excavation design and influence analysis.

5. CONCLUSIONS
3D geological models can guide geologicalanalysis in relevant application domains. This haspractical value for project planning, excavation
design, environmental impact analysis, and disasterprevention and reduction. Based on a comprehensive
analysis of previous research findings related to 3D
geological models, a new hybrid data model was
proposed to construct a 3D geological model. It is not
only convenient to dynamically update data, but also
makes it easy to construct 3D geological models andto carry out visualization and spatial analysis. It
automatically reasons complex geological structures
such as faults and pinch-out, extending the applicable
scope of 3D geological models. The successful
development and application of the 3D geologicalmodelling system GeoMo3D demonstrates that thisnew modelling method has flexibility andpracticability. There is further work to be done inorder to better serve relevant application fields ofgeological engineering. For example, to improve thefunctions such as virtual design of geological bodies,
attribute query and spatial analysis and inference arenecessary.

a

b

C

d

Cao D Y, Wang Z G. (2004). Direct 3Dinteration in 3D geological model visualization.
Journal of China University of Mining andTechnology. Volume 33, No. 4, pp. 384-387
Cheng P G, Liu S H, Wang W, et al. (2004).
Study and application of a new 3D geological model
construction
method.
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Jilin
University(Earth Science Edition). Volume 34, No. 2,
pp. 309-313
Chen X Y. (1995). A workstation for threedimensional spatial data research. In: The FourthInternational Symposium of LIESMARS, Wuhan, pp.
42-51
Chen X. X, Wu L. X, Shi W. Z, et al. (2004).
Diagonal generation by Smallest Vertex Identifier in
GTP model. Geography and Geo-Information
Science. Volume 20, No. 3, pp. 17-21
Gong J Y, Cheng P G, Wang Y D. (2004).Threedimensional modeling and application in geological
exploration engineering. Computers and Geosciences.
Volume 30, No. 4, pp. 391-404.
Lemon A M, Jones N L. (2003). Building solid
models from boreholes and user-defined crosssection. Computers and Geosciences. Volume 29, No.
3, pp. 547-555
Li L X, Tan J R. (1999). Multiple diagonal
exchanging algorithm for inserting constrainedboundary in constrained Delaunay triangulation.
Chinese Journal of Computers. Volume 2, No. 10, pp.
1115-1118
Rui X P, Yang Y G, Xi Y T. (2004). Study on
visualization of 3D stratum based on triangularprism. Journal of China University of Mining &Technology. Volume 33, No. 5, pp. 584-588
Wang C X. (2003). Study on geologicalmodeling in 3D strata visualization. Chinese Journalof Rock Mechanics and Engineering. Volume 22, No.
10, pp. 1722-1726
Wu L X. (2004).Topological relations embodied
in a generalized tri-prism(GTP) model for a 3D
geoscience modeling system. Computers andGeosciences. Volume 30, No. 4, pp. 405-418
Wu X B, Wang S X, Xiao C S. (1999). A new
study of Delaunay triangulation creation. Acta
Geodaetica et Cartographica Sinica. Volume 28, No.
1, pp. 28-35
Zhang Y, Bai S W. (2001). An approach of 3D
stratum modeling based on tri-prism volume
elements. Journal of Image and Graphics. Volume 6,
No. 3, pp. 285-290

Figure 3: Application case of 3D geological modelling.

6. REFERENCES

203

ISMS 2016

Paper No. 62

Measurement and analysis of virgin-rock temperature in Huanren Metal
Mine
CHANG De-qianga, b,*, LIU Jing-xiana, b, MAO Ninga, b, GE Shuang-youaaInstitute of Safety Engineering, School of Resource & Civil Engineering, Northeastern University, Shenyang, China, 110004
Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines, Northeastern University, Shenyang, China,
110004b

ABSTRACTWith the increase of mining depth, the heat-harm in high temperature deep mines has become increasingly
prominent and become a new obstacle for the development of mining in China. Two pitheads from Huanren Metal
Mine, a nearly one-thousand-meter-depth mine, were taken as the study objects of this paper. The deep-holetemperature measuring method was adopted to determine the rock temperature. The original rock temperature wasanalyzed theoretically, and the ventilation cooling depth, the geothermal gradient, and the distribution model of therock temperature were calculated and verified. The temperature of the deep rock was predicted and some pertinent
suggestions to control the thermal hazard were put forward. The results show that the ventilation cooling depth of
this mine is 20 m, and the geothermal gradient of the two pitheads is 2.3°C/100 m and 3.6°C/100 m. The model ofthe airflow temperature agrees well with the measured values. The research in this paper can provide theoretical andtechnical support for heat-harm prevention and control in Huanren Metal Mine and other similar mines.
KEYWORDS: mental mine; virgin-rock temperature; measurement; geothermal gradient

1. INTRODUCTION
In present day China, about 35 to 40 percent of
the mines have entered the deep mining stage and themining depths of nearly one hundred metal mines are
more than 1000 meters. It can be predicted that in thenext few decades more and more underground mines
will move into deep mining (Dong et al., 2009; Gu
and Li, 2003). With the increasing mining depth, theheat-harm has become increasingly prominent, which
seriously affects the health of workers, greatly
reduces labor productivity, and increases the accident
rate. The high temperature in deep mines has becomea new obstacle for the development of mining in
China. As the most direct and important undergroundheat source, heat from the wall rock takes about 48%of the total heat transferred into underground air(Donoghue et al., 2000; Hartman et al., 2012).
Therefore, the measurement and analysis of thevirgin-rock temperature provides very important
basic data for temperature-humidity air conditioning.
This study aimed to investigate the virgin-rocktemperature and the temperature distribution in therock and determine the geothermal gradient and theheat flow transferred from the rock to the air flow in
Huanren Metal Mine. As a nearly one-thousandmeter-depth mine, two pitheads in Huanren Metal
Mine were taken as the study objects. The deep-holetemperature measuring method was adopted todetermine the rock temperature. The original rocktemperature was analyzed theoretically. The
ventilation cooling depth, the geothermal gradient,and the distribution model of the rock temperature
were calculated and verified. The temperature of the
deep rock was predicted. The research in this paper
can provide theoretical and technical support forheat-harm prevention and control of Huanren Metal
Mine and other similar mines.

2. MEASUREMENT
2.1 Measurement instrument
Virgin-rock temperature can be calculated basedon the data obtained from borehole temperature (Vost,
1976). In this paper, the temperature was tested in a
deep borehole with armored type k thermocouple.
The compensating wire for the thermocouple was 25
meter long and sealed and protected by a Teflon tube.
The temperature was displayed by a digital
thermometer which was designed for type kthermocouple. The measuring range was from 50.0°C to 1300°C, the resolution was 0.1°C, and theprecision was 0.1% ±0.4°C.
Fifteen thermocouples were used in themeasurement; these thermocouples were allcalibrated before the test to ensure the accuracy of thedata.

*Corresponding author – email : changdeqiang@mail.neu.edu.cn

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

decided. Some boreholes in the level of -500 m, -530
m, -560 m, -600 m, -630 m, -660 m, -690 m in the
Songlan Pithead and -420 m, -480 m, -540 m, -630 m,-720 m, -760 m, -840 m in the Xiangyang Pitheadwere selected.

3. DATE ANALYSIS
3.1 Determine the ventilation cooling depth
As the typical rocks in the two pitheads were thesame, this measurement was only carried out in the
Songlan Pithead. The data from three boreholes werecollected at the level of -600 m. Rock temperatures atvarious distances to the wall in the borehole areshown in Figure 1.
28
27
26
25

Measuring point #1
Measuring point #2
Measuring point #3

24
23
22

℃
)

Rock temperature (2.2 Measurement scheme(1) Measurement of ventilation cooling depth
The temperature of the virgin-rock at the certain
depth in a small range is the same when theproperties of the rock are homogeneous. In the mine,
if the distance between the surrounding rock and thewall of the laneway is longer than the ventilation
depth, the temperature of the rock will be a constant,which is the virgin-rock temperature at this level. In
the test, three horizontal boreholes in typical rockwhose depths were not less than 25 meters wereselected as the sampling holes. The thermocouples
were put deeply at the bottom of the sampling holes
and the openings of the hole were sealed with mud.
In the next 24 hours, the temperature in the holes wasallowed to stabilize, and then the temperature and the
distance between the sample point and the laneway
wall were recorded. Next, the thermocouple waspulled out several meters and the test was repeateduntil the entire thermocouple was pulled out. The
ventilation cooling depth is the distance between thesample point and the laneway wall from which therock temperature does not increase and the highest
temperature is exactly the virgin-rock temperature at
this level.
(2) Measurement of geothermal gradient
The geothermal gradient is an important
indicator to rate the heat-harm in the mine and theessential data to predict the heat-harm and guide thetemperature lowering. The geothermal gradient canbe calculated with the data obtained by measuring thevirgin-rock temperature of different levels. In thispaper, the borehole for the rock temperature sampling
was ready-made. The measurement was carried out
according to the following steps:(a) Choose seven different levels in which theboreholes meet the test request can be found. The
distribution of the levels should be uniform from the
top to the bottom as far as possible. The borehole
should be horizontal, dry, and without flowing waterin it. The depth of the hole should not be less than 25
meters. The bottom of the borehole should keep far
away (>25 meters) from the structures which may
affect the rock temperature, such as the shaft, goaf,chamber, and so on.
(b) Insert the thermocouple into the borehole
until the depth is not less than the ventilation cooling
depth measured previously. Seal the opening withmud.
(c) Record the temperature after 24 hours.
(3) Position of the sample point
According to the test request, the in-site
condition was analyzed and the measure point was

21
20
0

2

4

6

8

10

12

14

16

18

20

22

Distance to wall in borehole (m)Figure 1: Rock temperature vs. Distance to wall in
borehole.

Due to the different velocities and temperature of
the air flow around the sample point, there were
obvious differences in the initial point and the change
process of the rock temperature between the threesample points. The rock temperatures all gradually
increased with the distance between the temperaturesample point and the wall of the laneway, thenstabilized and were not affected by the outside air
flow when the distance was more than 15 meters.
When the distance reached 20 meters, the rocktemperature of the three points became the same andno more change occurred with increased distance,that is to say, the ventilation cooling depth in themine was 20 meters, and the temperature at this depth
was the virgin-rock temperature.
3.2 Calculate the geothermal gradient
After in-site measurement, the virgin-rocktemperature at different levels in the Songlan Pitheadand Xiangyang Pithead were obtained, as shown in
Tables 1 and 2.

205

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Virgin-rock temperature at different levels in Songlan Pithead.
Level of sample points
-500m
-530m
-560m
Relative depth to 1st sample point (m)
0
30
60
0
0.3
0.6
Equivalent height (1/100m)
Virgin rock temperature (°C)
21.4
22.3
23.7

-600m
100
1
24.9

-630m
130
1.3
26.1

-660m
160
1.6
27.3

-690m
190
1.9
28.0

Table 2: Virgin-rock temperature at different levels in Xiangyang Pithead.
Level of sample points
-420m
-480m
-540m
Relative depth to 1st sample point (m)
0
60
120
0
0.6
1.2
Equivalent height (1/100m)
Virgin rock temperature (°C)
19.3
20.2
21.6

-630m
210
2.1
23.5

-720m
300
3
25.8

-760m
340
3.4
26.7

-840m
420
4.2
28.7

h′ =

hmax − h100(1)Where hmax is the maximum of all the levels, m;
h is the original levels of the sample points, m; h’ isthe equivalent height, 100 m-1. According to theresults of the geothermal gradient fitting shown in
Figures 2 and 3, the geothermal gradient of Songlan
Pithead was 3.6°C/100 m while that of Xiangyang
Pithead was 2.3°C/100 m. Compared with theaverage geothermal gradient of the earth crust, whichis 2.5°C/100 m, the geothermal gradient in the
Xiangyang Pithead is normal while that in the
Songlan Pithead is larger and should be paid more
attention to for the possible heat harm when themining depth is further increased.

(H − H a ) × G
100

(2)

Where tn is the virgin temperature of the rockwhich is H meters below the earth surface, °C; ta is
the rock temperature of the zone of constanttemperature, °C; H is the depth of the rock from theearth surface, m; Ha is the depth of the zone ofconstant temperature, m; G is the geothermal
gradient, °C/100 m.
35
30
25
20
y = 2.2726x + 18.978
R2 = 0.9969

15
10
5
0
0

1

2

3

4

5

Eqivalent height / 100m

Figure 3: Geothermal gradient fitting of Xiangyang
Pithead.

30

Origin rock temperature /℃

tn = ta +Origin rock temperature /℃

The geothermal gradient was derived by thefitting method. The levels of the sample points weretransferred to equivalent height by Equation 1 while
the temperatures remained unchanged. Then the dataof height and temperature was fitted with a line,
where the geothermal gradient is the slope of the line.

25
20

According to the information from the mining
company, the depth of the zone of constanttemperature in Huanren Mine is 30 meter, ta is 4.4°C
for the Songlan Pithead and 9.9°C for the Xiangyang
Pithead. The distribution models of the virgin-rocktemperature for the Songlan Pithead and Xiangyang
Pithead are Equations 3 and 4, respectively.

y = 3.5774x + 21.39
R2 = 0.9965

15
10
5
0
0

0.5

1

1.5

2

Eqivalent height / 100m

Figure 2: Geothermal gradient fitting of Songlan Pithead.

3.3 Distribution model of the virgin-rock temperature
The virgin-rock temperature at certain depths canbe calculated by Equation 2.

( H − 30) × 3.6100( H − 30) × 2.3
t n , X = 9.9 +100
t n ,S = 4.4 +

(3)
(4)

Based on these two equations, the temperature of
the deep rock can be predicted. Take Songlan Pitheadas example, the virgin-rock temperature will increase
to 30°C when the mining depth reaches -741 m. If themining depth reaches -936 m, the virgin-rock206

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

L⋅ K ⋅ P

temperature will be 37°C which will be a severe
problem.

Where L is the distance from the inlet, m; P isthe circumference of the laneway, m; Q is the air
quantity，m3 s-1, K is calculated as:

3.4 Air flow temperature
Based on the assumption that the inlet air
temperature in the laneway is constant and the heattransfer in the rock is stable, according to the heatexchange between air and rock, the air temperature
can be calculated by Equation 5 (Ventilation
Research Laboratory, 1976).
tl =( S − 1)tn + t0
SK=

4. CONCLUSION
In this paper, Songlan Pithead and Xiangyang
Pithead, two of pitheads of Huanren Metal Mine,
were studied. The virgin-rock temperature wasmeasured, the obtained data was analyzed
theoretically, the ventilation cooling depth, thegeothermal gradient and the distribution model of therock temperature were calculated and verified, andthe temperature of the deep rock was predicted. The
results showed that the ventilation cooling depth in
the Huanren Metal Mine is 20 meters. The
geothermal gradient in Songlan Pithead is 3.6°C/100
m while that in Xiangyang is 2.3°C/100 m. The
Songlan Pithead should be paid more attention to dueto the possible heat harm when the mining depth isfurther increased. The model to calculate the airflow
temperature is in agreement with the measured data,
which showed its good applicability in this mine.
This model can give strong support to predict andcontrol the heat harm in the mine. The heat harm in
the Huanren Metal Mine has already appeared
preliminarily and is not serious at this time, but itshould be closely monitored. With the increasing
mining depth, the heat harm will become more andmore severe. At the early stage, it can be improvedby optimizing the ventilation network. After that,

λ
υ 0.8

(7)

Where λ is the heat transfer coefficient,
W/m2 °C1; v is the average velocity of the air flow, m/s.
In order to verify the applicability of the model,
the data from -600 m level in the Songlan Pitheadwere put into the model, the value of the parameters
were listed in the Table 3.

Where t0 is the inlet air temperature in thelaneway, °C; tl is the temperature of the air which is L
meters far away from the inlet, °C; S is calculated as:

Based on the model, the temperature at the
sample point is 20.6°C while the measured
temperature is 20.3°C, the error is 1.48%. The model
agreed well with the measured data and can be used
to predict and control the heat-harm in the mine.

8.7λ
1.33 +(5)

Table 3: value of the parameters from Songlan Pitheadt0 / °Cv / m/sParameters
Value
12.8
1

(6)

S = 10 2600Q

tn / °C

P/mL/mλ / W/m2 °C

26.9

10

95

2.975

more effective cooling measures should be taken into
consideration.

5. ACKNOWLEDGEMENT
This work was supported by the National Natural
Science Foundation of China (51404064), theFundamental Research Funds for the Central
Universities (N130401002).
6.

REFERENCES

Dong, L.-j., Li, X.-b. and Li, P.-p. (2009).
Crucial Understanding and Decision-Making
Technology for Deep Mining, Nonferrous Metals,
Volume 61, pp. 116-120.
Donoghue, A. M., Sinclair, M. J. and Bates, G. P.
(2000). Heat Exhaustion in a Deep Underground
Metalliferous Mine, Occup. Environ. Med., Volume
57, pp. 165-174.
Gu, D.-s. and Li, X.-b. (2003). Science Problems
and Research State of Deep Mining in Metal and
Nonferrous
Mines,
MiningResearchandDevelopment, Volume 23, pp. 1-5.
Hartman, H. L., Mutmansky, J. M., Ramani, R.
V. and Wang, Y. (2012). Mine Ventilation and Air
Conditioning. John Wiley & Sons, pp.120.
Vost, K. (1976). Rapid Changes of Air
Temperature in Underground Airways, J. S. Afr. Inst.
Min. Metall., Volume 77, pp.262-268.
Ventilation Research Laboratory (1976). Prevent
Hoisting Shaft from Freezing through Preheating
Air by Geothermal Energy, J. Northeast. Univ.,
Volume 3, pp. 36-46.

207

ISMS 2016

Paper No. 187
The tensile properties of GFRP bars at different loading rates
Wenxue Chen a, b, *, Jun Wu a, Yuzhao Jiao c, Jiewen Zheng a and Xue Li daSchool of Civil Engineering, Henan Polytechnic University, Jiaozuo, China, 454000
Opening Project of Key Laboratory of Deep Mine Construction, Henan Polytechnic University, Jiaozuo, China, 454000
c
Shandong Safety Industrial Co., Ltd., Tai’an, Shandong, China, 271000
dSchool of Resource and Safety Engineering, China University of Mining and Technology, Beijing, China, 100083b

ABSTRACT
In order to study the effect of loading rates on the tensile property indexes of GFRP (Glass Fiber Reinforced
Polymer) bars, the tensile property experiments were conducted at four different loading rates by utilizing theelectro-hydraulic servo universal testing machine. The results show that: with increases in loading rate, the ultimate
tensile strength and the ultimate tensile strain increase, while the elastic modulus almost remains constant with theaverage value 28.5 GPa; the failure mode of specimens belongs to splitting failure and the stress-strain curves show
a linear relationship. Based on the results and analyses, a loading rate of 2 mm/min is recommended when
conducting experiments to determine the tensile property indexes of GFRP bars.
KEYWORDS: GFRP bar; tensile property; loading rate; stress-strain curve; elastic modulus

1. INTRODUCTIONGFRP bar (Glass Fiber Reinforced Polymer bar)is a composite made up of a resin matrix andcontinuously twistless glass fiber reinforcement
though the pultrusion process. Compared to rebar, itboasts advantages such as being light-weight, highstrength, chemical corrosion resistant (Micelli et al.,
2004; Kim et al., 2008), fatigue resistant (Uomoto andNishimura, 1995), anti-electromagnetic and inflaming
retardant, thus becoming an ideal alternative which is
gradually applied in civil (and mining) engineering
fields (Liu and Zhou, 2014.). Rebar is a plastic
material while GFRP bar is a brittle material;
therefore the structure design concepts of the two are
different. In order to ensure the safety of the structure
design, it is essential to deeply study the mechanicalproperties of GFRP bar. However, in terms of tensileloading rate, there are some differences amongexperiment specifications and researchers when
conducting the tensile experiment to determine thetensile property indexes of GFRP bar.
“ACI 440.1R-03” (ACI Committee 440, 2003a)
provides that the tensile loading rate should becontrolled at 100-500 MPa/min and “ACI 440.3R-04”(ACI Committee 440, 2004b) provides that the
specimen should be damaged in 1-10 min, no matter
what load control or displacement control is adopted.
“GB/T1447-2005” (GAQSIQ of the PRC andStandardization Management Committee of the PRC,
2005a) and “GB/T 13096-2008” (GAQSIQ of the
PRC and Standardization Management Committee of
the PRC, 2008b) also provide that the tensile loading*Corresponding author – email : wen1xue2@126.com

rate should be controlled at 5 mm/min when
determining the ultimate tensile strength and
2mm/min when determining the elastic modulus aswell as the ultimate tensile strain. Moreover, there areseveral specifications that not give a specific loading
rate when conducting the tensile experiment, such as“MT/T 1061-2008” (State Administration of Work
Safety, 2008) and “JG/T 351-2012” (MHURC of the
PRC, 2008).
It is the fact that the loading rates adopted by the
researchers are also not the same when they carriedout in tensile experiments. For example, Brahim
Benmokrane (Benmokrane et al., 2000) adopted aloading rate of 250 MPa/min when he researched thetensile properties of AFRP and CFRP bars. Young Jun
You (You et al., 2007 ) adopted the loading rateaccording to the specification “ASTM-D-3916”(ASTM, 2002) when he conducted the tensile
experiments of FRP bars. There was no specificloading rate given by S. Kocaoz (Kocaoza et al., 2005)
when he studied the tensile properties of GFRP bars.
Besides the researchers mentioned above, there havealso been a wide range of researchers from China
completing tensile experiments of GFRP bars, and theloading rates they chose also varied widely.
5 × 10-5s-1 were used by Jikai Zhou (Zhou et al., 2008)
4kN/time by Jing Chen (Chen et al., 2012), 2 mm/min
by Xinyue Zhang (Zhang et al., 2005). Particularly,
Guowei Li (Li et al., 2012) adopted a group ofloading rates which were 2, 4, 6, 10, 15 mm/min toresearch their effect on the tensile property indexes of
GFRP bars.
In this paper, in order to study the effect ofloading rates on the tensile property indexes of GFRP
bars, four different loading rates were adopted, whichwere 2, 10, 20, 50 mm/min respectively.

2. EXPERIMENTAL PROGRAM
2.1 Experimental materials
The whole thread GFRP bars adopted in thispaper are produced by Shandong Safety Industrial Co.,
Ltd., which have right-handed thread. The pitch ofthis GFRP bar is 10 mm, and the inner diameters aswell as the outer diameter are 18 mm and 20 mm,
respectively. The matrix material is unsaturated resin
and the reinforcement is the ECR24-2400D-601 typeglass fiber produced by Shandong Glass Fiber
Composite Co., Ltd. The specifications of seamlesssteel pipe are: 38 mm in outer diameter, 6.5 mm inthickness, and 50 mm in length; the efficient silent
broken agent is produced by Beijing Yuyi special
cement plant and the recommended water cement
ratio is 28%-35%; the type of strain gauge is
BX120-5AA and the value of sensitivity coefficient K
is 2.08.
2.2 Specimens preparation
Due to the low transverse strength of GFRP bar,
if the clamping is directly carried out at the ends, itwill be quickly crushed before the tensile failure
occurs. In order to avoid this defect, both ends of
GFRP bar are protected by the seamless steel pipes,
and are bonded by the efficient silent broken agent,
thus relying on the huge expansion pressure toprovide axial shear stress.
ACI 440.1R-03 (ACI Committee 440, 2003a) andACI 440.3R-04 (ACI Committee 440, 2004b)
recommend that the effective tensile length should be
no less than 40 times as long as the nominal diameterof the GFRP bar and should be no less than 100 mm.
JG/T 351-2012 (MHURC of the PRC, 2008) also
provides that the effective tensile length should be
400-600 mm. Due to the limitation of the maximum
tensile space of WAW-600B type electro hydraulicservo universal testing machine used in thisexperiment, the specifications of specimens are madeas follows: the full length is 600 mm, and theanchorage length at both ends is 200 mm, thus the rest
effective tensile length is 200 mm. The schematic
sketch of the specimen is shown in Figure 1.

20

38
25

efficient silent broken agent
10
seamless steel pipe GFRP bar

200

200

200

Figure 1: The schematic sketch of the specimen.

2.3 Experimental instruments
The instruments used in this experiment include

WAW-600B type electro hydraulic servo universal
testing machine and XL2118C type stress-strain
comprehensive parameter testing instrument, asshown in Figure 2.

Figure 2: WAW-600B type electro hydraulic servo universal
testing machine and XL2118C type stress-strain
comprehensive parameter testing instrument.

2.4 Experimental methods
The tensile experiments are conducted byutilizing WAW-600B type electro hydraulic servo
universal testing machine with the displacement
control method adopted and the loading rate were 2,
10, 20, 50 mm/min respectively. The tensile strain
were recorded by XL2118C type stress-strain
comprehensive parameter testing instrument with thequarter-bridge connection method used, and the strain
gauge was attached to the middle area of thespecimen.

3.
EXPERIMENTAL
ANALYSESRESULTSAND

The experimental results of tensile properties of
GFRP bars at different loading rates are listed inTable 1.
3.1 The load-displacement curves and the stress-strain
curvesThe load-displacement curves and thestress-strain curves are shown in Figures 3 and 4,
respectively. During the experiment, the strain gauges
were destroyed due to the deformation of thespecimen. As a result, the strain value in the second
half of the tensile experiment process was notrecorded.
As shown in Figure 3, there are platforms about 2
mm in the initial stage because there are minimal gaps
between the clamps and the slots. If pre-loading isapplied, then these platforms can be eliminated. It canbe seen from Figure 4 that the stress-strain curves are
consistent with the load-displacement curves in termsof the trends, which display a linear relationship.
3.2 Failure mechanism
During the experiments, there is no occurrence ofanchorage failure, which indicates that this anchorage
method is effective and reliable. The tensile failure

209

mode belongs to splitting failure. To be precise, thefiber split is evenly distributed throughout the entire
scale of effective tensile length and it looks like alantern as the fibers are scattered after splitting. The
splitting failure mode is shown in Figure 5.

Table 1: The experimental results of tensile properties of GFRP bars at different loading rates.
Loading rate
V(mm/min)Specimen No.
MGSL20-200F-1
MGSL20-200F-2
MGSL20-200F-3
MGSL20-200F-4
MGSL20-200F-5
MGSL20-200F-6
MGSL20-200F-7
MGSL20-200F-8
MGSL20-200F-9
MGSL20-200F-10
MGSL20-200F-11
MGSL20-200F-12

Ultimate load
Fu(kN)
150.88157.06
154.60166.80168.04159.80160.54170.92
164.45165.28169.08168.26

2

10

20

50

154.18164.88165.30167.54Ultimate strength
σu(MPa)Elastic modulus
E(GPa)

Ultimate tensile
strain εu(%)

480.5
500.2
492.4
531.2
525.2
509.0
511.3
544.3
523.7
526.4
538.5
535.9

31.0
27.6
30.0
26.2
26.0
29.9
25.7
27.8
30.1
31.9
27.3
28.8

1.55
1.81
1.64
2.03
2.06
1.70
1.99
1.96
1.74
1.65
1.97
1.86

160

180

140

160

525.1

526.4

533.6

29.5

27.4

27.8

29.3

1.67

1.93

1.90

1.83

140

120

120

100

Load/kN

Load/kN

491.0

80

100
80

60
60

40

40

MGSL20-200F-1
MGSL20-200F-2
MGSL20-200F-3

20

MGSL20-200F-4
MGSL20-200F-5
MGSL20-200F-6

20

0

0

0

2

4

6

8

10

12

14

0

2

4

Displacement/mm(1) V=2(mm/min)

8

10

12

14

(2) V=10(mm/min)

180

180

160

160

140

140

120

120

Load/kN

Load/kN

6

Displacement/mm

100
80
60

100
80
60

40

MGSL20-200F-7
MGSL20-200F-8
MGSL20-200F-9

20
0

40

MGSL20-200F-10
MGSL20-200F-11
MGSL20-200F-12

20
0

0

2

4

6

8

10

12

14

16

0

2

4

Displacement/mm(3) V=20(mm/min)

6

8

10

12

14

16

Displacement/mm(4) V=50(mm/min)Figure 3: The load-displacement curves.

210

350
350

300
300

250

Stress/MPa

Stress/MPa

250

200

150

100

0

2000

4000

6000

8000

10000

150

100

MGSL20-200F-1
MGSL20-200F-2
MGSL20-200F-3

50

200

MGSL20-200F-4
MGSL20-200F-5
MGSL20-200F-6

50

12000

0

2000

4000

6000

Strain/10-6

8000

10000

12000

14000

Strain/10-6(1) V=2(mm/min)(2) V=10(mm/min)

350
400

300

350
300

Stress/MPa

Stress/MPa

250

200

150

250
200
150

100

MGSL20-200F-7
MGSL20-200F-8
MGSL20-200F-9

50
0

2000

4000

6000

8000

10000

12000

MGSL20-200F-10
MGSL20-200F-11
MGSL20-200F-12

100
50
0

2000

Strain/10-6

4000

6000

8000

10000 12000 14000 16000

Strain/10-6(3) V=20(mm/min)(4) V=50(mm/min)Figure 4: The stress-strain curves.

Figure 5: The splitting failure mode.

In the process of experiments, when the load isincreased to about 45% of the ultimate load, the resin

and the fibers begin to split, accompanied by a clear
and crisp sound. With the increase of the load, thesplitting sound is continuous, and white cracks can beclearly seen on the splitting spot at the same time.
When it nearer to the failure load, the splitting soundbecomes louder and more concentrated, and the fibers
are split from the outside layer to the inside layer.
Finally, the specimen is damaged, accompanied with
an abruptly loud sound.
Based on the analyses of experimental phenomena
mentioned above, the tensile failure mechanism of
GFRP bars can be interpreted as follows: in the loading
process, the external fibers firstly bear the stress, andthen the resin matrix transfers them to the internal
fibers. Therefore, it is not uniformly and equivalently
distributed on the cross section, but an inversely
trapezoidal distribution that the stress gradually
decreases from the circumference to the center. That is
to say, with the increase of the stress, the external

211

fibers firstly reach the ultimate stress and fracture withthe stress redistribution at the same time. As the stresscontinues to increase, the fibers fracture gradually fromthe external layer to the internal layer, and eventually
the specimen is damaged. The failure mode belongs tobrittle failure.

30.0

530

29.5

29.0

520

Ultimate strength/Mpa
Elastic modulus/GPa
Ultimate tensile strain/%

510

28.5

500

28.0

490

27.5

480
0

10

20

30

40

50

27.0
60

2.0

1.9

1.8

1.7

1.6

Ultimate tensile strain/%

540

Elastic modulus/Gpa

Ultimate strength/MPa

3.3 Ultimate strength
The ultimate strength of GFRP bars at different
loading rates is shown in Table 1 and Figure 6.

1.5
70

Loading rate/mm/min

Figure 6: The trend graph of property indexes of GFRP bars.

As can be seen from Table 1, the ultimate strengths
are 491, 525.1, 526.4, and 533.6 MPa when the loading
rates are 2, 10, 20, 50 mm/min, respectively. Comparedto loading rate of 2 mm, the ultimate strength atloading rates of 10, 20, and 50 mm/min increases by
6.9%, 7.2%, and 8.7%, respectively. When comparing
the latter loading rate with the former one, thecorresponding ultimate strength is increased by 6.9%,
0.3%, and 1.4%, respectively.
According to Figure 6, it is particularly noticeable
that the ultimate strength sees a dramatically increasing
trend between the loading rates of 2mm/min and 10
mm/min, and afterwards it grows upwards steadily.
This is because the stress on the cross section of GFRP
bar is an inversely trapezoidal distribution, which leads
to the fact that the external fibers reach the ultimate
stress and fracture before the internal fibers. When theloading rate is lower, there is enough time for theexternal fibers to reach the ultimate stress and fracture,
which precedes the external fibers. Consequently, they
are not fractured in the meanwhile so that the ultimate
strength is lower. However, when the loading rate ishigher, there is not enough time for the external fibers
to precede the internal fibers, and they almost reach theultimate stress and fracture at the same time, thus theultimate strength is higher.
It is clear that the ultimate strength increases
significantly when the loading rate of 2 mm/minchanges into 10 mm/min and the increase is relatively

higher when the loading rate exceed 10 mm/min.
Taking the above factors into consideration ofengineering safety, a loading rate of 2 mm/min isrecommended when conducting experiments todetermine the tensile ultimate strength of GFRP bars.
3.4 Elastic modulus
Due to the instability of the strain values recordedby the instrument in the latter loading stage, the strain
values in the former loading stage, which are relatively
stable, are used to calculate the elastic modulus. The
calculation formula is shown as follows:
F1 − F2E=(ε 1 − ε 2 ) A
Where E is the elastic modulus of specimen,
and the unit is GPa; A is the cross-sectional area ofspecimen, and the unit is mm 2 ; F1 , ε1 are the load
which is 20 kN and its corresponding strain, and theunits are kN and dimensionless; F2 , ε 2 are the load
which is 50 kN and its corresponding strain, and theunits are kN and dimensionless.
As can be seen from Table 1 and Figure 6, all of
the elastic moduli of the specimens range between 25.7
GPa and 31.9 GPa, and the average value is 28.5 GPa.
When the loading rates are 2, 10, 20, and 50 mm/min,the average values of the elastic moduli are 29.5, 27.4,
27.8, and 29.3 GPa, respectively, and change by 3.5%,-3.9%, -2.5%, and 2.8%, respectively compared to theaverage value of 28.5 GPa. As the changes are small
and there is no obvious regularity, it is believed that theloading rates have little effect on the elastic modulus.
3.5 Ultimate tensile strain
The calculation formula of the ultimate tensile
strain is as follows:Fεu = uEA
Where ε u is the ultimate tensile strain, and theunit is dimensionless. Fu is the ultimate load, and theunit is kN .
As can be seen from Table 1, when the loading
rates are 2, 10, 20, and 50 mm/min, the average valuesof the ultimate tensile strain are 1.67%, 1.93%, 1.90%,
and 1.83%, respectively. Compared to a loading rate of
2 mm, the ultimate tensile strain at loading rates of 10,
20, and 50 mm/min increases by 15.7%, 13.7%, and9.6%, respectively. Comparing the latter loading ratewith the former one, the corresponding ultimate tensile
strain increases by 15.7%, -1.7%, and -3.6%,
respectively.
Theoretically, as the elastic modulus is an intrinsic
property of GFRP bar, the trend of the ultimate tensile
strain should resemble the trend of the ultimate212

strength with the increases in loading rate in Figure 6.
In reality, this is not the case and they see an opposite
trend after the loading rate of 10 mm/min. This
non-conformity can be interpreted by the discretenessof the elastic moduli, which are obtained throughcalculation.

4. CONCLUSIONS
Based on the above experimental results andanalyses, it can be concluded that:
With loading rate increases, the ultimate tensile
strength and the ultimate tensile strain increase, while
the elastic modulus remains almost constant with theaverage value at 28.5 GPa;
The failure mode of specimens belongs to splitting
failure, and the fibers gradually fracture from theexternal layer to the internal layer.
The stress-strain curves show a linear relationship,
which belongs to the scope of elastic deformation.
A loading rate of 2 mm/min or less isrecommended when conducting experiments todetermine the tensile property indexes of GFRP bars.
The anchorage method adopted in this paper iseffective and reliable, but utilizing the strain gauges torecord the strain values should be improved, and an
extensometer is recommended.

5. REFERENCESACI Committee 440. (2003a). ACI 440.1R-03.
Guide for the Design and Construction of Concrete
Reinforced with FRP Bars. American Concrete
Institute, Farmington Hills
ACI Committee 440. (2004b). ACI 440.3R-04.
Guide Test Methods for Fiber-Reinforced Polymers(FRPs) for Reinforcing Or Strengthening Concrete
Structures. American Concrete Institute, Farmington
Hills
American Society Testing and Materials. (2002).
ASTM D 3916. Standard test method for tensile
properties of pultruded glass-fiber-reinforced plastic
rods
Benmokrane, B., Zhang, B., Chennouf. A. (2000).
Tensile properties and pullout behavior of AFRP and
CFRP rods for grouted anchor applications.
Construction and Building Materials, No. 14, pp.
157-170
Chen, J., Huang, J., Chen. Q. (2012). Test researchon tensile mechanical properties of GFRP rebar.
Building science. Volume 28, No. 7, pp. 43-46
General Administration of Quality Supervision,
Inspection and Quarantine of the People's Republic ofChina, Standardization Management Committee of thePeople's Republic of China. (2005a). GB/T 1447-2005.
Fiber-reinforced plastics composites-Determination oftensile properties. Standards Press of China, Beijing

General Administration of Quality Supervision,
Inspection and Quarantine of the People's Republic ofChina, Standardization Management Committee of thePeople's Republic of China. (2008b). GB/T
13096-2008. Test method for mechanical properties ofpultruded glass fiber reinforced plastic rods. Standards
Press of China, Beijing
Kim, H.Y., Park, Y.H., You, Y.J., Moon, C.K.
(2015). Short-term durability test for GFRP rods undervariousenvironmental
conditions.
Composite
Structures, No. 83, pp. 37-47
Kocaoza, S. Samaranayake, V. A., Nanni, A.
(2005). Tensile characterization of glass FRP bars.
Composites, No. 36, pp. 127-134
Li, G., Ge, G., Ni, C., Dai, J., Mu, C. (2012). Effectof loading rate on tensile properties of full-scalespecimen of large-diameter glass fiber reinforced
polymer(GFRP) bar. Rock mechanics and engineering,
Volume 31, No. 7, pp. 1469-1477
Liu D., Zhou J. (2014). Discussion on theapplication of fiber reinforced plastics bars in Civil
Engineering.
Engineering
Technology.
DOI:10.13751/j.cnki.kjyqy.2014.07.195
Micelli, F., Nanni, A., Chen, S. (2004). Durabilityof FRP rods for concrete structures. Construction and
Building Materials, No. 18, pp. 491-503
Ministryof
HousingandUrban-Rural
Construction of the People's Republic of China. (2012).
JG/T 351-2012. Fiber reinforced composite bars.
Standards Press of China, Beijing
State Administration of Work Safety. (2008).
MT/T 1061-2008. Fiber-glass reinforced plastics bar ofbolt and accessories. The Coal Industry Press, Beijing
Uomoto T., Nishimura T. (1995). Static and fatigue
strength of FRP rods for concrete reinforcement. In:
Non-Metallic (FRP) Reinforcement for Concrete
Structures - Proceedings of the Second International
RILEM Symposium, L. Taerwe. (eds.), CRC Press, pp.
100-107
You, Y.J., Park, Y.H., Kim, H.Y., Park, J.S. (2007).
Hybrid effect on tensile properties of FRP rods withvarious material compositions. Composite Structures,
No. 80, pp. 117-122
Zhang, X., Ou, J., Wang, B., He, Z. (2005).
Comparison experimental study on mechanicalproperty of different GFRP bars. Fiber Reinforced
Plastics/Composites, No. 2, pp. 9-25
Zhou, J., Du, Q., Chen, L., Ma, X. (2008).
Experimental study on size effect in tensile mechanicalproperties of GFRP rebar. Journal of Hohai University,
Volume 36, No. 2, pp. 242-246

213

Part 2

Technology

ISMS 2016

Paper No. 3
A definition and evaluation index system of aging mines
MA Hu i a, LIAN Huiqing a, ZHU Hongjie bab

Safety Engineering College, North China Institute of Science and Technology, City, Beijing, China ,101601
China Shenhua International Engineering Co., Ltd, Beijing, China,100007

ABSTRACT
Because of the limited storage of coal resources, coal production progresses from growth to decline until eventual
mine closure. At present, aging mines have no clear name, conception, defined definition, and complete system.
Based on the analysis of the mine life cycle and the problems associated with mine development and conceptions in
the past, this paper aims to construct an evaluating index system of decrepit mines and define the index of weightlayer by application of the analytic hierarchy process (AHP), so as to provide a basis for development planning ofmine enterprises, and law-making for resource-based cities and countries.
KEYWORDS: aging mines; define; evaluation index system

1. THE LIFE CYCLE OF A MINE
Due to the fact that mineral resources are finite
and non-renewable, mining enterprises trend frombirth to death and prosperity to decline, just likeorganisms. The whole process of mine production
and the service cycle must go from exploration,building a well, putting into production, stableindustry, aging, and finally being shut down. This iscalled the life cycle of a mine.
According to "The economic structuretransformation of resources city", the statistics from
August 2003 by the national development and reform
commission, there are altogether 118 resource-based
cities in China, including 63 coal cities, 12 nonferrous metal cities, 8 ferrous metallurgy cities, 9 oilcities, and 5 other cities. These account for about
18% of the number of cities around the country and a
total population of 154 million people. China has
determined 69 resource-exhausted cities (counties
and districts). As of the middle of the 20th century,
two-thirds of state-owned mines have entered theaging stage and 440 mines will be closed. 50 resource
cities are experiencing resource failure in a total of
390 mines. 3 million workers have been laid-off and
10 million families’ lives have been affected.
The definition of aging mines anddetermination of an evaluation index system isvery important due to the complexity of the work of
aging mines closed underground material recycling
equipment, the shunt placement of mine workers, andthe processing and handling of history of creditor'srights debt.
The definition and evaluation index system of
aging mines is basic research which includes
evaluation theory, research methods, index systems,
and a classification scheme. At present, aging mines*Corresponding author – email : mahui1982@ncist.edu.cn

are short of a scientific definition, complete statisticalanalysis conclusions and comprehensive research.
This has adverse effects on the development of large
coal mining enterprises and the decisions ofgovernment developing. At the microscopic level thedefinition and evaluation index system of aging
mines can make sure the limited storage
characteristics of coal resources are considered inadvance. The index can choose the important point
and analyze the enterprise development strategy andchange into the developing period from thesenescence phase, avoid influence on layoffs, cut
down the number of persons employed and upper andlower relation in coal mining enterprises. At themacroscopic scale, the index system of aging mines
can help to more easily determine the weight index
for local government rewards for mining enterprises
in provinces. Based on the above reasons, it also
provides theoretical support and practical suggestions
for macroscopic development strategy, medium-longterm plan policies and regulations for local
government.

2. DEFINITION OF AGING MINES
The definition of aging mines is a complex
problem. Previous scholars have studied resource
depletion, but face closed mine appellation isdifferent. Common appellations are old mining, aging
depleted mines, resource crisis mines, old mines,
middle-late mines and crisis mines, and so on. The
definition of aging mines also has different points ofview, as follows.
(1) Some people like Lu Guxian believe that
resources crisis mines are due to a shortage formineral resources in the mining areas, the drying upof the recoverable reserves, or due to the change of3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

market conditions of the commodity pricefluctuations, changes in supply and demand so thatthe economical development and utilization of its
reserves of mineral resources are difficult to continue.
This leads to the decline of mine production,
significant excess production capacity, anddeterioration of operating conditions. Therefore in thepresent or the future there is a certain period of time
where it is difficult to maintain normal production
and business operation and facing closure or
bankruptcy of mining enterprises.
(2) Jia Yanjie thinks that aging mines mainly
have the following signs: consumption of mining
reserves more than two-thirds of the minerecoverable reserves; the residual service life of mineis less than 10; the number of tons of coal reaches to
3 people which 1 time more than the period ofdevelopment and stablity; the tons of coal toinvestment is 80 yuan, more than 60% higher than
the stable stage; the mine production has begun to
decline and the Nissan's level has dropped forstability and design ability.
(3) Li Qing and Li Kerong point out thequantitative standard of the coal enterprises indifferent stages of the life cycle. We can judge itfrom the mining coefficient of fixed number of years
and the mining ability structure coefficient. The socalled mining coefficient of fixed number of years is
judged mainly from the main business continued
ability in the future of coal mining, total reserves, andthe perspective of overall production capacity in the
future.
(4) On the basis of investigation and research,
the original state coal industry bureau made thestandard for coal mine resource depletion, and highash and sulfur turn around. It believes that one of thefollowing two conditions must be met in order to beconsidered an aging or resource depleted mine. Basedon the 1991 No. 211 document on May 13 of theoriginal coal, the mine can adopt reserves to reduce,
without augmenting resources at depths andperipheries, with remaining recoverable reserves ofaround 20% for the original design. According to theactual recoverable reserves, mine design capability
must consider the reserve coefficient calculation ofresidual service life of coal mine of no more than 5
per mine.
(5) In the study of coal aging scrap best point,some people like Huang Shude analyzed the different
well types, at different fixed number of years of the
production and development trend of production
under conditions of mine production and operationand put forward the mine into the aging point
judgment index system.
(6) On the basis of the name of mine and its
basic concepts, Lu Gang unified the designation of

aging mines, defined the concept of aging mines, andpointed out that the aging of mines is to point torecoverable resources drying up, basic coalproduction capacity experiencing a sharp drop in
production, and difficulty maintaining normal
production and operation of the mine.
In conclusion, many scholars concentrated on
the remaining recoverable reserves, residual length ofservice, production capacity, tons of coal cost, etc.
These scholars did not consider enterprise economic
benefits (especially not the income of coal industry toGDP), the degree of deep and peripheral resources
available, recycling feasible extent of loss ofresources, resources recycling feasible degree,
national policies, and regulations compliance andsafety. Based on this analysis, the current study puts
forward the idea that the aging mine is one thatexperiences a production plateau, economic
downturn, the remaining resources occurrence
condition deteriorates, cannot meet the normal
mining economic and technological conditions, tonsof coal cost, production capacity and the status of themine is not in conformity with the provisions of thestate.

3. CONSTRUCTION EVALUATION INDEXSYSTEM OF AGING MINES
3.1 Evaluation Index System of Aging Mines
According the characteristics of aging mines andthe principle of index system construction andintroduction the meaning of evaluation index should
be settled. The principles of the index system include
the objectivity, system, comparability, feasibility, anddynamic.
Table 1: Evaluation index system of aging mines.
ObjectRule hierarchy
Indicator layer
hierarchy
Sales profit ratio( A1)
Mine economic Asset-liability ratio(A2)efficiency( A)
Non-CoalIndustry
income ratio (A3)
The residual service life
living condition of for mine (B1)
Reserve-production ratio
Minemineral resources
grew into （ quality and decrease rate (B2)
The utilization degree ofsenescenc
quantity）( B)
deep department ande phaseouter resources (B3)Theeconomicandreasonable mining depth(C1)
EconomyFeasibility of resources
technology
loss recycled (C2)condition (C)Feasibility of resource
reutilization( C3)215

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

thetonsynthesizes
(D)

coal
cost

productivity andsafe condition( E)The
socialresponsibilities
performance
condition (F)

The
per
ton
coal
employees (D1)
The per ton coal funds
input (D2)Whether match nationallaws and regulations (E1)
Megaton coal mortality(E2)
Safety investment cost
rate (E3)The social contribution
rate (F1)
Capitaincomeof
employee( F2)
The total tax (F3)

3.2 The assurance of weight of index evaluation index
The layer analytical (AHP) was put forward in
the 20th century by a teacher, T.L. Saaty at theAmerican Pittsburgh University. It is a kind ofsystem analysis method that combines fixed amountand quality together and imitates the person's
decision thinking process. It is used to solve
complicated systems with many factors, especiallyhard fixed amounts of the analytical method of social
systems. AHP belongs to the index sign comparison
method, and it can judge with the consistency
examination to check whether the related index signimportance has a logic mistake. It gets rid of artificial
understanding of limits from a person to a great
extent, so it can be extensively applied in eachprofessional field. This text applied layer analyticalmethod assurance the decrepitude mineral well all
levels index sign weight of index. The layer analyzes
the foundation theory of methods.
(1) Aiming at rule hierarchy weight of index
with the AHP method, calculating results are shownin Table 2.
Table 2: Weight of rule hierarchy index.

T
A
B
C
D
E
F

A

B

C

D

E

F

weight of index

1
1/2
1/3
1/4
1/5
1/6

2
1
1/2
1/3
1/4
1/5

3
2
1
1/2
1/3
1/4

4
3
2
1
1/2
1/3

5
4
3
2
1
1/2

6
5
4
3
2
1

0.373
0.252
0.160
0.101
0.064
0.043

Calculating processes are as following：Firstly, number out each element’s product in a
judgment matrix, it accumulates: M 1=720; M 2=60;
M 3=4;M 4=0.25; M 5=0.0167; M 6=0.00139;
Secondly, computes Mi of 6Wi

； W1 = 2.934 ；W2 = 1.979 ； W3 = 1.260 ； W4 = 0.794 ； W5 = 0.505 ；W6 = 0.334

Thirdly, carry on unitary processing or regularprocessing to()

P = W1 ,W2 ,W3 ,W4 ,W5 ,W6 : that is

W1=0.373 W2=0.2518 W3=0.160 W4=0.1014
W5=0.0642 W6=0.0425
Fourth, the above characteristic vector is thepower begged while it still needs to carry on
consistency examination towards the judging matrix:① Compute the biggest characteristic value of6

6

λmax = ∑ (PW )i / nWi = 1 n ∑ (PW )i / Wi

i =1
i =1
matrix|②The consistency examines；
C R = C I / R I ； C I =( λ max-n）/（n-1）

if n=6 ， RI = 1.24 ， λ max=6.12 ，
C R = 0.0199 < 0.1 ,the consistency examination

passes.
(2) Compute an index sign layer index sign
power with reason respectively heavy, as Tables 3-8
show.
1) According to Mine economic efficiency (A1),asset-liability ratio (A2), the non-Coal Industry
income ratio (A3) influence toward mine economic
efficiency degree is different, calculating the powerof each index sign heavy, as Table 3 shows.
Table 3: Weight of mine economic efficiency index.
A A1 A2 A3 weight of index
A1
1
2
3
0.540
A2 1/21
2
0.297
A3 1/3 1/2
10.1632) According to the residual service life formine (B1), tReserve-production ratio decrease rate(B2), the utilization degree of deep department andouter resources (B3) to measure the degree ofdifferent by mineral well resources endow to acondition, compute index weight of index..
Table 4: Weight of resources reserves index.
B

B1

B2

B3

weight of index

B1

1

1/2

2

0.297

B2

2

1

3

0.540

B3

1/2

1/3

1

0.163

3) The economic and reasonable mining depth(C1), study on the feasibility of resources loss
recycled (C2), study on the feasibility of resource
reutilization (C3), measurement for mineral welleconomic technique conditional of the importantdegree is different, to draw out each index sign216

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016weight of index, as shown in Table 5.
Table 5: Weight of economic technique condition index.
C
C1
C2
C3
weight of index
C1

1

2

3

0.540

C2

1/2

1

2

0.297

C3

1/3

1/2

1

0.163

4) The per ton coal funds input (D2) and the per
ton coal employees (D1) to the ton coal cost isdifferent which gets the conclusion of an each index
sign of weight of index.
Table 6: Weight of ton coal comprehensive cost index.
D

D1

D2

weight of index

D1

1

3

0.75

D2

1/3

1

0.25

5) Whether match national laws and regulations(E1), Megaton coal mortality (E2), safety investment
cost rate (E3), these three factor’s influence on the
productivity and safety condition is different.
Compare the matrix and weight of index as Table 7
shows.

Table 9: Decrepitude mineral well evaluation index system.
Name ofStandard
layer index
Mineeconomic
efficiency(A)livingcondition ofmineralresources(B)

Economytechnology
condition(C)

Weight
of
index

0.373

0.252

0.160

Table 7: Weight of productivities and safe condition index.
E

E1

E2

E3

weight of index

E1

1

2

3

0.540

E2

1/2

1

2

0.297

E3

1/3

1/2

1

0.163

6) The social contribution rate (F1) and capita
income of employee (F2), total tax amount (F3) threesecond class index signs towards measuring theimportance that the Corporate Social Responsibility
implements condition is different to get thecomparing matrix and weight of index, as in Table 8.
Table 8: Weight of social responsibilities implement
condition index.
F
F1
F2
F3
weight of index
F1

1

1/2

2

0.297

F2

2

1

3

0.540

F3

1/2

1/3

1

0.163

According to the above analysis calculation, we
can get a decrepitude mineral well evaluation index
sign weight of index, as Table 9 shows.

the ton coalsynthesizes
cost (D)productivity
and safe
condition(E)
The social
responsibilities
performance
condition
(F)

0.101

0.064

0.043

Index sign layer inde
nameSales profit ratio(A1)
Asset-liability
ratio(A2)
Non-Coal Industry
income ratio(A3)The residual service
life for mine (B1)
Reserve-production
ratio decrease rate
(B2)
The
utilization
degreeofdeep
department
andouter resources( B3)
The economic andreasonable mining
depth (C1)
Study
on
the
Feasibilityofresources
loss
recycled (C2)
Study
on
the
Feasibilityofresource
reutilization (C3)
The per ton coalemployees (D1)
The per ton coalfunds input (D2)Whethermatch
national laws andregulations (E1)
Megatoncoal
mortality (E2)
Safetyinvestment
cost rate (E3)The
socialcontribution
rate
(F1)
Capita income of
employee (F2)
The total tax (F3)

Weight
of
index
0.540
0.297
0.163
0.297
0.540

0.163

0.540

0.297

0.163

0.75
0.25
0.540
0.297
0.163
0.297
0.540
0.163

Making use of the layer of this text introduction
analysis method to draw out the power of each
evaluation of index sign can provide a theoreticalfoundation to see whether the mineral well gets into adecrepitude period, from the decrepitude mineral wellevaluated index sign of system index sign analysis,
mine economic efficiency A, living condition ofmineral resources B, and economic techniquecondition C takes the most space. Sales profit ratio217

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

A1, reserve-production ratio decrease rate B2, andthe economic and reasonable mining depth C1, again
occupy an important position in this layer. The index
signs of national laws and regulations E1 and capita
income of employee F2 should also be considered.

4.

CONCLUSION

The main conclusions from the analysis of theconception of the decrepitude mineral well and thedecrepitude mineral well definition index system are
as follows:
On the foundation of the analytical mineral welllife cycle and the decrepitude mineral wellconception, we analyzed the existing concepts ofshortage and put forward a new decrepitude mineral
well conception, namely that a decrepitude mineral
well occurs after the mineral well’s steady production
period, the surplus resources endows with a claim
check piece depravation because the economic
efficiency falls, the economic technique condition
can not satisfy the mine, the ton coal cost
significantly increases, and the productivity and safe
condition do not satisfy the nation’s rules.
(2)Owing to the foundational research on the
resource potential of the decrepitude mineral wells
and the definition of the decrepitude degree,
evaluation theory, research on method, index sign
system and classification project, the decrepitude
mineral well lacks a scientific definition, integrity
statistics, analysis and comprehensive study, and adecrepitude mineral well evaluation index system.
Following the principles of objectivity, systemand comparition, possibility and dynamic state wereused to set up a decrepitude mineral well evaluationindex sign system. Mineral mountain economic
efficiency’s standard layer index sign is 7, and thesell profit margin index sign layer is 17.
The layer analysis method was applied to assure
all levels index sign power in decrepitude mineral
well evaluation. This provides a basis for making
development programming of mineral mountain
enterprises from both the micro view and the macro
view for resource cities and nation’s farsighted
development and law establishment.

5.

6.

REFERENCES

GUO Yuhong. Characteristics of input andoutput and economic evaluation method of aging
mine [J].Coal Economic Research.1990(11):39-41
HUANG Shude, GAO Yongju, ZHENG
Guanghua. Research of best point of scrap in aging
coal mine [J]. Journal of Henan Polytechnic
University(Natural Science). 1993, 34 ( 5): 28- 29
LU Gang, CHENG Wei ， HAN Keqi.
Simulation study on the life cycle identification of
the aged coal mine and mine[J]. Journal of Henan
Polytechnic University (Natural Science Edition).2009,28（5）:659～694
LU Gang.Research on Residual Coal
Workability Evaluation and Remining Technology ofAged Coal mine[D] China University of Mining andTechnology,2010
MA Hui, LIAN Huiqing, ZHU Hongjie. SWOT
analysis of aging mines' low carbon development[J].
The 2nd International Symposium on Mine Safety
Science and Engineering. 2013,259-261
REN Yixin, HAN Gang, DING Ru, WANG
Ning. Construction of circular economy mode of oldcoal mine. Mining and Metallurgical Engineering,
2008,28（4）:108～113
WANG Chun, WANG Baicheng. Research andpractice of old coal mine mining technology[J]. Coal
Technology,2006,25(2):48～50
WEI Guangxing. Summary and remarks ofenterprise life cycle theory [J].Productivity Research.
2005,(6):52-53

ACKNOWLEDGEMENT

I’d like to express my sincere thanks to all
people helped me, especially Mrs LIAN Huiqing ,MrZHU Hongjie ,Miss Dong Lili and Miss Pei Ying ，always support and encourage me in the process of
paper writing .
The paper is supported by The central university
basic scientific research business expenses（3142014021.

218

ISMS 2016

Paper No. 31

Numerical simulation of thermodynamic performance in a honeycomb
ceramic channel
Bo Lan a,b,*, You-Rong Li aa

Key Laboratory of Low-Grade Energy Utilization Technologies and Systems of Ministry of Education, College of PowerEngineering, Chongqing University, Chongqing, China, 400044b
China Coal Technology Engineering Group Chongqing Research Institute, Chongqing, China, 400037

ABSTRACT
In order to understand the thermodynamic performance in a honeycomb ceramic channel, a 3D numerical simulation
was carried out using FLUENT. The effects of mass flow rate, solid heat capacity, and reversal time on temperature
efficiency were investigated. Results show that with the increasing mass flow rate, the temperature efficiency
decreases linearly and the pressure drop increases linearly in each half-cycle. For computed cases the effect of solid
heat capacity on the temperature efficiency is negligible. With the increasing reversal time, the temperature
efficiency decreases slowly in the bed heated period, and is not influenced in the bed cooled period.
KEYWORDS: numerical simulation; honeycomb ceramic channel; thermodynamic performance; temperature
efficiency

1. INTRODUCTION
Methane (CH4) is a greenhouse gas (GHG) thatis 21 times more potent than carbon dioxide (CO2) interms of trapping heat in the atmosphere over a
timeframe of 100 years (Gosiewski et al., 2008).
Ventilation air methane (VAM) emitted fromunderground coal mines constitutes a major part ofgreenhouse gas emissions from coal mining and is awasted resource. The utilization methods of VAM
have been studied extensively in recent years (Su etal., 2005; Su et al., 2006; Yin et al., 2010; Karacan etal., 2011; Baris, 2013; Krzysztof et al., 2014;
Martinez et al., 2014; Zhang et al., 2014).
The utilization methods can be divide into
ancillary use and principle use (Su et al., 2005). For
the ancillary use, VAM is used to substitute ambient
air in combustion processes, including gas turbines,
internal combustion engines, and coal-fired power
stations. For the principle use, the methane in VAM
is used as a primary energy source.
Nowadays, only the thermal flow-reversal
reactor (TFRR) and catalytic flow-reversal reactor(CFRR) are seriously taken into account for industrial
usage. The only difference between these two devices
is with respect to the use of catalyst. Honeycomb
ceramic is the most important component of TFRR
and CFRR. However,
the thermodynamic
characteristics of honeycomb ceramic channel havenot been clearly studied.
The aim of this study is to investigate thetemperature migration rule in honeycomb ceramic
beds, and examine the effects of mass flow rate, solid* Corresponding author – email: lbmky@163.com

heat capacity, and reversal time on temperature
efficiency.

2. PHYSICAL
MODEL

AND

MATHEMATICAL

2.1 Physical model
There are millions of honeycomb ceramicchannels in a regenerative oxidation bed. The flow
and thermal performance of each honeycomb ceramicchannel is similar to the others.
The geometry of a single honeycomb ceramicchannel and the coordinate system is shown in Figure
1. The channel size is 3 mm × 3 mm and the wall
thickness is 0.7 mm. The length is 300 mm.
One heat exchange cycle is comprised of two
flow reversals, so each flow reversal is a half-cycle.
During the first half-cycle, hot gas enters from theright and leaves through the left. The bed is heated
and the fluid is cooled down. This half-cycle is called
the bed heated period. After a time interval the flow
direction is reversed. Cold VAM enters from the left
and leaves through the right. The bed is cooled down
and the VAM is heated. This half-cycle is called the
bed cooled period.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

where Rg is the gas constant.
Solid energy equation∂ ( ρ sT )λ= ∇ ⋅  s ∇T 
(5)
c

∂t
 ps

where ρ s , λs , c ps are the solid density, conductivity,
specific heat, respectively.

Figure 1: Physical model.

2.3 Physical parameters of fluid and solid
The physical parameters of fluid are listed inTable 1.

2.2 Governing equations
Table 1 :The physical parameters of fluid.
The honeycomb ceramic channel has a threeValue
dimensional unsteady flow. There are three different
Items
Unit
273
K
473
K
773 K
1173 K
heat transfer processes: heat conduction process3ρ
kg/m
1.293 0.746
0.456
0.301
inside the fluid, heat convection between the solidand fluid, and heat conduction inside the solid.
CpJ/(kg·K)
1005
1026
1093
1172
The following assumptions are introduced in the-2
λ10 W/(m·K)
2.44
3.93
5.74
7.63
present model: (1) radiative heat transfer is neglected-6μ10kg/(m·K)
16.7
26
36.2
46.7
because air, oxygen, and nitrogen are not able to emit
and absorb radiation energy; (2) the heat dissipation
The physical parameters of solid are defined ason the outer wall of the channel is neglected; (3) the
follows:
air physical parameters are applied for VAM and hot
fluid; (4) methane oxidation generally occurs in theρ s = 2500
kg/m3
combustion chamber, rather than in the honeycomb(6)ceramic channel, and this paper focuses on the heat=
λs 0.000666T + 1.305
W/(m·K)transfer law in the honeycomb ceramic channel,(7)
ignoring the effect of methane oxidation.
With the above assumptions, the governing=
C ps 0.23T + C ps 0
J/(kg·K)
equations of flow and heat transfer could be(8)
expressed as follows:
where C ps 0 is a parameter determined by the solid
Continuity equation∂ρmaterial.
(1)+ ∇ ⋅ ( ρU ) = 0∂t
2.4 Boundary conditions
where ρ , t , U are the fluid density, time, velocity,
A symmetrical boundary condition is applied forrespectively.
the
outer
walls of the honeycomb ceramic (x=0mm,
Momentum equation
x=3.7mm, y=0mm, y=3.7mm), and adiabatic∂ ( ρU )boundary condition for the front and back wall(2)
+ U ⋅ ∇ ( ρU ) = −∇p + µ∇ 2U + S(z=0mm, z=300mm). A coupled boundary condition∂t
is used for the inner walls of the honeycomb ceramic
where p , µ , S are pressure, the fluid dynamic
channel.
viscosity, source term, respectively.
Mass-flow-inlet boundary condition is applied
Fluid energy equation
for the inlet, and pressure-outlet boundary conditionλ
∂ ( ρT )for the outlet. The inlet temperatures of hot and cold+ ∇ ⋅ ( ρUT ) = ∇ ⋅  ∇T  + Φ
(3)
fluid
are constant and equal to 1173 K and 293 K,


∂t
 cp

respectively.
where T , λ , c p , Φ are temprature, the fluid
2.5 Numerical methods
conductivity, the fluid specific heat, dissipative
The model is solved by FLUNET. The governing
function, respectively.
equationsare discretized by the finite differenceState equation
method. The central difference approximation isp = ρ Rg T
(4)applied for the diffusion terms and the second orderof upwind scheme is used for the convection terms.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The SIMPLEC algorithm is applied to couple thepressure and velocity variables.
In order to check the validation of this model, asimulation is carried out under the same conditions
with the case carried out by (Zhang et al., 2010). In
the case, The channel size is 3 mm × 3 mm, the wall
thickness is 1 mm, and the length is 100 mm. The
obtained pressure drop is 15.7 Pa with inlet velocityof 2 m/s, which is comparabe with the result of 15 Pa
carried out by Zhang (2010).

3. RESULTS AND DISCUSSION
A 3D numerical simulation is carried out toinvestigate the thermodynamic performance byvarying mass flow rate, solid heat capacity, andreversal time. In this work seven cases are computed,
as shown in Table 2. The mass flow rate and reversal
time are represented as Qm and tr , respectively.

Table 2: The seven cases (A-G) computed in this work.
Items

Unit

A

B

C

D

E

F

G

Cps0

J/kg·K

907

907

907

750

1050

907

907

Qm

kg/s

1×10-5

1.5×10-5

2×10-5

1×10-5

1×10-5

1×10-5

1×10-5

tr

s

30

30

30

30

30

15

45

3.1 Thermodynamic performance in the honeycomb
ceramic channel
In the bed heated period the hot fluid
temperature ( Th ) is higher than the solid temperature( Ts ), and heat transfers from the hot fluid to the solid.
As time goes by, the solid temperature increases
gradually. The solid temperature profile along theflow direction moves upward, as shown in Figure 2.
It leads to a reduction of the temperature difference
between the fluid and solid. The heat storage capacityof the solid reduces and the fluid outlet temperature
increases. As a result, the fluid temperature
distribution moves upward over time. The
temperature change rates of the hot fluid and solid are-1.83 K/s and 2.14 K/s, respectively.
In the bed cooled period the rules are reversed.
Due to the lower cold fluid temperature ( Tc ), heattransfers from the solid to the fluid. The temperature
distribution of the cold fluid and solid along the flow
direction moves down over time, as shown in Figure
3. The temperature change rates of the cold fluid andsolid are 1.77 K/s and -2.12 K/s, respectively.
Logarithmic mean temperature differences
between the fluid and solid decrease over time ineach half-cycle, as shown in Figure 4. Meanwhile theheat flux on the inner walls of the channel decreases
linearly, and the heat transfer capability deteriorates,
as shown in Figure 5.
3.2 Effect of mass flow rate
In order to evaluate the heat exchange
performance of the honeycomb ceramic channel, thetemperature efficiency is defined as follows:
The temperature efficiency in bed heated period

T − Th ,oε h = h ,i

Th ,i − Tc ,i(9)where Th ,i and Th ,o are the inlet and average outlet
temperatures of the hot fluid, respectively, and Tc ,i isthe inlet temperature of the cold fluid.
The temperature efficiency in bed cooled period

T − Tc ,iε c = c ,oTh ,i − Tc ,i(10)where Tc ,o is the average outlet temperature of thecold fluid.
Figure 6 shows the effect of mass flow rate on
the temperature efficiency. In the bed heated period,
the temperature efficiency decreases linearly with theincrease in mass flow rate. The reason is that moreheat is intaken by a higher mass flow rate, and thesolid cannot fully absorb the increasing heat, andmore heat is carried out by the hot fluid. In the bed
cooled period, the temperature efficiency also
decreases with the increasing mass flow rate.
Figure 7 shows that the pressure drops are
increasing with the increase in mass flow rate in eachhalf-cycle. With the same mass flow rate, thepressure drop in the bed heated period is higher thanthat in the bed cooled period.
The above results indicate that reducing mass
flow rate is positive for improving temperature
efficiency and reducing pressure drop.

221

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 4 :Variation of logarithmic mean temperature
difference between the fluid and solid in one heat exchange
cycle for case A

Figure 2: Temperature distributions of the hot fluid andsolid along flow direction in bed heated period for case A.
Figure 5: Variation of heat flux in one heat exchange cycle
for case A.

Figure 3: Temperature distributions of the cold fluid andsolid along flow direction in bed cooled period for case A.

Figure 6: Effect of mass flow rate on the temperature
efficiency.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 7: Effect of mass flow rate on pressure drop.

temperature efficiency is almost not influenced byreversal time.

3.3 Effect of solid heat capacity
Figure 8 shows that the larger the specific heat is,
the more significant the variation of outlet
temperature in each half-cycle. However the variationof average outlet temperatures is small for both hot
and cold fluid in three computed cases.
As shown in Figure 9, in the bed heated period
the temperature efficiency is almost not influenced byheat capacity, and in the bed cooled period thetemperature efficiency increases slowly with theincreasing heat capacity.

Figure 10: Effect of the reversal time on the temperature
efficiency

4. CONCLUSION

Figure 8: Outlet temperatures of hot and cold fluid in one
heat exchange cycle ( Th , o : hot fluid, Tc , o : cold fluid).

A 3D numerical simulation was performed toinvestigate the thermodynamic performance inhoneycomb ceramic channel. The following
conclusions were made:1) In the bed heated period the temperaturechange rates of the hot fluid and solid are -1.83 K/s
and 2.14 K/s, respectively. In the bed cooled period
the change rates of the cold fluid and solid are 1.77
K/s and -2.12 K/s, respectively. Logarithmic mean
temperature differences between the fluid and solid
decreased over time in each half-cycle, and the heat
flux on the inner walls of the channel decreased
linearly.
2) With the increasing mass flow rate, thetemperature efficiency decreased linearly, and thepressure drop increased linearly in each half-cycle.
3) For computed cases the effect of solid heat
capacity on the temperature efficiency is ignorable.
4) With the increasing reversal time, thetemperature efficiency decreased slowly in the bed
heated period, and was almost not influenced in the
bed cooled period.

5. ACKNOWLEDGEMENT
Figure 9: Effect of solid heat capacity on the temperature
efficiency.

3.4 Effect of reversal time
Figure 10 shows the effect of reversal time on
the temperature efficiency. In the bed heated period,
the temperature efficiency decreases slowly with theincreasing reversal time. In the bed cooled period, theThis work is supported by National Science andTechnology Major Project (Project Number
2011ZX05041-005).

6. REFERENCES
Baris K. (2013). Assessing ventilation air
methane (VAM) mitigation and utilization
opportunities: A case study at Kozlu Mine, Turkey.

223

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Energy for Sustainable Development, Volume 17, pp.
13-23.
Gosiewski K., Matros Y.S., Warmuzinski K.,
Jaschik M., and Tanczyk M. (2008). Homogeneousvs. catalytic combustion of lean methane—air
mixtures in reverse-flow reactors Chemical
Engineering Science, Volume 63, pp. 5010-5019.
Gosiewski, K., and Pawlaczyk, A. (2014).
Catalytic or thermal reversed flow combustion ofcoal mine ventilation air methane: What is better
choice and when. Chemical Engineering Journal,
Volume 238, pp. 78-85.
Martinez D.M., Cluff D.L., and Jiang X. (2014).
Numerical investigation of the burning characteristics
of ventilation air methane in a combustion based
mitigation system. Fuel, Volume 133, pp. 182-193.
Karacan C.O., Ruiz F.A., Cote M., and Phipps S.
(2011). Coal mine methane: A review of capture andutilization practices with benefits to mining safety
and to greenhouse gas reduction. International
Journal of Coal Geology, Volume 88, pp. 121-156.
Karakurt I., Aydin G., and Aydiner K. (2011).
Mine ventilation air methane as a sustainable energy
source . Renewable and Sustainable Energy Reviews,
Volume 15, pp. 1042-1049.
Su, S., Beath, A., Guo, H., and Mallett, C. (2005).
An assessment of mine methane mitigation andutilization technologies. Progress in Energy andCombustion Science, Volume 31, pp. 123-170.
Su S., and Agnew J. (2006). Catalytic
combustion of coal mine ventilation air methane.
Fuel, Volume 85, pp. 1201-1210.
Yin J., Su S., Yu X.X., and Weng Y.W. (2010).
Thermodynamic
characteristics
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concentration methane catalytic combustion gas
turbine. Applied Energy, Volume 87, pp. 2102-2108.
Zhang Y.X., Doroodchi E., and Moghtaderi B.
(2014). Utilization of ventilation air methane as anoxidizing agent in chemical looping combustion.
Energy Conversion and Management, Volume 85, pp.
839-847.
Zhang Z.X., Liu Y.Q., Gao Z.Q., and Liu
R.X.(2010). Simulation study of flow and heattransfer in ceramic regenerator. ICE&Powerplant,
Volume 116, pp. 18-22.

224

ISMS 2016

Paper No. 32

Dust Dispersion Analysis Based on the Rosen-Rammler Distribution Function
Yao Haifei a,b, Zhang Qun a,babSafety Branch, China Coal Research Institute Company Limited, Beijing, China, 100013
National Key Lab of Coal Resource High Efficient Mining and Clean Utilization, Beijing, China, 100013

ABSTRACT
According to the principle of deriving mine dust distribution from the Rosen-Rammler distribution function, dust
particle size distribution data at four places on the 4339 working face in Wangzhuang Coal Mine were regressionanalyzed so as to get the dust particle size distribution law. The results show that in the area of 5 m away from theworking face in the intake airway, the percentages of mine dust of less than 5μm, 5 to 10μm and larger than 10μm in
particle size are 14.8%, 32.5% and 52.7%, respectively, with a concentrated distribution of 5 to 20μm. The size ofmine dust concentrates in the range of 5 to 10μm for the transfer point, in the range of 5 to 10μm for the 50# supportof the working face, and in the range of 5 to 20μm for the area of 20 m away from the working face in the outlet
lane. Some corresponding dust-proof suggestions were finally put forward on the basis of the characteristic of mine
dust distribution in different places.
KEY WORDS: mining; mine dust; dispersion; distribution functions; regression analysis

1. INTRODUCTION
As one of the most important properties of dust,
dispersion is defined as the ratio of various sizes ofdust in the whole composition, which has important
relationship with miner’s silicosis (Jin, 1993). The
particle size distribution law of dust has closed
relationship with the labor environment, theimplementation of dust-suppression measure and the
choice of dust-suppression equipment (Shi et al.,2007).
All the dust particle size distribution measured
by various methods and instruments are needed to
explore the accurate distribution law using a suitable
mathematical method (Isabelle et al., 2005). The
common distribution laws are as follows: normal
distribution, logarithmic normal distribution and
Rosen-Rammler distribution (Wang, 1991).
The mineral and rock that can generate dust
during mine production are brittle materials. The dust
formed by brittle materials demonstrates the skewed
distribution law which has higher bias coefficient(Wang and Hu, 1994). The logarithmic normal
distribution can be used to fit the skewed distribution,
but it can’t fit accurately because of the bias
coefficients of different dust particle size distribution
can’t be no difference (Bhaskar, 1988). It is reported
that the Rosen-Rammler distribution function as akind of empirical formulas which has closed
relationships with specific dust particle size
distribution, can be used to express skewed dust
particle distribution (Ou, 2006; Zhen et al., 2005).
The reasonable dust-suppression measures can beproposed by the evaluation of workplace*Corresponding author – email : yhf8000@163.com

environment and dust effects according to the RosenRammler distribution.

2. THE DERIVATION MECHANISM OF
THE FORMULA
The expression of Rosen-Rammler distributionfunction as follows (Dai, 2000),n(1)
R = 100e − β ⋅ x
R——The cumulative distribution of quality,
indicate the ration of greater than the accumulative
total value of one kind of dust in all kinds of dust,that is the residual rate on the sieve (or named
cumulative distribution on the sieve), %；x——The dust particle size， µm；
β, n——The coefficients related with dust
particle size.
The relationship between R and dust particle size
is nonlinearity according to the Rosen-Rammler
distribution function. The nonlinear relation can betransformed to linear relation by the transformation
method.
The detailed process as follows:

Natural logarithm:  100 ln ln = ln β + n ln xi  R （2）

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
Imagine ln xi = xi′ ，   100 ln ln = y i′  R ， ln β = a ，n = b , formulation (2) can be exchanged to:yi′ = a + bxi′ 。
Actually, the regression value can be named
estimated value (expressed by yi′ = a + bxi′ ) becauseof the deviation between regression value and actual
value. Then this issue can be calculated by linear
regression methods.
The common standard to evaluate the regression
line is the least squares theory. The existedtheexperimental
point: (xi′, yi′ )(i = 1,2,3,, n ) ,minimum regression line of quadratic sumnn2y ′ − y ′ = ( y ′ − a − bx′ ) is the best.

∑(
i =1

i

i

) ∑
i =1

i

i

The minimum of regression line of quadratic
sum is existed according to the quadrature methods incalculus. a, b are:Lx′y′b=
; a = y′ − b x′
Lx′x′
（3）
In the equation:n∑ x′ ;

x′ = i =1
n

i

n

∑ y′

y′ = i =1
n

(

i

)

2

n
n
2
1 n 
2
Lx′x′ = ∑ xi′ − x′ = ∑ xi′ −  ∑ xi′  ；n  i =1 
i =1
i =1
n
n
n
1 n
Lx′y′ = ∑ xi′ − x′ yi′ − y′ = ∑ xi′ yi′ − ∑ xi′∑ yi′
n i =1 i =1
i =1
i =1

(

)(

)

The detailed regression calculated procession:(1) Calculated the number of various dust
particle sizes according to the analysis result of dust
sample using microscope.
(2) Calculated the weight of various dust particle
size. The volume of dust is calculated according to
the volume calculated method of sphere because ofhomogeneous of dust.

(3) Calculated the ratio of the weight of various
dust particle size in the total weight.
Pwi =ni d i3× 100%

n

∑n d
i =1

i

3
i

(4)

3. THE EXAMPLE ANALYSIS
3.1 The Introduction of Working Face
3# coal seam as the continental lake type coal
mined in the 4339 working face in Wangzhuang Coal
Mine is in lower-middle part of geologicalstratification located in Shanxi group of Permian
System. The thickness of stable coal seam is about
7.06~7.30m, average 7.18m, the angle of coal seam isabout 0°~15°, average 7.5°. The outside ofworking face is westward uniclinal structure, theangle of inclination is relative larger (can achieve to
15° partly).
The dust of coal is explosive. The length offlame is 30mm, spontaneous combustion has not
happened. The pressure and temperature of ground isnormal. The temperature is 16~18℃. The tangent
line of working face is 185.5m which has the
direction of north-south; the length of excavation:wind road is 730m, shipping road is 710m. Working
face is inclined longwall, retreating comprehensive
mechanized top-coal, backward type comprehensive
mechanized top-coal drawing a low mining overall
height all caving mining method. The ventilation ofworking face is E type.
3.2 The Statistical Parameters of Dust Dispersion in
Working Face
The parameters of dust particle size dispersion in
4339 working face were listed in Table 1~4. The test
places are 5m away from the working face in intake
airway, transfer point, the 50# support of the working
face and 20m away from the working face in outlet
lane.

Table 1: Statistical parameter of dust particle size distribution 5m away from the working face in intake airway
Particle size (μm)
<2
>10
∑
2～5
5～10
Particle Number (n)
204
17
7
1
229
Number particle size dispersion n/∑n
89.08%
7.43%
3.06%
0.43%
100.00%
Represent particle sized (μm)
1
3.5
7.5
15
The equivalent amount of weight nd3
204
729
2953
3375
7261
Number particle size dispersion nd3/∑nd3
2.81%
10.04%
40.67%
46.48%
100.00%Quality of the cumulative ∑nd3
204
933
3886
7261
7261
Quality of the cumulative dispersion R
100.00%97.19%
87.15%
46.48%
Table 2: Statistical parameter of dust particle size distribution in transfer point
Particle size (μm)
<2
>10
2～5
5～10
Particle Number (n)
190
49
18
2
Number particle size dispersion n/∑n
73.36%
18.92%
6.95%
0.77%
Represent particle sized (μm)
1
3.5
7.5
15
The equivalent amount of weight nd3
190
2101
7594
6750

∑
259
100.00%16635

2263rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Number particle size dispersion nd3/∑nd3
1.14%
12.63%
45.65%
40.58%
100.00%Quality of the cumulative ∑nd3
190
2291
9885
16635
16635
Quality of the cumulative dispersion R
100.00%98.86%
86.23%
40.58%
Table 3: Statistical parameter of dust particle size distribution in 50# support of the working face
Particle size (μm)
<2
>10
∑
2～5
5～10
Particle Number (n)
222
106
22
1
351
Number particle size dispersion n/∑n63.25%
30.20%
6.27%
0.28%
100.00%
Represent particle sized (μm)
1
3.5
7.5
15
The equivalent amount of weight nd3
222
4545
9281
3375
17423
Number particle size dispersion nd3/∑nd3
1.27%
26.08%
53.27%
19.37%
100.00%Quality of the cumulative ∑nd3
222
4767
14048
17423
17423
Quality of the cumulative dispersion R
100.00%98.73%
72.65%
19.38%
Table 4: Statistical parameter of dust particle size distribution 20m away from the working face in outlet lane
Particle size (μm)
<2
>10
∑
2～5
5～10
Particle Number(n)
230
65
22
4
321
Number particle size dispersion n/∑n
71.65%
20.25%
6.85%
1.25%
100.0%
Represent particle sized (μm)
1
3.5
7.5
15
The equivalent amount of weight nd3
230
2787
9281
13500
25798
Number particle size dispersion nd3/∑nd3
0.89%
10.80%
35.98%
52.33%
100.0%
Quality of the cumulative ∑nd3
230
3017
12298
25798
25798
Quality of the cumulative dispersion R
100.00%99.11%
88.31%
52.33%

3.3 The Regression Calculation of Dust Dispersion
Degree in Working FaceThe representative particle sizes d (listed inTable 1~4) and regression calculated data obtained

Particle size
X(μm)
2
5
10
∑

Particle size
X(μm)
2
5
10
∑

Particle size
X(μm)
2
5
10
∑

by the cumulative distribution of quality were listed
in Table 5~8.

Table 5: Regression dust particle size 5m away from the working face in intake airway
y 'i( y 'i ) 2
2
x 'i

100
(ln⋅ ln)R-3.5578-1.9838-0.2664-5.8080y 'i( x 'i )(ln x)

100 2(ln⋅ ln)R(ln x) 2

0.69311.60942.30264.605112.6577
3.9356
0.071016.66430.48042.59025.30208.3726

Table 6: Regression dust particle size in transfer point( y 'i ) 2x 'i( x 'i ) 2

100
)
R

(ln x)(ln⋅ ln

100 2)
R(ln x) 2-4.4684-1.9095-0.1033-6.48120.69311.60942.30264.605119.96673.64630.010723.62360.48042.59025.30208.3726(ln⋅ ln

Table 7: Regression dust particle size in 50# support of the working facey 'i
( y 'i ) 2
2x 'i( x 'i )100)
R(ln x)(ln⋅ ln

100 2)
R(ln x) 2-4.3598-1.1409
0.4953-5.0055

0.69311.60942.30264.605119.00761.30180.245320.55460.48042.59025.30208.3726(ln⋅ lnx 'i ⋅ y 'i(ln⋅ ln

100⋅ ln x)R-2.4659-3.1928-0.6134-6.2721x 'i ⋅ y 'i(ln⋅ ln

100⋅ ln x)R-3.0971-3.0732-0.2378-6.4080x 'i ⋅ y 'i(ln⋅ ln

100⋅ ln x)R-3.0218-1.83621.1404-3.7176227

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 8: Regression dust particle size 20m away from the working face in outlet laney 'i
( y 'i ) 2
2

Particle
size
X(μm)

x 'i

2
5
10
∑

100
(ln⋅ ln)R-4.7172-2.0849-0.4345-7.2366(ln x)(ln x)

0.69311.60942.30264.605122.2523
4.34690.188826.7880

0.48042.59025.30208.3726

3.4 The Deduction of Distribution Function of Dust
Dispersion Degree in Working Face
Take the place of 5m away from the working facein intake airway for example. According to the datumin Table 1, the follows can be achieved:n
1  n  n 
Lx′y′ = ∑ xi′ yi′ −  ∑ xi′  ∑ yi′ n  i=1  i=1 
i =1


1
2
Lx′x′ = ∑ xi′ −  ∑ xi′ n  i =1 
i =1
n

2.0

(5)
When R=50％，the dust and particles size is median 100 nln
 = βx50 ，that
is
 R 
ln 2
ln 2
=
x50 n= 2 = 10.407μm.
0.0064
β
X(μ)
R(%)

100
⋅ ln x)R-3.2695-3.3555-1.0004-7.6254(7)−0.0015 x 2.67

=8.3726-(4.6051)2/3=1.3036b=Lx’y’/Lx’x’=2.6434/1.3036= 2.0277
1 n
1 n
a = y′ − b x′ = ∑ yi′ − b ⋅ ∑ xi′
n i =1n i =14.6051− 5.8080=− 2.0277 ×= −5.0486
3
3
n=b=2.0277，a=lnβ= -5.0486，
β = e −5.0486 = 0.0064
The dust particles distribution function in theplace of 5m away from the working face in intake
airway in Wangzhuang Coal Mine:

diameter expressed by х50, then(ln⋅ ln

The deduction method is the similar to the above.
The dust particles distribution function of transfer
point, 50# support of the working face and 20m awayfrom the working face in outlet lane can be obtained
as follows:
2.72(6)
R = 100e −0.0018 x … x50 = 8.92 µm
3.042

R = 100e −0.0064 x

2

R = 100e −0.0018 x … x50 = 7.09µm=-6.2721-(4.6051)×(-5.8080)/3=2.6434n

x 'i ⋅ y 'i

( x 'i )100 2(ln⋅ ln)R 100 nln
 = βx , R 

ln 2 = βx50n ，so… x50 = 9.95µm(8)
R = 100e
The dust particles size dispersion law can beobtained by Rosen-Rammler distribution function
and the method is similar to the above.
3.5 The Analysis of the Quality Cumulative
Distribution of Dust Dispersion Degree in Working
Face
The dust particles distribution function in theplace of 5m away from the working face in intake
airway in Wangzhuang Coal Mine is R = 100e −0.0064 x
and Table 9 can be listed.
Table 9 showed the value of dust dispersion
degree in some range of particle size. The percentageof the particle size lower than 5μm is 14.8%, 5~10μm
is 32.5%, larger than 10μm is 52.7%, larger than
30μm is 0.3% in the place of 5m away from theworking face in intake airway. It is indicated that the
dust particle size is within 5~20μm. It is reported thatthe dust size lower than 5μm is the most harmful tohuman and is the key element leading to miner’s
silicosis (Liu, et al., 2007). The air in intake airway isfresh, so the big particle size entrained dust is thereentrainment of dust after blow excitation
deposition, which is less harmful to human.
2.0

Table 9: Quality cumulative distribution of dust distribution5m away from the working face in intake airway
0
1
2
3
4
5
6
7
8
9
10
20
30
40
50
100 99.4 97.5 94.4 90.3 85.2 79.4 73.1 66.4 59.5 52.7 7.7 0.3 3.6E-03 1.1E-05

The dust particles distribution function in the place oftransfer point in Wangzhuang Coal Mine is2.72
R = 100e −0.0018 x and Table 10 can be listed.
It can observed from Table 10 that the percentageof the particle size lower than 5μm is 13.4%, 5~10μm
is 47.75%, larger than 10μm is 38.9%. And theparticle size larger than 20μm is 0.2%. It is indicatedthat the dust particle size is mainly in 5~10μm, andthere are few big size particles. As one of the mostimportant dust generated places, automatic sprinklingwater spray can be used to restrain the dust in transfer
point.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 10: Quality cumulative distribution of dust distribution in transfer point
3
4
5
6
7
8
9
10
20
30

X(μ)

0

1

2

R(%)

100

99.8

98.8

96.5

92.5

86.6

79.0

69.9

The dust particles distribution function in the place of
50# support of the working face in Wangzhuang Coal
3.04
Mine is R = 100e −0.0018 x and Table 11 can be listed.
It can observed from Table 11 that thepercentage of the particle size lower than 5μm is
21.3%, 5~10μm is 64.8%, larger than 10μm is 13.9%.
And there are few particles whose size is larger than
20μm. It is indicated that the dust particle size ismainly in 5~10μm and the concentration of respirable
dust is higher. So this place is the key prevention areaof this working face.

59.8

49.2

38.9

0.2

7.2E-0740

50

1.5E-16

2.1E-31

It can be concluded that the method of coal seamwater injection, coal winning machine interior andexterior spray and air curtain dust technology playgood effects in this working face. However, the better
effect can be achieved by other elements such as theproperties of coal, the condition of coal layer and the
choice of the parameter of cutting mechanism (thetype, size, amount, acutance and setting direction ofpicks). For the situation that the dust has spread, theflow field of airflow should be tested and the nozzle
and wet dust collector should be rightly set to preventthe dust spreading to sidewalk area.

Table 11: Quality cumulative distribution of dust distribution in 50# support of the working face
1
2
3
4
5
6
7
8
9
10
20
30
8.9
6.6
100 99.8 98.5 95.0 88.5 78.7 65.9 51.3 36.7 23.9 13.9
E-06
E-23

X(μm)

0

R(%)

The dust particles distribution function in theplace of 20m away from the working face in outlet
lane in Wangzhuang Coal Mine is R = 100e −0.0015 x
and Table 12 can be listed.
It can be observed from Table 12 that thepercentage of the particle size lower than 5μm is
10.4%, 5-10μm is 40%, larger than 10μm is 49.6%.
And the particle size larger than 20μm is 1.2%. It is

40
1.0
E-56

50
5.4
E-113

indicated that the dust particle size is mainly in 520μm.
Dust removal by ventilation and water wet are
the main dust prevention measures in intake airway.
The two measures have good effect in first settling
but it cannot last as the increasing of dust. The dust
will be risen again by the wind and the concentrationof dust in intake airway will be increased again.
Spray binder can prevent dust, dust will be wetted
and cannot fly again (Qi et al., 2007).

2.67

Table 12: Quality cumulative distribution of dust distribution 20m away from the working face in outlet lane
X(μm)

0

1

2

3

4

5

6

7

8

9

10

20

30

40

50

R(%)

100

99.9

99.0

97.2

94.1

89.6

83.6

76.3

67.9

58.9

49.6

1.2

1.9E-04

4.6E-11

4.0E-21

4. CONCLUSION
In this work, the properties, range of application,
deduction mechanism and regression method of the
Rosen-Rammler distribution function were discussed.
The usage and analysis method of this function was
explained by the example of 4339 working face.
According to the related advices and evaluations
obtained by the regression law on the effect of dust
prevention measures, we can get the conclusions asfollows:(1) The Rosen-Rammler distribution function asa kind of empirical formulas can explain skewed dust
particle distribution. The data processed by the
Rosen-Rammler distribution function can describe
the dust particle distribution law.
(2) The percentage of the particle size lower
than 5μm is 14.8%, 5~10μm is 32.5%, larger than

10μm is 52.7%, larger than 30μm is 0.3% in the placeof 5m away from the working face in intake airway.
It is indicated that the dust particle size is in 5~20μm.
(3) The dust particle size is mainly in 5~10μm,
and there are few big size particles in the place oftransfer point. Transfer point can restrain the dust byautomatic sprinkling water spray.
(4) It is indicated that the dust particle size ismainly in 5~10μm and the concentration of respirable
dust is high in the place of 50# support working face.
It can be concluded that the method of coal seamwater injection, coal winning machine interior andexterior spray and air curtain dust technology playgood effects in this working face. However, the better
effect can be achieved by other elements such as theproperties of coal, the condition of coal layer and the
choice of the parameter of cutting mechanism (thetype, size, amount, acutance and setting direction of229

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

picks). For the situation that the dust has spread, theflow field of airflow should be tested and the nozzle
and wet dust collector should be rightly set to preventthe dust spreading to sidewalk area.
(5) It is indicated that the dust particle size ismainly in 5~20μm in the distance of 20m away fromthe working face in outlet lane. Spray binder can
prevent dust, dust will be wetted and cannot fly
again.

University of Technology. Volume 37, No.3, pp.
317-319.

5. ACKNOWLEDGEMENT
The authors gratefully acknowledge foundation
by International Cooperation in Science andTechnology Special Project (2015DFR70900).

6. REFERENCES
Bhaskar, R. (1988). Experimental studies of dust
disperition in mine airways. Mining Engineering. No.
3, pp. 191-195.
Dai, L.Y. (2000). Research on the RosinRammler particle size distribution function. Industrial
Safety and Dustproof. Volume 16, No.3, pp. 15-17.
Isabelle, D., Jean-Luc, H., and Bernard, B.
(2000). Taking-off modal of particles with a wide
size distribution. Chemical Engineering andProcessing. Volume 44, pp. 160-162.
Jin, L.Z. (1993). Coal Mine Dust Control.
Beijing, Coal Industry Press, 318p.
Liu, Y., Jiang, Z.A., Cai, W., Zhou, F.Z., Guo,D., and Liu, B.D. (2007). Numerical simulation of
the dust movement rule in fully-mechanized coalfaces. Journal of University of Science andTechnology Beijing. Volume 29, No.4, pp. 351-353.
Ou,
S.N.
(2006).
Researches
andexperimentation of the synthetical dust-prevention
technology in Weijiadi Coal Mine. Beijing, Civil &Environment Engineering School, University ofscience and technology Beijing.
Qi, H.G., Jin, L.Z., and Fu, Q.G. (2006).
Research and Application of efficient fire
suppression and dustproof material. Beijing, Coal
Industry Press, 163p.
Shi, C.H., Ou, S.N., and Jin, L.Z. (2007). A
study and analysis on the law of motion of the coal
dust. Journal of University of Science andTechnology Beijing. Volume 29, No.2, pp. 1-5.
Wang, B., and Hu, S.X. (1994). Study on thelaw of mine dust distribution in Tie jing shan. China
mining. Volume 1, No.3, pp. 71-72.
Wang, C.B. (1991). Measurement results andanalysis of dust dispersion. Safety in coal mines.
No.5, pp. 26-27.
Zhen, G.B., Kang, T.H., Cai, Z.Y., and Yin,
Z.H.
(2006).
AppliedtheRosin-Rammler
Distribution Function to Study on the Law of Coal
Dust Particle-Size Distribution. Journal of Taiyuan

230

ISMS 2016

Paper No. 39

Fuzzy comprehensive evaluation of emergency capability of port coal storage
base with G1 method
Siheng Suna, b, Guozhong Huanga,*, Longzhe Jina,b, Yage Lia,b, Xue Zhaoa,babDepartment of Safety Science and Engineering, University of Science and Technology Beijing, Beijing, China, 100083
Mine Emergency Technology Research Center, Beijing, China, 100083

ABSTRACTPort coal storage base has strategic significance in China's energy; once an accident occurs, the level of emergency
capacity is very important. Therefore, in this paper, the fuzzy comprehensive evaluation method based on the G1
method is proposed for emergency capability assessment. Firstly, the Delphi method is used to establish the index
system of emergency capability assessment. To determine the index weight, the G1 method, a kind of method where itis needless to test its consistence, is adopted to calculate the weight of each index. The fuzzy comprehensive
evaluation model for the emergency capability assessment is then made. Finally, the feasibility and effectiveness ofthe method are illustrated using an example. Results show that the method provides a new perspective and tool for
emergency capability assessment.
KEYWORDS: emergency capability assessment; index weight; G1 method; fuzzy comprehensive evaluation

1. INTRODUCTIONPort coal storage bases are not only an importantbase for energy storage, but also an important channel
for the “coal transportation from west to east and northto south”. Once an accident occurs, it will have asignificant impact on the state power supply. Althoughmost of the port enterprises have prepared an
emergency plan, there are still many problems such as
imperfect plans, imperfect emergency equipment, andthe lack of social rescue linkage mechanisms.
Therefore, it is necessary to comprehensively evaluate
emergency abilities and strengthen the construction of
emergency capacities for the weak link, in order toimprove the disposal capacity of port accidents andreduce accident losses.

2. THE INDEX SYSTEM OF EMERGENCYCAPABILITY ASSESSMENT
Emergency capability assessment of port coalstorage bases involves is very complicated. Thissystem needs to be integrated with the relevant factors
affecting the emergency response capability according
to the level of the factors and the relationship between
the factors.
The Delphi survey method is adopted to select theevaluation index, according to the feedback from theexpert and emergency capability evaluation plan ofport coal storage bases (Tian and Yang, 2008). The
index system contains nine primary indexes, marked
U1, U2, …, U9: monitoring and early warning,
emergency support, emergency organization, training
and drills, launched the emergency response,*Corresponding author – email :hjxhuanggz@163.com

command and coordination, emergency disposal,
recovery and rehabilitation, and survey summary.
30 representative grade two indexes are selectedon the basis of studying the features and contents ofprimary indexes, marked as U11, U23, U73, etc. The
index system is shown in Table 1.
Table 1: Index system of emergency capability assessment.
Assessment
Primary Index
Grade Two Index
objectrisk identification
and analysis
safety monitoring
monitor and warn
safety check
accident warning
emergency response
teamemergency supplies
emergency
supportemergency
Emergency
equipment
Capability
emergency fund
Assessment
emergency planof Port Coal
emergency
Storage Baseemergency
regulationsorganization
emergencyorganization
personnel training
training and drills
emergency drills
alarm andnotification
emergency launchemergency
personnel response3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

command andcoordination

emergency
disposal

recovery andrehabilitation

survey summary

field emergency
disposal
emergency
command decision
coordination
organization
emergency
resources
deployment
emergency teamlevel
medical aid ability
logistic support
alert evacuation
technical support
in-place cleaning
recovery disposal
rehabilitation
disposal
accident
investigation
accident summary
revise theemergency plan2) Select the most important or least important
indicator from the rest of the index set containing (m-1)
indexes, marked Xj.
…….
Select the most important or least important
indicator from the rest of the index set containing(m-(k-1)) indexes, marked Xn.
…….
Mark the rest index as Xk.
Thus, the sequence of order can be determined.
The next step is to determine the level of importance
between adjacent indicators.
3.2 Determine the level of importance between
adjacent indicators
Experts use rk to express the degree of importanceof the adjacent index between Xk-1 and Xk.
ω
k = m, m − 1, … ,3,2
rk = k−1�ωk
The level of importance between adjacentindicators can be calculated according to the orderrelation.
For the value of rk, refer to Table 2.
Table 2: The level of importance between indicators
Instructionrk

3. DETERMINE THE INDEX WEIGHTWITH G1 METHOD

1.0

Index Xk-1 and index Xk are equally important

The AHP method (Saaty, 1980) has been widely
applied to calculate the weight of each index at present.
When this method meets many factors or big problems(Liu et al., 2006), it is difficult for the judgment matrix
to meet the requirement of consistence and hard tofurther divide into groups. In this paper, the G1

1.1

The ratio of the index Xk-1 and index Xk between
equally important and slightly important

1.2

Index Xk-1 is more slightly important than index Xk

1.3

The ratio of the index Xk-1 and index Xk between
slightly important and obviously important

1.4

Index Xk-1 is more obviously important than index Xk

1.5

The ratio of the index Xk-1 and index Xk between
obviously important and strongly important

1.6

Index Xk-1 is more strongly important than index Xk

1.7

The ratio of the index Xk-1 and index Xk between
strongly important and extremely important

1.8

Index Xk-1 is more extremely important than index Xk

method (Guo，2002), a kind of method where it isneedless to test its consistence, is adopted to calculate
the index weight of each factor in evaluating the
emergency capability of port coal storage bases.
3.1 Determine the order relation
Definition: If the evaluation index Xi is more
important (or not less) than Xj relative to a certain
evaluation criterion (or goal), denoted as Xi>Xj.
Definition: If the evaluation index of X1, X2, …,
Xm, compared with an evaluation criteria (or target)
has the following relationship type, the order relation
is determined according to the ">".
Xi>Xj>…>Xk i,j,…,k=1, 2, …, m
Establish the order relations for the evaluationindex set {X1, X2, …,Xm} according to the following
steps:
1) Select the most important or least important
indicator from the index set containing m indexes,
marked Xi.

3.3 Calculate the index weightk = m, m − 1, … ,3,2
ωk−1 ≥ ωkm−1
ωm = (1 + ∑k=2 ∏m（1）
i=k ri )k = m, m − 1, … ,3,2 （2）ωk−1 = rk ωkωk represents the weight of the NO. k index.

232

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The G1 method is especially suitable for when
there are many factors and a large scale.

4. FUZZY COMPREHENSIVEEVALUATION
The fuzzy comprehensive evaluation method(Tong, 2010) is a kind of comprehensive evaluation
method for complex systems with multiple levels andmultiple factors, based on fuzzy mathematics andapplying the principles of fuzzy relation synthesis toquantify the unclear boundary factors. Because theassessment is concerned with many factors, themulti-level fuzzy evaluation method is used in thispaper. Based on fuzzy mathematics theory (XuGe-ning，2010), the fuzzy comprehensive evaluationof the emergency capacity of the coal storage base iscarried out.
4.1 Evaluation factors
According to the index system of emergency
capability assessment, determine the evaluation
factors.
set: U = {U1 , U2 , … , U9 } , U1 = {U11 , U12 , U13 , U14 } ,,U2 = {U21 , U22 , U23 , U24 }U3 = {U31 , U32 , U33 } , U4 = {U41 , U42 } , U5 ={U51 , U52 , U53 } , U6 = {U61 , U62 , U63 } , U7 ={U71 , U72 , U73 , U74 , U75 } , U8 = {U81 , U82 , U83 } ,U9 = {U91 , U92 , U93 }4.2 Comment sets
Comment set is a set of evaluation results of theevaluation object. According to the fuzzy
characteristic of emergency response capability
evaluation index，5 grades of reviews (i.e., excellent,good, general, poor and very poor) were used as theevaluation sets to evaluate emergency capability
assessment of port coal storage bases, marked
V = {v1 , v2 , v3 , v4 , v5 } . In order to more directlyreflect the evaluation results, the 5-comment sets wereassigned a value from 0-100, as shown in Table 3.

Table 3: The values of comment sets.
value
100-8080-60
60-40Comment
sets

excellent

good

general

40-20

20-0

poor

Very
poor

4.3 Degree of membership
Because it is difficult to quantify the impact of
emergency response capabilities, the fuzzy statisticalmethod is used to determine the degree of membership.
The expert graded the indicators according to thegiven set of V, and then registered the statistics of thefrequency of each target. The membership degree ofindex uij is a ratio between the frequency and the total
number of experts.

𝑟𝑖𝑗𝑙 =𝑛𝑖𝑗𝑙
�𝑁

By determining the membership degree, thefuzzy evaluation matrix is obtained.

𝑟𝑖11
𝑅𝑖 = � ⋮
𝑟𝑖𝑚1

⋯
⋱
⋯

𝑟𝑖15
⋮ �
𝑟𝑖𝑚5

4.4 The assessment of Primary Index
According to the weight matrix ωi andevaluation matrix R i , carry on the grade two index
and primary index evaluation calculation.

ω1 𝑅1⎡ω 𝑅 ⎤⎢ 2 2⎥
R = B𝑖 = ωi 𝑅𝑖 = ⎢ ω3 𝑅3 ⎥⎢… …⎥
⎣ ω9 𝑅9 ⎦4.5 Fuzzy comprehensive assessment
After each evaluation index of the index layer isevaluated, the evaluation matrix C is obtained byfuzzy comprehensive evaluation of the criteria layer
index Ui .
C = WR = [c1 , c2 , c3 , c4 , c5 ]The comprehensive evaluation matrix C ischaracterized by the form of membership degree, but
the result is not very intuitive. Select the median valueof the value of the critical value of the evaluation
grade, 𝐷 = (90,70,50,30,10), as the rank weighted
vector of the evaluation set:
𝐸 = 𝐶𝐷𝑇
According to E value, determine the level of
emergency response capability level.

5. DETERMINE THE EMERGENCYCAPABILITY LEVEL
By analyzing one of the port coal storage base in
Hebei province, the emergency capability wasevaluated.
5.1 Calculate the index weight with G1 method
Use the G1 method to calculate the weight of eachlayer index，taking U1—U9, 9 primary indexes as thecriteria layer indexes as an example. First, rank theimportance of each index of the criterion layer. The
sequence relationship identified by the expert is233

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

U7>U2>U1>U6>U5>U4>U8>U3>U9,recorded asx1>x2>x3>x4>x5>x6>x7>x8>x9.
Experts give the importance ratio rk of adjacentindicators xk and xk-1 according to Table 2. The
ratios
ω3
ω4
ω6
ω7

are

ω1
ω2

= r2 = 1.2 ，= r4 = 1.2 ，

ω4

ω5
ω7

= r7 = 1.4 ，

ω8

ω2= r3 = 1.3 ，

ω3
ω5= r5 = 1.1 ，= r6 = 1.3 ，

ω6
ω8= r8 = 1.3 ，

ω9= r9 = 1.1 .

According to formulas (2) and (3), calculate theωi in order and get the criterion layer index weightvector:w=(0.416,0.1841,0.0454,0.0825,0.1073,0.118,0.22
09,0.059,0.0412)
Similarly, weight the grade two indexes. The
results are as shown in Table 4.
Table 4: The index weight values of the index system.
Primary Index weight
Grade Two Index
weightrisk identification
0.1696and analysis
monitor andsafety monitoring
0.285
0.1416warn
safety check0.3419accident warning
0.2035emergency
0.1534
response teamemergency
0.2761
emergency
supplies
0.1841
supportemergency
0.184
equipment
emergency fund0.3865emergency plan
0.3431
emergency
emergency
0.2451
regulations
0.0454organization
emergency
0.4118organization
personnel training 0.5455
training and0.0825drillsemergency drills
0.4545alarm and
0.3125
notification
emergency
emergency
0.10730.3125launchpersonnel response
field emergency
0.375
disposal
emergency
0.4588command decision
coordinationcommand and0.2353organization
0.118
coordination
emergency
resources
0.3059deployment
emergency team
0.3296emergency
level
0.2209disposal
medical aid ability
0.169

recovery andrehabilitation

surveysummary

0.059

0.0412logistic support
alert evacuation
technical support
in-place cleaning
recovery disposal
rehabilitation
disposal
accident
investigation
accident summary
revise theemergency plan

0.21970.128
0.15370.30930.433
0.25770.28410.34090.375

5.2 Determine the degree of membership
Choose the expert judgment method to calculate
the index membership degree. Taking a13 as an
example, select ten experts to judge. If 2 experts thinkit’s excellent, 4 good, 3 general, 1 poor, the degree ofmembership is (0.2,0.4,0.3,0.1,0).
After statistical analysis, the results are as shownin Table 5.
Table 5: The evaluation index membership degree.

U11
U12
U13
U14
U21
U22
U23
U24
U31
U32
U33
U41
U42
U51
U52
U53
U61
U62
U63
U71
U72
U73
U74
U75
U81
U82

V1
0.2
0.3
0.4
0.2
0
0.1
0
0.1
0.1
0.1
0.1
0
0.1
0.1
0.1
0.2
0.1
0.1
0
0
0
0
0.1
0.1
0.1
0.1

V2
0.4
0.4
0.4
0.4
0.1
0.2
0.1
0.2
0.3
0.2
0.3
0.2
0.2
0.3
0.2
0.2
0.3
0.2
0.1
0.1
0.1
0
0.2
0.2
0.3
0.2

V3
0.3
0.2
0.2
0.4
0.3
0.3
0.3
0.4
0.4
0.5
0.5
0.4
0.5
0.4
0.4
0.5
0.4
0.4
0.4
0.3
0.3
0.4
0.4
0.3
0.4
0.5

V4
0.1
0.1
0
0
0.4
0.4
0.4
0.3
0.1
0.1
0.1
0.3
0.1
0.1
0.2
0.1
0.2
0.2
0.3
0.4
0.5
0.4
0.2
0.3
0.2
0.1

V5
0
0
0
0
0.2
0
0.2
0
0.1
0
0
0.1
0.1
0.1
0.1
0
0
0.1
0.2
0.2
0.1
0.2
0.1
0.1
0
0.1

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

U83
U91
U92
U93

0.1
0.2
0.2
0.1

0.3
0.4
0.4
0.3

0.4
0.4
0.3
0.4

0.2
0
0.1
0.2

0
0
0
0

According to the results of Table 5, the fuzzy
relation evaluation matrix Ri is constructed. Taking
U1 as an example, the corresponding evaluation
matrix is:
0.2 0.4 0.3 0.1 0
0.3
0.4 0.2 0.1 0�
𝑅1 = �
0.4 0.4 0.2 0 0
0.2 0.4 0.4 0 0

5.3 The assessment of Primary Index
To evaluate the primary index U1:
𝐵1 = 𝜔1 𝑅1 = (0.2969,0.4,0.2577,0.454,0)
In the same way, the results of other primary
index evaluation can be obtained.
𝑅1
⎡𝑅 ⎤
⎢ 2⎥
𝑅
⎢ 3⎥
⎢𝑅4 ⎥
R = ⎢𝑅5 ⎥
⎢𝑅6 ⎥
⎢𝑅7 ⎥
⎢𝑅8 ⎥
⎣𝑅9 ⎦
0
0.29690.4
0.2577 0.0454⎡0.0663 0.1663 0.3387 0.3614 0.0675⎤⎢ 0.1
0.2755 0.4412 0.1490 0.0343⎥
⎢
⎥
0.1 ⎥
0.4455 0.2091
0.2⎢0.0455= ⎢0.1375 0.2313 0.4375 0.1313 0.0625⎥
0.2306 0.0847⎥
0.4⎢0.0694 0.2153⎢0.0282 0.1062 0.3348 0.37598 0.1549⎥⎢ 0.1
0.2567 0.4433 0.1567 0.0433⎥⎣0.1625 0.3625 0.3659 0.1091
0 ⎦5.4 Fuzzy comprehensive assessment
Using fuzzy comprehensive evaluation todetermine the risk level:
C = WR= [0.1043 0.22 0.3649 0.2351 0.0757]
𝐸 = 𝐶𝐷𝑇 = 50.84
Therefore, the comprehensive evaluation of
emergency capability of the coal storage base in Hebei
province is 50.84, between 60 and 40. The level isgeneral and needs to strengthen.

The fuzzy comprehensive evaluation model isestablished according to the fuzzy feature of the index.
The feasibility and effectiveness of the method were
illustrated by an example.
This paper provides a new perspective and toolfor emergency capability assessment. However,
emergency capability assessment is complex andimperfect, and therefore still requires further study.

7. ACKNOWLEDGEMENTFirst and foremost, I would like to show mydeepest gratitude to my supervisor, Professor Jin
Longzhe and Huang Guozhong. They are respectable,
responsible and resourceful scholars, who haveprovided me with valuable guidance in every stage of
the writing of this thesis. When establishing the index
system, calculating the numerous index weight, they
put forward the valuable comments for the selection of
the index and calculation method. I shall also extend
my thanks to my scientific research team for theirkindness and help. Finally I wish for grand success of
ISMS 2016.

8. REFERENCES
GUO Ya-jun. (2002). Comprehensive Evaluation
Theory and Method, Beijing: Science Press, 167 p.
LIU Jian, ZHENG Shuang-zhong and DENG
Yun-feng.(2006) Weight Determination of Indexes in
Evaluation of Emergency Response Ability Based on
G1.China Safety Science Journal. Volume 16 NO.1,
pp. 30-33.
Saaty.T.L.(1980) The Analytic Hierarchy
Process, Mcgraw-Hill (Tx), New York.TIAN Yi-lin
and YANG Qing. (2008) Study of the Evaluation
Index System Model of the Emergency Capability on
Emergency, Journal of Basic Science andEngineering, Volume 4 NO.2, pp. 200-207.
TONG Rui-peng. (2010). The Application ofCommon Safety Evaluation Method, Beijing: China
Labor and Social Security Publishing House, pp.
200-205.
XU Ge-ning, JIANG Fan. (2010). Safety
Assessment on the Crane based on FAHP, Journal of
Safety and Environment. Volume 10 NO.2, pp.
196-200.

6. CONCLUSION
The Delphi method is used to establish the index
system of emergency capability assessment. Using theG1 method can reduce the amount of calculation andeasily find the index weight.

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Paper No. 41

ISMS 2016

Study on External Protective System of Waterproofing Refuge Chamber in
Guilaizhuang Gold Mine
Shengnan Ou a, Longzhe Jin a, b,*, Song Li c, Shu Wang a, b, Yage Li a, Zhiling Huang aaSchool of Civil and Environment Engineering, University of Science and Technology Beijing, Beijing, China 100083
Mine Emergency Technology Research Center, University of Science and Technology Beijing, Beijing, China 100083
c
Shandong Gold Guilaizhuang Mining Co. Ltd., Shandong, China 273300b

ABSTRACT
Refuge chamber, which have a positive impacts on facilitating escape for miners trapped underground by a fire,
explosion, or rock collapse, need further perfection and research with respect to waterproofing function at present in
China in case of mine floods. A waterproofing refuge chamber, designed for the survival of 50 miners for at least 96
hours, along with its waterproofing, airtight, and other essential requirements has been proposed in Guilaizhuang
gold mine in Shandong province. Focusing on the external protective system of the water-proof refuge chamber,critical items (including the water-proof door, bulkhead, and lining) are systematically presented in this paper.
Specifics like exhausting and draining under water, were also take into consideration in the research. Accordingly, awaterproofing evacuation unit, emergency evacuation unit, and emergency drainage unit were designed. Tests andsimulation results indicated that the refuge chamber had good positive pressure maintenance, air-tight property, andwater-proof performance.
KEYWORDS: water-proof protective refuge chamber; external protective system; protective performance; field test;
simulation analysis

1. INTRODUCTION
Refuge chamber, constructed by concrete andflame retardant inflatable material, equipped with
sufficient breathable air, adequate foods and water,
reasonable carbon dioxide scrubbing and temperature
control (MSHA, 2008), have a positive impact on
facilitating escape for miners trapped underground by
a fire, explosion, or rock collapse (Saleh, 2011).
Current researches in the field has mainly discussed
the protective characteristics in cases of gas outburst,
fire, and explosion emergencies in undergroundmines (Gao, 2013;Meyr Jr, 2013). As investigated, asignificant amount of non-coal mines, especiallythose located in north, south, and south-west of
China, are under complex hydrological-geologicalcondition. In addition, most mines are continuously
digging into deeper mining, where the risk of water
burst increases as the depth of the tunnel increases(Xing, 2010). Thus, current emergency refuge
technology needs further perfection and research withrespect to the water-proof function to improve its
applicability and safety.
In this paper, a water-proof refuge chamber was
proposed in Guilaizhuang gold mine in Shandong
province according to the practical situation in theunderground mine . It was designed for the survivalof 50 miners for at least 96 hours. This paper focuses*Corresponding author – e-mail : lzjin@ustb.edu.cn

on its external protective system. Compared withcurrent refuge chamber in China, the water-proof
function and both anti-hydrodynamic pressure andanti-penetrability performance were taken into
consideration in this case. Critical items (water-proof
door, bulkhead, and lining were included), as well assome specifics items (like exhausting and drainage inflood scenario) were systematically studied andpresented in the paper. Then, site tests and simulation
through ABAQUS software were carried out to verify
the protective performance.

2. ESSENTIAL REQUIREMENTS
Based on an overall consideration of geologicalconditions, major hazard and accident underground,production status and mining plan, as well as current
escape and rescue plan, the refuge chamber was set
adjacent to the main roadway at the absolute altitudeof −150 m, and 200 m away from the eastern mining
boundary. Essential requirements were as follows:(1) Capacity & Size
When in water inrush or other emergency case,miners should preferentially escape from the harmfulenvironment to above ground; refuge chamber are forthose miners trapped underground (Brake, 1999).
According to statistical data of underground workers,
up to 46 miners can be counted as protective objects.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Thus, the refuge chamber was designed for thesurvival of 50 miners for at least 96 hours, with areserve factor of 1.2.
According to relevant regulations (State
Administration of Work Safety, 2011), refugechamber should contain two entrances, a living zone
area of no less than 60 m2, and a transition zone
should be more than 3 m2. Considering the width ofdevices and operability, dimensions of the livingzone profile are 4500 mm × 3500 mm (net width ×
net height), with an available area of 81 m2, while thetransition zone area is 2700 mm × 2700 mm, and 27
m2 respectively.
(2) Waterproofing
Guilaizhuang gold mine, once a open pit surface
mine, has been transferred to underground mining.
The nearest entrance is at the elevation of -30 m.
According to the geologic investigation report, thismine is under medium-complicated hydrologic
condition. Uncertain quantity of karst caves, existingat an elevation of approximately -30m and recharged
by atmospheric precipitation, were the main sourcesof inflows into the mines. Table 1 tabulates mine
inflow rate of each main roadway.
Table 1: Mine inflow rate of each main roadway.
Elevation of
AquiferDrawdown
Inflow
roadway (m)thickness (m)(m)
rate (m3/d)
-50
42.77
180.13
9100
-100
52.77
230.13
12353
-150
56.07
280.1314553

The vertical distance from the aquifer andnearest entrance to the refuge chamber is 120 m.
Assuming an inundated case with reserve factor of
1.2, the refuge chamber is expected to resist 1.5 MPa
hydrodynamic load. As there is electrical equipment,
food, water and other components stored inside, thewater-proofing protection grade of the refugechamber should be at level two (no water penetrationis acceptable, damp area should be less than 2‰
tolerable), according to Chinese National Standard
GB 50108-2001 (MOHURD, 2008).
(3) Other requirements
Other requirements include: airtight, hightemperature and fire resistant; functions of gas
monitoring, warning alarm, telecommunication andsignaling transmission; adequate power, energy, food,water and first aid tools; proper components for basic
survival needs. (State Administration of Work Safety,2011).

3. WATERPROOF CONSTRUCTION &AUXILIARY FACILITIES

3.1 Door & Bulkhead
Over-sized or over-weight doors may increase
operation difficulty and even cause failure to open or
close the door for the miners injured in the accident.
Thus, a thin-shell water-proof door (ML type, Wuhan
Mingqing Environmental Protection Engineering
Technology Co., Ltd) with dimension of 1500mm W
× 1800mm H was applied in this case. The doorframe,an I-shaped composite frame structure, and door leaf,
stiffened thin-shell structure with square rubber strip
mounted around, were wedged by a cuneiform slide
block mechanism to achieve the expected sealing
requirement. As tested underground, the average time
to fully open then close the door with two miners wasin the range of approximately 4 to 6 minutes. During
the incident, trapped sediment with the water flow
would lead to leakage through the gap between thedoorframe and leaf. Thus, to reduce the likelihood ofsuch sediment retention, the floor of the refugechamber was designed to be 500 mm higher than theouter roadway floor, and a 200 mm high threshold
was set.
Water-tight bulkhead, expecting to withstand 1.5
MPa water pressure, was designed as a wedge-shaped
reinforced concrete structure, with a thickness of1000 mm (determined by calculation on the basis ofshear strength theory and compressive strength
theory). Available experiences have suggested that
seepage in poured concrete structures often occurredat cracks or pipe penetrations. Thus to maintainintegrity of the wall, the embedded through-pipes,
which were installed in-situ during the casting of theconcrete, were all designed as U-shape, passing
through under the wall. All the through-pipes weresealed carefully with expanding water bar and sealant.
Rigid water-proofing casing was adopted for exhaust,
compressed-air-supplying, water-supplying, drainage,
and reserved pipes; while flexible water-proof casing
was adopted for those power cable through-pipes.
The distances from the pipe to wall angle andbetween adjacent through-pipes were designed under
the requirements of technical code for waterproofing
of underground works (MOHURD, 2008).
3.2 Supporting structure
The cross-section of the refuge chamber was aclassic three-centered arch, and the composite shelllining, which consisted of a supporting layer andwater-proofing layer, was applied. The supporting
layer was designed to take ground load or other load,
while the waterproofing layer was mainly for waterproofing and air-tight purpose.
(1) Supporting layer
Based on engineering analogies, the main
parameters for the supporting layer were listed asfollows: anchor, made of deformed steel bar with one

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direction of screw thread rotating leftward andwithout longitudinal bar (Φ 20 mm × 2400 mm) , wasinstalled according to the distribution of 800 mm ×
800 mm (row × column); primary sprayed concrete
lining was constructed with 50 mm thick concrete(intensive grade of C25); secondary sprayed lining
was of 100 mm thickness, with reinforcement of steel
bars (Φ 10 mm) at a grid of 150 mm × 150 mm; third
poured concrete lining was constructed by C30
concrete, with a thickness of 100 mm.
(2) Waterproofing layer
The waterproofing lining was constructed ofwater-tight concrete (strength grade: C40;
impermeability grade: P8) and steel mesh (Φ 10 mm),with the main reinforcement of 300 mm × 300 mm
grid, and connecting reinforcement of 600 mm × 600
mm grid. The thickness of lining was 350 mm(calculated by thick wall cylinder theory).
Self waterproofing components (wall and waterproofing layer) are the main part to resist potential
harmful substance from outside, their actual
performance can be influenced by several factors (Qi,2007):• Anthropic aspects like improper design or
maintenance,
construction
qualitydissatisfaction, etc.;• Environmental aspects like high temperature
fume, harmful gases, mineral water, impulsion
pressure, and drilling-and-blasting operations
nearby, etc.;• Inherent defects of concrete, which would
gradually grow with time and cause structural
performance deterioration.
Among the mentioned factors, anthropic
implications can be controlled by reasonable
designation and management. However, being
involved in complex disaster surrounding, concrete
performance, especially permeability, may decrease
afterwards, and further causing structural damage.
Both watertightness and airtightness would be
affected. This will be fully studied in the future.
3.3 Auxiliary facilities(1) Water-proof evacuation unit
Overpressure relief valve, of which the outlet
installed at a height of 0.5 m above the floor of the
refuge chamber, was used for regulating pressure
inside the refuge chamber. It is possible that wateroutside could flow inside through the valve in theevent of water inrush. Thus, a particular designed
evacuation unit, composed of a controllingcomponent (consisted of hydrostatic release unit,
guide sleeve, piston, cylinder barrel, etc.), brake
valve (installed out of the refuge chamber), andpressure release valve (installed inside the refugechamber), was mounted at the outlet of theoverpressure relief valve. In a normal state, the brake
valve remains open so that the overpressure relief
valve can work regularly to keep a safe air pressure
inside the refuge chamber. When the outer waterpressure rises to 5 kPa (critical pressure of thehydrostatic release unit), the outer brake valve would
close automatically by controlling component toprevent the water inflow and keep refugees safe. In
this case, to avoid over-pressure inside the refugechamber, compressed air lines or borehole should be
cut off; and habitable circumstances will be sustainedby a compressed oxygen/air cylinder or chemical
oxygen generator, with the assistance of air scrubbing
and conditioning methods.

Figure 1: Water-proof evacuation unit.

(2) Emergency evacuation unit
The refuge chamber may be completely isolated
from the external environment once the evacuation
unit described in Section 3.1 closed down in water
inrush emergency. Based on our previous study,
within a totally sealed space (internal volume of 24.5m3) with 10 subjects living in it, the barometerreadings varied from -400 Pa to 1200 Pa in the
duration of nearly 9 hours, and it was predicted thatthe maximum pressure would be up to 8718 Pa in 96
hours (Li et al., 2015). In addition, if air supplied bycompressed air lines running throughout the mine
was not cut off in time due to wrong operation orother reasons after the evacuation unit closed, thepressure inside the refuge chamber would rapidly rise
to a hazardous level. Thus for the sake of safety, anemergency evacuation unit with capacity of 100 m3/h
was installed in the refuge chamber. The outlet of theevacuation line was placed in the -110 m levelroadway, and proper protection measures were taken.
(3) Emergency drainage unit
Wastewater in the refuge chamber can be drained
via floor drains when the water level in the main
roadway is lower than 600 mm. Otherwise, anemergency drainage unit with the capacity of 20 m3/h
and discharge head of 50 m would be used.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4. TESTS & SIMULATION ON
PROTECTIVE PERFORMANCE
4.1 Hydrostatic test of water-proof door
The hydrostatic test of the water-proof door was
carried out in Structure Mechanics Laboratory of
China Ship Scientific Research Center in Jiangsu
Province. The door was mounted in a flat position as
required (SAC, 1991); then pressurize hydrostaticpressure to 2.0 MPa by a pressure gradient of 0.5
MPa, and maintain for 30 minutes. A total number of
20 measuring points were monitored in theexperiment. Figure 2 shows the distribution and thestrain changing curve of five representative points.
No deformation or leakage was observed on the door
frame after the experiment. The door showed aperfect water-resistant performance.

Figure 3: Positive pressure maintenance: (a) experimental
site; and (b) change curve of differential pressure between
inside and outside of refuge chamber.

In the experiment, all the openings were sealed
and the door was closed, but to keep the evacuation
unit operating at a normal state, and regulate theventilation airflow rate at 150, 200, 300, 600, 900,
1200, and 1500 m3/h respectively. It can be seen that,the differential pressure in and out of the refugechamber, as shown in Figure 3, increased withventilation rate. The maximum differential pressure
was up to 900 Pa, but not harmful to health. The
results indicated that the refuge chamber is able tomaintain and regulate inner pressure as required.
4.3 Air impermeability performance test
The refuge chamber was kept in a completely
confined state during the test. All doors and openings
are closed as well as the evacuation unit. Pressurize
the inner space with compressed air until thedifferential pressure rises above 1000 Pa. Thechanging curve of differential pressure afterwards
was shown in Figure 4. It can be seen that thepressure decreased rapidly from nearly 1300 Pa to
below 250 Pa in the first 200 seconds, then stabilized
at around 50 Pa in 10 minutes. The airtightrequirement is fulfilled.

Figure 2: Hydrostatic test of water-proof door: (a) fivetypical measuring points distribution; and (b) strain curve ateach point.

4.2 Positive pressure maintenance test

Figure 4: Air permeability performance.

4.4 Test & Simulation on water-proof lining(1) Property of waterproofing concrete sample

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Figure 5: Experimental results of water-proof concrete
sample: (a) uniaxial compressive behaviour; and (b)splitting tensile behaviour.

The uniaxial compressive behaviour, splittingtensile behaviour, and anti-penetrability performanceof concrete sample were tested according to Chinese
National Standards (MOHURD, 2002; MOHURD,
2009). Acoustic emission (AE) was adopted to reveal
the damage evolution of each sample. The following
experimental equipment was used: WEP-600
hydraulic universal tester (Changchun Chaoyang Test
Instrument Co., Ltd), DH3821 static strain testing
analyzer (Jiangsu Donghua Testing Technology Co.,
Ltd; resolution: 1με; system indication error:≤0.2%±3με); SZ120 resistance wire strain gauge(Xingtai Kehua Resistance Strain Gauge Plant;sensitivity: 2.06±0.1%); PCI-2 6 channel AE system(Physical Acoustics Co., Ltd); BY-HS16B concrete
impermeability instrument (China Academy of
Building Research; nominal pressure: 1.6 MPa;pressure maintenance error: ±0.05 MPa). All thetested samples were kept in standard conditions for
28 days.
Table 2: Parameter setting of calculation model.
No.
Part
Material model
Element
Classic MohrSurround1
Coulomb
CPE4RPing rockplasticity model
Elastic-plastic
2
AnchorT2D2
model
Elastic-plastic
3
Rebar
T2D2
model

4

Concrete

Concrete
plasticity
damage model

CPE4RP

The tested concrete samples presented anaverage ultimate compressive strength of 50.27 MPa,
splitting tensile strength of 4.24 MPa, andimpermeability coefficient of 1.53×10-11 m/s. Figure
5 shows the stress and AE counts changing curve of
one of the samples under centric axial compression
and splitting tension states respectively. With theincreasing magnitude of stress, especially near thecritical point, internal cracks formed and propagated,leading to final damage. Due to significantly lower
tensile strength, stresses produced byloads,
temperature changes, shrinkage, settlement, etc.
would induce active or dormant cracks on theconcrete structure. Thus, in the following simulation
analysis, a concrete damage plasticity model was
employed to identify the possible crack information
zones within the waterproof lining.
(2) Simulation on water-proof lining
A two-dimensional model of waterproof lining
for calculating its seepage and stress fields in water
inrush emergency was established by ABAQUS
software. The finite element mesh extended to 40 m
× 40 m, seven times the excavation size. The
tunnelling process, consisting of excavation andsupport installation steps (six steps in total), wassimulated in the analysis by adding and removing
corresponding elements. After the step-by-steptunnelling process, a pore pressure of 1.3 MPa wasloaded on the boundary of the top surface, 1.7 MPa at
the bottom, while at the vertical boundary the porepressure linearly increased with depth. MohrCoulomb plasticity model, elastic-plastic model, andconcrete damaged plasticity models were adopted in
the calculation to identify the behaviour of
corresponding material. As concrete is strong incompression but weak in tension, only the tension
damage behaviour was considered in the simulation.
Tensile damage was specified as a function of
cracking displacement, calculated on the basis of thestress-strain curve obtained in Section 3.4.1 andrelevant references (Jankowiak, 2005; Guo, 1997).
Model details are shown in Table 2.

Material properties
Young's modulus: 10.0Gpa; poisson's ratio: 0.26; cohesion: 2.0MPa; internal
friction angle: 35°; dilation angle: 0°; and void ratio: 0.639.
Density: 7800kg/m3; Young's modulus: 214GPa; poisson's ratio: 0.27; andsectional area per anchor: 3.14×10-4m2.
Density: 7800kg/m3; young's modulus: 190GPa; poisson's ratio: 0.3; andsectional area per rebar: 7.85×10-5m2.
Poisson's ratio: 0.2; dilation angle: 30°; Flow potential angle: 0.1; biaxial
and uniaxial tensile ultimate strength ratio: 1.16: constant stress ratio: 0.667;
viscous coefficient: 0.0005; compression recovery: default; stress and strain
data of C25 concrete: research results taken from Guo (Guo, 1997);
parameters of C40 concrete (young's modulus, stress, strain, permeability

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coefficient, and damage factor): test values.

Figure 6: Simulation results of water-proof lining under 150m water pressure: (a) physical displacement components; (b) current
magnitude and components of the pore fluid effective velocity vector; and (c) tensile damage variable.

Figure 6 illustrates the simulation results of thewaterproofing lining under 1.5 MPa hydrodynamic
pressure. It can be seen that maximum distortion
appears at the arch bottom and magnitude of seepage
velocity extends to the 10-8 order as compared to nowater state. In general, the supporting structure
fulfills the expected requirements. The distribution oftensile damage variable of the waterproofing lining,which further identifies the possible crack formation
zones and suggests ways to avoid their development,
revealed that when under 1.5 MPa hydrodynamic
pressure, the tensile damage at the arch bottom andside wall were relatively higher, ranging from 0.2 to
0.5. Thus these areas should be intensively monitored
during regular maintenance and repaired in time.

5. CONCLUSION
Based on an overall consideration of practicalconditions, a waterproofing refuge chamber with acapacity of 50 miners for at least 96 hours has been
proposed in Guilaizhuang gold mine in Shandong
province. Its external protective system, mainlycomposed of a thin-shell water-proof door, watertight bulkhead, and composite shell lining, wasdesigned to withstand 150 m hydrodynamic pressure
with a water-proofing protection grade of level two,and also to fullfill the requirements of airtightness,fire resistance, etc.. A waterproofing evacuation unit,
emergency evacuation unit, and emergency drainage
unit were designed to solve the problem of
exhausting and draining under water. The protective
performance of the refuge chamber has been verified
by hydrostatic tests of the water-proof door, apositive pressure maintenance test, and air
permeability performance test. Meanwhile, a twodimensional simulation on the waterproofing lining
through ABAQUS software suggested that the tensile
damage at the arch bottom and side wall wererelatively higher when under 1.5 MPa hydrodynamic
pressure, which provides a scientific basis for regular
maintenance. Further research on protective

performance evolution after typical disasters will be
carried out in the future.

6. ACKNOWLEDGEMENT
This work was supported by the Ministry of
Science and Technology of China through ProjectNo. 2012BAK09B07 under the National Key
Technology Research and Development Program
during the 12th Five-year Plan Period.

7. REFERENCES
Brake, D., and Bates, G. (1999). Criteria for thedesign of emergency refuge stations for anunderground
metal
mine.
AUSIMM
PROCEEDINGS, 1999. The Australian institute ofmining and metallurgy, pp. 1-8.
Gao, N., Jin, L. Z., Huang, X., Zhang, T., andTao, G. Y. (2013). Study of airtight explosion-proof
barrier system in a mine refuge chamber. Disaster
Advances, Volume 6, pp. 241-249.
Guo, Z. H. (1997). The strength and deformationof concrete: experimental foundation and constitutive
relation, Tsinghua University Press, Beijing.
Jankowiak, T., and Lodygowski, T. (2005).
Identification of parameters of concrete damage
plasticity constitutive model. Foundations of civil andenvironmental engineering, Volume 6, No. 1, pp. 5369.
Li, Q. K., Jin, L. Z., Li, J., and Liu, J. P. (2015).
Experimental research on air pressure variation in
refuge chamber. Journal of China Coal Society,
Volume S1, pp. 139-143.
Meyr Jr, R. A. (2013). Development of 15 psi
safe haven polycarbonate walls for use inunderground coal mines. University of Kentucky.
MOHURD. (2002). GB/T 50081 -2002 Standard
for test method of mechanical properties on ordinary
concrete. Beijing: China Architecture and Building
Press.

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MOHURD. (2008). GB 50108-2008 Technicalcode for waterproofing of underground work.
Beijing: China planning press.
MOHURD. (2009). GB/T 50082-2009 The Test
Method of Long-term and Durability on Ordinary
Concrete. Beijing: China Architecture and Building
Press.
MSHA. (2008). Health Administration, US
Department of Labor. 30 CFR Parts 7 and 75 Refuge
Alternatives for Underground Coal Mines; Final
Rule.
Qi, F. (2007). Study on waterproof test and anticrack technique of fiber concrete structure in subway
station. Shanghai Jiao Tong University.
SAC. (1991). MT258-1991 ML-type thin shellwaterproof gate. Beijing: China Standards Press.
State Administration of Work Safety. AQ 20332011 Regulations for construction of emergency
refuge system in metal and nonmetal undergroundmine. Beijing: China Standards Press.
Saleh, J. H., and Cummings, A. M. (2011).
Safety in the mining industry and the unfinishedlegacy of mining accidents: Safety levers anddefense-in-depth for addressing mining hazards.
Safety science, Volume 49, No.6, pp. 764-777.
Xing, D. M., Ye, Y. C., and Zhao, W. W. (2010).
Statistical Analysis and Safety Management
Countermeasure of Mine Water Inrush Accident in
China. Metal Mine, No. 6, pp.178-181.

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Paper No. 52

ISMS 2016

Hazard detection and comprehensive control technologies of the integrated
resource coal mine goafs in China
Wen LI
Mine Safety Technology Branch of China Coal Research Institute, Beijing, China, 100013
State Key Laboratory of Coal Mining and Clean Utilization(China Coal Research Institute), Beijing, China, 100013
Beijing Mine Safety Engineering Technology Research Center, Beijing, China, 100013

ABSTRACTGoaf disaster has become a major problem for the integrated resource coal mines in China. Based on an analysis ofgoaf disaster types and characteristics, hazard detection and comprehensive control technologies are systematically
put forward. The control technologies include goaf hazard detection technologies which combine ground survey
with undermine detection; the goaf risk classification and assessment technologies combined with risk degreeclassification, qualitative with quantitative evaluation; the goaf disaster monitoring technologies which combine
local and regional monitoring with joint monitoring undermine and on the surface; the goaf comprehensive control
technologies which combined open stripe grouting with roof caving on the surface or undermine; and the goaf safety
guarantee technologies which combine matching funds and policy support with administrative supervision. The
results show that goaf disasters are divided into four types according to the disaster forms in integrated resource coalmines. The four types are comprised of the abandoned old goafs or permeable pit shafts, goaf fires including coal
combustion and gas explosions, the poisonous and harmful gas in goaf emissions, and the abnormal geologicaldisasters. The goafs have the characteristics of unknown distribution, different kinds of disaster types, concealment,
and unpredictability. The control principles were summarized and put forward in the form of an advance summaryof ground survey, an undermine detection follow up, hazard assessment and evaluation, in-place monitoring andsupervising, comprehensive control for disaster reduction, and a guarantee of safety measures.
KEYWORDS: integrated resource coal mines; goafs; ground survey; undermine detection; monitoring; disasterprevention and control; safety guarantee.

1. INTRODUCTION
Since September 2005, China has been carryingout the integration of coal mines, The number of coalmines has been reduced from 25,000 in the year 2005
to 11,000 in the year 2014.
The integrated resource coal mines haveexperienced a series of hazards and accidents, such as
water, fire, or roof hazards caused by unknown goafs
due to the original local small coal mines often
having a lack of basic data. The problem of goaf
hazards has become a major trouble facing the
integrated resource coal mines in China.
Aimed at coal mine goaf hazards, much researchhas been carried out on the instability mechanism ofgoaf pillars and roofs (Liu et al., 2014; Wang et al.,2008; Zhang et al., 2008), geophysical detection
technology (Li et al., 2011b; Liu et al., 2012), andcomprehensive prevention and control technologies(Li, 2011a; Li et al., 2014; Li W and Li J, 2015;
Zhang et al., 2013) in coal mine goafs. However,there is a lack of systematic analysis concerning thegoaf types, characteristics, detection, and control
technologies. Based on the analysis of goaf hazard*Corresponding author – email: vinly.li@163.com

types and characteristics, hazard detection andcomprehensive
control
technologies
aresystematically put
forward.
The
availabletechnologies include the goaf hazard detection
technologies which combine ground surveys with
undermine detection; the goaf risk classification andassessment technologies combined with qualitativeand quantitative risk degree classification evaluation;
the goaf hazard monitoring technologies which
combine local and regional monitoring with joint
monitoring undermine and on the surface; the control
technologies which combine open stripe grouting
with roof caving on the surface or undermine; and thegoaf safety guarantee technologies which combine
matching funds and policy support withadministrative supervision. The present study aims toconstruct a system and framework for the hazard
detection and comprehensive control technologies of
the integrated resource coal mine goafs in China.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

INTEGRATED
MINE
GOAF

4. DETECTIONTECHNOLOGIESOFINTEGRATED RESOURCE COAL MINESGOAFS HAZARD

According to the statistics of State
Administration of Coal Mine Safety in China, since
the year 2000, there have been 103 accidents of coalmines goaf hazards in integrated resource coal mines.
Based on the complex geological conditions, the goaf
hazards were divided into four types according to thehazard forms. These four types are comprised of theabandoned old goafs or permeable pit shafts, goaf
fires including coal combustion and gas explosions,the poisonous and harmful gas in goaf emissions, andthe abnormal geological disasters, including goaf
collapse, ground subsidence, and mine earthquakes
induced by sudden large-scale goaf collapse.
Statistics show that the total number ofabandoned old goaf or permeable pit shaft accidents
is the largest, accounting for 61% of all accidents.
Roof limestone water is responsible for 44.4% ofabandoned old goaf water disasters. Roof aquifer
waters, including roof sandstone water and roof
limestone water are the main waters filling the goafs.

The analysis of 103 cases of coal mine goaf
accidents showed that most of the accidents were
induced by unknown abandoned old goafs. The
detection technologies were limited and proper safety
management was not in place.
In recent years, cities in Midwest China such as
Ordos City, Yulin City, Linfen City, and Jincheng
City have carried out coal mine goaf detection workwithin the scope of whole cities, and have achieved
remarkable results. These practical experiences
provide reference for the integrated resource coalmine goaf prevention and control.

3. CHARACTERISTICS OF INTEGRATEDRESOURCE
COAL
MINE
GOAF
HAZARDS IN CHINA
There are four characteristics of integrate
resource coal mine goaf hazards in China.
Firstly, the distribution of abandoned old goafs is
unknown due to disorderly exploitation and lost
historical mining data. The goafs have become amajor security risk.
Secondly, the goafs have different kinds ofhazard types. The occurrence of accidents in coalmine goafs is the result of the combined action ofmining, geology, and management. In addition, thegoaf hazards may be triggered by other hazard types,
such as water or fire hazards.
Thirdly, the goafs are concealed and accidents
happen suddenly. Generally speaking, unless thesurface collapses or cracks, there is underground
dynamic mine pressure, abnormal gas concentration,
or water inrush, the goaf hazards are often difficult tofind. Once they occur, they are difficult to control.
Fourthly, goaf hazards are unpredictable.
Because of the different geological and mining
conditions, the occurrence of goaf accidents are notregular, and are difficult to predict. In recent years,
some coal mine groups and research institutes havecarried out related research, but the prediction of goaf
hazards is still in the exploration stage.

4.1 Ground survey
Most of the integrated resource coal mine goafs
cannot be reached. Ground surveys are the mostsuitable method to adapt underground advanced
geological detection or drilling methods in lanes nearabandoned goafs. Ground survey includes fieldreconnaissance and surveying, geophysical grounddetection, and ground drilling. The work process
involves data collection and analysis, exchanging
with coal mine technical personnel, fieldreconnaissance and surveys (including remotesensing geological surveys), range determination,
geological detection methods and scheme design,
data acquisition, data processing and interpretation,
drilling verification and data reinterpretation, report
preparation, return visits to the results, revising
reports, and the final report submission.
The main methods for goaf geophysical grounddetection are the shallow seismic method, the highdensity resistivity method, the controlled source
audio frequency magnetotelluric method, and the Eh4
magnetotelluric method.
dot mark
12

13

14

15

17

18

1190
1170
1150

Ωm

N
16

11

Elevation(m)2. MAINTYPES
OFRESOURCE
COAL
HAZARDS IN CHINA

19

No.2 high resistanceNo.1 high resistance

20 1190

1170
1150

1130

1130

1110

1110

1090

1090

1070

1070

1050
440

1050
800

60
55
50
45
40
35

480

520

560

600

640

680

720

760

30
25
20

Distance(m)Figure 1: The typical apparent resistivity comprehensive
profile including goafs.

The typical apparent resistivity comprehensive
profile including goafs is shown in Figure 1. The
darker color indicates higher resistivity. Between the
distances of 510m to 590m and 650m to 800m, there
are two higher apparent resistivity regions from244

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

which the presence of old abandoned goafs werededuced. They were verified by drilling boreholes.
4.2 Undermine detection
For integrated resource coal mines, especiallythose that are threatened by water inrush hazards, it isrecommended to adapt the principles of ‘forecastingin advance, detection before tunneling or mining’.
Undermine detection includes undermine drilling
detection, geophysical detection, and geochemical
detection. Undermine drilling detection is theconventional method, while geochemical detection isoften used to detect water quality or source whenwater inrush hazards may happen. Undermine
geophysical detection involves advanced detection intunnels, inner working face detection, as well as roof
and floor detection.
Advanced detection in tunnels is mainly used in
the detection of abandoned goafs and their water
distribution, fault, collapse columns, or otherabnormal structures in front of tunnel. Conventional
geophysical detection methods are the mine transient
electromagnetic method, the mine DC resistivity
method, the mine seismic method including theRayleigh wave method, and the reflected wave
method.
The typical apparent resistivity comprehensive
profile of advanced detection in tunnels is shown in
Figure 2. The blue color indicates lower resistivity. In
front of the left tunnel about 60m from the tunnel
face there exists a lower resistivity region, fromwhich water bearing goafs were deduced. The waterin the lower resistivity region was later drained.

Figure 2: The typical apparent resistivity
comprehensive profile of advanced detection in tunnel.

Inner working face detection is mainly used in
the detection of fault, collapse columns, or otherwater bearing structures in the working face. The
conventional geophysical detection methods are themine DC electric perspective methods (including
audio frequency electric perspective method andresistivity CT method), the radio wave perspective or

CT methods, the mine reflected wave method, andthe mine channel wave seismic method.
Roof and floor detection is mainly used in thedetection of aquifers, impermeable layers, water
conducting passages, limestone karst and its
development, faults in the roof and floor, and fracturedevelopment zones. The conventional geophysicaldetection methods are the mine transient
electromagnetic method, the electrical sounding andelectrical section methods, the high-density resistivity
method, and the mine reflected wave method ortransmission wave method.

5. COMPREHENSIVE PREVENTION AND
CONTROLTECHNOLOGIESFORINTEGRATED RESOURCE COAL MINE
GOAF HAZARDS
Based on extensive practice, the principles forthe comprehensive prevention and control ofintegrated resource coal mine goaf hazards weresummarized and put forward, including groundsurveys in advance, undermine detection follow up,
hazard assessment and evaluation, in-placemonitoring and supervising, comprehensive control
for hazard reduction, and guarantees of safetymeasures.
5.1 Goaf hazard assessment and evaluation
With changes in the ecological environment ofcoal mines, mining conditions, mining methods, andintensity, goaf hazards have become a dynamic
process. It is important to carry out risk gradingclassification and assessment, qualitative evaluation,and quantitative evaluation of goaf hazards.
The qualitative evaluation of goaf hazards
mainly includes the Safety Checklist Analysis
Method, the Accident Tree Analysis Method, theEvent Tree Analysis Method, and the Preliminary
Hazard Analysis Method. The quantitative evaluationof goaf hazards mainly includes the Fuzzy
Comprehensive Evaluation Method, the Analytic
Hierarchy Process Method, and the Index
Classification Method. The Index Classification
Method is often used to determine the impact ofvarious mining and geological factors and establish arisk classification index.
For example, There are 20 influence factors forold abandoned goafs in Shendong mining area. They
are mining height, dip angle of coal seam, buried
depth of goafs, fault distribution near goafs, uniaxial
compressive strength of overlying rock and coalpillars, principal stress differences between
maximum and minimum, the direction of groundstress, the accumulation of water in goafs,
spontaneous combustion in goafs, goaf area, the ratio

245

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

between coal pillar width and height, the ratio
between mined and remained, the conditions of roof
control, ground subsidence conditions, the goaf sealconditions, the surrounding coal seam mining
conditions, whether the goafs instability events
happened or not, the distribution of surface buildings
above goafs, and the remain time of goafs.
The Index Classification Method is used tocomprehensively assess the risk of old abandoned
goafs in Shendong mining area. The Index W is listed
in formula as follows,n

W = ∑ Gi
i =1

n

∑G

(1)

i max

i =1

In formula (1), Gi max represents the maximum
rating value of number i influence factor, Gi
represents the actual rating value of number i
influence factor, and n represents the number of
influence factors.
Five risk grading classification was divided as
Grade I risk (especially significant risk, W ≥ 0.85 ),Grade Ⅱ risk (significant risk, 0.75 ≤ W < 0.85 ),monitoring currently involves the displacementmonitoring of overlying strata destruction, the surface
subsidence monitoring, and the monitoring of coalpillar stability. The goaf monitoring systems may
borrow the experiences of seismic network layout forrock burst monitoring, develop micro-seismic
monitoring technology, automatic monitoring
technology of internal displacement of rock mass,and temperature on-line monitoring technology.
A set of monitoring systems was developed in
the Shendong mining area involving micro-seismic
monitoring, working face pressure monitoring,borehole stress monitoring, rock mass internal
displacement monitoring, ground borehole television
watching, and surface displacement monitoring,which all provided basic research for dynamic
pressure control when mining under room and pillar
goafs. In addition, borehole seismic technology was
introduced for overburden failure monitoring of goafsin Yitai Coal Group.
The comprehensive monitoring system of goafs
is shown in Figure 3.

Grade Ⅲ risk (greater risk, 0.65 ≤ W < 0.75 ), GradeⅣ risk (general risk, 0.50 ≤ W < 0.65 ), Grade Ⅴ risk
(less risk or no risk, W < 0.50 ). 154 old abandoned
goafs were assessed using the Index Classification
Evaluation System in Shendong Mining area. The
results are shown in Table 1.
Table 1: The risk assessment results of old abandoned
goafs in Shendong mining area.
Grade
Goafs
Coal mine name
num.
Ⅰ
Ⅱ
Ⅲ
Ⅳ
Ⅴ
DALIUTASHANGWA

39
7

0
0

0
1

1
3

38
3

0
0

HALAGOU

8

0

0

5

3

0

WULANMULUN

12

0

0

0

12

0

BULIANTA

10

0

0

0

10

0

SHIGETAI

7

0

0

1

6

0

LIUTA

9

0

0

5

4

0

CUNCAOTA1

2

0

0

0

2

0

CUNCAOTA2

8

0

1

0

6

1

YUJIALIANG

48

0

0

3

45

0

BAODE

4

0

0

1

3

0

Total

154

0

2

19

132

1

5.2 Monitoring and supervisory technologies of goafs
The monitoring and supervisory systems of goafs
are far from established in normal coal mines, besides
lots of monitoring equipment being installed withinsome advanced coal corporations in China. The

Figure 3: The comprehensive monitoring system of goafs.

5.3 Comprehensive control technologies of goafs
For abandoned old goafs or permeable pit shafts,
goaf fires including coal combustion and gas
explosion, and poisonous and harmful gases in goaf
emissions, ground surveys and undermine detection
should be carried out. The design of water drainage,
ventilation, and fire control should then be put
forward. Finally, special measures should be madeaccording to the goaf hazard types and degree.
For the abnormal geological hazards including
goaf collapse, ground subsidence, mine earthquakes
induced by sudden large-scale goaf collapse, the open
stripe is adopted where there are no importantbuildings on the surface of the goaf and the buried
depth is less than 100m. In addition, the grouting
method is often adopted where there exists importantbuildings, and the roof caving method is adopted

246

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

where the goaf recovery rate is more than 40% andthe coal beneath the goaf needs to be mined.
5.4 safety measures for guarantee of goafs
The safety technologies mainly involve matchingfunds, policy support, and administrative supervision.
First of all, the matching of funds by thegovernment or coal groups should be implemented.
Secondly, goaf detection, preventionl and control
should be supported by the state, provincial, andindustrial policy. Thirdly, administrative supervisionby the government and the coal industry is an
important link in preventing goaf hazards. In addition,technical measures are another fundamental
guarantee of safety.

6. CONCLUSIONS
China faces a long and hard process in theprevention and control of integrated resource coalmine goaf hazards, because goafs have thecharacteristics of unknown distribution, different
kinds of hazard types, concealment, andunpredictability. The following control principles
should be implemented: ground surveys in advance,
undermine detection as a follow up, hazard
assessment and evaluation in time, monitoring andsupervising in place, comprehensive control for
hazard reduction, and guaranteed safety measures.

Li W and Li J. (2015). Coaf disastercharacteristics of resource integration coal mines andtheir control countermeasures. Safety in Coal Mines.
Volume 46, No. 7, pp. 179-181,185.
Liu C.Y, Yang J.X, Yu B, etc. (2014).
Destabilization regularity of hard thick roof group
under the multi gob. Journal of China Coal Society.
Volume 39, No. 3, pp. 395-403.
Liu R.T, Li W and Ma H.S. (2012). Field
investigation and surface detection techniques ofabandoned coal mine goafs. Cai(ed.) RockMechanics: Achievements and Ambitions. Taylor &Francis Group. pp. 27-30.
Wang J.A, Shang X.C, Liu H, etc. (2008). Studyon fracture mechanism and catastrophic collapse ofstrong roof strata above the mined area. Journal of
China Coal Society. Volume 33, No. 8, pp. 850-855.
Zhang J.Y. (2008). The laws of overlying strata
influenced by newly increased load on the surface
above worked-out area. Journal of China Coal.
Volume 33, No. 2, pp. 166-170.
Zhang J.Y, Wang H.F, Zhang B, etc. (2013).
Exploration of mining goaf and comprehensive
control technology of safety hidden dangers. Coal
Science and Technology. Volume 41, No. 10, pp. 7680.

7. ACKNOWLEDGEMENT
The study was supported by National Natural
Science Foundation of China (51304117), Science
Development Foundation of China Coal Technology& Engineering Group Corp (2014QN013),
Innovation Foundation of China Coal ResearchInstitute (2014JC07).

8. REFERENCES
Li C.Q and Yao X. (2004). The theoretical study
and application of a new technique for the treatmentof mined-out area. Gold. Volume 25, No. 3, pp. 2225.
Li W. (2011). Risk Assessment of Room Method
Goafs Instability. China Safety Science Journal.
Volume 21, No. 3, pp. 95-100.
Li W, Mu Y, Zhang J.Y and Xu Y.J. (2011).
Optimization of surface detection technology andmethod of mine goafs. Coal Science and Technology.
Volume 39, No. 1, pp. 102-106.
Li W, Zhang B and Bi Z.W. (2014). Isolation
roof caving control and monitoring technology ofroom and pillar method goafs. 2014 ISRM European
Rock Mechanics Symposium (EUROCK 2014),RockEngineering and Rock Mechanics: Structures in andon Rock Masses, London: Taylor and Francis
Group.pp. 931-936.

247

Paper No. 57

ISMS 2016

Multi-bed type oxidation reactor applied to the coal mine ventilation air
methaneWeifeng Zou a,b,*, Bo Lan a,b, Jiandong Kang a,ba

Key Laboratory of Low-grade Energy Utilization Technologies & Systems of Ministry of Education, College of PowerEngineering, Chongqing University, Chongqing, China, 400044b
Chongqing Research Institute Co.,Ltd. of China Coal Technology & Engineering Group, Chongqing, China, 400037

ABSTRACTThe utilization of coal mine ventilation air methane plays an important role in saving energy, reducing pollution,
improving the safety in coal mine production, and adjusting the energy structure. The thermal flow-reversal reactor
is one of the main technologies of ventilation air methane utilization which is at a critical stage of industrial
application. The thermal flow-reversal reactor of MEGTEC company and those designed by some Chinese scholars
generally use a two-bed type. The gas that is detained in the oxidation chamber and reversal valves will not enter the
combustion chamber, but through the chimney directly into the atmosphere when switching the flow direction, theaverage oxidation rate of the reactor will be reduced due to the residual gas.
In order to solve the problems including low oxidation rate of methane, pressure build-up of the main fan, and highfailure rate of valves in existing two-bed type oxidation reactor of coal mine ventilation air methane, an innovative
structure with multi-bed type oxidation reactor has been designed. The paper analyzes the unique advantages of themulti-bed type oxidation reactor by elaborating on the working principles of three-bed and five-bed type device. In
the design of the oxidation device for industrial demonstration projects, the device whose processing capacity is
100,000 m3/h adopts the five-bed type structure from the aspects of methane oxidation rate, waste heat utilization
effect, cost, etc. The thermodynamic calculation process of regenerative chambers as the core unit of the oxidation
device is described in this paper.
The technology has an industrial demonstration project whose reactor uses a five-bed type design located in
Chongqing Songzao Datong No.1 mine. This project can produce 64800 t of superheated steam and reduce
emissions of CO2 equivalent to 107000 t annually, and therefore has excellent energy-saving and emission reduction
benefits.
KEYWORDS: multi-bed type; coal mine ventilation air methane; thermal flow-reversal oxidation; industrial
application

1. INTRODUCTION
Coal bed methane is a kind of clean and efficientenergy which is one of the rising unconventional
natural gases in recent years. The ventilation air
methane (VAM) accounts for about 60% of total
methane emissions from coal mines, and its
utilization plays an important role in saving energy,
reducing pollution, improving the safety in coal mine
production, and adjusting the energy structure(Gosiewski et al., 2009). However, the developmentof the utilization technology is restricted by factors
such as low concentration, large air volume andinstability of ventilation air methane. The thermal
flow-reversal reactor (TFRR) is one of the maintechnologies of VAM utilization which is at a criticalstage of industrial application. The small thermaloxidation device has a processing capacity of 1000m3/h and was designed by Zheng. It uses a two-bed
horizontal type (Zheng et al., 2009). The methane* Corresponding author – email: zwf_cqmky@163.com

oxidation rate is slightly higher than 95% of thisdevice. The thermal oxidation device with amaximum processing capacity of 1000 m3/h was
designed by Lv. It also uses a two-bed horizontal
type (Lv et al., 2011). The device should be operated
steadily when the flow is in the range of 400-800m3/h and the concentration of methane is in the rangeof 0.5%-0.8%. The thermal oxidation device has amaximum processing capacity of 500 m3/h and was
designed by Wang. It uses a two-bed vertical typeand some experimental studies are carried out basedon this device (Wang et al., 2012). The MEGTEC
Company whose oxidation device uses a two-bed
vertical type also is the most representative of thistechnology abroad. It has been found that the current
oxidation device of VAM on the regenerative
chamber structure is generally a two-bed type.
However, the gas that was detained in the oxidationchamber and reversal valves will not enter the3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016combustion chamber but goes through the chimney
into the atmosphere directly when switching the flow
direction, so the average oxidation rate of the reactor
will be reduced due to the residual gas (Kang et al.,2015). To solve this problem, this paper puts forward
the design idea of the multi-bed type for the structureof thermal flow-reversal reactors.

National Science and Technology Major Project. A
lot of studies have been carried out based on theutilization system of coal mine ventilation air
methane. The experimental system is shown in
Figure 2.

2. THE NECESSITY OF DEVELOPING THE
MULTI-BED REGENERATIVEOXIDATION REACTOR
2.1 Working principle of two-bed type regenerativeoxidation reactor
For a two-bed type oxidation reactor, there are
two combustion chambers, one as the inlet and theother as the outlet of mixed gas. After the reactor isheat-actuated, the VAM flows at ambient temperaturefrom the low temperature side (e.g., chamber 1) into
the regenerative chamber, then is heated, oxidized
and released as thermal energy. The released energy
during methane oxidation is recovered by ceramic as
the gas moves to the outlet side of the chamber. This
process is often referred to as the upper half cycle ofthe circulating operation. At this time, chamber 1 isin the thermal release stage and chamber 2 is in thethermal storage stage. The direction of VAM flow
should be switched and the reversed process carriedout, and the system should be auto-thermal
operational with continuous transformation between
two chambers at high temperature and low
temperature.

Figure 2: Diagram of two-bed type TFRR experimental
system.

The two-bed type thermal flow-reversal reactor
has some inevitable disadvantages due to structure, as
follows.
a. There will be a large fluctuation of the gas
flow rate from the total intake to zero when switching
the flow direction, so that the main fan will be
suppressed and its life will be affected.
b. The flue gas flow rate of the waste heat boiler
will periodically fluctuate, which may affect thequality of the superheated steam in the use of waste
heat.
c. The large size of valves results in a large force
being requires for action and failure rate will be high.
d. The gas distribution in the regenerative
chamber and the combustion chamber is not uniform
and it is not conducive to the oxidation of methane in
VAM because of the large cross section of theregenerative chamber.
e. The gas who was detained in the oxidationchamber and reversal valves will not enter the
combustion chamber but go through the chimney into
the atmosphere directly when switching the flow
direction, so the average oxidation rate of reactor can
only reach 95% due to the residual gas.

Figure 1: Schematic of two-bed type TFRR.

3. WORKING PRINCIPLE OF MULTI-BED
TYPE TFRR

2.2 Disadvantages of two-bed type TFRR
Chongqing Research Institute of China Coal
Technology & Engineering Group independently
developed a small test device of TFRR with aprocessing capacity of 1000 m3/h during the 11th
Five-Year Plan period of China, named Low
Concentration Coal Bed Methane Utilization
Technology and Equipment which belongs to the

The core idea of multi-bed regenerativeoxidation reactors is to add some regenerative
chambers for oxidizing the methane in VAM, andalso to add a regenerative chamber whose mainfunction is sweeping. For a three-bed type oxidation
reactor, as shown in Figure 3, there are three
regenerative chambers, one as the inlet, one as theoutlet of mixed gas, and another as the inlet ofsweeping gas. For a five-bed type oxidation reactor,249

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016as shown in Figure 4, there are five regenerative
chambers, two as the inlet, two as the outlet of mixedgas, and another as the inlet of sweeping gas. The
data in Table 1 uses the five-bed type oxidation
reactor as an example. A complete working cycle
consists of five cycles, where each regenerative
chamber periodically switches between the threestages of thermal storage, sweeping, and thermal
release.

high temperature flue gas
low temperature flue gas
ventilation air methane
sweeping gas

sweeping fan

main fanchimney

Figure 3: Structure schematic diagram of three-bed type
TFRR.

high temperature flue gas
low temperature flue gas
ventilation air methane
sweeping gas

sweeping fan

main fanchimney

Figure 4: Structure schematic diagram of five-bed type
TFRR.
Table 1: Work process of five-bed type TFRR.
No.
Bed 1 Bed 2 Bed 3 Bed 4 Bed 5
Cycle 1aabbcCycle 2caabbCycle 3bcaabCycle 4bbcaaCycle 5abbcaNote: a. thermal storage, b. thermal release, c. sweeping

The present study also considered the situation ofincreasing the number of bed on the basis of the fivebed type oxidation reactor. The numerical simulationand theoretical calculation of the seven-bed and ninebed type oxidation reactor were carried out. It was
found that there would need to be a large number ofvalves due to the increase of the oxidation beds. The
control of oxidation reactors is very complex and notconducive to its stable operation. In addition, the cost
will increase and the economical profits will be

reduced. Therefore, the so-called multi-bed type of
TFRR in industrial applications usually refers to thethree-bed or five-bed type devices.

4. ADVANTAGES OF MULTI-BED TYPE
TFRR
Compared with the two-bed type oxidation
reactor, the multi-bed type oxidation reactor has thefollowing advantages:
a. There are more than two chambers in themulti-bed type oxidation reactor and one of them isdesigned to sweep the detained gas. The methane in
VAM is not oxidized and distributed between thereversal valves and regenerative chamber to the
combustion chamber in the traditional structure of theoxidation reactor when the flow direction is switched,so it avoids discharging into the atmosphere directly.
b. The cross-sectional area of the oxidationchamber should be decreased, and its gas distribution
is more uniform due to the smaller processing
capacity of a single chamber of the multi-bed typeoxidation reactor. This avoids the non-uniform
distribution of gas in traditional oxidation reactors
which should oxidize the larger flow rate of mixedgas.
c. The working state should be changed fromintake to sweep in only one chamber of the inlet
chambers, and the rest of the inlet chambers remainunchanged when switching the flow direction. The
gas flow rate is less, and the effect of waste heatutilization is better.

5. INDUSTRIAL
APPLICATIONMULTI-BED TYPE TFRR

OF

5.1 Selection of industrial device
An industrial demonstration project will beestablished in the 12th Five-Year Major Project(Direct use technology of low concentration coal bed
methane) as a continuation of the research tasks of
11th Five-Year Major Project of China. Based on thesummary of the application, the industrial device
whose processing capacity is 100000 m3/h will be
intended to adopt a multi-bed type structure design.
The results obtained by calculating andanalyzing the parameters of two-bed, three-bed, andfive-bed type structures according to the design andcalculation method of the regenerative heatexchanger are shown in Table 2. The industrial
device whose processing capacity is 100000 m3/h
adopted the five-bed type structure from the aspectsof methane oxidation rate, waste heat utilization
effect, cost, etc.

250

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 2: Comparison of different structure types.
Single cross-sectional area of regenerative
chamber（m2）Single volume of regenerative chamber（m3）Total volume of regenerative chamber（m3）Volume of heat preservation material（m3）Device size(m3)Reversing valves
Number of reversing valves
Number of sweeping valves
Cost of regenerative chamber （RMB, Million Yuan）
Cost of valves （RMB, Million Yuan）
Cost of heat preservation material （RMB, Million Yuan）
Total cost （RMB, Million Yuan）
oxidation rate of methane

5.2 Design of industrial device
The thermal flow-reversal reactor of coal mine
ventilation air methane is a precise and complex
system. The whole device is composed of theregenerative chambers, combustion chambers, somevalves, and so on. As the core part of the device, theregenerative chamber is the cornerstone in the courseof whole device design. The heat exchange area, thevolume, and the size of the regenerative chamber are
calculated according to the design method of theregenerative heat exchanger. The thermodynamic
calculation process is as follows:a. The heat ( Q ) required for VAM in a cycleof flow reversal
Q V f ( c ''f t ''f − c 'f t 'f )τ h (1)=Where: V f is the flow rate of VAM that beheated, m3/s.
c 'f , c ''f are the inlet and outlet specific heat of
VAM, J/(kg·K).
t 'f , t "f are the inlet and outlet temperature of
VAM, ℃.
τ h is the duration of VAM for heating, s.
b.

The flue gas outlet temperature( t "y ) of

regenerative chamberQ 
1  ' 't "ycy ty −
=
 (2)
" 

Vyτ yη cy 
Where: Vy is the flow rate of flue gas, m3/s.

c 'y , c"y are the inlet and outlet specific heat offlue gas, J/(kg·K)；
t y' is the inlet temperature of flue gas, ℃

τ y is the duration of flue gas for cooling, s.

two-bed typeThree-bed typeFive-bed type

4×5.5=22

4×5.5=22

4×2.95=11.8

46
92
107
14.4×4.7×8
DN1300
4
0
110.4
60

46
138
145
18.6×4.7×8
DN1300
6
3
165.6
99

23
115
177
18.45×4.7×8
DN1000
10
5
138
95

53.5

72.5

88.5

223.9
95%

337.1
98%

321.5
98%

η is the heat efficiency of regenerative
chamber, η = 0.9～0.95.
c. Thelogarithmic
difference ( ∆t )∆t − ∆tmin∆t = max(3)
ln ∆tmax ∆tmin

mean

temperature

Where: ∆tmax =t y' − t "f , ∆tmin =t "y − t 'f .
The convection heat transfer coefficient ( α )W 0.5
α = 7.5φ 0.33 (4)deWhere: φ = 0.184T 0.25 , the temperaturecorrection factor, T is temperature, K.
de is the equivalent diameter of honeycomb
ceramic, m.
W is the velocity of flow at the minimum crosssection, m/s.
e. The integrated heat exchange coefficient (
K)
d.

K=

 1

S
1
+
+
1 τ y + 1 τ f )( α yτ y α f τ f 6λ(τ + τ )
y

−1

(5)

f

Where: S is the thickness of honeycomb
ceramic, m.
α f , α y are the convection heat transfer
coefficient of VAM-side and flue gas-side,
W/(m2·K).
λ is the thermal conductivity of honeycomb
ceramic, W/(m·K).
f. The heat exchange area of a regenerative
chamber ( A )Q(6)A=
K ∆tη (τ y + τ f )g.

The volume of a regenerative chamber ( V )251

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

V=

A
(7)
av

Where: av is the specific surface area ofhoneycomb ceramic, m2/m3.
h. The horizontal cross-sectional area of aregenerative chamber ( F )
Vf
(8)
F=
Wf σ

The height of regenerative chamber ( H )
V
(9)
H=
F
According to the calculation formulas above, thebasic parameters of the industrial device (processing
capacity of VAM is 100000 m3/h) are given and the
FORTRAN software are used for thermodynamic
calculations. The related parameters and calculation
results are shown in Table 3.
i.

Where: W f is the velocity of VAM, m/s.
Table 3: Parameters and thermodynamic calculation results.
No.
Items
1
VAM Processing capacity of single oxidation bed
2
Inlet temperature of VAM
3Outlet temperature of VAM
4
Flow rate of flue gas
5
Inlet temperature of flue gas
6Outlet temperature of flue gas
7Heat loss coefficient
8
Logarithmic mean temperature difference
9
Duration of the cycle of flow reversal
10
Volume of honeycomb ceramic
11
Circulation cross-sectional area
12
Height of honeycomb ceramic
13
Total volume of honeycomb ceramic
14
Size of regenerative chambers
15
Velocity of VAM

In this point, it is necessary to point out that theparameters obtained such as the height of thehoneycomb ceramic and the circulation crosssectional area are based on the determined parametersand structure of the honeycomb ceramic. In thispaper, the selection of honeycomb ceramic and its
layout principles are omitted, see Figure 5.

Figure 5: Schematic diagram of ceramic’s layout.

5.3 Industrial demonstration projectThe
industrialization of this utilization
technology is promoted through the establishment of
the industrial demonstration project of the VAM.
Some industrial tests were carried out about theindustrial demonstration system in which the reactor
uses a five-bed type design in Chongqing Songzao
Datong No.1 mine, to investigate the effect ofcollecting cover, test the methane oxidation rate of

Units
m3/h
℃
℃
m3/h
℃
℃
%
℃
min
m3
m2
m
m3
m×m×m
m/s

Numerical values
50000
20
787
50000
900
60
5.0
70
3
23.35
11.12
2.1
116.7518.45m×4.7m×2.6m
1.86

the reactor, test the technology of steam produced bywaste heat, and to improve and perfect the industrial
device according to the test results.

1. Diffusing tower. 2. VAM collecting cover. 3. Mixer.
4. TFRR. 5. Waste heat boiler. 6. Chimney.
Figure 6: Schematic diagram of industrial demonstration
system for VAM utilization.

The whole system is composed of the VAM
collecting and mixing system, regenerative oxidation
reactor, the waste heat utilization system, and themonitoring system, as shown in Figure 6. The
ventilation air methane is exhausted from theventilating shaft and sent into the pipeline aftercollection by the collecting cover, then brought into252

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the oxidation reactor by induced-draft fan. The
methane in VAM is heated and oxidized and theoxidation products such as CO2 and H2O (water
vapor) are discharged into the atmosphere. The
burner in the combustion chamber will burn diesel oil
to preheat the regenerative ceramic for starting thereactor. In the test of waste heat utilization thedrainage gas is mixed with VAM in order to makethe volume fraction of methane reach 1%, and takepart of the high temperature flue gas to the boiler, toproduce superheated steam.

Figure 7: Scene diagram of industrial demonstration
project.

The construction of the demonstration project
was completed in October 2015 at which point thesystem was debugged. It is estimated that when it isput into operation, it will produce 64800 t ofsuperheated steam and reduce emissions of CO2
equivalent to 107000 t annually, and therefore has
excellent energy-saving and emission reduction
benefits.

6. CONCLUSIONS
a. Through the introduction of working
principles of the traditional two-bed type oxidation
reactor, it is found that this type of reactor has somedisadvantages including low oxidation rate ofmethane, pressure build-up of the main fan, and thehigh failure rate of valves.
b. In view of the design idea for a multi-bed typeoxidation reactor, their unique advantages are pointed
out by comparing with the two-bed type oxidation
reactor.
c. By calculating and analyzing the parameters of
two-bed, three-bed, and five-bed type structures, theindustrial oxidation reactor whose processing
capacity is 100000 m3/h adopted the five-bed typestructure design, and according to the design andcalculation method of the regenerative heatexchanger, the thermodynamic calculation process
and results of regenerative chamber were introduced.
d. When the demonstration project located in
Chongqing Songzao Datong No.1 mine is put into
operation, it will produce 64800 t of superheatedsteam and reduce emissions of CO2 equivalent to107000 t annually, and therefore has excellent
energy-saving and emission reduction benefits.

7. ACKNOWLEDGEMENT
This study was financially supported by National
Science and Technology Major Project of China(2011ZX05041-005).
8.

References

Deng, H.X., Xiao, Q. and Xiao, Y.H. (2014).
Design method of thermal flow-reversal reactor for
ventilation air methane based on regenerative heatexchange model. Journal of China Coal Society,
Volume 39, No. 7, pp. 1302–1308.
Feng, T., Wang, P.F. and Hao, X.L. (2012).
Experimental study on thermal flow-reversal
oxidation of coal mine ventilation air low
concentration methane. China Safety Science Journal,
Volume 22, No. 10, pp. 88–93.
Gosiewski, K. and Warmuzinski, K. (2007).
Effect of the mode of heat withdrawal on theasymmetry of temperature profiles in reverse-flow
reactors. Catalytic combustion of methane as a test
case. Chemical Engineering Science, Volume 62, pp.
2679–2689.
Gosiewski, K., Pawlaczyk, A. and Warmuzinski,
K. (2009). A study on thermal combustion of lean
methane-air mixtures: simplified reaction mechanismand kinetic equations. Chemical Engineering Journal,
Volume 154, pp. 9–16.
Kang, J.D., Lan, B. and Zou, W.F. (2015).
Design and application on five-bed type thermal
accumulation oxidized device of mine ventilation air
methane. Coal Science and Technology, Volume 43,
No. 2, pp. 136–139.
Lv, Y., Jiang, F. and Xiao, Y.H. (2011).
Experimental study of coal mine ventilation methane
oxidization. Journal of China Coal Society, Volume
36, No. 6, pp. 973–977.
Wang, P.F. (2012). Study on theory andexperiment of thermal flow-reversal oxidation of coalmine ventilation air methane. Central South
University, Hunan, China.
Xiao, Q., Deng, H.X. and Lv, Y. (2012). Lean
methane-air premixed-gas heating process research.
Journal of Mining & Safety Engineering, Volume 29,
No. 2, pp. 295–300.
Zheng, B., Liu, Y.Q. and Liu, R.X. (2009).
Oxidation of coal mine ventilation methane ofthermal flow-reversal reactor. Journal of China Coal
Society, Volume 34, No. 11, pp. 1475–1478.
Zhou, X. (2009). Experiment study of coal mine
ventilation air methane oxidation. Institute ofEngineering Thermophysics Chinese Academy of
Science, Beijing, China.

253

ISMS 2016

Paper No. 85

Water disaster investigation and control in coal mine of Southern China
LIANG Qing-hua
China Coal Technology Engineering Group Chongqing Research Institute, Chongqing, China, 400039

ABSTRACT: The number of coal mines in Southern China was the possession of more than 60% of the total coal.
This area was a large undulating terrain, and the terrain was so complex that the exploration was very difficult. The
water damage had a great effect on southern mines. They were mainly threatened by the karst water and the goaf
water. This thesis was studied through mining geophysics and its methods, which were able to fit the characteristics
of karst regions. Using those methods, we could detect and determine the location, size, distribution, and water-filledsituation of geological anomalies that was closely related to mineral water disasters. Based on the characteristics ofthe mine on geology, water damage, mine drainage, this thesis studied the prevention and control measures for coalmine features in southern China to carry out scientific governing for mine water damage.

The number of coal mines in Southern China
takes up more than 60% of the total coal. This area islarge undulating terrain, and landform was complex,
so it was very difficult to explore [1]. There weregreater affected by water damage. They were mainly
threatened by limestone karst water and the goaf
water. Due to faults or karst pipeline conducts water
body，this made a great deal of mine water inflow
and high drainage costs, and also often caused water
inrush accidents[2]. It was a great threat to mine safety
production. Meanwhile, long time of the small coalmining caused a large number of the formation ofshallow goafs[3]. The area of water accumulation was
not clear, which brought great secure risk to the later
period of mine[4,5]. Therefore, the study of
exploratory methods to water disasters and governing
ways had an important reference significance in
China Southern mine.

1. THE SOUTHERN CHINA MINE WATERDISASTER CHARACTERISTICS
There was a large topography of Southern region
and a complex landform in China. Southern mine
karst water disaster and goaf water disaster had
certain regularity[6].
1) Karst water inrush was the main pipe flow,
and it was fast and violent. So the disaster was verystrong. In the process of roadway development, it
would encounter a variety of karst water, whichmainly for cave, collapse column, underground rivers
and other pipeline flow.
2) Relationship between the distribution andstructure of the cave was close. Caves were often
interlinked with underground rivers, the surface ofrivers, and even other aquifers. Distribution between*Corresponding author – email : linqing1110@163.com

caves was also closely related to the structure ofstratigraphy.
3) Goaf water scope was unclear, and the goaf
water inrush was generally rapid. Due to more
mountains in the south of China, mine production
capacity was small. Because of a shortage of funds,
most of mines were not equipped with the necessarygeophysical and geochemical exploration means, thepower of prevention and control water was relatively
weak.

2. THE MINING EXPLORATIONMETHODS AND EQUIPMENT IN
SOUTHERN CHINA
For example, in the mining area of Zunyi, minewater disaster exploration, based on caves,underground rivers and goafs, was the main target ofprobe. According to various geophysical methods andapplicable results of hydro geological exploration in
the Southern mine, we chose three karst hydrogeology geophysical methods that were groundtransientelectromagnetic
method(TEM),
underground geological radar (GPR) and mining
transient electromagnetic method (TEM). Our
exploration approaches were mainly hydrogeological investigation, ground geophysical,
underground geophysical prospecting and drilling.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Altitude(m)For two examples of Changqing Mine andLushuidong Mine in Southern China (Figure 2 andFigure 3), the figure fully reflected the region's
stratigraphic changes, but also reflected the goaf
water situation.

Mileage (m)Figure 2: Changqing Mine apparent resistivity contour
sectional view
Figure 1: Southern Coal geophysical andcomplex terrain construction site
Altitude(m)

900
800
700
600
500
400
主平硐

300
200
100
0

200

400

600

800

1000

1200

1400

1600

1800

390
375
360
345
330
315
300
285
270
255
240
225
210
195
180
165
150
135
120
105
90
75
60
45
30
15
0

1) Mine hydro-geological investigation: Throughthe mine hydro-geological investigation in many
regions, we mainly found the relationship of the mineamong water source, channel, fill, diameter anddischarge. Southern mining, which mainly waterfilled channel had faults, karst pipeline, goafs, closed
poor drilling.
2) Ground geophysical exploration: To enhance
the signal of noise ratio and resolution of datacollection as the core guiding ideology, taking into
account the ground conditions of the Southern mine
complex, we mainly chose the V8 multifunctional
electricalmeter,
high-current
transientelectromagnetic instrument and super high density
electric method.
3) Combined with large fixed source of TEM
and Large current of TEM, we observed that under
the condition of geological and topographical , thelarge fixed source of TEM had the advantages of highefficiency, high exploration depth, and could
penetrate the high resistivity shielding layer. With
this method, we could obtain good geological resultsin guiding water structure and water bearing zone
detection.
In the case of poor conditions of terrain, large
current of TEM could reduce the power supply coiland the receiving coil in this area. It made theefficiency multiplied in this field. We had achieved
good detective results with these two detection
methods.

1000

2000

2200

2400

Mileage (m)Figure 3: Lushuidong Mine apparent resistivity contour
sectional view4) A good exploration, combined with
undergroundgeophysicalexplorationandgeochemical exploration: A variety of geophysicaland geochemical exploration was a useful means tocomplement. Mine of GPR could carry out closely
effective detection (30-50m) in front of the tunnel
face, mine of TEM could be effectively detected on
the water body for remote detection (80-100m), andmine in geochemical exploration was mainly watercontented recognition for the goaf.
Considering that there exist 20m blind areas inmine TEM, We need to avoid blind areas in mine
detection. After a lot of practice, we adopt the mine
TEM tracking detection used as shown in Figure 4.
The detection distance is 100m, and the driving
distance is 80m; the next cycle reaches 80m to detect.
In accordance with such 80m cycle detection, we can
avoid blind area. By analyzing TEM response

255

2600

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

characteristics of typical water flowing abnormal
body, apparent resistivity contour is low resistance ina large scope when goaf or large collapse column isin the water filling conditions, and the continuity of
low resistivity anomaly is better.

TunnelSector detection area

50

-20

-30

-40

-50

-60

-70

-80

-90
50

40

40

30

30

20

20

10

Horizontal (m)Figure 4: The track layout of sector detection the driving
face

10

Water point
0
-20

-30

-40

-50

-60

-70

0
-90

-80

Depth (m)Figure 5: The contour map of apparent resistivity fortunnel detection

On the contrary, there is no blind area of theradar, which can detect continuously. Radar echo
reflection method is mainly used for analysis.

Fall column

Figure 6: The radar detection results map of 3# coalconcentrated track tunnel in coal mine mining area
(10.9m fall column boundary)

3. THE COAL MINE WATER DISASTER’SCONTROL METHODS IN SOUTHERN
CHINA
The principle of control mine water disaster was“Prevention, plugging, discharge, drainage and cut ”
in China. According to Southern mining

characteristics of geology, water disaster, minedrainage, combined grouting sealing and interception,
we should carry out scientific control of mine water
disaster.
1) Karst water drainage
Drainage was the best way to karst water
governing According to the hydro-geologicalconditions of mine, main methods were used inhydrophobic drilling, hydrophobic tunnel and otherprojects to carry out drainage.
2) Plugging on water gushing point
When tunnel crossed over the water inrush thatthreaten collapsed column in karst fracture zone, weshould take advance pre-grouting method and ensuremine safety.
3) Drainage for thin coal seam of goaf water
Goaf water range and pressure in hydrocephalus
should be clear before drainage. If we weren’t sure,
we could take geophysical method to identify thescope and the amounts of goaf water. At the sametime, we still need to perform the mining policy
while probing, to prevent local or other low-lying
water.
4) Tests for water disaster treatment effectFor safe’s sake, we had examined the effect oftreatment on mine water disaster. The main test
methods were geophysical exploration and drilling.
Geophysical methods of water-rich region, drainage
or grouting treatments were used to solve it.

4. EXPERIENCES AND CONCLUSIONS
1) The main method of exploration of the Southmine area was transient electromagnetic method(TEM). In the case of flat terrain, TEM with large
fixed loop was generally used to detect, and in thecase of steep terrain, TEM with large current was
generally used to detect. Coal mine detection by
TEM and Ground Penetrating Radar (GPR), was
combined with drilling, which could solve the water
detection.
2) The commonly used method of water disastergovernance was adit water gravity in South China
coal mine. In the aspect of karst water prevention,
drainage was the best way to control. Slip-casting
was also a better way for controlling karst water. The
control effect of mine water disaster must be
inspected. After inspection and safety, the productionof work could be carried out.

5. REFERENCESDONG Shu-ning, et al. (2008). Practicaltechnology and equipment for mine water prevention
and control, Coal Science and Technology, Volume
36, No. 3, pp. 8-11.

256

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

LIU Zhi-xin. (2008). Study on the distribution
and application of mine transient electromagnetic
field. China University of Mining and Technology,
Xuzhou, pp.35-40.
LIANG Qing-hua, WU Yan-qing, SONG Jin.
(2010). Study on the qualitative analysis andapplication of radio wave tunnel perspective. Journalof Chongqing University(Natural Science Edition),
Volume 33, No. 11, pp. 113-118.
YANG Si-Tong, CHENG Jiu-Long. (2012). The
method of small structure prediction ahead with
Rayleigh channel wave in coal roadway and seismic
wave field numerical simulation. Chinese Journal
Geophysics, Volume 55, No. 2, pp. 655-662.

LIU Sheng-dong, LIU Jing, YUE Jian-hua.
(2014). Development status and key problems ofChinese mining geophysical technology, Journal of
China Coal Society, Volume 39, No. 1, pp.19-25.
Wang Dong-wei, et al. (2011). Application ofmine transient electromagnetic method to advanced
detecting of roadway head. Chinese Journal ofEngineering Geophysics, Volume 8, No. 4, pp.
403~407.
WANG Shuang-mei. (2006). Summary of
research methods on height of transmissive fracture
belt [J]. Jiangsu Geology, Volume 30, No.1, pp.
64~66.

257

ISMS 2016

Paper No. 102

The lifting and separating system for ground maneuvering rescue equipment
GAO Yukun, GONG Xuejiao, HUANG Zhian*, ZHANG Yinghua
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing, China, 100083

ABSTRACTAt present, the research of our country specific emergency system of ground maneuvering rescue equipment has notbeen carried out. The field of special mine rescue equipment lacks specific lifting and separating facilities. To solve
the above problems, this study innovatively designed a Lifting and separating system that matches with the groundmaneuvering rescue equipment. The design of the Lifting and separating system mainly includes the following four
aspects: the Lifting control room, Lift arm material section, size of telescopic boom, and the Selection of hydrauliccylinder for telescopic boom. This study uses ANSYS for the research and analysis. In the process ofmine rescue, this system can enhance the economy and flexibility of hedge facilities and improve the technology ofmine safety emergency rescue in China. The system also has important economic value and social significance forenterprises.
KEYWORDS: lifting and separating system; mine rescue; ANSYS simulation

1. INTRODUCTION
At present, the field of mine special rescue
equipment (Liu, 2010) still lacks specific lifting andseparating facilities. Large and middle rescue
equipment is mostly used in external miniature truckcranes or gantry cranes (Schlick, 1975), which is
influenced by the site space and manoeuvrability.
The platform for the Lifting and separating system
was designed to solve the above problems. The
system design is based on the platform control unit,
which has the advantages of being built-in,lightweight, having a simple structure, andconvenient operation.
The main purpose of the system is for use in mine
rescue. The system has the effect of seismic noise
reduction and integrated management and control(Zhang, K.J., 2012), and therefore the built-in
platform, independent control room, and theequipment unit can be assembled and separated
quickly. This is conducive to the rapid expansion of
the rescue platform and rescue construction (Xu andDu, 2009).

2. COMPOSITION OF LIFTING AND
SEPARATING SYSTEM
The Lifting and separating system mainly includes
four parts (Liu, 1999): hydraulic pump station, boom,
control unit, and auxiliary facilities. The hydraulicpump station is in the right side of the rescue vehicle
control area and the telescopic boom and crane andother major components with the anchor buckle areon the platform of two high strength steel truss. The
structure is stable and reliable. The structure is shownin Figures 1 and 2.

Figure 1: Arrangement of lifting and separating system.

*Corresponding author – email : huang_za@qq.com

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Device specific parameters are as shown in Table 1
and equipment layout is as shown in Figure 3.
Table 1: Size, weight of the control room equipment.
Dimensions (length *Weight kg
Partwidth * height)mm
insidebox body
Figure 2: Assembly and assembly drawings for lifting andseparating system.

3.

Operating table
Air conditioner（Inside ）Air conditioner

DESIGN OF LIFTING AND
SEPARATING SYSTEM

The design of the lifting separation system (Cunand Sun, 2010) mainly includes two parts, namely thelifting and hoisting systems.
3.1 Study on the design of the control room
The system of hanging arm lifting the control
room (Lin, 2012) is located on the tail of theplatform, weighing about 1 tonne and the load
distribution is uniform. The console, locker, airconditioning, and machine weight are arranged
around the room, increasing the torque balance.

（Outside ）File cabinet
Chair
Fire
Extinguisher
Others
Total
Remarks（1670*1920*1850）
outside500（1750*2000*1920）
750*1500*1200

125

680*190*240

7620*200*440

24900*390*1700
800*320*500

25
10
16

707
Design of lifting the maximum load of
1000kgFigure 3: Design of control room layout.

In order to test the scientific nature and rationalityof the design of the control room and to ensure thesafety of the experiment (Liu, 2005), a 2 min driving
test is carried out. For the test to achieve the desired
effect the load control room layout should bereasonable and the design requirements of hoistingshould be met.
3.2 Determination of material section of boom
(1) Selection of telescopic boom material
At present, the material of the lifting arm is madeup of various types of alloy steel and low carbon
steel. Heavy lifting appliances mainly use highstrength low carbon alloy steel, and the medium andsmall cranes adopt 16Mn. Considering the cost andthe design of the lifting weight is not large, the cranematerial design uses 16Mn.
(2) Section of the telescopic boom
The main body of the main arm uses 16Mn
material. Overall the choice of materials and structureof the design considers safety and the economic
applications of the principle (Huang and Ou, 2011). It
is optimal to reduce the weight of the boom and toachieve the overall optimization of the suspension
arm and the whole system performance (Chen, 2012).
3.3 Determination of dimensions of telescopic boom
(1) The design of the main and sub arm's length259

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The design of the main boom length is determinedby the basic arm length and the extended length.
(1)lmax =l0 − (k − 1)a + (k − 1)l =l0 + (k − 1)l 'In the optimization design platforms, according toengineering experience, lap length should be
extended to the length of 1/4 to 1/5 for the second
section crane arm, and l ' =（）0.2~0.25 li for thesecond section hanging arm.
The second section telescopic boom is fully
recovered from the main arm, and there is a long
distance C, which mainly is the main arm of thehydraulic cylinder stretching mechanism and thefastening device. This space is often within the rangeof 0.25-0.44 m. Therefore, the main pair of two arm
structure lengths has the following relations:(2)
li0 =li0+1 + c − a

The two section telescopic boom, lap length of thesecond section telescopic boom, and jib is equal to
1/5 of the extended length. The main vice hanging
arm joint length and the length of the structure are:(3)=
l2'' 0.2=l；l20 1.2l
0(4)l1 = 1.2l + (k − 1)(c − a )(2) Check the length of the main and auxiliary arm
Through the above calculation, we can know thatthe length of the main arm is satisfied with the lengthof 4-31, and the length of the second sections canmeet the design requirements and engineering use.
(5)l0 = l10 + a (k − 1) ≥ 1.2l + (k − 1)c =1.2(l ' + a ) + (k − 1)c
According to the above calculations andverification, the vice arm of the section and thelengthoftherelevant
surplus:=l10 3.1(=m); l2' 1.6(=m); a2 0.3(m)In summary, the boom sections design size andcross section are determined as shown in Figure 4.

Figure 4: Boom size chart.

3.4 Calculation and selection of hydraulic cylinder
for telescopic boom
(1) The inner diameter of the cylinder of hydrauliccylinderSet the maximum load of the arm Q=1.5 T for thetelescopic cylinder to bear the maximum pressure:
(6)
F
=
1.9
=
Q 2.85Tmax
Combined with the practical requirements, thehydraulic cylinder of the allowable working pressureis 5 MPa, D=60.03 mm, combined with the innerdiameter of hydraulic cylinder, D=63 mm.
(2) Hydraulic cylinder piston rod diameter
calculation
a. Design
Combined with the movement speed of thepiston rod, ϕ =1.33. d=31.38 mm. Combined withthe series of piston rod diameter, d=32 mm.

n is the safety factor and considering the security, then is 5 after testing the strength of the hydrauliccylinder to meet the design requirements.
c. Hydraulic cylinder stability test
It can be determined when the piston rod size is
d=50 mm, the arm is safe and reliable, and meets thestrength and stability calculations.
(3) Calculation of the hydraulic cylinder wall
thickness and diameter
The platform telescopic hydraulic cylinder wall
thickness and diameter to meet the strength
requirements under load. D1 =67 mm.
To sum up, we can draw telescopic hydrauliccylinder structure parameters of hydraulic cylinder
diameter: 63 mm. Hydraulic cylinder diameter: 67mm; piston rod diameter: 50 mm.

b. Hydraulic cylinder strength test
The platform lift arm is 16Mn, so σ b is 345 MPa;

4. THE FINITE ELEMENT ANALYSIS OFTELESCOPIC ARM BASED ON ANSYS

260

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.1 Finite element model of telescopic boom
(1) Entity model
The first section is 180*135 mm, the wall
thickness is 17.5 mm, the length is 3100 mm; thesecond section is 145*100 mm, the wall thickness is
10 mm, the length is 2900 mm, the assembly depth is1000 mm; the material is structural steel, the elastic
modulus is 200 GPa, the Poisson's ratio is 0.3.

Figure 7: Constraint and load chart of the telescopic arm.

The geometric model is shown in Figure 5.

Figure 8: working plan of the telescopic boom

Figure 5: Geometric model of telescopic boom.

4.2 Analysis of finite element calculation results oftelescopic boom
In order to verify the security and reliability ofthe telescopic boom, the second section of the boom
is completely out of the operating conditions for
simulation verification.
(1) The overall structure

Figure 6: Grid division of telescopic boom.

(2) Unit selection and grid division

As shown in Figure 8, the maximum deflectionof the structure is 45.6 mm. The maximum stress ofthe structure is 167.4 MPa, far less than the allowablestress of the material ([ σ ] =345 MPa), which appears
in the first section of the arm frame and the second
arm frame. These results are shown in Figures 9 and
10.

The platform lift arm model was built to selectthe unit. Shell element shell63 and solid45 wereselected for the simulation of solid element to choose
the unit body belonging to 8 node 6 unit, hanging arm
model scale: node number 3201, unit number 41821.
Grid divisions are as shown in Figure 6.
(3) Model of the contact of the boom
Because of the telescopic arm, between the main
and auxiliary boom depends mainly on the chute andthe plate of a lubricated contact force transfer.
Therefore, we must deal with the model of thecontact of the boom.

Figure 9: The overall structure of telescopic boom.

(4) Arm loading and constraint handling
The load of the telescopic boom mainly
includes: the control room load, steel wire rope, andthe supporting force of pull arm. Under the premiseof considering the surplus coefficient, the control
room load is 1t, as shown in Figure 7. The C isapplied to the 9800N surface.

Figure 10: The maximum stress concentration point of thestructure of telescopic boom.

(2) The second cantilever crane;
Through Figure 2, we can know that in the 11
section of the arm, the stress concentration is mainly
distributed in the junction with the first arm, the261

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

intersection of the arm, and the maximum stressconcentration is consistent with the overallsimulation results.

other stress concentrations, alloy steel is used. Thisnot only optimizes the weight of the boom but alsoachieves the overall optimization of the performanceof the split system of the arm and the whole hoisting
system.
3) The telescopic boom is composed of twoparts, the main arm and the outer part. The length ofthe main, sub arm's length, design size, and crosssection were determined.

Figure 11: Stress chart of the second cantilever crane.

Figure 12: Maximum stress concentration point of thesecond cantilever crane.

(3) The first cantilever crane
The maximum deflection of the first cantilevercrane is 16.8 mm, as shown in Figure 13, less thanthe overall structure maximum deflection of 45.6mm.
The supporting role of the main arm of the hydrauliccylinder is minimal, which in turn verifies therationality of the hydraulic cylinder structure.

4) Based on the ANSYS finite element
simulation, we know that when the two rectangulararms are made of 16Mn material, the section size
meets the designing demand, and the maximum rated
starting weight is 1 tonne and the extension length is
1.9 m, the strength and stiffness of the arm conforms
to the safety requirements. The whole telescopic
boom is safe and reliable.

6. ACKNOWLEDGEMENT
It is with great pleasure that we acknowledge thegenerous financial support of National Natural
Science Foundation of China (project number:
51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).

7. REFERENCES

Figure 13: Working plan of the first cantilever crane.

5. CONCLUSIONS
1) According to the uniformity of load
distribution, the control room of the crane hoisting
system has been designed and is comprised of theconsole, locker, air conditioning, and outsidemachines, increasing the torque balance. The lifting
point is arranged in the control indoor four beamcolumn side with a special four legged chain slingconnected. The field test achieved the desired effect,
showing that the load control room layout isreasonable and satisfies the design requirements ofhoisting.
2) The design uses rectangular cross sections.
The main arm of the main body uses 16Mn asmaterial, and for the four corners of the weld andChen, T.T. (2012). A visual management andmonitoring tool for cross-organization emergency
response workflows. Information Technology
Journal. Volume 11, pp. 1341-1356.
Cun, T.T.Y and SUN, L. (2010). Development
history of 20t hydraulic excavator for Hitachi
construction machine. Engineering machinery andmaintenance. Volume 8, pp. 88-92.
Huang, Y.J. and Ou, J.C. (2011). Status anddevelopment trend of sudden disaster emergency
rescue equipment. China Hospital. Volume 15, pp.
52-53.
Lin, J. (2012). Mine rescue "Noah's Ark" -- Jiang
Lu Electromechanical group Co. Ltd of mine rescue
vehicle function. Hunan security and disasterprevention. Volume 1, pp. 36.
Liu, Q.H. (2010). Analysis and Prospect oftechnical status of rescue and rescue vehicle. China
Emergency Rescue. Volume 5, pp. 16-17.
Liu, Q.D. (1999). Study on sliding type loader.
Engineering Machinery. Volume 10, pp. 32-34.
Liu, Y. (2005). The first China mine rescue car
made in Xiamen. Xiamen Daily. Volume 11, pp. 17.

262

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Schlick, D. (1975). Mine emergency operations of
the mining enforcement and safety administration.
United States Department of the Interior Mining
Enforcement
andSafetyAdministration
Informational Report. Volume 11, pp. 34-35.
Xu, K.S. and Du, P.D. (2009). System to
Guarantee
Emergence
Response
Equipment
emergency resuce equipment. Forestry Labour
Safety. Volume 2, pp. 11-16.
Zhang, K.J. (2012). Importance of scientificmanagement for mine rescue equipment. Reform andopening. Volume 2, pp. 89.

263

ISMS 2016

Paper No. 103
Safety and stability of the maneuvering rescue platformGAO Yu-kun, Ji Yu-Chen, HUANG Zhi-an*, ZHANG Ying-hua

State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing 100083, China

ABSTRACTWith the continuous developments in the field of mining rescue, mechanical rescue equipment has been growing
more complex and automatic, which leads to higher requirement for the safety, stability, and carrying ability ofplatform foundations. In response to these requirements, the present study designed an overall layout of the
maneuvering rescue platform equipment. Upon consideration of the load arrangement rationality of the rescue
platform, the humanity and convenience of the on-board equipment function, and the safety of the electric device,
the overall layout of the vehicle was divided into two units: the device unit and the control unit. After completing theoverall layout design, the security and stability of the platform was verified and analyzed. The results proved that thedesign of the maneuvering rescue platform met the requirements for the stability and safety of the mine rescue
mission. The platform can be quickly deployed over a long distance with suitable mobility and carrying capacity.
KEYWORDS: maneuvering rescue platform; stability; modifications
Once a water permeating accident or other minegas outburst accident occurs, emergency rescue
platforms should arrive in the rescue site andestablish temporary rescue command posts in the
shortest possible time (Huang and Ou, 2011). The
village, field, and hillsides on the way to mine
rescues can be difficult to maneuver (Zhang, 2012;
Yu, 2000), therefore, the security and stability of
rescue platforms is very important.

1. THE OVERALL LAYOUT OF THE
MANEUVERING RESCUE PLATFORM
The nature of the maneuvering rescue platform
and other specialty vehicle design modifications isbasically the same. The main difference is that theultimate goal of the maneuvering rescue platform
design is to reach the rescue site and accomplish therescue mission. The roads to the rescue site aremostly rugged and complicated to maneuver.
Therefore, the vehicles need to be more reliable andstable.
When maneuvering rescue platforms, thecharacteristics of the on-board equipment need to beconsidered, including device functions, volume,
mass, and many other factors. Maneuvering rescue
platforms integrate the air supply system, power
supply system, the flow of food supply systems,
monitoring, and control communications systems.
Once the destruction of the underground system has
occurred, the maneuvering rescue platform canprovide power, communications, and food for the
refuge chamber through the orifice docking device.

*Corresponding author – email: huang_za@qq.com

Figure 1: Layout left view of the maneuvering rescue
platforms.

The overall layout of the vehicle is divided into
two units: the device unit and the control unit. As
shown, the device unit is made up of the aircompressor, water tanks, generators, transformers,
pump station, and most of the power and rescue
equipment. The functions of the control unit arecontrolling communications, electricity transmission,monitoring, and other functions.
2.

THE DISTRIBUTION OF LOAD AND
THE CENTER OF MASSIn maneuvering rescue platform design, whatneeds to be considered is the quality of different
vehicle equipment, features, and rational layout
location equipment. This is necessary to facilitate theoperator's quick and accurate control. Intrinsic safety
design needs to be performed according to equipment
function and reasonable partition. By calculating the
distance between the gravity center of the main
harness and the front axle of the platform, the relative
space position of the vehicle equipment should bereasonably arranged. In order to fully ensure platform

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016security, it is necessary to improve the system's
practicality and aesthetics (Liu, 1994; Cui, 1986).
The calculation is as follows:
1) Establish a Cartesian coordinate system. The
origin of coordinates is in the vehicle axle. The
extension of the two vehicle axle is the Y-axis andthe roof plumb line is the Z axis. Coordinate positive
direction is chosen, as shown in Fig.2.
2) The major equipment parameter list is shownin Table 1, including mass and the centroid location,with the relative distance of the axes and the like.

capacity of Gmax=1T>G, which is within theallowable load range, and not overweight.
n

=
Frear

Table 1: Maneuvering rescue platform centroid position ofmajor equipment and the quality of their list.
Centroid
WeightNO. moment
Parts Names
Y-axisG/Kg
distance/mm
air
1
F1
4500
1950
compressor
electric
2
F2
540
4465
generator
3F3transformer
460
4525
…
…
…
…
…
n-2
F n-2
lazy arm
310
5297
n-1
F n-1
control board
125
5735
n
Fn
water tank
600
3903
Fsum
Sum
8750
2460.98
CentroidCentroid
X-axisNO. moment
Parts Names
heightdistance
Z/mm
/mm
air
1
F1
1875
0
compressor
electric
2
F2
1480
-465
generator
3F3transformer
950
886
…
…
…
…
…
n-2
F n-2
lazy arm
3032
0
n-1
F n-1
control board
1260
-697
n
Fn
water tank
1680
105
F sum
Sum
1608.49
5.48

3) From Table 1, the total equipment weight is
G=8750kg. Fukuda Ollin CTX5200 vehicle chassis
parameters are used to allow a maximum carrying

i i

=
L

i =1

32371456= 6225.28kg
5200

(2-

1) Ffront =F -Frear =8750-6225.28=2524.72kg

(2-2)
(2-3)
(2-4)

Figure 2: Maneuvering rescue platform x-y coordinate
system schematic.

∑ FY

B
F ×( + X )7966715
2Fleft === 4401.50kg
1810
B

Fright =F -Fleft =8750-4401.5=4348.50kg

According to the above calculation:
Platform chassis front axle maximum load Ffront=3250
kg>Ffront = 2524.72 kg, rear axle maximum
axle
axle load Frear axle = 6750 kg>Frear = 6225.28 kg. The
overall design of the platform weight does not exceed
the original parameters of the permissible range ofthe vehicle, and it was in line with the safety
requirements. On the other hand, after the platform
modifications, load was close to full capacity. It is
important to note the use of usual safe driving tactics,
and to avoid the use of emergency brakes. While in
the latter part of the platform design, what needs tobe further considered is the streamlining harness, useof lightweight materials, optimized chassis, and othermeasures to increase the flexibility of the platform.

3. LONGITUDINAL STABILITY
In order to ensure the platform with security andstability, longitudinal stability studies of the modified
platform were performed.
The rescue platform utilized the Fukuda standard
commercial chassis without any modifications, so
there were no parking brake problems. The only
major considerations for longitudinal stability of theplatform analysis are the longitudinal tipping andlongitudinal slippage (Zhang, 1997; Shuichi, 1981),
as shown in Figure 3.

Figure 3: Maneuvering rescue platforms longitudinalstability diagram.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Verification is calculated as follows:
Platform maximum sideslip angle is calculated
as:

Y ×φ
2460.981× 0.5= arctanθslip = arctan=15.64
L − Z ×φ
5200-1608.49 × 0.5（3-1）

When climbing, the maximum slope angle iscalculated as:

L −Y
5200 − 2460.98== 59.53arctanθ downhill = arctanZ1608.49（3-2）
When downhill, the maximum slope angle iscalculated as:θ climbing = arctan

Y
2460.98= arctan=56.83 （3-3）
Z
1608.49

Calculation of the above formula shows that
θslip<θclimbing, θslip<θdownhill, θslip<Prev θturn, suggestingthat when vehicle instability occurs, sliding
phenomenon occurs. However, overturn will notoccur, which ensures the platform's longitudinalstability and security. In addition, the results showthat θclimbing and θdownhill are about four times the θslip,
which shows that the overall vehicle longitudinal
conversion is quite reliable. Once sliding occurs, thedriver of the maneuvering rescue platform would
have enough time to correct for the slide. This
ensures the safe emergency disposal.
4.

LATERAL STABILITY

The lateral stability of the platform directly
affects how the vehicle travels in horizontal
centrifugal force. Horizontal centrifugal force isrelated to the stability of the vehicle state and must be
determined in the reliability test and verified as animportant platform indicator for road safety.
Research on lateral stability mainly includes two
aspects: cornering stability and cross slope stability.
4.1 Cornering stability
Analysis shows that the platform has a tendency
to tilt outwards when subjected to centrifugal force
around a corner.
The centrifugal force on the platform is inversely
proportional to the turning radius, but is proportional
to the speed.
If the platform corner has a minimum radius of
Rmin=6.25 m (chassis factory parameters). thencornering limit speed when the platform slides iscalculated as:

Vslip = g × φ × Rmin== 5.53m/s
9.8 × 0.5 × 6.25

（4-1）
Cornering limit speed when platform rollover
occurs is calculated as:
Rmin × b × g
6.25 × 9.8 ×1930
V== 6.06m/s
turn =
2Z
2 × 1608.49（4-2）
In the formula, car gage b =1930mm (chassis
factory parameters).
It can be seen from the above calculation
process, Vturn>Vslip, that platform lateral stability isreliable when cornering. Also, the surplus quantity of
the Vturn and Vslip is relatively low, indicating that
although safety of the platform is not a problem,
there is room for improvement in stability. Vehicle
rollover under conditions of the limit cannot be ruled
out, because of the high speed or too-small turning
radius. The best way to improve stability is to reduce
the overall centroid height Z of the platform toachieve Vturn >> Vslip over the state, which is also an
important aspect of late platform optimizing.
4.2 Cross slope stability
Cross slope stability, with respect to theplatform, is measured by:
b
>φ
2× Z
（4-3）
b
1930
=
=0.60
2 × Z 2 ×1608.49（4-4）
According to the results, 0.60>Φ = 0.50,
therefore, the design with the cross slope is safe.
However, in order to better ensure the safety of theplatform, the platform should be loaded with areasonable arrangement: for example, compact
integrated devices should be chosen and theequipment should be put in a lower position. The
purpose of reducing centroid height by the abovemeans is to increase the driving safety of theplatform.
4.3 Wind resistance
Platform modified equipment for the purpose ofcooling and elimination of flue gas is placed in theroof of the vehicle platoon, which indirectly increases
the wind age area of the vehicle with increases ofplatform height.
The Bernoulli equation shows:
v2
（4-5）
wp =
1600

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Consider that the work conditions of theplatform are no more than 5 wind strength, andtherefore take 5 wind speed (v = 10.7 m/s) for theauthentication parameter in formula 4-6:
10.7 2=
wp = 0.0072kN / m 2
1600
（4-6）
The roof platform exhaust fan height is about
0.25 m, and the wind area is about 0.45 m2, so theexhaust fan wind torque:

F =wp × 0.25 × 0.45 =81kg ⋅ m（4-7）
The overturning moment platform can afford:

1.61 14087.5kg ⋅ m
Fplatform =F × Z=8750 ×=

Liu Z Y, He X G. (1994). Special purpose
vehicle structure. Wuhan University of technology
press. 175 p.
Shuichi Iida. (1981). Commonly used indicatorof physics. Science press. 236 p.
Yu Z S. (2000). Automobile theory. China
Machine Press. 15 p.
Zhang H X. (1997). Automobile design. China
Machine Press. 89 p.
Zhang K J. (2012). The significance of mine
rescue equipment scientific management. Reform &Openning, No. 2, pp.89.

（4-8）
From the above calculation, G=F=8750 kg,
Z=1.61 m, F<<Fplatform. This shows that the draggenerated by the wind on the exhaust fan for
emergency rescue platforms is negligible. The
platform has wind resistance and the ability to resist
overturning.
5.

CONCLUSIONS

A platform was modified to ensure theuniformity and reasonable load distribution as muchas possible. The platform had good stability when
loaded, with uphill and downhill angles being within
the maximum angle limit.
Platform rollover would not occur when loaded
and cornering within the maximum allowed angle.
The platform would be permitted within the
maximum load under conditions of full and full
fittings.
The cooling fan on the roof caused an increase in
the wind area due to the increased height, however
the wind resistance was reduced. The platform has
wind resistance and the ability to resist overturning.
6.

ACKNOWLEDGEMENT

It is with great pleasure that we acknowledge thegenerous financial support of the Hebei centralenergy Fengfeng Group, the National Natural Science
Foundation of China (project number: 51474017) andNatural Science Foundation of Xinjiang Uygur
Autonomous Region of China (2014211B013).

7. REFERENCES
Cui J. (1986). Special purpose vehicle design.
Shaanxi science and technology press.115 p.
Huang Y J, Ou J C. (2011). Status anddevelopment trend of sudden disaster emergency
rescue equipment. Chinese Hospitals, Volume 15, No.
12, pp. 52-53.

267

Paper No. 105

ISMS 2016

The performance optimization experiment of a wet high-frequency vibrating
grid
Zhang Yinghua, Liu Jia, Huang Zhian*, Gao Yukun
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing, China, 100083

ABSTRACTDust preventing is of great significant in mine safety production. The wet high-frequency vibrating grid is one of themost efficient dedusting systems. Therefore, optimizing the dedusting parameters of wet high-frequency vibrating
grids is meaningful in controlling dust. Two of the most important parts of wet high-frequency vibrating grids are
the spray dedusting system and the vibrating grid filtration system. This study optimized these two systems
respectively to obtain the influence of various factors on the two systems by using the method of orthogonal
experiment and then chose the two factors which have the greatest impact on comprehensive optimization. The
results can be used in mine dedusting practice to reduce the incidence of pneumoconiosis and improve work
efficiency.
KEYWORDS: Vibrating wire grid; dust removal mechanism; orthogonal experiment; performance optimization

1. INTRODUCTION
Underground dust is wide spread and lasts for along time, therefore, dust suppression by spraying has
always been the main measure to control mine dust.
A variety of forms are in practice, such as wind-water
spraying, magnetized water dust suppression, precharged water spray dust suppression, high-pressure
spraying, etc. (Liu et al., 2011; Wang, 2010; Dong,
2014). Traditional dedusting methods can be divided
into dry dedusting and wet dedusting. Mine dust isalways damp, therefore the bag filter and electrostatic
precipitator can't be used normally. Wet dust
collectors used in mines mainly include the venturi
scrubber, cyclone dust collector, foam dust catcher,
impact dust collector, self-swash dust catcher, anddust removal fan. These dust collectors have simple
structures, convenient maintenance, and reliable
operation (Song, 2010; Chen, 2013; Li et al., 2011).
However, as the underground conditions are complex
and changeable, some new equipment and technology
has not been generalized effectively (Shi, 2005).
The wet high-frequency vibrating grid is one of
the most efficient dedusting systems. Optimizing thededusting parameters of the wet high-frequency
vibrating grid is meaningful in controlling dust. This
study first did deep research on the dedustingmechanism of the wet high-frequency vibrating gridand then optimized the vibrating grid system and thespray system of the grid by an orthogonal
experiment. Afterwards the wet high-frequency
vibrating grid system was synthetically optimized.

*Corresponding author – email : huang_za@qq.com

2. DEDUSTING MECHANISM OF WET
HIGH-FREQUENCY VIBRATING GRID
The wet high-frequency vibrating grid includes
spray dedusting and vibration fiber grid dedusting.
When the dust-laden air flows through the sprayer,some dust is crashed, intercepted, condensed, andsettled. Spray dedusting mainly uses inertial
impaction, interception, and Brownian diffusion andother short-range dust catching mechanisms.
Vibrating grid dedusting is uses sonic vibration. By
the acoustics principle, the particles in the sound field
will vibrate under the effect of sound waves. The
small particles have high vibration velocity and large
particles have low vibration velocity, which makedifferent sizes of particles agglomeration power
forward, so that the larger particles will get closer tothe small particles and collide, combine into larger
particles, making it easier to be trapped.
Supplemented by spraying dedusting, this method
can achieve high efficiency of reducing the respirable
dust concentration. The acoustic agglomeration effectof the vibrating grid is also related to its amplitude,
where the greater the amplitude, the higher thecollection efficiency. The amplitude is related to thewind speed flow where the higher the wind speed, thegreater the amplitude of the vibrating grid, the soundcondensation effect is more significant, and thededusting effect is better. However, at, extremely
high wind speeds, damage will be caused to thevibrating grid.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3. OPTIMIZATION EXPERIMENTRESEARCH ON WET HIGHFREQUENCY VIBRATING GRID
DEDUSTING PARAMETERS
3.1 Experimental procedure and principle
1) Measure the dust mass flow through before
and after the wet high-frequency vibrating grid
Put the filter membrane into the culture dish withtweezers moistened with alcohol, and weigh them inthe one over ten-thousand analytical balance after
drying them in the drying oven, record the initial
data. Start the two dust samplers before and after thegrid to obtain the filters with dust before and after
dedusting. Place the filters into the culture dishoriginally used to weigh and record the data. Subtract
the initial mass from the total mass of dust filters andculture dish to obtain the dust mass before and after
dedusting. Refer to the following formulas:(1)
Mbefore = M1 − MO(2)
Mafter = M2 − MO
Mbefore is the dust mass before dedusting. M1 isthe total mass of filters and culture dish before
dedusting. M0 is the initial mass of filters and culture
dish. Mafter is the dust mass after dedusting. M2 is thetotal mass of filters and culture dish after dedusting.
2) Determination of dedusting efficiency
Side-sampling is applied in this experiment.
Place two dust samplers before and after the grid in
the simulating roadway. Start two dust samplers at
the same time, set the flow rate to 20 L/min and thesampling time to two minutes. Take out themembrane filter according to the above method toweigh the filter and calculate the dedusting efficiency
according to the following formula:1000⋅（M −M ）

后
前
(3)
η=
Lt
ƞ is the dust concentration of sample point,

mg/m3 ；Mbefore is the dust mass before dedusting,mg; Mafter is the dust mass after dedusting, mg; L isthe sampling flow rate, L/min; t is the sampling time,min.
3) Determination and calculation of dedusting
resistance
The experiment indicates the dedusting
resistance with pressure loss, and set the airflow of
inlet pipe and outlet pipe to be equal, then the
average total pressure difference between the airflow
of inlet and outlet pipe can be obtained by theaverage static pressure difference. The two sectionsof the static pressure difference can be measured witha pitot tube and compensation micro-manometer andcalculated as:(4)∆P = P1 − P2

ΔP is the pressure loss, Pa; P1 is the pressure at
the inlet section, Pa; P2 is the pressure at the inlet
section, Pa.
3.2 Design and production of wet high frequency
vibrating grid dedusting experiment system
1) Production of vibrating grid board
Set the iron grid board frame internal andexternal size as 35 cm × 35 cm, 27 cm × 27 cm
according to the simulation roadway size. Wrapped
the Nylon lines equally spaced around the two sidesof the vibrating grid frame and make the fibers
remain extremely tight. The produced vibrating gridis shown in Figure 1:

Figure 1: Vibrating grid.

2) Spray system connection
The nozzle parameters of the spray system are
as follows: the diameter is 1.5 mm, rated pressure is 4
Mpa, diffusion angle is 70°, and the measuring
device used a LZS – 15 flow meter.
The devices were connected by 25 mm highpressure rubber hose, and the metal ring pipe
connectors were used to connect the connection parts.
The spray system connection order is shown in figure
2.

Figure 2: Spray system connection order.

3) Assembly of dust generation system
Dust generation system is made up of a fan anddust injection parts. In order to simulate the windspeed in the actual roadway (3-5 m/s), choosing the
BPT12-13 pipeline ventilation fan as the generation

269

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016device, its air volume Q = 150 m3/h, and wind speed
is about 4.2 m/s.

The experimental design is shown in Figure 3:

Figure 3: Experimental device design.

3.3 Vibrating grid dedusting orthogonal experiment
To obtain the most efficient parameter combinationof the fiber grid dedusting system, select thecollection efficiency as assessment indicator.
Maintaining water quantity as 1.33 L/min, spraydistance as 15 cm, carrying on the orthogonal
experiment under this condition, the experimental
results are shown in Table 1. Analyze the variance on
the above data, the results are shown in Table 2.

Table 1: Vibrating grid dedusting orthogonal experimental results.
Experimental
Condition

Experimental
ResultA1B1C1A1B2C2
A1B3C3
A2B1C2A2B2C3A2B3C1A3B1C3A3B2C1A3B3C2

89.1
92.5
94.6
92.3
94.4
96.8
95.9
98.0
99.2

F Ratio

F Critical-value

Significance21441.952

19.000

＊
＊

Line

1

2

3

Factor
1
2
3
4
5
6
7
8
9
Mean Value 1
Mean Value 2
Mean Value 3
Range

Grid Board number
1
1
1
2
2
2
3
3
3
92.06794.50098.367
6.300

Fiber Diameter
1
2
3
1
2
3
1
2
3
92.43394.96797.533
5.100

Parallel Number
1
2
3
2
3
1
3
1
2
94.90095.33
94.9670.700

Table 2: Vibrating grid dedusting efficiency variance analysis
Square ofDegree ofFactorDeviance
Freedom
Grid Board Number

60.562Fiber Diameter

29.0162928.952

19.000Parallel Number
Error

0.736
0.04

2
2

17.52419.000270

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

0

1

2

3

4

actual level and ordinate is the average dedusting
efficiency, as shown in Figure 4.

98
97
96
95
94
93
92
0.22

0.24

0.26

0.28

0.3

B Fiber Diameter(mm)A Grid board number(piece)

Dedusting Efficiency（%）

99
98
97
96
95
94
93
92
91

Dedusting Efficiency（%）

Dedusting Efficiency（%）

Draw pictures on grid board number, fiber
diameter, and parallel number. The abscissa is the

95.4
95.3
95.2
95.1
95
94.9
94.8
0
2
4
6
C Parallel Number(thread)

Figure 4 : Factors affecting dedusting efficiency analysis of orthogonal experiment.

The significant analysis shows that the factors
affecting the dedusting effect order are as follows:
grid board number, fiber diameter, and parallel
number. Therefore, select grid board number andfiber diameter as two factors for the integrated
optimization orthogonal experiment factors.
The optimal level is the highest total level of thethree factors’ optimal level. It can be obtained from
Table 1 that the optimal combination is when the gridboard number is 3, the fiber diameter is 0.29 mm, theparallel number is 2 (A3B3C2), and the dedusting
efficiency is 81.2%.

3.4 Spray dedusting orthogonal experiment
To obtain the most efficient parameter
combination of the spray dedusting system, select thecollection efficiency as the assessment indicator.
Maintain the grid board number as 2, fiber diameteras 0.26 mm, and carry on the orthogonal experiment
under these conditions. The experimental results areshown in Table 3.Analyze the variance of the data.
The results are shown in Table 4.

Table 3: Spray dedusting orthogonal experimental results.
Line

1

2

3

Factor
1
2
3
4
5
6
7
8
9
Mean Value 1
Mean Value 2
Mean Value 3
Range

Spray Water Volume
1
1
1
2
2
2
3
3
3
91.66793.86798.6336.966

Spray Distance
1
2
3
1
2
3
1
2
3
93.70096.06794.4002.367

Nozzle Angle
1
2
3
2
3
1
3
1
2
94.23394.86795.067
0.834

Experimental
Condition

Experimental
ResultA1B1C1A1B2C2
A1B3C3
A2B1C2A2B2C3A2B3C1A3B1C3A3B2C1A3B3C2

90.0
93.1
91.9
93.2
95.4
93.0
97.9
99.7
98.3

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 4: Spray dedusting efficiency variance analysis.
Square ofDegree ofFactorDeviance
Freedom

F Ratio

F Critical-value

Significance19.000＊＊Spray Water Volume

76.0962

352.296

Spray Distance

8.869

2

41.06019.000Nozzle Angle
Error

1.136
0.22

2
2

5.259

19.000level and ordinate is the average dedusting efficiency,
as shown in Figure 5.

76.5

Dedusting Efficiency(%)

79
78
77
76
75
74
73
72
71

Dedusting Efficiency(%)

Dedusting Efficiency(%)

Draw graphs of the spray water volume, spraydistance, and nozzle angle. The abscissa is the actual

76
75.5
75
74.5
74
73.5

0.8
1
1.2 1.4 1.6 1.8
A Spray Water Volume(L/min)

5

10
15
20
25
B Spray Distance(cm)

76
75.5
75
74.5
74
73.5
73
72.5
72
50

70
90
110
C Nozzle Angle(°)

130

Figure 5: Factors affecting dedusting efficiency analysis of orthogonal experiment.

The significant analysis shows that the factors
affecting the dedusting effect order is as following:
spray water volume, spray distance, and nozzle angle.
Therefore, select spray water volume and spraydistance as two factors for the integrated optimization
orthogonal experiment factors.
The optimal level is the highest total level of thethree factors’ optimal level. It can be obtained from
Table 3 that the optimal combination is that the spraywater volume as 1.67 L/min, the spray distance as 15cm, the nozzle angle as 60° (A3B2C1), and thededusting efficiency is 79.7%.

3.5 Wet high frequency vibrating grid dedustingparameter optimization experimentAccording to the two orthogonal experiments
above, choose four factors for comprehensive
optimization experiments, namely, grid board
number, fiber diameter, spray water volume, andspray distance. Select dedusting efficiency anddedusting resistance as evaluation indicators.
1) Dedusting efficiency orthogonal experimental
result analysis
The dedusting efficiency orthogonal experimental
results are shown in Table 5. Analyze the variance ofthe data. The results are shown in Table 6.

Table 5: Dedusting efficiency orthogonal experimental result.
Line

1

FactorFiber Diameter

1
2
3
4
5
6
7
8
9

1
1
1
2
2
2
3
3
3

2

3

Spray Water
Volume
1
2
3
1
2
3
1
2
3

Grid Board
Number
1
2
3
2
3
1
3
1
2

4

Experimental
Condition

Experimental
ResultA1B1C1D1
A1B2C2D2
A1B3C3D3
A2B1C2D3
A2B2C3D1
A2B3C1D2
A3B1C3D2
A3B2C1D3
A3B3C2D1

88.8
93.9
98
92.1
95.5
95.2
93.3
93.1
97.3

Spray Distance
1
2
3
3
1
2
2
3
1

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Mean Value1
Mean Value2
Mean Value3
range

93.56794.26794.5671.000

91.40094.16796.833
5.433

Table 6: Dedusting efficiency variance analysis.
Square ofFactorDeviance
Fiber Diameter
1.580

92.36794.43395.6003.233

93.86794.13394.4000.533

Degree ofFreedom2

F Ratio

F Critical-value

3.700

19.0002

103.71719.000＊＊Spray Water Volume

44.287

Grid Board Number

16.087237.67419.000Spray Distance
Error

0.427
0.43

2
2

1.000

19.000abscissa is the actual level and ordinate is the averagededusting efficiency, as shown in Figure 6.

94.8
94.6
94.4
94.2
94
93.8
93.6
93.4

Dedusting Efficiency(%)

Dedusting Efficiency(%)

Draw graphs of fiber diameter, spray water
volume, grid board number, and spray distance. The

0.22

0.24

0.26

0.28

0.3

98
97
96
95
94
93
92
91
0.9

96
95.5
95
94.5
94
93.5
93
92.5
92
1
2
3
C Grid Board Number(piece)

1.1

1.3

1.5

1.7

1.9

B Spray Water Volume(L/min)
Dedusting Dfficiency(%)

Dedusting Efficiency(%)

A Fiber Diameter(mm)0Significance

4

94.5
94.4
94.3
94.2
94.1
94
93.9
93.8
5

10
15
20
D Spray Distance(cm)25

Figure 6: Factors affecting dedusting efficiency analysis of orthogonal experiment.

The significant analysis shows that the factors
affecting the dedusting effect order are as follows:
spray water volume, grid board number, fiber
diameter, and spray distance.
2) Dedusting resistance orthogonal experimental
result analysisThededustingresistanceorthogonal
experimental results are shown in Table 7. Analyze
the variance of the data. The results are shown in
Table 8.

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Table 7: Dedusting resistance orthogonal experimental results.
Line
1
2
3
Spray Water
Grid Board
FactorFiber Diameter
VolumeNumber
1
1
1
1
2
1
2
2
3
1
3
3
4
2
1
2
5
2
2
3
6
2
3
1
7
3
1
3
8
3
2
1
9
3
3
2
Mean Value1
59.11756.53042.013
Mean Value2
62.10362.30062.087
Mean Value3
64.64767.03781.767Range
5.530
10.50739.754

Table 8: Dedusting resistance variance analysis.
Square ofFactorDeviance
Fiber Diameter
45.9704
Spray Distance
1
2
3
3
1
2
2
3
1
61.35762.73361.7771.376

Degree ofFreedom2

Experimental
Condition
A1B1C1D1
A1B2C2D2
A1B3C3D3
A2B1C2D3
A2B2C3D1
A2B3C1D2
A3B1C3D2
A3B2C1D3
A3B3C2D1

F Ratio

F Critical-value

Experimental
Result
33.15
60.37
83.83
56.63
81.66
48.02
79.81
44.87
69.26

Significance15.39019.000Spray Water Volume166.1192

55.61419.000＊Grid Board Number

2370.569

2

793.629

19.000＊Spray Distance
Error

2.978
2.99

2
2

1.000

19.000Dedusting Resistance(Pa)Dedusting Resistance(Pa)

70
65
60
55
50
0.22

0.24
0.26
0.28
A Fiber Diameter(mm)

0.3

90
80
70
60
50
40
30
0

1
2
3
C Grid Board Number(piece)

4

Dedusting Resistance(Pa)abscissa is the actual level and ordinate is the averagededusting resistance, as shown in Figure 7.

Dedusting Resistance(Pa)Draw graphs of fiber diameter, spray water
volume, grid board number, and spray distance. The

70
65
60
55
50
0.9

1.1
1.3
1.5
1.7
B Spray Water Volume(L/min)

1.9

8

10

22

70
65
60
55
50
12
14
16
18
D Spray Distance(cm)20

Figure 7: Factors affecting dedusting resistance analysis of the orthogonal experiment.

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The significant analysis shows that the factors
affecting the dedusting effect order are as follows:
grid board number, spray water volume, fiber
diameter, and spray distance.
3) Determine the optimal level combination
The optimal level is the highest total level of thefour factors’ optimal level. It can be obtained from
Tables 5 and 7 that the optimal combination is when
the fiber diameter is 0.23 mm, spray water volume is1.67 L/min, grid board number is 3 and spraydistance is 20 cm (A1B3C3D3), the dedusting
efficiency is 78.0%, and the dedusting resistance is
83.83 Pa.
It can be seen from Figures 6 and 7 that the
combination of A3B3C2D1 might be called the best
combination. Its dedusting efficiency is 77.3% anddedusting resistance is 69.26 Pa. Compared withcombination A1B3C3D3, combination A3B3C2D1
has lower dedusting efficiency, but its dedusting
resistance is also smaller, thus it can be obtained thatthe wet high frequency vibrating grid dedusting
optimal combination of parameters is that thevibrating grid fiber diameter is 0.29 mm, the spraywater volume is 1.67 L/min, the grid board number is2, and the spray distance is 10 cm, namely
A3B3C2D1.
4.

CONCLUSION

In the orthogonal experiment of the vibrating
grid, the influence factors on the dedusting effect are
ranked as follows: grid board number, fiber diameter,and parallel number. Therefore, we select grid board
number and fiber diameter as the integrated
optimization orthogonal experiment factors. Firstly,
grid board should be used more in the system inconsideration with dedusting resistance, economic
costs and other factors. Secondly, fine fiber diameteris supposed to be avoided according to the materialand costs.
In the orthogonal experiment of spray dedusting,the influence factors on the dedusting effect are
ranked as follows: spraying rate, the distance ofspray, and the angle of nozzle. We select the first two
factors as the integrated optimization orthogonal
experiment factors. Firstly, spraying rate is supposed
to be increased in consideration of dedusting
resistance and costs. Secondly, at a distance of 15 cm
between the spray and grid board the performance isbest. In practice, the actual distance can bemagnified.
We obtain four factors used by a comprehensive
optimization
experimentthroughprevious
experiments. Their dust removal effect rankings are
as follows: grid board number, fiber diameter,
spraying rate, and the distance of spray. By analyzing
the combination of parameters, we conclude that the

optimal combination of wet high-frequency vibrating
grid parameter values are: 0.29 mm (vibrating wire
grid fiber diameter), 1.67 L/min (spraying rate), 2(grid board number), and 10 cm (distance of spray).

5. ACKNOWLEDGEMENT
It is with great pleasure that we acknowledge thegenerous financial support of National Natural
Science Foundation of China (project number:
51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).

6. REFERENCES
Chen, Y.H. (2013), Experiment on charged fog
dedusting technology. Modern Mining, Volume 8, pp.
105-106.
Dong, W.Y. (2014), China coal mine dust
control technology status and prospects. Science andTechnology Information, Volume 4, pp. 225-227.
Liu, Y.B., Bai, Y.H. and Hou, J.G. (2011).
Talking about the development of fully mechanizedsublevel caving and the existing problems andcountermeasures. Coal Mine Safety, Volume 06, pp.
160-162.
Li, Y.C., Zhang, Y.H. and Xiong, S.S. (2011),
Study on dedusting technology with high-pressure
atomizing and vibrating fiber grid. Nonferrous Metals(Mining Section), Volume 1, pp. 58-61.
Song, J.G. (2010), High pressurized external
spraying dust control technology of fully mechanizedcoal mining face and applied research. CoalEngineering, Volume 10, pp. 43-45.
Shi, X.X. (2005), Current development and dust
control technology research of fully mechanized coalfaces. Journal of Safety Science and Technology,
Volume 1, No. 1, pp. 41-43.
Wang, H.Q. (2010), Coal mine dust and removal
technology and optimization of existing. Yunnan
Vocational Institute of Energy Technology, Volume
24, pp. 26-28.

275

ISMS 2016

Paper No. 107

Borehole docking system design for underground refuge chamber and groundmaneuver rescue equipment
ZHANG Ying-hua, SONG Shou-yi, HUANG Zhi-an*, GAO Yu-kun
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing 100083, China

ABSTRACT
In order to target the problems of poor and low efficiency that arise during the borehole docking process of groundequipment and refuge chamber in emergency refuge system, this study presents a borehole docking system designed
for ground maneuver rescue equipment. The system includes three parts: the hole docking device and orificedocking device and docking fixation device. The bottom hole docking device is inside the refuge chamber which isdesigned for three lines: the food transmission pipe, air pressure pipe, and power and signal transmission line. The
orifice docking device is mainly for fast docking of ground equipment and emergency rescue vehicles, and theexternal protection sealing device is designed to the protect orifice docking device from harsh outdoor
environments. The docking fixation device is the connecting fastening core of the borehole docking device and is
responsible for safeguarding system functions such as air pressure, power transmission, and food supply. Field test
results show that the system runs well after the docking of emergency rescue vehicle and refuge chamber. Air
pressure, water supply, and power transmission run smoothly. The operation of monitoring, control, and personnel
positioning systems is normal. The borehole docking system met the needs of the refuge chamber. It enhanced theflexibility and economy of the mine refuge facility.
KEYWORDS: emergency refuge system; refuge chamber; borehole docking system
1.

INTRODUCTION

The establishment of an emergency refuge
system is an effective guarantee of mine safe
production. As the main part of the coal mine safety
facilities, the borehole type refuge chamber has theadvantage of having high security and no limit torefuge time (Sun, H., 2014). At present, the groundsupporting facilities of borehole type permanent
refuge chambers are mostly the control rooms. A
large number of necessities and rescue equipment are
stored in the ground control room, which has led tothe high cost of its construction and maintenance.
This limits the application of the borehole type refugechamber (Han et al., 2011; Wang et al., 2011).
Therefore, the development of ground maneuver
rescue equipment which is suited for undergroundemergency rescue systems came into being. The
ground maneuver rescue equipment matched withborehole type refuge chambers can provide groundemergency rescue for the underground refugechamber (Ni and Yao, 2014). The current designs ofborehole docking systems for ground maneuver
rescue equipment are not perfect, therefore, it isnecessary to design a new borehole docking system.
On the basis of the original borehole of the
refuge chamber, the present study describes thedesign of a new kind of borehole docking system forthe ground maneuver rescue equipment. The system*Corresponding author – email : huang_za@qq.com

mainly includes three parts, including the bottom
hole docking device, orifice docking device, anddocking fixation device.

2. BOTTOM HOLE DOCKING DEVICE
The bottom hole docking device is placed insidethe underground refuge chamber and connected withthe upper orifice docking device. The upper andlower parts are connected with quick connectors; they
can be used to convey wind, water, power, and signal.
These transmission functions and physical interfaces
are independent of each other (Hu, J., 2010).
2.1 Underground connection mode
The connection modes of the high-pressured air
hose, power cable, monitoring and control line,
shielded transmission line and food (water)transmission pipeline in the refuge chamber are
shown in Figure 1.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the rescue platform fast interface panel. The power
cable uses a dedicated transmission fast interface.
The esophageal flow path uses the threaded hosequick connector and the high-pressured air hose uses
a flange bolt connection. The concrete connection
mode of these pipelines is shown in Figure 3.

Figure 1: Diagram of underground connection mode.

2.2 Docking device configuration
The structure of the bottom hole docking device
is designed to fully take into account the principles ofsafety and reliability. Bottom hole docking is divided
into three lines. At the bottom there is liquid food(water) transmission line interfaces. Both sides arefor interfaces of a high-pressured air hose and apower cable. Their internal connections are shown in
Figure 2.

Figure 2: Design of docking device interface connection.

Transmission connections of power supply,
communication signal, monitoring, and control
signals are achieved using aviation plug fast
connections. One end of the cables connected withthe pipes is associated with underground docking
device interfaces, and the other end is connected with

Figure 3: Pipeline interfaces schematic diagram.

3. THE ORIFICE DOCKING DEVICE
The orifice docking device is mainly for fast
docking between ground equipment and emergency
rescue vehicles. It shortens the connection time
because it can help build temporary command places
quickly. The location of the orifice docking device
should be carefully considered. According to theposition of the underground refuge chamber andground environment, it should be placed in a flat,
open area. The design of protection and auxiliary
equipment should also be reasonable, easy to open,
waterproof and fireproof, with security explosionproof characteristics.
3.1 External protection sealing devices
External obturator is the establishment of an
external protective cover to protect the orificedocking device. It should be waterproof, fireproof,
and explosion-proof. At the same time it should havea protective effect on various orifice pipe interfaces
and quick connectors. The docking device should be
intact when the device is used to dock and it should
achieve the best possible effect (Zhou et al., 2013).
The design is shown in Figure 4.
In order for the external protection obturator tobetter fulfill its function, it is constructed of highstrength isolating walls as a framework for external
protective equipment. It is made up of the four
following parts:

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

from corrosion and other damage due to rain andsunlight all year around. After finishing the TPCprotective cover, a circular bottom arch is poured on
the high strength of the wall. The arch radius isconsistent with the radius of the high strength wall.
3.2 System docking device
The analog bottom hole docking device andorifice system device can be divided into three parts:
the liquid food (water) pipeline interface, highpressured air hose interface, and the power signal line
interface. Except for the intermediate part of theorifice that sets aside space for the connection, thespace is connected with the closed holder (Jin et al.,2012; Wang, 2013). The design is as shown in Figure
5.

Figure 4: Design of external protection sealing devices.

1) The foundation
External protective devices are generally locatedin flat areas, where there is small gravel and prime
soil compaction. The foundation is excavated tomake it solid and reliable, backfilled with the originalsoil, and then the ground water is treated with highgrade cement.
2) Anti-flood stage
Moisture generated by rainwater can impact all
types of electronic devices and internal pipe joints ofprotection devices. Therefore, they should be builtwith an anti-flood stage of more than 1m higher than
the flood level at the high strength isolating wall.
Meanwhile, in order to facilitate the job of rescue
workers, treads and drainage ditches need to beestablished beside the anti-flood stage.
3) High strength isolating wall
A high strength isolating wall is constructed withmasonry and concrete made of high index cement.
Orifice size is determined according to the specificconditions of each mine. The thickness of the wall isgenerally around 0.3 m, with a height of no less than
1.2 m. After the masonry wall is built to waterproof
the wall outside, waterproof coating can be brushed
in the wall, or the pasted tarpaulins approach can beused.
4) Protection door
The TPC-protective door needs to be airtight.
One side of the door should lock, as rescue personnel
need to unlock the door. Due the inaccessibility to
non-staffs, after opening the TPC-protective door,
staff can peform regular maintenance.
5) Protective coverBecause of harsh protection conditions outside,
setting the TPC-protective cover over the DPSprotection door can be more effective to protect it

Figure 5: Design of docking system device.

1) Water pipe docking(1) Liquid food transmission pipeline
One end of the liquid food delivery pipeline isconnected with the orifice docking system by screwtype quick connector; the other end is connected withthe maneuver rescue platform using D-type quickconnectors.
(2) Chamber water-rescue system switching device
When the underground water system is damaged
or the water pressure gauge displays abnormally inthe refuge chamber, and the water quality issignificantly turbid, the water rescue value can beturned on, taking advantage of the rescue platform tohelp deliver water.
2) Air pressure and oxygen supply pipeline docking(1) Gas transmission pipeline
After the mine disaster, the gas transmission
pipeline (the main source of chamber’s oxygen) is
capable of transporting a steady stream of fresh air to278

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the chamber in order to prolong the survival time of
the trapped personnel. To ensure the interface works
effectively and to extend the service life of theinterface, when not in use the interface must be
sealed with a Jacob locking plug to prevent foreign
matter entering the system to pollute the water.
(2) Oxygen self-help system switching device inchamber
When the return air system is damaged or thedraft indicator shows that the air may be mixed withpoisonous gases, and air transportation issignificantly decreased, the air pressure supply value
can be turned on, taking advantage of the rescue
platform to provide enough air to the chamber.
3) Power system docking(1) Power signal cable
The power signal cable that connects the rescue
platform with the refuge chamber has the Mining
Products Safety Approval and Certification. It has
good insulating performance, stable transmission, theexternal protective layer is waterproof, anti-wet, andhas protective ability.
Taking into account the scene of the rescuecomplex, the length of the pipeline should beappropriate, multiplied by the number of not less than
1 of the rich coefficient, in order to prepare for use.
(2) Power system switching device in chamber
Normally the power of the underground refugechamber is connected to underground circuits
through comprehensive security lines. After the mine
disaster, underground substations may be damaged
and the power ring network may not supply power
normally. The independent power supply line of the
maneuvering rescue platform will be turned on to
supply power. For operation, one must open the
power system switching device. The power
generation unit on the rescue platform will provide
power in the chamber.
4) Monitoring and control, personnel positioning,communication docking device
The device integrates all the interfaces used formonitoring and control, personnel location, andtelephone communication. Generally it is divided into
two parts: the power docking interface and signal
docking interface.
(1) Power docking interface
The power interface is provided with a fastinterface of three-phase four wire system. It can
provide 660 V, 380 V, 220 V, 127 V stable AC
power supply, and provide power for the maneuver
rescue platform and refuge chamber.
(2) Signal docking interface
The signal interface includes three kinds ofinterfaces: monitoring and control, personnel
location, and telephone communication. Theirfunctions are the establishment of the communication

between the maneuver rescue platform and theunderground refuge chamber, the real-timemonitoring of the indoor personnel, the change of theenvironment parameters. They also provide detailed
information for the field rescue.

4. DOCKING FIXATION AND OTHER
ANCILLARY DEVICES AND FIELD
TEST
4.1 Docking fixation device
The docking fixation device is the connecting
fastening core of the borehole docking device. The
device controls the oxygen pressure to the chamber,power transmission, liquid supply, monitoring andpersonnel positioning, telephone communication
function. The device is mainly composed of H steel,high strength bolts, dovetail card, wire rope, andother components. The specific layout is shown in
Figure 6.

Figure 6: Internal connection diagram of the system.

4.2 borehole docking accessory device
The accessory device of the protection of theborehole is mainly made of two kinds of surface
protective coating and outdoor rescue equipment.
1) Surface protective coating
In addition to the external orifice brushwaterproof coating, it can also be brushed with anticorrosion, rust-proof, non-toxic, anti-aging lipids
ester paint. The paint safety level is adequate tosatisfy the regulation of Standard for Hygienic Safety
Evaluation of Equipment and Protective Materials in
Drinking Water which is issued by the Ministry of
Health P. R. China. It can prevent coating due toprolonged exposure, weathering, and erosion as aresult of potential harmful ingredients from theorifice pipe into the refuge chamber.
2) Outdoor rescue equipment(1) Military tents
The standard hexagonal military tent is chosen in
outdoor rescue equipment. It is made of steel pipe279

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

frame. Its structure is simple and reliable and isquick and easy to disassemble. The tent is wind
resistant and the waterproof performance is good,with a large interior space. It has a compact structure
and a collection of special canvas bags. It can beplaced on the platform side of the toolbox, for instantaccess and long-distance transport.
(2) Explosion proof lamp
The case is made of a special aluminum alloymaterial. It can withstand strong impact, lighting
protection class up to IP66. The lamp has a turning
angle of 360°, tilt angle of 135°, and any position canbe illuminated via hand-held lamp. It has an optional
tripod, lifting in the 1.2 m to 3 m height range. The
lamp can be adjusted in height by an optional handle,
to meet the needs of various rescue work site lighting.
4.3 Field test
After connecting the emergency rescue vehicle
with orifice docking device, rescuers can clearlyobserve real-time data of refuge chamber monitoring
and control, personnel positioning and otherfacilities. At the same time, through the phone or via
video communication, the rescuers can quickly andconveniently communicate with the undergroundexperimenters. After turning on the control
mechanism, the pressure of the air, the water, and thepower supply run smoothly, meeting the design
requirement of the refuge chamber.
5.

CONCLUSIONSThe borehole docking system to connect groundmaneuvering rescue equipment with underground
refuge chambers consists of three parts: the bottom
hole docking device, orifice docking device, anddocking fixation device. The system is mainly
connected to the ground and underground for air,food (water), power, monitoring and control,
personnel positioning, communication and otherfunctions.
All components of the system have been tested
strictly in the field. The system can satisfy the needsof rapid orifice docking after underground emergency
situations. The system has a low cost, high mobility,
good compatibility, and is safe, reliable, and easy tomaintain. It improves the convenience and economyof permanent refuge chamber.
The underground docking device and orificedocking device developed for ground maneuveringrescue vehicles can connect ground supply system
and underground rescue system in a short time,
improving the rescue efficiency.

Science Foundation of China (project number:
51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).
7.

REFERENCES

GAO, N., JIN, L., WANG, L. and YOU, F.
(2011). Research and application of oxygen supply
system in Changcun Coal Mine refuge haven. Journalof China Coal Society. Volume 5, pp. 149-153
HU, J. (2010). Permanent and temporary fixedshelters construction in mining area. SHANXI Coal.
Volume 30, No. 7, pp. 71-72,82
JIN, L., ZHAO, Y., GAO, N. and WANG, L.
(2012). Research and design of permanent refugechamber in GUANGXI Dachang copper mine.
Mining Technology. Volume 12, No. 5, pp. 40-42
Ni H, Yao Y. (2014) Construction method anddevelopment tendency of mine refuge chamber. CoalEngineering, Volume 46, No. 1, pp. 12-13,17
Sun H. (2014) Research and design on ground
drilling type refuge chamber. China High TechEnterprises, No. 19, pp. 26-28
WANG, R. (2013). Design and application
analysis of large diameter rescue hole refugechamber. Zhongzhou Coal. No. 4, pp. 87-89
WANG, T., ZHAO, Y., JIANG, Y. and SONG,
Y. (2011). Design and application of underground
refuge cave in mine. Coal Mining Technology.
Volume 16, No. 4, pp. 33-36
ZHOU, J., JIANG, S., PEI, W. and ZHANG, Z.
(2013). Ground boreholes system design forpermanent refuge chamber in Xishahe Mine. Safety
in Coal Mines. Volume 44, No. 1, pp. 97-99

6. ACKNOWLEDGEMENT
It is with great pleasure that we acknowledge
the generous financial support of National Natural

280

ISMS 2016

Paper No. 108

Use of the Analytic Hierarchy Process in safety control of rescue equipment
Zhang Yinghua, Sun Qian, Huang Zhian*, Gao Yukun
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing, China, 100083

ABSTRACT
Ground maneuver rescue equipment is complex, therefore, systematic analysis and risk assessment of the rescue
equipment needs to be carried out. This evaluation method provides positive guidance and reference for the
management and maintenance of the equipment system.
At present, many countries adopt the risk matrix method to assist in decision-making about the safety control ofimportant systems. There is a relationship between the possibility and importance of the factors that influence thedevelopment of the transaction. The risk matrix method can be used to find this relationship and to stratify the data.
It also has a good effect on systems in which objective judgment is weak. The present study refers to the matureevaluation system in the field of abroad car production, combines the actual rescue situation of Fengfeng District inJizhong Energy Group, and aims to establish a subjective evaluation system with special characteristics forunderground emergency refuge systems. This evaluation system uses the method of scoring combing weightcombined with the analytic hierarchy process. It provides a scientific basis and effective reference for daily use andmaintenance of the entire system.
KEYWORDS: analytic hierarchy process; ground maneuver rescue equipment system

1. INTRODUCTION
Ground maneuver rescue equipment which
supports the emergency refuge system is complex.
During routine maintenance and rescue drills, it
requires not only that the relative rules must be
executed in installation and operation, but also thatthe unit of high weights in the system are controlled(Gao and Mu, 2000).
At present, many developed countries use therisk-matrix method for decision-making on majoraffairs and safety control of important systems. When
processing systems with large amounts of data, thismethod does not have high reliability and accuracy.
When using the risk-matrix method, the consistencyof the risk matrix should be tested (Sun and Liu,
1999). If it cannot pass the test, it should be checked
and adjusted until it has passed the test. On one hand,
this method is time-consuming and laborious; on theother hand, the consistency of the evaluation matrix
is low, due to differences in experience andunderstanding of evaluation personnel (Hartman,2002).
To solve these problems, this study refers to themature evaluation system of the field of abroad car
production, combines the actual rescue situation of
Fengfeng District in Jizhong Energy Group, andattempts to establish a subjective evaluation systemwith consideration for the special characteristics ofunderground emergency refuge systems. Thisevaluation system uses the method of scoring*Corresponding author – email : huang_za@qq.com

combing weight combined with the analytic
hierarchy process. Through the evaluation of
personnel subjective scores on the factors that
influence the criterion layer, the weight of the safetycontrol index and the total score are concluded(Zhang, 2000). Lastly, the validity and necessity of
AHP application will be proven through the computerconsistency test and adjustment. This evaluation
system assesses the safety status of maneuver rescue
equipment systems objectively, and identifies risks
and vulnerabilities. It can reduce the difference ofconsistency between the evaluation matrixes andthought of judges, propose the orientation of thesafety control, and provide a scientific basis andeffective reference for daily use and maintenance ofthe entire system. This method can evaluate theprotection focus of maneuver rescue equipment
systems effectively, and have a positive effect onsafety management of the entire system.

2. ANALYTIC HIERARCHY PROCESSThe analytic hierarchy process divides all kindsof factors which affect the decision-making
objectives into target layer, criterion layer, andscheme layer. Through the interaction between thelevels, the weight of each factor to the target levelcan be determined qualitatively and quantitatively, inorder to help the decision makers to make theappropriate decision (Chen and Crolla, 1996).

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

First, the AHP lists the factors that affect thetarget, and sets them into different levels according to
the logic of the relationship between them. Second, itbuilds a hierarchical model according to the degree ofmembership between different levels. Then it
determines the ranking from the bottom layer
combing the subjective judgment and themathematical method of the evaluation personnel.
Finally, according to the calculated weight factor, it
determines the impact of the target level and can
assist decision makers to judge the planning (Jing etal., 2006).
After the establishment of the matrix, it should
be judged by a consistency test to determine whether
it is reasonable or not. If it passes the verification, theevaluation system meets the requirements. If it did
not pass the verification, the judgment factor should
be checked and adjusted, so that it can be inaccordance with the logical relationship of themathematical judgment. After the consistency test of

the criteria layer, the consistency between the levelsof the hierarchical model is tested (Guo et al., 2008a).

3. ESTABLISHMENTOFFUZZYEVALUATION INDEX SYSTEM FORRESCUE EQUIPMENT SYSTEMS
3.1 Hierarchical structure model
The influence factors on the safety and stabilityof the ground maneuver rescue equipment system aremany, so it is necessary to take comprehensive
consideration, combine the evaluation of individual
performance index, and make a reasonable summary
before establishing the AHP hierarchy model (Guo etal., 2008b). Referring to the mature evaluation
system in the field of abroad car production (Xu etal., 2009), and combining the actual rescue situationof Fengfeng District in Jizhong Energy Group, ahierarchical structure model was established, as
shown in Figure 1.

Figure 1: Hierarchical structure model of the ground maneuver rescue equipment system.

3.2 Scoring the scheme layer
Referring to the mature evaluation system ofSociety of Automotive Engineers, and combining theactual rescue situation (Fan et al., 2004), the scheme
layer is scored by percentile system. With 5 points asa file, the higher the score, the more important it is.
Specific scoring is as follows: C1=70, C2=75, C3=75,

C4=80, C5=85, C6=75, C7=85, C8=80, C9=80, C10=80,
C11=75, C12=80, C13=90, C14=85, C15=80, C16=85,
C17=85, C18=85, C19=85, C20=85, C21=90, C22=80,
C23=80, C24=85, C25=80, C26=75, C27=80, C28=80,
C29=80, C30=75, C31=80, C32=70, C33=80, C34=70,
C35=70, C36=80, C37=80.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3.3 Establishing judgment matrix
According to the above data, five evaluation
personnel establish the pairwise comparison matrix,
the comparison matrix values are as follows.
Safety stability:
A1/A2=1/4, A1/A3=1/3, A1/A4=2, A2/A3=1,
A2/A4=3, A3/A4=3;
Platform base:
B2/B3=1/2, B2/B1=1/2, B3/B1=2;
Equipment system:
B5/B6=1/4, B5/B4=1/3, B5/B7=2, B6/B4=1,
B6/B7=3, B4/B7=3;
Hoisting system:
B10/B11=3, B10/B9=1/2, B10/B8=1/2, B11/B9=1/3,
B11/B8=1/3, B9/B8=3;
Drilling system:
B13/B12=2, B13/B15=3, B13/B14=4, B12/B15=3,
B12/B14=2, B15/B14=2;
Vehicle chassis: C1/C2=1/2, C2/C3=3;
Equipment selection:
C4/C6=2, C4/C5=1, C6/C5=1/2;
Air supply system: C9/C10=3;
Water rescue system: C11/C12=1/2;
Power supply system:
C14/C13=1, C14/C15=1/2, C13/C15=1/2;
Control monitoring system:
C19/C18=1, C19/C20=1/2, C19/C17=2, C19/C16=2,
C19/C21=1/2, C18/C20=1/2, C18/C17=1/2, C18/C16=1/2,
C18/C21=1/2, C20/C17=1, C20/C16=1/2, C20/C21=1/3,
C17/C16=1/2, C17/C21=1/2, C16/C21=1/2;
Power unit: C22/C23=1;
Telescopic mechanism: C25/C24=1/3;
Control unit: C27/C26=1;
Assistant system: C29/C28=2;
Bottom hole docking device:
C31/C30=2;
Orifice docking device: C32/C33=1/2;
Other ancillary facilities: C34/C35=2;
Docking fixation device: C37/C36=2.

4. SYSTEM APPLICATION BASED ON
THE ANALYTIC HIERARCHY PROCESSFirst, the hierarchical structure is drawn asshown in Figure 1.
Secondly, the judgment matrix of all levels
should be assigned with values, and the consistency
should be tested to ensure that the calculated value ofthe judgment matrix is less than 0.1. The consistencyof the combination weight vector is also tested toensure the level of comparative judgment.. When the
judgment matrix is not consistent, it is reasonable tocarry out inspection and make adjustments.
Software can sort the weight of the scheme layer
and other layers quickly and facilitate the follow-up
studies. The weight value of each factor is as follows:

C1=0.0101, C2=0.0232, C3=0.0088, C4=0.0106,
C5=0.0106, C6=0.0053, C7=0.0501, C8=0.0167,
C9=0.0549, C10=0.0198, C11=0.0169, C12=0.0337,
C13=0.0111, C14=0.0111, C15=0.0223, C16=0.0387,
C17=0.0274, C18=0.0217, C19=0.0345, C20=0.0322,
C21=0.0657, C22=0.0473, C23=0.0473, C24=0.1228,
C25=0.0409, C26=0.0370, C27=0.0370, C28=0.0116,
C29=0.0232, C30=0.0096, C31=0.0192, C32=0.0161,
C33=0.0322, C34=0.0073, C35=0.0036, C36=0.0100,
C37=0.0050.

5. ANALYZINGRESULTSOF
THE
ANALYTIC HIERARCHY PROCESS
5.1 Analyzing the scheme layer
By comparing the above results, it can be foundthat the weight value has the following rules:
C24>C21>C9>C7>C22>C23>C25>C16>C26>C27>C19>C12>C20>C33>C17>C2>C29>C15>C18>C10>C31>C11>C
8>C32>C28>C13>C14>C4>C5>C1>C36>C30>C3>C34.
It can be concluded that the telescopic arm,
telephone communication system, air compressor,
load distribution, and power transmission have more
influence on security and stability of the system.
Therefore, they should be a main focus of the design,use, and maintenance process. When analyzing thefactors with higher weights, it can be found that thesefactors will directly affect the security and stability of
the whole system.
5.2 Analyzing the criterion layer
The score of each criterion layer can becalculated by combining with the index weight
coefficient of the target layer and the subjective
evaluation of each criterion. For example, factors of
the criterion layer related to platform base A1 are load
C1, car body space C2, chassis pass C3, weight C4,
volume C5, maintenance economy C6, load
distribution C7, space utilization C8. The weight
coefficient of each index is 0.0101, 0.0232, 0.0088,
0.0106, 0.0106, 0.0053, 0.0501, 0.0167. Then thescore of platform based A1 is: 0.0101 × 70 + 0.0232 ×
75 + 0.0088 × 75 + 0.0106 × 80 + 0.0106 × 85 +0.0053 × 75 + 0.0501 × 85 + 0.0167 × 80 = 10.848.
In the same way, the total score of otherindicators can be calculated, as shown in Table 1.
Table 1: The score of criterion layer.
criterion layer
Platform base A1
Equipment system A2
Hoisting system A3

score
10.84833.072
29,797

Drilling system A4

7.922

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

From Table 1, it can be seen that the equipment
system A2 and the hoisting system A3 are more
important for the safety and stability of the wholesystem. The influence factors are two times morethan the influence of the platform base A1 anddrilling system A4.
The score of equipment system A2 is slightly
higher than the score of hoisting system A3. It isnecessary to strengthen the daily safety management
and control of the equipment system and hoisting
system. Although the score of platform base A1 anddrilling system A4 is not high, the key factors
affecting the system also need to strengthen theirsafety management and control.

6. CONCLUSIONSAt present, there is no specific evaluation system
for ground maneuver rescue equipment. Referring to
the mature evaluation system of the field of abroad
car production combined with the actual rescue
situation of Fengfeng District in Jizhong Energy
Group, this study established a subjective evaluation
system with consideration for the special
characteristics of underground emergency refuge
systems.
In order to minimize the subjective uncertainty,
this evaluation used the method of scoring combing
weight combined with analytic hierarchy process.
Through the evaluation of personnel subjective scoreon the factors that influence the criterion layer, theweight of the safety control index and the total score
were found.
The validity and necessity of AHP application
will be proven through a consistency test of computerand adjustment. This evaluation system objectively
assesses the safety status of maneuver rescue
equipment systems and identifies risks andvulnerabilities. It can reduce inconsistencies between
the evaluation matrixes and thought of judges.
Through comprehensive consideration of theresults of the evaluation test results and the weight
coefficient of the ground mobile rescue equipment
system, this study proposes the orientation of thesafety control, and provides a scientific basis andeffective reference for daily use and maintenance ofthe entire system.

8. REFERENCES
Chen, D.C. and Crolla D A.A. (1996)
Comprehensive study of subjective and objective
vehicle handling behavior. Vehicle System
Dynamics. Volume 25, No. 1, pp. 66-68.
Fan, X.Y., Qiao, J.P. and Chen, Y.B. (2004)
Application of analytic hierarchy process inassessment of typical landslide danger degree.
Journal of Natural Disasters. Volume 13, No. 1, pp.
72-76.
Gao, Y. and Mu, D.Y. (2000) AHP method in
assessment of airline safety. China Safety Science
Journal. Volume 10, No. 3, pp. 38-41.
Guo, J.Y., Zhang, Z.B. and Sun, Q.Y. (2008)
Study and applications of analytic hierarchy process.
China Safety Science Journal. Volume 18, No. 5, pp.
147-153.
Guo, J.Y., Zhang, Z.B., Sun, Q.Y. (2008)
Applications of AHP method in safety science.
Journal of Safety Science and Technology. Volume 4,
No. 15, pp. 69-73.
Hartman D. (2002) Application of the analytic
hierarchy process to select characterization and riskbased decision-making and management methods forhazardous waste sites. Environmental Engineeringand Policy. Volume 3, No. 1-2, pp. 1-7.
Jing, Q.Z., Jiang, X.H., Yang, J.S. and Zhou,
Y.F. (2006) Study on index system of capability of
production safety in coal mine based on AHP. China
Safety Science Journal. Volume 16, No. 9, pp. 74-79.
Sun, R.S. and Liu, H.H. (1999) Assessment
theory and practice for airline safety. China Safety
Science Journal. Volume 9, No. 3, pp. 69-74.
Xu, Y., Zhou, Y., Sun, X. and Yu, Y. (2009)
Synthesized assessment method for coal mine safety
based on fuzzy analytic hierarchy process. China
Safety Science Journal. Volume 19, No. 5, pp. 147152.
Zhang, J.J. (2000) Fuzzy analytical hierarchy
process. Fuzzy System and Mathematics. Volume 14,
No. 2, pp. 80-88.

7. ACKNOWLEDGEMENT
It is with great pleasure that we acknowledge thegenerous financial support of National Natural
Science Foundation of China (project number:
51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).

284

ISMS 2016

Paper No. 109

Research on new high-water solidified materials to reinforce coal andeliminate gas outburst
Yinghua Zhang, Peiling Zhou, Zhian Huang*, Yukun Gao, Qiang Luo
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines(University of Science and Technology Beijing),
Ministry of Education, Beijing, China, 100083

ABSTRACTAs coal and gas outburst is one of the main mine disasters, it is very important to prevent and eliminate the coal andgas outburst. Grouting setting liquid into coal can strengthen the coal seam, increase rigidity coefficient (f), andreduce expansion energy of gas. According to the related experimental procedures of cement paste, experiments on
the performance of complex materials that high-water material added with different admixtures were carried out.
Results showed that: as the increase of water-cement ratio (W/C), the mobility and setting time were all increased,
but compressive strength and rupture strength were declined, furthermore, high-water material showed earlystrength, which can reach 80% of 14 days compressive strength when it is 7 days. As a rapid setting and earlystrength cement, Na2SiO3 had the best effects on shortening setting time, when dosage was 3% , the initial setting
time and the final setting time were 13min and 21min shorter than blank samples, while the compressive strength
increased more than 2 times. As retarder, the initial setting time can extend to 83min when compounding withtartaric acid of dosage of 0.4%. Through the orthogonal experiment the best additive ratio was determined, which
was W/C=2, tartaric acid with dosage of 0.2%, Na2SiO3 with dosage of 3%, bentonite with dosage of 12%.
Reinforcement simulation experiment showed that, grouting radius of new setting liquid was 250mm when grouting
pressure was 60KPa, 7d rupture strength and compressive strength were 5.2MPa and 6.4MPa, and were 37% and 88%
higher than ordinary high water material, which was effective for reinforcing coal and eliminating gas outburst.
Key words: gas outburst; setting liquid; reinforce coal; high-water solidified materials; rapid setting and earlystrength cement, retarder

1.

INTRODUCTION

Gas outburst is one of the natural disasters thatthreaten the safety of coal mine (Qin, B.T. et al.,2013). Forming coal sample simulation results
showed that, the stress and gas pressure was thepower of gas outburst, and the strength of coal was
the resistance, thus, gas outburst can be prevented byreinforcing the strength of coal(Yong, Q.L. et al.,2005; Zhu, J.K., 2011; Fu, J.H. et al., 2009).
Reinforcing coal and eliminating gas outburst isthat grouting setting liquid into coal, which caninfiltrate into the space of the coal and reinforce thecoal (Gao, G.F., 2006). The study of grouting setting
liquid by domestic and foreign scholars showed thatsetting liquid has effective effects on prevention ofgas outbursts, the lower of its permeability and thegreater of its consolidation strength, the better of its
effects (Anon et al., 2006; Huang, Z.A. et al., 2010).
High water material is a new type of special cement
mixed material, whose water cement ratio can be as
high as 3:1, and have the characteristics of goodliquidity, good permeability, high strength, andadjustable performance parameters (Jiang, X.H. et al.,*Corresponding author – email : huang_za@qq.com

2010; Lu, L.C., et al., 2005; Yan, Z.P. et al., 2006).
Elimination of high water material setting liquid forgas outburst has been demonstrated by experiments
and filed experiments by Zhang C.Y. and Xiao P.C.
et al., and after handling of setting liquid, f of coalseam was highly increased and ΔP was decreased
from 35.5 to 2 (Zhang, Y.H. et al., 2003; Feng, G.M.
et al., 2011). Whatever, elimination effects of gas
outburst is still not ideal, and high water material has
the characteristics of adjustable performance,
therefore, a new type of high water material can beresearched by compounding with admixtures, which
can improve the efficiency of elimination of gas
outbursts.

2.

MECHANISM OF REINFORCING COALAND ELIMINATING OUTBURST

When grouting setting liquid into coal, on the
one hand setting liquid infiltrate into the space of thecoal, and free gas, partially adsorbed gas is driven outof the grouting coal seam, on the other hand setting
liquid and coal is cemented together, which close thepassage of gas desorption. At the same times, the3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

NEW HIGH-WATER SOLIDFIED
MATERIALS TO ELIMINATEOUTBURSTThe key of the method of reinforcing coal andeliminating gas outburst is the development of setting
liquid. To conform to the special environment of coalmine and the requirements of grouting, the setting
liquid must be low viscosity, good fluidity and canenter tiny pores. High water material is a new type of
special cement mixed material, which is constitutedof A component and B component, A component issulphate-aluminate cement clinker and B component
consists of gesso and lime. Powder material of A
component and B component mixed with water
respectively, then rapid setting and solidify throughphysical and chemical reactions (Cha, J. et al., 2010).
3.1 Experimental materials
Sulphate-aluminate cement clinker, deflocculant;
retarder (calcium lignosulfonate and tartaric acid),
rapid setting and early strength cement (sodium
silicate, triethanolamine, sodium chloride and sodium
aluminate), coal powder et al..
3.2 Methods and Instruments
Refer to the cement testing procedures andstandards, make experiments on mobility, viscosity,
syneresis rate, stability, setting time, compressive
strength, tensile strength. Main instruments: NJ-160B
cement paste mixer, NDJ-5S digital rotary
viscosimeter, setting time standards detector,
40mm×40mm×160mm testing module, digital
hydraulic pressure testing machine, HBY-40B
standard curing box, et al..
3.3 Results and discussion
1) Effects of water cement ratio（W/C） on theproperties of high water material
The W/C of high water material can be as highas 3:1, which has effects on mobility and earlystrength. High water materials when W/C=1.0, 1.5, 2,
2.5, 3 were prepared respectively, among them theratio of A component and B component was 1:1,
researching on the viscosity and setting time of thesetting liquid, the results were shown as Table 1.
It can be seen from Table 1 that: As the increaseof W/C of A component and B component, viscosity
was decreased, and setting time was increased, final
setting time when W/C=3.0 was 4 times of W/C=2.5,
the increase of final setting time was larger than the

Table 1: Effects of W/C on viscosity and setting time
Viscosity
Setting time
Final
InitialA
B
W/C
settingsettingcomponent
componenttime /
time // 𝑚𝑃𝑎 ∙ 𝑠
/ 𝑚𝑃𝑎 ∙ 𝑠
min
min
1.0
817
502
17
24
1.5
60
464
25
50
2
15
316
30
56
2.5
12
86
43
70
3.0
15
50
100
240

Weighed a certain amount of A component and
B component, and the ratio was 1:1, mixed withbentonite whose dosage was 10% to improve stability,
poured into the blender, then, make testing module
for the experiments.
6(a)Rupture strentgh of 7 day
Rupture strentgh of 14 day

5

Rupture strentgh/MPa

3.

initial setting time. Hence, as the increase of W/C,
the mobility was increased, but the increasing ofsetting time too much was not conducive to grouting.
The following study focused on the strength ofdifferent W/C.

4
3
2
1
0

0.5

1.0

1.5

2.0

2.5

3.0

W/C
18

(b)
15

Compressive strength/MPa

water prolapsed by solidification enter small pores,
closing gas desorption passage with capillary force,
which made the free gas cannot be formed by theadsorption gas, reducing the amount of gas involved
and decreasing gas desorption rate (Xiao, P.C., 1994;
Wu, Q. et al., 2010; Zhang, C., 2014).

Compressive strength of 7 day
Compressive strength of 14 day

12
9
6
3
0

0.5

1.0

1.5

2.0

2.5

3.0

W/C

Figure 1: Strength of 7 day and 14 day under
different W/C(a) Rupture strength; (b) Compressive strength

As shown in Figure 1, compressive strength andrupture strength declined as W/C increased, 14 daycompressive strength was 17.51MPa and 14 day
rupture strength was 6.05Mpa when W/C=0.5, but 14
day compressive strength and 14 day rupture strength286

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

reduced the maximum and liquid with Na2SiO3
reduced minimum. Therefore, the setting liquid with
Na2SiO3 has big early strength and changed little over
time.
60

60

50

50

40

40

30

30

20

20

10

None

Na2SiO3 Compound1 Compound2

NaAlO2

Final setting time/ min

Initial setting time
Final setting time
Initial setting time/ min

was less than 1MPa. 14 day compressive strength andrupture strength were almost close to 7 daycompressive strength and rupture strength, indicatingthat high water material had the character of earlystrength, the strength of 7 day had reach 80% of 14day, this performance is very good for dealing withurgent situations.
2) Influence of rapid setting and early strength
cement on the high water material
High
water
materialwithadjustableperformance, therefore, the better performancesetting liquid can be obtained by compounding with
admixture. When W/C=2.5, bentonite dosage is 12%,
adding rapid setting and early strength cement to thehigh water material, then, studied on the properties ofsetting liquid. The species and dosage of rapid setting
and early strength cement was shown in Figure 2.

10Species of rapid setting and early strength cement

Figure 3: The effects of rapid setting and early strength
cement on setting time

0.8

0.54MPa

1.2(a)0.68MPa

Compound1
Compound2
NaALO2

0.43MPa

None
Na2SiO3

0.4

1d

7d
Days of rupture strength

2.0

None

1.6

Compound2
NaAlO2

0.93MPa

1.2

14d

Compund1

Na2SiO3(b)

1.04MPa

0.0

1.01MPa

Rupture strength/MPa

It can be seen from Figure 3 that setting time
was decreased obviously when there was rapid
setting and early strength cement. Among the rapid
setting and early strength cements, Na2SiO3 that
dosage was 3% had the biggest influence on initial
setting time, initial setting time of the setting liquidwith Na2SiO3 was 17min, which was 13min shorter
than the blank sample. The greatest impact on the
final setting time was that liquid with NaAlO2, which
was 24min shorter than the blank sample. As theincrease dosage of compound, setting time wasdeclined but changed a little.Not only the setting timechanged but also the solidification strength, when
adding rapid setting and early strength cement.
Compressive strength and rupture strength were used
to represent the mechanical strength of grout stone, as
shown in Figure 4, the strength were all increased
when added rapid setting and early strength cement.
(1) From the aspect of rupture strength, thestrength of setting liquid with Na2SiO3 was biggest
each period, rupture strength of 14 day was 0.68MPa
higher than blank sample. For the same sample, 7 day
rupture strength was the biggest, because of theevaporation of water, 14 day rupture strength was
decreased, among them, liquid with compound

1.6

Compressive strength/MPa

Figure 2: Species and dosage of rapid setting and earlystrength cement(2) From the aspect of compressive strength, it
was increased as time increased. Compressive
strength was increased after adding rapid setting andearly strength cement, the most obviously was
Na2SiO3, whose 1 day strength was 1.58MPa and was
2.4 times of blank sample (0.65MPa), 7 day and 14
day strength was the biggest too. The 14 daycompressive strength of setting liquid with NaAlO2
was 1.64MPa, which was small than that with
Na2SiO3.

0.8
0.4
0.0

1d

7d

14d

Days of compressive strength

Figure 4: The effects of rapid setting andearly strength cement on compressive
strength and rupture strength(a) Rupture strength; (b) Compressive strength287

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 2: Influence of retarder on the high water material
RetarderInitialsettingtime/ minFinalsettingtime/min

0.25

35

59

0.35

41

62

0.45

58

135

Tartaric acid

0.2

43

78

Tartaric acid

0.3

67

105

Tartaric acid

0.4

119

167

Name
Calcium
lignosulfonate
Calcium
lignosulfonate
Calcium
lignosulfonate

Dosage（%）

In addition, compounding with retarderinfluenced the mobility of the liquid. As shown in
Figure 5, mobility was increased obviously, theincreasing effects of tartaric acid was bigger thancalcium lignosulfonate. As the increase of the dosageof retarder the mobility increased. The mobility canbe 410mm when the dosage of tartaric acid was 0.4%,
which was 1.4 times of blank sample, when the
dosage of calcium lignosulfonate was 0.45%, themobility of the liquid was 1.2 times of blank sample.
Because of high water material is in the range ofeasy setting, thus, if mobility is the reference
standard, then, tartaric acid will be the best retarder.
Above all, W/C, rapid setting and early strength
cement and retarder were the factor influence the

450
400
350
300

Mobility/ mm3) Influence of retarder on the high water
materia
The early strength of high water material asincreased after compounding with rapid setting andearly strength cement, nevertheless, the mobility of
the liquid was declined, and setting time decreased
too much, which was not conducive to thepenetration in coal. On the other hand, mobility andsetting time can be adjusted through mixing withretarder.
In this work, calcium lignosulfonate and tartaricacid was used as retarder, Table 2 depicted thatsetting time increased as the increase of dosage ofretarder. The effects of tartaric acid on the setting
time was relatively large, the initial setting time of
calcium lignosulfonate when dosage was 0.2% wasclose to that tartaric acid that dosage was 0.2%.
When the dosage of tartaric acid was 0.2%, the initial
setting time was 118min and final setting time was
167min, which were 83min and 108min longer thanthat of blank sample respectively.

performance of setting liquid. Ultimately, the best
composition was determined by multi factor
orthogonal experiment, which was W/C=2:1, retarder
was tartaric acid whose dosage was 0.2%, rapid
setting and early strength cement was Na2SiO3 whose
dosage was 3%, bentonite dosage was 12%.

250
200
150
100

Tartaric acid
Calcium lignosulphonate50
00.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45
Dosage/ %Figure 5: Effects of retarder on mobility of high water
material

4.

COAL REINFORCEMENTEXPERIMENTIn order to study the effects of grouting setting
liquid, grouting process was simulated in the lab, theexperiment model as Figure 6. Firstly, particle size ofcoal particles was selected, which were more than
2mm and less than 5mm, secondly, grouting new
setting liquid on the coal. The grouting effect were
showed in Figure 7.

Figure 6: Grouting simulation experiment model

From the simulation experiment can be drawn
that, dispersed particles were bonded together
effectively by new setting liquid, and the strength
was great. The grouting radius was 250mm whengrouting pressure was 60KPa, which indicated thatthe new setting liquid had good adhesion andpermeability.
Testing the strength of solidified body, rupture
strength and compressive strength were showed as
Figure 8. From Figure 8 we can see that the 1d, 7d,
14d strength of new setting liquid all have increased,
7d rupture strength and compressive strength were288

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

5.2MPa and 6.4MPa respectively, and wererespectively 37% and 88% higher than ordinary highwater material.

Figure 7: Grouting effect picture
7
New high-water solidified materials
High-water solidified materials

6

Rupture strength/MPa

5.2

37%

5
4

(a)
4.6

3.8

3.8
2.9

3
2

Na2SiO3 of dosage of 3%, initial setting time can beshortened by 13min, 14d rupture strength andcompressive strength were increased by 0.68MPa
and1.04MPa.
(3) Setting time and mobility can be adjusted byretarder, as a retarder tartaric acid had significant
influence on the setting liquid. The initial setting timeof tartaric acid that dosage was 0.2% was equal tothat calcium lignosulfonate that dosage was 0.35%,
the initial setting time and final setting time wereextended 83min and 108min. When the dosage oftartaric acid was 4%, the mobility of setting liquid
was 410mm, which was increased by 31%.
(4) Finally, the best ratio was: W/C=2, tartaricacid with dosage of 0.2%, Na2SiO3 with dosage of
3%, bentonite with dosage of 12%.
(5) Reinforcement simulation experiment of the
new setting liquid showed that, grouting radius was
250mm when grouting pressure was 60KPa, 7d
rupture strength and compressive strength were5.2MPa and 6.4MPa respectively. The new highwater solidified materials with high strength and highfluidity was effective for the reinforce coal andeliminate gas outburst.

2

6.

ACKNOWLEDGEMENT

1
0

1 day

7 day
Days of rupture strength

14 day8Compressive strength/MPa

7

New high-water solidified materials
High-water solidified materials
6.4

6

7.3

(b)

88%

5
4.7

4.1

4
3

3.4
2.3

2
1
0

1 day

7 day
Days of compressive strength

14 dayFigure8: Strength of coal dealing with new setting liquid(a) Rupture strength; (b) Compressive strength5.

It is with great pleasure that we acknowledge thegenerous financial support of National Natural
Science Foundation of China (project number:
51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).

CONCLUSIONS(1) As W/C of high water materials increased,setting time increased, viscosity declined and strength
declined too. When W/C=0.5, 14d compressive
strength was 17.51MPa, rupture strength was
6.06MPa, nevertheless, 14d compressive strength andrupture strength were less than 1MPa when W/C=3.0.
(2) While high water material mixed withdifferent rapid setting and early strength cement,
which has the most obviously changing effects was
Na2SiO3. When setting liquid compound with

7.

REFERENCES

Anon. (2006). Self-consolidation grout. Masonry
Construction the World of Masonry. Volume 19, No.
1, pp. 30-34
Cha, J., Li, S.K., Li, J.H. (2010). Study on the
durability of super early strength concrete. Journal of
Wuhan University of Technology. Volume 32, No. 7,
pp. 48-50
Fu, J.H., Chen, Y.P. (2007). The status andcontrol countermeasures of coal and gas outburst incoal mine in China. Journal of Mining and Safety
Engineering. Volume 24, No. 3, pp. 1253-259
Feng, G.M., Jia, K.J., Li, F.K. (2011). Researchon the control of open backfill mining with ultra highwater materials. Journal of China University of
Mining and Technology. Volume 40, No. 6, pp. 841845
Gao, G.F. (2006). Status and related problems ofcoal gas outburst mechanism. Industrial Safety andEnvironmental Protection. Volume 32, No. 12, pp.
36-38

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Huang, Z.A., Li, Y.F., Zhang, Y.H., Gao, Y.K.,
Chen, S.G. (2010). New grouting material toreinforce coal and eliminate outburst. Journal of
University of Science and Technology Beijing.
Volume 32, No. 7, pp. 833-837
Jiang, X.H., Guo, Z.X., Liu Q.Z. (2010). Effectof the amount of admixture of sulphoaluminate
cement concrete chloride ion permeability. Twentyfirst Century building materials. Volume 2, No. 2, pp.
23-25
Lu, L.C., Chang, J., Ye, Z.M. (2005). Aluminate
silicate minerals and synthesis of high performance
cement. Journal of silicate. Volume 33, No. 1, pp. 5762
Qin, B.T., Lu, Y., Yin, S.J., Cao, K. and Wang,
M.G. (2013). Prevention and control technique ofcomplex disaster caused by gas and spontaneous
combustion for fully-mechanized sublevel caving
face in close-distance seams. Journal of Mining &Safety Engineering. Volume 30, No. 2, pp. 311-316
Wu, Q., Zhang, B.Y., Wang, H.Q. (2010). New
hydrate-based technique for coal and gas outburst
prevention and low-concentration coal mine gas
separation. Journal of Heilongjiang Institute of
Science and Technology. Volume 20, No. 1, pp. 2327
Xiao, P.C. (1994). New technology of coal
outburst prevention in Shimen. Coal Mine
Modernization. Volume 10, No. 4, pp. 24-26
Yan, Z.P. (2006). Study on the microstructure ofa soft soil in high water setting material. Rock andsoil mechanics. Volume 25, No. 2, pp. 275-278
Yong, Q.L., Liu, Z.D., Sun, X. J. (2005).
Theoretical calculation for equilibrium solubilities
andcompositionalcoefficientoftitaniumcarbonitrides in Ti-bearing micro alloyed steel. SteelIron Vanadium Titanium. Volume 26, No. 3, pp. 1218
Zhu, J.K. (2011). Application of Shimen coalcuring technology to prevent coal and gas outburst.
Coal Engineering. No. 1, pp. 39-40
Zhang, Y.H., Liang, T.Z., Cui, J.K. (2003).
Application Research of high water material in water
injection, dust prevention and sealing technology in"Three Soft" coal seam. Journal of China Coal
Society. Volume 28, No. 1, pp. 46-49
Zhang, C. (2014). Research on instability
mechanism for sealing segment of boreholes andreinforcing dynamic sealing techniques. China
University of Mining and Technology. 23p

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Paper No. 110

Key technologies for extinguishing large-area goaf fires in closely spaced
shallow coal seams
Botao Qina,*, Quanlin Shia, Junzhe Yanga, Hetang Wanga, Lihui ZhangbaFaculty of Safety Engineering, Key Laboratory of Gas and Fire Control for Coal Mines of Ministry of Education, China
University of Mining & Technology, Xuzhou, Jiangsu 221116, Chinab
Bulianta Coal Mine, Shenhua Shendong Coal Group Corporation Limited, Erdos, Inner Mongolia 017209, China

ABSTRACTThe present study examines the spontaneous combustion fire in large-area goaf of the 22305 fully caving face at the
Bulianta coal mine in north-western China. The cause of the spontaneous combustion in the goaf of closely spaced
shallow coal seams is analysed. To deal with the problem of serious air leakage combined with a large fire area anda hidden fire source that could easily re-ignite, a proposed set of key techniques for extinguishing goaf fires is put
into practice. This mainly comprises sealing the air leakage cracks, high-flow injection of liquid nitrogen, andinfusion of a large quantity of foam inhibitor. The results show that these measures rapidly extinguished the goaf fire,
lowered the CO concentration from 43,051 ppm to less than 25 ppm, and reduced the temperature in the goaf toabout 20°C. The 22305 face was subsequently safely reopened and quickly put back into production within threemonths.
KEYWORDS: coal seam; spontaneous combustion of coal; goaf fire; liquid nitrogen; foam inhibitor

1.

INTRODUCTION

Coal is the main energy source in China,accounting for about 70% of the production andconsumption of primary energy (Tang and Li, 2013).
The Chinese coal mining industry is mainly
concentrated in the north-west (Fan, 2016). The
Shendong mining area, located in north-western
China, is China’s largest coal production base, with a
250 million tonne output in 2012. However, the coalseams in the Shendong area are prone to spontaneous
combustion. Contributing to this problem is theshallow burial depth (30-200 m) and the close
spacing between the two coal seams (30–50 m), bothof which are factors that lead to severe air leakage
during the mining process. Thus, spontaneous
combustion occurs very frequently in this mining
area, threatening mineworkers’ safety and producing
large amounts of toxic gases, as well as sulfur,
mercury, selenium and other harmful substances thatcause significant local atmospheric pollution (Luoand Liang, 2003; Gu and Zhang, 2012; Kuenzer et al.,2007; Wang, 2009). Therefore, it is of great
importance to take effective measures to prevent andextinguish spontaneous combustion fires in closely
spaced shallow coal seams.
At present, coal mines in Shendong usually use
conventional technologies, such as water injection,
clay grouting, nitrogen injection and so on, to control
spontaneous combustion fires. However, theeffectiveness of these conventional technologies is
unsatisfactory, since water injection and clay

*Corresponding author – email : qbt2003@163.com

grouting commonly encounter the problems of small
diffusion range, easily drained water and slurry, and aweak cooling capacity of nitrogen (Wang et al., 2012;
Wang, 2008). For example, in June 2012, a serious
spontaneous combustion fire occurred in the goaf ofthe 22305 fully caving face in the Bulianta coal mine,
which is the largest mine in the Shendong area. The
peak concentration of CO was detected to be in thetens of thousands of parts per million. Initially themine used water injection and clay grouting in an
attempt to extinguish the fire, but the COconcentration showed no obvious decrease and thefire zone continued to spread. This caused the closureof the 22305 face, cutting off abundant coal resources
and trapping expensive mining machinery. Clearly, amore positive and effective fire control technology
was urgently needed.
This paper takes the Bulianta fire as a typicalcase. By analyzing the characteristics and causes of
spontaneous combustion in this shallow coal mine
where the coal seams are closely spaced. A set of
efficient fire prevention and extinguishing techniques
is proposed and practiced.

2. METHODS AND SCHEME
2.1 Analysis of causes of coal spontaneous
combustion
The 22305 face was put into operation on 16
June 2012. At 2:00 p.m. on 23 June, blue charcoal
smoke was detected coming from the goaf alongside3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the return airway. The CO concentration was up to1600 ppm in the upper corner and reached 300 ppm
in the return airway. The coal face stopped
production during the morning shift of 24 June when
the face had advanced only 47 m. As mentioned
above, water injection and clay grouting did notcontrol the fire in time, and on 24 July the coal face
was sealed off. The reasons for the goaf fire were as
follows:(1) About 2.0 m of top coal was not mined out,
so abundant broken coal remained in the goaf. The 12
goafs of the Bulianta mine, together with the adjacentShangwan mine, formed a total goaf area of 19.7
million square metres. The coal seams are prone tospontaneous combustion,and the shortest
spontaneous combustion period, between the date ofcoal seam exposed to air and the date of occurring
spontaneous combustion, was only 30 days. Adding
to the problem, the porosity of the coal increased
dramatically when soaked in water (Figure 1), rapidly
raising its oxygen absorption rate and further
increasing the risk of spontaneous combustion.

Figure 2: Typical air leakage fractures in the Shendong
mining area.

(3) When mining the upper coal seam, a great
many mining-induced fractures form in the roof rockof the goaf and propagate to the ground surface(Figure 3), allowing surface water and undergroundwater seepage to enter the goaf, with the result beingthat a large volume of water accumulates there. Then,
when the underlying coal seam is mined, theaccumulated water is discharged into the mine,causing large volumes of air to leak from the mine
below the goaf to replace the lost water. For example,
in the goaf above the 22305 face-originally the resultof mining the upper seam (the 22304 face)-1.1
million m3 of water was discharged. This amount,
together with the 475,000 m3 of water drained fromthe goaf of the 22305 face itself, greatly increased the
air leakage.

Figure 1: SEM image of pore structure of coal (a) before
water soaking; (b) after water soaking.

(2) The coal seams in the Shendong mining area
are very shallow, with a thick layer of loose
overburden material that has very low strength intension and compression, and low resistance todeformation, all of which make it vulnerable to theformation of mining-induced fissures and fractures.
The roof rock of the goaf is very thin; consequently,
surface subsidence and deformation is very difficult
to control. As a result, pathways for air leakage
between the goaf and the ground surface formed
readily during mining, causing serious air leakage
into the goaf (Figure 2). In addition, the Bulianta
Mine has more than 90 connecting roadways between
the goaf and the lower coal seam currently being
mined, potentially providing a very large number ofunderground air leakage pathways.

Figure 3: Schematic diagram of mining-induced fracturesconnected to the ground surface.

2.2 Plugging air leakage channels
At the surface, a combination of artificial andmechanical backfill was used to plug the leakage
fractures and cut off the air leakage channels. To
block the underground air leakage channels, shotcrete
was used to reinforce the sealing walls in theconnecting roadways.
As shown in Figure 4, sulfur hexafluoride (SF6)
tracer gas was used to investigate the distribution of
the air leakage pathways and analyse the air leakage
effect of fracture propagation over different periods.

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Figure 4: Detection of air leakage pathways using SF6.

2.3 Injecting liquid nitrogen
The temperature of liquid nitrogen is -195.8 °C,
and its latent heat of vaporisation is 199 kJ/kg. Liquid
nitrogen quickly evaporates into gaseous nitrogen at atemperature of -193 °C; one tonne of liquid nitrogenforms 780 m3 of nitrogen gas. Thus liquid nitrogen
absorbs more heat-in other words, has a greater
cooling effect-than nitrogen gas (Yuan and Wan,
2013).
The liquid nitrogen system consisted mainly of amoveable storage tank containing liquid nitrogenproduced by Shenhua Coal Liquefaction Plant (asshown in Figure 5), a cryogenic centrifugal pump andstainless steel piping. Figure 6 illustrates the processof injecting the liquid nitrogen: first, the liquid
nitrogen was transferred by the cryopump to thedelivery pipeline; then, the liquid nitrogen was
directly injected into the high temperature points ofthe fire zone through a series of 20 holes drilled fromthe ground surface. The liquid nitrogen extinguishedthe fire and suppressed the possibility of explosion,and also absorbed a great deal of heat as itvapourized.

Figure 5: Lorry carrying storage tank of liquid nitrogen.

Figure 6: Liquid nitrogen injection process.

To rapidly reduce the temperature of the firezone and displace the harmful gases accumulated in
the goaf, the liquid nitrogen was poured into the goaf
through 20 drill holes (MH26–MH45) from theground surface, as show in Figure 7. Between 24 Julyand 7:00 a.m. on 20 August 2012, approximately
13,250 tonnes of liquid nitrogen were poured into thehigh-temperature zone.

Figure 7: Location map of drill holes MH26–MH45 forliquid nitrogen injection.

2.4 Diffusion of foam inhibitor
The foam inhibitor was generated from slurry ofyellow mud or fly ash, compressed air and a solutionof foaming agent and retardant. The foam was
generated at a rate of 600–1000 m3/h, with a stability
time of 12 h, and an effective diffusion radius morethan 60 m. Using this volume of foam as the carrier,
together with its wide diffusion characteristics, theretardant was carried to greater lateral distances andhigher points in the fire area than could be reached byconventional liquid or solid fire-fighting mediums.
The foam generating equipment mainly consisted of ametering pump, foam generator and foam delivery
hose.
Figure 8 shows the fire extinguishing process ofthe foam. First, a metering pump adds the solution of
foaming agent and retardant at a given ratio into theslurry of yellow mud or fly ash; then, compressed air
is mixed with the slurry, producing a large volume of293

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

foam; finally, the foam is injected into the fire zone
via a delivery hose and drill holes.

Figure 8: Preparation equipment of foam inhibitor.

Between 10 and 20 August 2012, a total of 770
tonnes of foam inhibitor was injected into the firezone though 10 holes (ZJ5–ZJ14) drilled from theground surface. The locations are shown in Figure 9.

Figure 9: Location map of drill holes ZJ5–ZJ14 for foam
injection.

3. RESULTS AND DISCUSSION
Following the injection of liquid nitrogen andfoam into the goaf fire zone, sampling analysis of thefire index gases was conducted at eight measuring
points (Figure 10) at ground level and underground.
The continuous sampling test results showed that theconcentration of fire index gases, O2, CO, C2H2 andC2H4, declined continuously (Figure 11).

Figure 10: Location map of measuring points for fire zone.

Figure 11: Change trend of different index gases.

Seen from Figure 11a and 11b, the oxygen
concentration in the fire zone was below 5.0% from 6
August 2012, the acetylene (C2H2) concentration
remained steady at 0 ppm from 9 August and theconcentration of ethylene (C2H4) remained steady at
0-5 ppm from 11 August. In addition, theconcentration of carbon monoxide (CO) gradually
decreased during the period that the coal face wasclosed from a peak value of 43,051 ppm to a stablevalue of 5 ppm. The air temperature of the closed firezone stabilized at around 20°C. According to Chinese
Coal Mine Safety Regulations, these values indicatedthat the goaf fire at the 22305 coal face had been
extinguished, and conformed to the conditions underwhich the face could be unsealed. The face wassafely unsealed on 21 August and productionsmoothly resumed on 23 August.
After production was resumed at the Buliantacoal mine, the concentrations of index gases
remained normal, with CO concentration steady at 67 ppm, the minimum concentration of O2 was 19.8%,
and the concentration of the other gases was 0.02–
0.08%. This indicated that the foam inhibitor had
effectively prevented the further fragmentation ofcoal in the goaf. From 8 October 2012, the 22305
coal face had safely advanced 558 m.

4. CONCLUSIONS
Spontaneous combustion fires in the goaf of
fully mechanized caving faces mining two closely
spaced shallow coal seams are characterized by alarge volume of air leakage, a large fire zone and ahidden fire source. These conditions are highly prone
to spontaneous combustion ignition and re-ignition,and conventional fire prevention and extinguishingmethods such as water injection, grouting andnitrogen gas injection are largely ineffective incontrolling such fires.
In these conditions, air leakage cracks are readilycaused by the mining process, causing a high rate of
air leakage into the goaf and providing a sustainableoxygen supply that is ideal for initiating spontaneous
combustion of coal. Therefore, taking positive
measures to block the air leakage channels is very
important.
When low-temperature liquid nitrogen fills asealed goaf, it quickly vaporises at normal pressuresand temperatures. The cold nitrogen gas then quickly
spreads to fill the entire fire area, displacing the othergases generated by the fire. The oxygen
concentration drops rapidly, smothering the fire. The
cold nitrogen gas also lowers the temperature of thefire zone by absorbing heat as it converts from theliquid to the gaseous phase, due to its latent heat ofevaporation.

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Foam inhibitor pumped into the goaf spreads
widely throughout the fire-prone zone, transporting
the fire retardant to areas that would otherwise beinaccessible to single liquid or solid fireextinguishing materials. This makes it highly suitablefor controlling fires occupying large spaces in thegoaf, and/or hidden fires, and for preventing
spontaneous combustion re-ignition.

5. ACKNOWLEDGEMENT
This work was supported by the National Natural
Science Foundation of China (No. U1361213,
51476184) and A Project Funded by the Priority
Academic Program Development of Jiangsu Higher
Education Institutions (PAPD).

6. REFERENCES
Fan W., Liu B.F., Ouyang X., An D. and Hu
Z.H. (2016). Analysis on market sales status andmeasures of coal enterprises, Coal Economic
Research, Volume 36, No. 1, pp. 68–70
Gu, D. and Zhang, J. (2012). Modern Coal
Mining Affected to Underground Water Deposit
Environment in West China Mining Area, Coal
Science and Technology, Volume 40, No. 12, pp. 12–
15
Kuenzer, C., Wesslin, W., Zhang J. et al. (2007)
Concepts for Green House Gas Emission Estimationof Underground Coal Seam Fires, GeophysicalResearch Abstracts of the EGU General Assembly,
pp. 164-170.
Luo, H. and Liang, Y. (2003). Current Status andPerspective of Forecast and Predict ion Techniques
for Spontaneous Combustion of Coal, China Safety
Science Journal, Volume 3, No. 13, pp. 76–78
Tang, X. and Li, S. (2013). Research on themeasures of energy problem of industrialization in
our country, Economic Issue, No. 1, pp. 124-126
Wang, H. (2009). The research of coal mine fire
safety and the phenomenon of spontaneous
combustion in China, Science &Technology for
Development, No. 12, pp. 12-15
Wang, B., An, S. and Guan W. (2012). Detection
and Governance of the Spontaneous Combustion
High-temperature Region in Shallow Burial andThick Coal Seam. Safety in Coal Mines, Volume 43,
No. 45, pp. 45-49
Wang, D. (2008). Mine fires, Xuzhou:
China University of Mining and Technology Press,
245 p.
Yuan, Z. and Wan, L. (2013). Application ofliquid nitrogen system to control fire in coal mine.
Coal Engineering, No. 3, pp. 45-49.

295

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Paper No. 112

The assessment of emergency capability of coal mines based on AHP-fuzzycomprehensive method
Shu Jiao Tonga,*, Zong Zhi Wub, Ru Jun Wanga, Ying Quan Duoaa

Key Laboratory of Major Hazard control and Accident Emergency Technology, State Administration of Work Safety,
Academy of Safety Science and Technology, Beijing, China, 100012
b
China's State Administration of Work Safety, Beijing, China, 100713

China

ABSTRACT
In order to improve emergency management capabilities and the prevention and control of major accidents, it isimportant to study various methods for the assessment of the emergency capabilities of coal mines. This paper aims
to bring about an analytic hierarchy process (AHP) and fuzzy comprehensive method to assess the emergency
capabilities of coal mines. Firstly, the key elements of the emergency management for coal mines are analyzed
based on the theories of the emergency management. From the precaution, response, and recovery aspects, theassessment index system of the emergency management capabilities for coal mines is built and the basic indexes ofeach element are confirmed and discussed. Furthermore, a multi-level fuzzy comprehensive evaluation model formine emergency management capability is built based on the AHP (Analytic Hierarchy Process) and fuzzy
mathematics. The assessment index system and mathematical model are applied to a selected mining enterprise
whose assessing result was “high”. Some shortcomings of the emergency system of the coal mine were analyzed andsome suggestions were proposed to improve the emergency capabilities for the coal mine. The study is helpful for
emergency management and the prevention of major accidents in coal mines.
KEYWORDS: coal mine; emergency capability; AHP; fuzzy comprehensive assessment

1.

INTRODUCTION

It is well known that coal resources are an
important foundation for energy and raw materials.
China's coal industry has made remarkableachievements after nearly a decade of rapid
development and production safety in mining has
greatly improved. However, safety management incoal mines is still not good enough and lots ofaccidents have happened in the last decades.
According to the statistics, the mortality rate of coalmines in China is 2.81 in 2005, 2.04 in 2006, 1.49 in
2007, 1.18 in 2008, 0.89 in 2009, 0.75 in 2010, and0.56 in 2011. Meanwhile, the mortality rate of coalmines is about 0.05 to 0.03 in the United States,
Australia, and other developed countries in recent
years. The mortality rate for one million tons of coalmines in China is almost 30 to 50 times that of theUnited States and other advanced countries. The mostimportant reasons for the coal mine accidents in
China are the imperfect emergency system and poor
emergency management.
Effective emergency and rescue can lessen thecasualties and wealth losses of mining accidents.
Emergency management capability assessment is an
important part of safety management in coal mines.
At present, the relevant research on the safety of coalmines mainly concentrates on risk assessment andsafety management methods, and it is limited in the*Corresponding author – email: tongshujiao@mail.neu.edu.cn

study of emergency management, especially in thequantitative calculations. Most studies focus on
theoretical discussion and qualitative analysis.
Therefore, in order to improve the emergency
management capabilities to prevent or control major
accidents, it is important for the safety of coal mines
to study the methods of assessment of emergency
management capabilities.
In this paper, the key elements of the emergency
management for coal mine were analyzed based on
the theories of emergency management. The
assessment index system of the emergency
management capability for coal mines was built and amulti-level fuzzy comprehensive evaluation model
for mine emergency management capability was built
based on AHP and fuzzy mathematics. The
assessment index system and mathematical model
were applied to a selected mining enterprise to findout the shortcomings of the existing emergency
system. Finally, some conclusions and suggestions
were proposed to improve the emergency capabilities
of coal mines. The study results will be helpful inadvancing safety and emergency management
scientifically to prevent and control major accidents
in coal mines. At the same time, the results provide atheoretical basis and management guidance forgovernment departments to manage coal mines.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2.

KEY ELEMENTS OF EMERGENCY
MANAGEMENT FOR COAL MINES

Emergency refers to how to answer the
emergent conditions. Usually it means the treatment
measures adopted when the emergent conditions
happen, and it includes a series of safety techniquesand measures adopted to avoid accidents or lessen
casualties and wealth loss in production. Therefore, it
is often called accident emergency. Emergency
management includes rapid and early warning,
effective control, and active treatment to minimize
losses during the concurrent and feedback of theunexpected accidents. Emergency management
capability is the capability to deal with and avoid
risk, and it involves the former preparation, disaster
response, and support and rebuilding after the natural
or manmade disaster.
The objects of emergency management are theunexpected incidents that could induce large
casualties, wealth loss, and environment pollution.
The capability of emergency management is thecapability to control the unexpected incidents. The
capability of emergency management for coal mines
means the capability to control major unexpected
accidents. The assessment of emergency management
can be useful in realizing the precaution and controlof major accidents.

From the Figure 1, it can be seen that the
precaution capability, response capability, andrecovery capability constitute the emergency
capability of coal mines. The precaution capability B1
includes six indexes such as regulations andstandards B11, safety management B12, emergency
organization and plans B13, emergency resources B14,
and training and education B15. The response
capability B2 includes six indexes such as emergency
comunication B21, rescue actions B22, medical aid
B23, resources allocation B24, and refuge andevacuation B25. The recovery capability B3 includes
five indexes such as scene cleaning B31, damage
evaluation and insurance B32, emergency plan update
and improvement B33, rebuilding B34, plan
improvement, and perfection B35.
In order to assess the emergency capability ofcoal mine, it is necessary to build the scientific andreasonable index system and apply the operable
assessment methods to the emergency management
system, and make comprehensive assessment to get aconclusion periodically. All the jobs will find out themerit and shortcoming of the emergency
management, and the actual capability of emergency
management of coal mine will be enhanced step by
step.

3.
Emergency capability of coal mine(A)

Precaution
capability(B1)

Legal risk
tolerance(B2)

Moral risk
tolerance(B3)

B11……B15

B21……B25

B31……B35

Figure 1: Structure of emergency capability of coal mine.

Emergency management is a lasting andpersistent process. The key elements of emergency
management include four phases: precaution,
preparation, responds and recovery (Fan, 2011). The
precaution and preparation phases share many
common elements, so they are always combined inpractice. The structure of emergency capabilities ofcoal mines is shown in Figure 1.

ASSESSMENT INDEX SYSTEM OF
EMERGENCY CAPABILITS FOR COALMINES BASED ON AHP

3.1 Analytic Hierarchy Process
AHP (Analytic Hierarchy Process) (Chen et al.,2009; Zheng et al., 2010) is a kind of decisionmaking method that is applied widely to solve
relatively obscure or complicated decision problems
by qualitative and quantitative analysis methods.
Because the emergency capability of coal mines is acomplex decision problem, the assessment model ofthe emergency capability of coal mines can beestablished based on the AHP (Analytic Hierarchy
Process) method.
AHP quantifies the judgement made by theexperience of the decision maker. Furthermore, it canlayer our thought process and compare related items
and check the rationality of the compared result step
wisely to supply the convictive criterion. Many
decisions can be solved by the analytic hierarchy
process.
The steps of AHP include:(1) Building hierarchy structure model;(2) Establishing judgment matrix;(3) Consistency checking for judgment matrix;(4) Calculating weight vector;(5) Calculating combinatorial weight vector;(6) Overall consistency checking;297

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

(7) Fuzzy comprehensive judgment.
3.2 Assessment indexes
According to research on the emergency
capability evaluation of coal mines and the AHP
method, combined with the advices of emergency,
safety, management, and fire experts, acomprehensive index system of emergency capability
for coal mines is built from the perspective of thewhole process of the emergency management of coalmines. The assessment indexes system of theemergency capability of coal mines is built in Table
1.
Table 1: Assessment indexes system for coal mines.
Top layer
Second layer Third layer（index layer）

Emergencycapabilityof coalmine
APrecaution
capability
B1

Response
capability
B2

Recoverycapability
B3

Regulations and standards
B11
Safety management B12
Eemergency organizationand plan B13
Emergency resources B14
Training and education B15
Emergency comunication
B21
Rescue actions B22
Medical aid B23
Resources allocation B24
Refuge and evacuation B25
Scene cleaning B31
Damage evaluation andinsurance B32
Emergency plan update andimprovement B33
Rebuilding B34
Plan improvement andperfection B35

It is obvious that the assessment index system
includes multilevel indices. There are three
emergency elements in the second-level andseventeen elements in the third-level. Each secondlevel index includes many third-level indices. There
are six items in the precaution capability, six items in
the response capability, and five items in the recovery
phase. All the seventeen items reflect the capabilityof the emergency management for major accidents ofcoal mines.
3.3 Calculating index weight
Based on the AHP, the assessment model of theemergency capability of coal mines has been built toanalyze the actual emergency management capabilityof the enterprise in this paper. Firstly, the weight thateach index affects the object was assured by analyzing
all the scores confirmed by experts, then thequalitative indexes were quantified, and theemergency capability of coal mines was confirmed atlast. Thus, we can estimate the actual emergency
management capability of coal mine enterprises.
The judgment matrix can be established byinviting the experts to mark all of the indices. The
indices judgment of A is illustrated in Table 2.
Table 2: Judgment Matrix for A
A

A1

A2

A3

A1

1

1/3

4

A2

3

1

6

A3

1/4

1/6

1

According to the above judgment matrix, theweight of each index can be calculated bymathematical tools such as MATLAB, and also theweight vector and the consistency test. All the results
are shown in Table 3.
Table 3: Consistency checking of the judgment matrix.
Judg
consisten
ment
n
λmax
CI
RI
CR
cy
matrixA
3
3.03 0.01 0.58 0.03
Pass
B1

5

5.23

0.05

1.12

0.05

Pass

B2

5

5.33

0.08

1.12

0.07

Pass

B3

5

5.08

0.04

0.90

0.03

Pass

Where, n is the number of indexes; λmax is the
maximum eigenvalue of judgment matrix; CI is theconsistency index, When CI is more than 0 slightly,
the matrix A will be in relatively good agreement,
otherwise, the consistency of A is poor.
Based on the above table, the consistency ratio CRof each judgment matrix is less than 0.1, whichindicates the consistency checking is ok. The weightof each index is shown in Table 4.
Table 4: Weight vector of each layer of index system.
Judgment
Weight vector(w)matrixA

0.2706 0.6442 0.0852

B1

0.2615 0.0634 0.5128 0.1290 0.0333

B2

0.4047 0.1769 0.0590 0.2551 0.1043

B3

0.4620 0.1739 0.1778 0.0862 0.1002

4. FUZZY COMPREHENSIVE ASSESSMENT
MODEL
The fuzzy comprehensive evaluation is performedby using the single factor evaluation results andevaluation object related. The corresponding
evaluation matrix is constructed and the decision298

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016weighting factor importance degree of each factor isused for the fuzzy transformation. Finally theevaluation results are found. Through the fuzzycomprehensive evaluation, risk management decisions
can be quantitatively calculated for each oil and gas
pipeline construction project. In order for the final
evaluation results to have practical reference
significance, the vector and the fraction vector areused to calculate a total score, and then the control
method of rating scores to determine the result of theevaluation belongs to the grade.
4.1 Building indices
According to the indices system built in Table 1,establish collection U:
U={B1, B2, B3}
U1={B11, B12, B13, B14 , B15}
U2={B21, B22, B23, B24 ,B25}
U3={B31, B32, B33, B34, B35}
4.2 Establishing judgement collection
The capability of emergency management for coalmines can be divided into five levels from high tolow.
Judgement collection={V1, V2, V3, V4, V5}
V1=higher，V2=high，V3=middle，V4=lower，V5=low.
In the calculation of the total system scores, risk
management and decision-making can refer to Table 5
to determine the pipeline risk tolerance decision
value. Then, the level of risk factor can be confirmed
according to the decision value and also risk decision
can be determined.
Table 5: Value and level of emergency management
capability.
Risk
level

Assessment
ValuesLevel ofmeasurement1˃90Highermaintain

2

90～76

High

Advanced

375～60

Middleneed Advanced

4

59～50

Lower

Must Advanced

5

＜49

Low

rectify

4.3 Fuzzy comprehensive assessment
There is a fuzzy mapping from U to V, where. The fuzzy mapping f
can identify a fuzzy relationship between U and V; therefore, Rf can be
expressed as a fuzzy matrix.

Thus, a comprehensive evaluation can be performed.
5.

A CASE STUDY

In this paper, a coal mine was taken as a case to
study risk tolerance and decision making. Using theestablished emergency capability model of fuzzycomprehensive assessment, the emergency capability
value of the coal mine is carried out to determine thelevel of the emergency of the coal mine.
Before evaluation, relevant experts to judge ,ust
be recruited and the importance of each index ofemergency capability on the effect of each index of
the coal mine must be compared. By inviting10
relevant experts including coal mine, safety,
technology, emergency, and fire experts, theimportance of each index of the coal mine can be
confirmed. The arbitrarily corresponding matrix ofrisk factors can be determined to find the score of the
fuzzy comprehensive evaluation. Finally, the level of
emergency capability of the coal mine can be
determined.
In order to explain the calculation, we can takethe precaution capability B1 as an example. The
experts’ judgments on the precaution capability arelisted in Table 6.
Table 6: Judgments of experts to the precaution capability
B1.
HigherHigh

Middle

Lower

Low

B11

0.3

0.5

0.2

0

0

B12

0.8

0.2

0

0

0

B13

0.7

0.3

0

0

0

B14

0.2

0.3

0.5

0

0

B15

0

0

0

0

1

So the Rf can be expressed as a fuzzy matrix asfollows.
 0.3

 0.8
R ( B1 ) =  0.7

 0.2
0


0.5
0.2
0.3

0.2
0
0

0
0
0

0.3
0

0.5
0

0
0

0

0
0

0
1 

Then,

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016R=
wB1 • R ( B1 )B1T

 0.2615   0.3
  0.0634   0.8=  0.5128  •  0.7
  0.1290   0.2
 0.0333   0 = ( 0.5139 0.3360

0.5
0.2
0.3
0.3
0

0.2
0
0
0.5
0

0.1168

0

0
0

0
1 

0
0
0
0
0

0.0333)0RB2=(0.3490 0.2326 0 0 0.4184)
RB3=(0.7393 0.1472 0.0274 0 0.0862)
So,
0.116800.02740000.0333 
0.4184 
0.0862 R=
wA • R ( A )A
T 0.2706   0.5139 0.3360
 =  0.6442  •  0.3490 0.2326
 0.2856   0.7393 0.1472
 = ( 0.4949 0.2895 0.0773

0.116800.027400
0
00.1383)0.0333 
0.4184 
0.0862 Then, the emergency capability of the coal minecan be got by RA·(93,80,70,55,45)T, and the result is
82.16. Therefore, according to the decision standard
values listed in Table 5, the level of the coal mine ishigh but the emergency regulations and standards,
emergency training, and education still need to bestrengthened.
6.

7.

ACKNOWLEDGEMENT

The research work was supported by National
Science and Technology Foundation of China underGrant No. 2015BAK16B03 and Basic Science andTechnology Foundation of CASST under Grant No.
2016JBKY12.

Also, 0.5139 0.3360

R ( A ) =  0.3490 0.2326
 0.7393 0.1472
emergency management level and preventing major
accidents.
(4) The practical application shows that the
emergency capability of the coal mine is “high”.
However, the emergency regulations and standards,
emergency training, and education still need to bestrengthened.

CONCLUSIONS(1) The capability of emergency management forcoal mine means the capability to control major
unexpected accidents. Emergency management is alasting and persistent process which includes
precaution, response, and recovery.
(2) The assessment index system includes
multilevel indices. The three phases of emergency
management constitute the second-level indices. Eachsecond-level index includes many third-level indices,which sum to fifteen items. There are five items in the
precaution phase, five items in the preparedness
phase, five items in the response phase, and four itemsin the recovery phase. All the fifteen items directlyreflect the capability of the emergency management
for major accidents.
(3) The capability of the emergency management
for coal mines can be assessed by establishing theanalytic hierarchy process model, and the assessment
result can reflect the actual emergency management
degree. All the studies are helpful in improving the8.

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Paeka H.J., Hilyard K. (2010). Theory-BasedApproach and Understanding Public Emergency
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301

ISMS 2016

Paper No. 121

Study on local temperature controlling technology and equipment in heatdisaster coal well
Haijun Wua,b, Haifei Yaoa,b, Changfu Xua,b, Haiyan Wanga,b, Laizai Tanca

Mine Safety Technology, China Coal Research Institute, Beijing, China, 100013
National Key Lab of High Efficient Mining and Clean Utilization of Coal Resources, Beijing, China, 100013
c
Nanjing Wuzhou Refrigeration Limited Liability Company, Nanjing, China, 211100b

ABSTRACT
Along with the continuous increase of coal resource mining depth, high temperature and heat disaster is becoming
more and more serious. The health of workers under coal wells can be threatened at any time and the safe mining ofcoal resources is seriously impacted. In order to eliminate coal well heat disasters, scholars at home and abroad have
inputted a lot of time and energy. They have researched the controlling theory of coal well heat disasters. Theydeveloped cooling equipment for high temperatures and have achieved some results. However, the equipment is toolarge and as a result it is hard to move. The power of the equipment is high so it costs a large amount of electric
power. Maintenance costs are huge, and therefore the application of this technology is not ideal.
Based on this, the present study firstly analyzed the influence factors of coal well heat disaster. Then, the calculation
method of cooling load in coal wells was researched. The authors put forward the technology for controlling local
high temperatures. The ZLS-90 movable cooling equipment was developed successfully which includes arefrigeration compressor, evaporator, water cooling condenser, and expansion valve. The property of the compressor
plays an important part in the cooling effect of the whole system. After comparing, the GEA bock compressor waschosen. The enthalpy difference comprehensive testing system was used to test the performance of the equipment.
Test results showed that all performance indexes comply with the design requirements. The property is also stable.
This paper also proposes discharging heat with a heat-rod to deal with the heat of condensation as well as using theheat synthetically. Effective cooling can be carried out by means of local temperature controlling technology andequipment. In that case, the working environment under coal wells would be guaranteed and the safe production ofcoal wells would be guaranteed. It would realize efficiency, conservation, and the environmental protection of
resources.
KEYWORDS: heat disaster; temperature controlling technology; enthalpy difference; heat-rod

1. INTRODUCTION
Coal is the main energy source for our country
and world. It occupies an irreplaceable position in the
primary energy consumption structure (Yang D D,
2013). With the increasing mineral resources
exploitation level and gradual enhancing of degree of
mechanization, shallow buried coal resources are
draining off and deep mining is gradually dominating(Cao X L, 2010). In recent years, countries aroundthe world have entered deep mining areas (Singh etal., 2003). The mining depth of some coal in
Germany and Russia has amounted to 1400-1500 m(Nimaje and Tripathy, 2010). The depth of Kariton
Vere gold mine in South Africa is 3800 m
underground and its upright shaft is about 4500 m
deep (Gangopadhyay and Dutt-Lahiri, 2005). Some
metal mines in India and Brazil are more than 2000
m (Li H J, 2009). There are more than 30 mines thatexceed 1000 m deep in Canada and more than 10
mines in America (Abdelaziz et al., 2003). At present
in our country's proven reserves, 1000-2000 m deep*Corresponding author – email : wuqing129@163.com

coal reserves accounted for 53.2% of total reserves(Wu J T et al., 2010). Dozens of mines are more than
1000 m deep (Feng D Q et al., 2013). Currently, themining depth is rising at a rate of 8 to 16 m/a in
China (Feng X L and Chen R H, 2005). Deep miningof coal will be the main problem we face in the
future.
With the increase of mining depth, temperatureof the surrounding rock is rising constantly (Vosloo
et al., 2012). Electromechanical devices, people, hotwater, coal, and gangue all emit heat. All of thesecause severe environments of high temperature andhigh humidity which lower the working efficiency
and affect equipment operation (Hughes et al., 2006).
It seriously hinders the normal construction andefficient production of mines. Even worse, it gives
rise to worker’s sunstroke and dehydration, or evendeath. Besides water, fire, gas and roof, deep wellheat disaster has been one of the major disasters that
restricts the development of the coal industry (Xin S
et al., 2012). In order to control deep well heat3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

disasters, scholars at home and abroad have done a
lot of research from the aspects of theory, technique,and equipment. The scholars have developed a seriesof cooling equipment. However, there are still many
problems such as a lack of theoretical research, large
and hard to move cooling equipment, expensive tomaintain, and difficult to let out the heat ofcondensation (Cao Q K et al., 2010). It is necessary
to carry out research on cooling technology andequipment of deep coal well heat disasters.

2. DISTRIBUTION CHARACTERISTICS
AND INFLUENCING FACTORSANALYSIS OF HEAT DISASTER COAL
WELL
By 2014, there are more than 150 heat disastercoal wells which mainly distribute in the east of
China (Figure 1). Among these heat coal wells, 20
wells represented by Pingdingshan, Fengcheng and
Xuchang are distributed in Central China. More than
40 wells represented by Yanzhou, Xinwen, Xuzhou(including Datun), Juye, Huainan and Huaibei are
distributed in East China. In Northeast and North
China, there are more than 30 heat disaster coal wells
represented by Fengfeng (Handan), Xingtai, Datong,
Kailuan, Tiefa, Beipiao, Fushun, Liaoyuan and Jixi
(Zhang L et al., 2009). The rest are scattered in
Hunan, Gansu, Guangxi, etc.

Figure 1: Distribution of heat disaster coal wells.

According to the survey, heat sources that cause
deep coal heat disasters are the changes of surface
atmospheric state, temperature rise of air selfcompression, heat emitting from surrounding rock,heat emitting from electromechanical device, heatreleasing from transport of coal and gangue, heat of
hot water, and other heat sources. Take typical heatdisaster coal wells, Panxi mine, Jining 3# mine,
Pingdingshan 5# mine, Tangkou mine, Dongtan mine
etc. for example. We analyzed the proportion of allthese influence factors in heat disaster. The researchshows that heat emitting from surrounding rock,electromechanical devices, and hot water are themain factors of heat disaster, as shown in Table 1 andFigure 2.

Table 1: factors incidence of part heat disaster coal wells.
heat sources

surroundingrock

electromechanicaldeviceterrestrial
heat

hot
water

oxidation

Dongguashan
√
√√
√√
√
√
copper mine
Panxi coal
√√
√
√√
√
well
Jining 3#√√√√√√
coal well
Pingdingshan
√√
√√
√√
√
5# coal well
Qishan coal
√
√
√√
√
well
Chengjiao√√√√√√
coal well
Sanhejian√√√√√coal well
Baiji coal
√√
√
√
well
Pingdingshan
√√
√
√√
√
8# coal well
Dongtan coal
√√
√
√√
√√
√
well
Annotation: “√√” represents main reasons. “√” represents general reasons.

aircompression

lack
of
air

transportation
process

human
body

√

√

√

√

√

√

√

√

√

√

surfaceclimate

√

√
√
√

√

√
√

√
√

√

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

decreasing equipment being bulky in volume, high inenergy consumption, expensive to maintain, difficult
to move and so on, we present local temperature
controlling technology and movable equipment. Bymeans of the technology and equipment, we can cool
the local thermal environment of working-face in
exploiting and mining. It not only reduces the energy
consumption of the equipment, but also meets therequirements for local temperature controlling.

Figure 2: Affecting factors ratio of heat disaster coal wells.

3. COOLING LOAD COMPUTINGMETHOD OF COAL WELLTEMPERATURE DECREASING
There are multiple methods for the cooling load
calculation of heat disaster coal well temperature
decreasing. Some are based on the heat sources of thecoal well, some are based on the air enthalpy of the
air intake and air outlet, while others are based on the
refrigeration station (Xin S et al., 2011). Computed
results belied with the actual cooling load needed.
Therefore, it is not scientific to confirm therefrigerating capacity of cooling equipment.
Resource utilization is low and the cooling effect is
not ideal. Based on this, the current study puts
forward the correction cooling load calculation
method of coal well temperature decrease. The
computational formula is:
Qcold = k（Qemit - ΔQ）= k（Qw + Qj + Qr + Qm + Qk + Qc + Qy + Qs - ΔQ）

In the formula: Qcold -refrigerating capacity needed,

4.1 Develop movable cooling equipment
Aiming for local thermal environment cooling
only, the refrigerating capacity of the equipment canlower suitably. According to the air supply situationof the exploiting and mining working-face in mostcoal wells, we chose 90kW as the effective
refrigeration capacity of the equipment (nominalworking conditions: dry-bulb temperature of inlet air
30℃, relative humidity 85%, temperature of air-out
25℃, air capacity 300 m3/min). It can guarantee thatthe temperature of air transmitted to the working-faceis lower than 26 ℃ . The relationship between air
capacity disposed and inlet air temperature is shownin Figure 3.

Figure 3: Relationship between air capacity disposed andinlet air temperature (air-out temperature 25℃).

kW; k-correction factor, 1.05; Qemit -emiting heat ofheat sources, kW; ΔQ -absorption heat of roadway
air, kW; Q w -emiting heat of surrounding rock, kW;
Q j -emiting heat of electromechanical device, kW;
Qr -emiting heat of people, kW; Qm -emiting heat ofcoal and gangue, kW; Qk -emiting heat of air self
compression, kW; Qc -emiting heat of air leak fromgoaf, kW; Q y -emiting heat of oxidization, kW; Qs emiting heat of hot water, kW.

4. LOCAL TEMPERATURECONTROLLING TECHNOLOGY AND
EQUIPMENT IN HEAT DISASTER COAL
WELLS
Aiming at numerous problems in preventing andtreating coal well heat disaster, such as temperature

The movable cooling equipment is comprised of
a compressor, condenser, evaporator, electronic
control system, and so on. In order to accord with
explosion-proof requirements, we chose a BOCK(FX14/1366) piston open-type compressor equippedwith an explosion-proof electric machine. The powersource of the electric machine is a three-phase fourwire system, quaternary. A thermostatic expansion
valve was used in the throttle mechanism.
Performance parameters of the compressor are shownin Table 2.
Either an evaporative condenser or shell-andtube condenser can be chosen. These two types ofcondenser each have their own merits and demerits.
The ultimate length of the refrigerating fluid
connecting hose should firstly be considered (Figure4). The W type represents the single biggest length ofconnecting hose 1 and connecting hose 2. The

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

evaporator is lower than the compressor in the rightside while higher in the left side. N type represents
the single biggest length of connecting hose 3 andconnecting hose 4. The condenser is higher than thecompressor in the right side while lower in the left
side. Lv/L is the ratio of the connecting hose height
difference value and single tube length. Lv/L≈0 incoal wells. Analysis conclusion: the biggest
Table 2: Performance parameters of the compressor.
Condensation
temperature Tc/℃
15
Cold capacity/W
16800030
Power /kW
15.7
Cold capacity/W
15900035Power /kW
19.6
Cold capacity/W
15000040
Power /kW
23.3
Cold capacity/W
14100045
Power /kW
26.7
Cold capacity/W
13200050Power /kW
29.9

connecting hose length of the condenser is about 60
m and the biggest connecting hose length of theevaporator is about 22 m. Based on the above
analysis, the shell-and-tube condenser was selected.
R407C was chosen as the refrigerating fluid andwater as the cooling medium.

Evaporation temperature To/℃
10
5
0
-5
140000 116000 95000 77300
17.3
18.1
18.1
17.6
133000 110000 89700 72800
20.6
20.8
20.3
19.3
125000 103000 84200 68200
23.6
23.2
22.3
20.9
117000 96300 78600 63500
26.4
25.5
24.1
22.4
110000 89700 73000 58700
29.0
27.7
25.9
23.8

Figure 4: Ultimate length analysis of refrigerating fluid
connecting hose.

The evaporator is an important component of therefrigeration system. It is a sort of dividing wall typeheat exchanger. Direct evaporative cooling was
designed. Floating air temperature outside the coiled
tube is reduced by the evaporation of refrigerating
fluid in the coiled tube. In order to decrease theinfluence of dust under the well on heat transfer ofthe heat exchanger, slick coil pipes were used for theevaporator. This type of pipe is convenient to rinse.
Calculating parameters of the evaporator are as
follows: air supply volume 300 m3/min, dry-bulb
temperature/wet bulb temperature of inlet air 30/28℃,
the temperature of air-out 25℃. Slick copper pipes(φ16×1.2) were bent to an 800 mm single length.
There are 36 pathways with 342 pipes. The air
resistance is about 900 Pa.
As a kind of movable cooling equipment used incoal wells, its electronic control system should
automatically monitor the main technical parameters
and running status of the equipment. It should also
adjust automatically according to actual situation.
The electronic control system should show air-out
temperature, air-out humidity, air suck, and exhaustpressure of the compressor. The electronic control

-10
62200
16.6
58400
18.0
54500
19.2
50600
20.4
46600
21.6

-15
49400
15.3
46200
16.4
43000
17.4
39700
18.4
36400
19.4

-20
38600
13.9
35900
14.8
33200
15.6
30400
16.5
27600
17.3

-25
29600
12.4
27200
13.2
24800
13.9
22500
14.7
20100
15.6

system is the key of equipment operation andautomatic control. So, it should have the function of
being explosion-proof as well as have air exhaustpressure protection, over temperature protection,
overload protection and so on. After systematic
design and manufacturing, the movable coolingequipment was named ZLS-90 mine explosion-proof
refrigeration unit.
4.2 Performance testing of the cooling equipment
The comprehensive enthalpy difference method
was used to test the performance of the coolingequipment. The enthalpy difference test system
adopts the testing philosophy of air enthalpydifference method or means of liquid secondaryrefrigerant in the primary side and water heat meter
method in the subordinate side. The system can test
air blast capacity, refrigerating capacity, consumed
power, electric current, EER (energy efficiency ratio)
and other technical parameters of cooling equipment
accurately. Using the programmable controller as thecore, running equipment can adjust test conditions
automatically during the testing process. Data
collecting, processing, and saving are carried out by acomputer. It can also generate testing reports andanalyze the results by itself. Testing principles of thesystem are shown in Figure 5.

305

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Air-cooled Air-cooled
Air-cooled Air-cooled
chiller unit1 chiller unit2 chiller unit3 chiller unit4

Moisturizing
Stop valvePWindcabinetS

Solenoid valve

M Two-way

Thermostatic
water tankP

Sluice valve
P Pressure gage
M Three-way

regulating valve

regulating valve

Water pumpFlowmeter

Ball valve
Pressuremeasuring-point
Temperature
measuring-point
FilterReducing valve
Safety valve
Butterfly valve
Check valve

M

Outdoorcompressor
condensing unit
Outdoorcompressor
condensing unit

Humidifier
Heating coil pipe

Evaporation coil pipe

Outdoortesting cell

Overflow

Outdoor air
processor

Overflow

Surface cooling coil pipeWind tunnel

Indoor air
processor

Heating coil pipe
Evaporation coil pipe

Pollutiondischarge

TestedmachineHumidification coil pipe
Humidifier

Humidification coil pipe

TestedmachineOverflow

Surface cooling coil pipe
Pollutiondischarge

Indoortesting cell

Pollutiondischarge

Humidifier

Indoorcompressor
condensing unit

Overflow

Heating coil pipe
Evaporation coil pipe

Outdoor air
processor

Humidification coil pipe

Humidifier

Pollutiondischarge

P
Outdoorcooling towerP
Indoorcooling tower

Figure 5: Testing principle of the enthalpy difference test
system.

In accordance with the relevant procedures,
performance testing of the refrigerating equipment

was carried out. Calculating data and results areshown in Table 3 and Figure 6.
As shown in Table 3 and Figure 6, refrigerating
capacity and other performance indexes of thecooling equipment all satisfy the design values. The
performance is good and stable. The coolingequipment is portable, so it can be moved easily andquickly with the help of a mine platform lorry. Thiscan save a lot of time because it is not necessary to
add refrigerating fluid repeatedly after each move.
With this equipment, we can implement effective
cooling to mining and driving work face and otherlocal thermal environments.

Table 3: Calculating data and results of ZLS-90 mine explosion-proof refrigeration unit.
items
unit
NO1
NO2
NO3
NO4
NO5
air quantity
m3/h
18065.330 18063.747 18071.212 18076.135 18074.847
heat exchange ofkW
112.884111.136112.282
112.801112.185
air side
heat exchange ofkW
121.733
121.712121.850
121.592
122.080
water side
input power
kW
30.10630.09430.09730.09330.098
COP
kW/kW
8.771
8.683
8.744
8.775
8.739
deviation
%
7.904
9.561
8.578
7.850
8.855
water resistancekPa
26.04726.07026.10326.07426.054
sensible heatkW
37.90637.12037.58037.21836.674
latent heatkW
74.97974.01574.70275.58375.511
inlet air enthalpy
kJ/kg
91.03990.83291.11691.22491.535outlet air
kJ/kg
70.91971.01971.10771.12871.537enthalpy

NO618072.565

NO718081.917

result18072.251

112.539113.016112.406

122.169

122.121121.89430.0808.768
8.710
26.05737.15075.38891.61830.0948.787
8.087
26.12736.35576.66191.84730.0958.752
8.506
26.07637.14375.26391.31671.55571.70771.282The heat collector is connected to the discharging
port of the movable refrigeration unit. The
evaporation zone of the heat-rod is inserted into theheat collector. In that case, the condensation heat in
the heat collector can be discharged to the upper
space or surface by the heat-rod. Finally, the heat canbe used synthetically.

6. CONCLUSION
Figure 6: Performance test curves of ZLS-90 mine
explosion-proof refrigeration unit.

5. MINE CONDENSING HEAT EMISSIONSTECHNOLOGY
There are currently three primary types of minecondensing heat emissions to local cooling underwells: heat discharging by water, heat discharging bywater and fresh air, and heat discharging by waterand ventilation air methane (Zhou T et al., 2012).
There are some problems, such as being difficult todischarge or having a high failure rate of thedischarging device. In view of this, we proposed todischarge condensation heat by heat-rod technology.

Through the above research, we can come to thefollowing conclusions:(1) Heat disaster coal wells are mainly
distributed in Central China, East China, Northeast
and North China. The rest are scattered in West andSouth China.
(2) For most of the mines, heat emitting fromsurrounding rock, electromechanical devices, and hot
water are the main factors that cause heat disaster.
(3) The ZLS-90 mine explosion-proof
refrigeration unit was designed to cool local hightemperature environments. It is the ideal equipment
to improve local thermal environments and has theadvantage of being lightweight to move, having low
energy consumption, stable properties, good cooling306

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

effects and it is not necessary to add refrigerating
fluid repeatedly after each move.
(4) Using heat-rod technology to discharge minecondensing heat, it is simple in craft, convenient,
swift, long in service life, and good in its discharging
effect.

7. ACKNOWLEDGEMENT
The authors gratefully acknowledge foundation
by International Cooperation in Science andTechnology Special Project (2015DFR70900),
Technology Innovation Fund of China Coal ResearchInstitute (2010CX09).

8. REFERENCES
Abdelaziz EA, Saidur R, Mekhilef S. (2011) A
review on energy saving strategies in industrial sector.
Renew Sust Energy Rev. Volume 15, pp. 150-168.
Cao Q K, Zhang S H, Yang W. (2010) Deepmine cooling and geothermal resource utilization.
Journal of Liaoning Technical University(Natural
Science). Volume 29, Supp 1, pp. 40-42.
Cao X L. (2010). Deep mine high temperature
heat hazard resourceful utilization technology in
Sanhejian coal well. BeiJing, China University of
Mining and Technology.
Feng D Q, Zhao X D, Chen Z. (2013)
Application of local cooling technology in deepmining of Xuzhuang Coal well. Industry and Mine
Automation. Volume 39, No. 3, pp. 92-97.
Feng X L, Chen R H. (2005) Research andDevelopment on Air-cooling in Deep Hightemperature Mines at Home and Abroad. Yunnan
Metallurgy. Volume 34, No. 1, pp. 7-10.
Gangopadhyay, P. K., Dutt-Lahiri, K. (2005)
Detecting Coal Fires with Remote Sensing: A
Comparative Study of Selected Countries , Resource
Management in Asia-Pacific Region (RMAP)
Working Paper No. 58, RMAP Program, Research
School of Pacific and Asian Studies. The Australian
National University, Canberra, ISSN- 1444.
Hughes A, Howells MI, Trikam A, Kenny AR,
van Es D. (2006) A study of demand-side
management potential in South African industries. In:
Proceedings: Industrial and commercial use of energy(ICUE) conference, August, Cape Town.
Li H J. (2009) Technology for Air Control in
Coal well Cooling. Warm Circulating and Air
Control. No. 6, pp. 43-45.
Nimaje D. S., Tripathy D. P. (2010) Thermal
Studies on Spontaneous Heating of Coal. The Indian
Mining & Engineering Journal. p. 10.
Singh, R. V. K., Singh, V. K. (2009) Status of
Mine Fire of Jharia Coalfield and Suggestions forPrevention and Control. National Seminar on

Reinventing Jharia Coalfield, MGMI, Dhanbad
Chapter.
Vosloo J, Liebenberg L, Velleman D. (2012)
Case study: energy savings for a deep-mine water
reticulation system. Apply Energy. Volume 92,
pp.328-35.
Wu J T, Chen X M, Xia J. (2010) Research andApplication of Mobile Refrigerator to Deep Mine
Temperature Reduction. Coal Science andTechnology. Volume 38, No. 10, pp. 86-88.
Xin S etc. (2011) Prevention and Cure of Heat
Disaster in Coal Wells. Beijing, Coal Industry
Publishing House, 216 p.
Xin S, Fu H L, Yan X Y. (2012) New Designing
Idea of Centralized Cooling System for Coal Well.
Safety in Coal Wells. Volume 43, No. 3, pp. 60-63.
Yang D D. (2013) Research on feature ofthermal disaster and the control effect in zhuji coalwell. An Hui, AnHui University of Science andTechnology.
Zhang L, Chen S, Yu F. (2009) Several mine
cooling technologies. Shandong Coal Science andTechnology. No. 3, pp. 152-153.
Zhou T, Xiang D, Chen Y H, etc. (2012)
Engineering practice and discussion on condensing
heat emission during local cooling engineering.
China Coal. Volume 38, No. 12, pp. 90-94.

307ISMS 2016

Paper No. 151

Effect of forming technology on oxygen supply performance of oxygen candles
in refuge spaces
Liu Jian-guo, Jin Long-zhe, Gao Na*, Wang Wei-xiang, Shen Jie
Civil and Environment Engineering School, University of Science and Technology Beijing, Beijing, China, 100083

ABSTRACTThe present study investigated the forming technology of oxygen candles in a refuge space, for a more stable andreliable oxygen supply. Chlorine was found in the wet pressing process, revealing that dry pressing has a better
forming effect on oxygen candles. Three types of oxygen candle blocks (OCBs) were pressed through dry pressing
at pressure-application speeds of 0.1, 0.3, and 0.5 kN/s, respectively, for a pressing time of 10 min. Fromcompression strength and combustion experiments, the ultimate compressive strengths (UCS) obtained for the three
OCBs were 3.83, 5.48, and 5.83 kN. The stability coefficients of oxygen production (SCOP) were U1 = 0.966, U2 =0.724, and U3 = 0.770. From the results of these experiments and observation of combustion residue of OCBs, it was
found that the stability of oxygen production decreases when the pressure-application speed within an appropriatepressure range is increased.
KEYWORDS: Oxygen candle; forming technology; dry pressing; pressure-applying speed;sStability of oxygen
production

1. INTRODUCTION
In China, the current mode of oxygen supply to
refuge spaces is through conventional forced air
systems or compressed oxygen cylinders (Gao et al.,2012). However, in forced air systems oxygen is
supplied through underground pipe networks, whichusually have poor independence, as they might be
destroyed in big mine accidents. Furthermore,compressed oxygen cylinders require regular
maintenance, and are prone to quick discharge or
explosions when exposed to high temperatures or fire
(Jin et al., 2015). With technological developments
regarding refuge spaces in China, the use of oxygen
candles as an emergency oxygen source has attracted
the attention of many scholars.
Oxygen candles are a type of oxygen supply
equipment that releases oxygen through chemical
reactions using chlorate or perchlorates as the source
material. They have several advantages such as easeof use, large oxygen storage capacity (OSC), and fast
oxygen production (Wang et al., 2010). The working
principle of oxygen candles is the release of oxygen
through thermal decomposition of chlorates (Fan etal., 2006). The decomposition reaction of chlorate isshown in equation (1):(1)
where M is a type of alkali metal.
The heat required for the decomposition ofchlorate is provided by the combustion of metal
powders, such as iron powder and magnesium*Corresponding author – email : aggie198308@163.com

powder. The reaction for the combustion ofmagnesium is shown in equation (2):(2)
At high temperatures or in the presence of
impurities, a small amount of chlorate decomposes
and releases chlorine, as shown in equation (3):(3)
After passing through a filter material, theoxygen is directly released into the refuge space.
Wang et al (2010) studied chlorine suppressants andchlorine gas filtering materials for oxygen candles.
Zhang et al. (2013) studied the adsorption propertiesof carbon monoxide in emergency refuge facilities.
Furthermore, Gao et al. (2015) studied an oxygen
supply system and purification in a mine refuge
space.
However, considering their use in refuge spaces,
oxygen candles also present some shortcomings, suchas heterogeneous, fast and uncontrollable oxygen
release rate, and concentrated and high heat output
from the reaction. In foreign countries, oxygen
candles were extensively studied during the 1990s,
followed by a systematic study of the catalysts, metal
fuels, combustion fluctuations in oxygen candles, andthe effect of particle size on combustion
performance. In China, (Jin et al., 2014; Jin et al.,2015; Wang et al., 2014) the characteristics ofoxygen supply in refuge spaces and the effect of M
(M = catalysts, formula, candle structure) on oxygen3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016supply performance (OSP) of oxygen candles werestudied through thermogravimetric analyses andorthogonal experiments (Zhang et al., 2013).
However, effective research is still lacking regarding
the effect of forming technology on the OSP ofoxygen candles.
In this study, the influence of different forming
technologies on the OSP of oxygen candles wasinvestigated by changing the forming technology,pressure-application speed, and holding time. The
results have important significance in improving thestability and reliability of oxygen candles regarding
OSP.

Zhong ShengZhou Mine Technology Center), whichis shown in Figure 1b, and the dates were recorded
using the KJ70N system in a computer.

2. EXPERIMENT
2.1 Experimental Apparatus
A ball mill (KE-2L Planetary ball mill, Qidong
HONGHONG Instrument Equipment Factory, China)
was used to crush the components. Three oxygen
candle blocks (OCBs) were prepared using a stainlesssteel die, which was designed and fabricated in-house(dimensions: 160 mm long，60 mm ID，80 mm
OD), and an oil press (YES-300, Jinan Huaxing
Testing Machine Co., Ltd., China).
After wet pressing, the OCBs were dried in an
incubator (WM-BD temperature incubator, Shanghai
Weiming Electronic Mechanical Equipment Co.,
Ltd., China).
The OCBs were subjected to reactions in asealed chamber, which was also developed in-house(600 × 600 × 600 mm), as shown in Figure 1a.
Oxygen concentration in the sealed chamber wasmonitored in real time using a mining
multi-parameter measuring device (CD7, Beijing

Figure 1: Sealed chamber and CD7 mining multi-parametermeasuring device.

Details of the chemicals used in the experiments
are provided in Table 1.

Table 1: Chemicals used in the experiments.
Chemicals

Mol.wt.

Grades of purity(China)Manufacturer

Sodium chlorate (NaClO3)
Manganese (Mn)
Cobalt(Ⅲ) oxide (Co2O3)
Kaolin106.4454.94
165.86258.16

EP
2N
2N
CP

Sinopharm Chemical Reagent Co., Ltd.
Johnson Malthey Chemicals Ltd.
Shanghai Fengshun Fine Chemicals Co., Ltd.
Sinopharm Chemical Reagent Co., Ltd

2.2 Methods
Dry pressing and wet pressing experiments:
The components (86.22% NaClO3, 5.88% Mn, 4.90%
Co2O3, 3% kaolin) (Jin et al., 2015) were processedin the ball mill for 5 min (particle size ≤ 100 μm),
and a powder was obtained. In the dry pressing
experiment, 145 g of the powder was placed on thestainless steel die, and subjected to a pressure of 35
kN at a pressure-application speed of 0.1 kN/s, andthen the pressure was held for 5 min. They were thenunloaded, and dried at 60°C for 12 h. Finally, theblocks were observed and their physical parameters

were measured. In the wet pressing experiment, 5 ml
and 10 ml of water were added to two groups of thepowder weighing 145 g each and stirred
homogeneously. The following processes were thesame as in dry pressing.
Pressure-application speed and holding time
experiments: in this study, three pressure speeds
were defined, including slow pressing (0.1 kN/s),
medium pressing (0.3 kN/s) and rapid pressing (0.5kN/s). Three groups of the powder each weighing
145 g were subjected to slow pressing, medium
pressing, and rapid pressing, and after reaching the309

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

target pressure (35 kN), it was maintained for 10 min(Table 3). They were unloaded and their physicalproperties were measured. Later, the combustion
experiment was conducted in the sealed chamber, inwhich oxygen concentration was monitored in realtime using the CD7. The experiment was stopped
until the oxygen concentration no longer increased,
and then the combustion residue of OCBs wereobserved. Finally, the OSP of all OCBs wasdetermined.
2.3 Data processing
Processing
of
data
from
the
pressure-application speed and holding time
experiment: Complete pressing time of the oxygen
candles is equal to the sum of the holding time andpressing time, as shown in equation (4):tc = tp + th(4)
where tc is complete pressing time of oxygen candle,
tp is pressing time, and th is holding time.
Oxygen concentration can be determined using
CD7, and the growth rate of oxygen concentration
per second can be calculated by equation (5):VX1-X2 = ( CX2 - CX1) / CX1(5)
where VX1-X2 is the growth rate of oxygen
concentration from time X1 to time X2 (X2 - X1 =1), and CX1 and CX2 are the oxygen concentrations attime X1, and X2, respectively.
In this study, U is defined as the stability
coefficient of oxygen production (SCOP), and isexpressed in equation (6):2
1
U = arctan |(6)|𝜋

3. RESULTS AND DISCUSSION
3.1 Dry pressing and wet pressing experiments
In the dry pressing and wet pressing
experiments, pressure-application speed was 0.1
kN/s, the target pressure was 35 kN, holding time
was 5 min, and the OCBs were dried at 60°C for 12
h. As shown in Figure 2, after drying, a number ofirregular cracks appeared in the surface of
wet-pressed OCBs with slight expansions in upperand lower bottom parts. The color of the wet-pressed
OCBs was darker than that of dry-pressed OCBs.
During wet pressing, surface temperature of the
OCBs was increased, and trace amounts of chlorine
was detected. Through compression strength
experiments, the density and ultimate compressive
strength (UCS) of W1 and W2 were found to besignificantly higher than that of D1, as shown in
Table 2. In addition, although the density was similar
between W1 with W2, the UCS of W2 was higher
than that of W1.

Figure 2: Dry-pressed and wet-pressed OCBs.

𝑉X1−X2 −𝑉X2−X3

A larger value of U indicates more stableperformance of oxygen production. The value of U
lies between 0 and 1.
Table 2: Parameters of dry-pressed and wet-pressed OCBs.
Pressure
Pressurized
Quantity
HighlyDensity × 10-3
MCS
Number/kN
speed /kN/s/g/mm/g·mm-3
/kN
D1
35
0.1
144.06
28
1.821
2.87
W1
35
0.1
145.04
22
2.333
24.81
W2
35
0.1
139.34
21
2.348
32.46
Note: D1 is the dry-pressed OCB; W1 is the OCB with 5 ml of added water; W2 is the OCB with 10 ml of added water.

The UCS of the wet-pressed OCBs was higher
than that of dry–pressed OCBs.
However, asconstant heat is required for drying, the wet pressing
process requires a longer time. In addition, thedistribution of internal pores are heterogeneous after
drying since it is difficult to mix the powder andwater homogeneously, leading to differences in theamount of water inside the OCB. Homogeneous
pores were produced after the water evaporated
during the drying process. In addition, the powderappeared to react with water because the surface
temperature of the aqueous powder was clearly

increased and trace amounts of chlorine weredetected. This is not only harmful but also reduces
the effective oxygen occlusion amount and theperformance of OCBs. Consequently, dry pressing is
considered to have a better forming effect.
3.2 Pressure-application speed and holding time
experiments
As shown in Table 3, the density of OCBs,
pressed at different pressure-application speeds for aconstant complete pressing time, showed a slightincreasing
trend
with
increasesin310

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016pressure-application speed. The pressure-application
speed had little effect on the density of the oxygen
candle. As shown in Figure 3, the UCS of the three

OCBs were 3.83 kN, 5.48 kN, 5.83 kN, and there wasa positive correlation between the UCS of OCBs,
pressure-application speed, and holding time.

Table 3: Parameters of OCBs in the pressure-application speed and holding time experiments.
Pressurized speed/
Pressure time
Holding time
QualityHighlyNumber
KN/S
/min
/min
/g
/mm

Density/×10-3
g·mm-3

1

0.1

5.8

4.2

144.50

29.0

1.762

2

0.3

1.9

8.1

144.65

29.0

1.764

3

0.5

1.1

8.9

144.71

28.9

1.771

0.6
Increased rate of oxygen
concentration

7.0
6.0

Pressure/KN

5.0
4.0
3.0
2.0

0.0
0

10 Time/s 20

35.0
32.5

C(O2)/%

30.0
27.5
25.0
22.5

15.0

0
3-4

30

The results of the combustion experiment are
shown in Figure 4. Oxygen concentration began torise from 2 s and reached the highest at 4 s, and thenit remained fluctuating at around 31%. Note that themain reaction occurred between 2–4 s. The growthrate of oxygen concentration was calculated, and theresults are shown in Figure 5. According to theresults, U1 = 0.966, U2 = 0.724, and U3 = 0.770.

17.5

No.1
No.2
No.3

Time interval
Figure 5: Velocity diagram of oxygen concentrations in asealed chamber.

Figure 1: Experimental curves of compressive strength.

20.0

0.2

2-3

No.1
No.3
No.2

1.0

0.4

No.1
No.2
No.3

0 1 2 3 4 5 6 7 8 9 10 11 12
Time/S
Figure 2: Oxygen concentration curve in a sealed chamber.

After the reaction was complete and the OCBs
cooled to room temperature, the asbestos clothwrapped around the OCBs were removed, and the
OCBs were cut along the diameter, as shown in
Figure 6. According to the observation of thesections, OCB No. 1 was completely burnt, andhomogeneous holes were distributed across the burnt
area in the shape of an upright cone. The burnt areaof OCB No. 2 was small and distributed withheterogeneous holes. The combustion area of No. 3
was even smaller than that of No. 2 and wasconcentrated around the center of upper part;
heterogeneous holes were also observed. In addition,
caking was also observed in the right part of OCB No.
3.
During the entire process, not only did the shapeof powder particles change, but the volume anddensity also changed constantly (Yu et al., 2000).
In pressing processes, friction exists between themold wall and powder particles, as well as between
individual powder particles. The friction between
powderparticles
increasedwhenthepressure-application speed was increased, andconsequently, powder flow ability was decreased.
This resulted in increased pressure loss andheterogeneous distribution of density in the OCBs.
This is the main reason for the larger andheterogeneous holes that occurred in the combustion
area of OCBs No. 2 and No. 3 and also for the caking
in the unburned area in OCB No. 3. In addition,

311

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 6: Photographs of OCBs after combustion

although a long holding time can enhance thephysical properties of the OCBs, the air between
powder particles is reduced, and the average distance
between powder particles is decreased. As such, theeffective area of combustion decreases, weakening
the heat absorption capacity of unburned areas. The
decomposition reaction of sodium chlorate powder
stops without adequate heat, resulting in the large
unburned areas in OCBs No. 2 and No. 3. According
to the value of SCOP and observation of combustion
residue of OCBs, the collating sequence of
combustion stability is No. 1 > No. 2 > No. 3.
From the experiments, the following conclusion
can be drawn: in dry pressing, the physical propertiesof oxygen candles can be improved by increasing thepressure-application speed and holding time.
However, the rate of oxygen production isinconsistent, Furthermore, long holding times will
increase the density of oxygen candles, reduce heattransfer capability, and eventually lead to a stop in
the middle of the reaction.

Fundamental Research Funds for the Central
Universities (FRF-TP-15-043A3), and the China
Postdoctoral Science foundation (2014T70039,
2013M540666).

4. CONCLUSIONS

7. REFERENCES

Through dry pressing and wet pressing
experiments, this study revealed that the dry pressingof oxygen candles has a better forming effect. The
UCS and SCOP of the OCBs, pressed atpressure-application speeds of 0.1 kN/s, 0.3 kN/s, and
0.5 kN/s, were 3.83 kN, 5.48 kN, and 5.83 kN and U1= 0.966, U2 = 0.724, and U3 = 0.770, respectively.
From the observation of combustion residue, it can beconcluded that increases in the pressure-application
speed, within an appropriate pressure range,
decreases the stability of oxygen production.
Further research will focus on optimizing thepressing process of oxygen candles throughquantitative
studiesontargetpressure,pressure-application speed, and holding time.

Fan, M., Bu, J.J., and Zhen, H,Y. (2006). The
research on actuality and development of oxygen
candle. Ship Science and Technology, Volume 28, No.
2, pp. 16–20
Gao, N., Jin, L.Z., Wang, L., and You, F. (2012).
Research and application of oxygen supply system inChangcun coal mine refuge haven. Journal of China
Coal Society, Volume 37, No. 6, pp. 1021–1025
Gao, N., Liu, J.G., Jin, L.Z., Li, L., Huang, X.,
Zhou, L., and Fan L.L. (2015). Study and experimentof the system of oxygen supply and purification in themine refuge space. Journal of China Coal Society,
Volume 3, pp. 616–622
Jin, L.Z., Wang, Y., Wang, S., and Zhan, Z.N.
(2014). Distribution regularity study of air pressure
supply to mine refuge chambers. Journal of
University of Science and Technology Beijing,
Volume 08, pp. 1007–1012

5. ACKNOWLEDGEMENT
This study was supported by the National
Natural Science Foundation of China (5150417), the

6. NOMENCLATURE
OCB
UCS
SCOP
OSC
OSP
tc
tp
th
VX1-X2CX

oxygen candle block
ultimate compressive strengths
stability coefficients of oxygen
production
oxygen storage capacity
oxygen supply performancecomplete pressing timepressing time
holding time
growth rate of oxygen
concentration from time X1 totime X2 (X2 - X1 = 1)
oxygen concentrations at timeX

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Jin, L.Z., Wang, S., Liu, S.C., and Zhang, Z.
(2015). Development of a low oxygen generation
rate chemical oxygen generator for emergency refuge
spaces in underground mines. Combustion Scienceand Technology, Volume 187, No. 8, pp. 1229–1239
Shafirovich, E., Garcia, A., Swamy, A.N., Mast,
D.J., and Hornung, S.D. (2012). On feasibility ofdecreasing metal fuel content in chemical oxygen
generators. Combustion and Flame, Volume 159, No.
1, pp. 420–426
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Varma, A., Kshirsagar, G., and Ellison, J.E. (2007).
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(2010). Research on application of chlorate oxygen
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313

Paper No. 152

ISMS 2016

Experimentation on a new type of mining emergency rescue relay cabin
Shen Jie*, Gao Na, Jin Long-zhe, Fan Lin-yu, Wang Wei-xiang, Liu Jian-guo
Civil and Environmental Engineering, University of Science and Technology Beijing, Beijing, China, 100083

ABSTRACTThis study designed an innovative mining emergency rescue relay cabin by comparison with existing hedging
facilities with respect to function, service object, structure, size, and system components. The structures and systemsof the emergency rescue relay cabin were designed and implemented. An air-tightness test indicated a test chamber
relief rate of 26 Pa/min, which meets the requirements. Furthermore, an airsleeve air supply test indicated an air
supply rate of 220 L/min, which is sufficient for the staff replacing the equipment in the emergency rescue relay cabin.
The total air supply volume was 9680 L, which can be supplied via two bottles of 40 L, 15 MPa compressed air.
KEYWORDS: Emergency rescue relay cabin; relay cabin site selection; system and structure; tightness test; airsleeve
air supply test

1. INTRODUCTION
The main hedging facilities of existing undergroundemergency systems include fixed refuge chambers andmovable rescue capsules, both of which possess
advantages such as being able to accommodate aconsiderable number of personnel, complete internal
protection systems, and broad security protection
ranges. However, several problems are currently
hindering the application of refuge chambers and rescue
capsules. Among these are long construction time, highusage, operation, and maintenance costs, andconcentrated protection on the work surface in themining area. To resolve these issues, this study
investigated and designed a new type of mining
emergency rescue relay cabin. Compared with existingunderground hedging facilities, the new mining
emergency rescue relay cabin has various advantages,
such as small size, flexible usage, easy installation andtransportation, diversity in protection objects, and low
production cost (Li, 1989; Ni et al., 2013; Wang et al.,2010; Sun, 2011a). Combined with existingunderground hedging facilities, this new type of
emergency rescue relay cabin can achievecomprehensive coverage of the underground hedging
space, not only lowering the cost of building
underground emergency rescue systems, but also
providing timely resources and equipment tounderground hedging and rescue personnel, and both
improving mine rescue efficiency and reducing
casualties.

2. CHARACTERISTICS
2.1 Application feature comparison*Corresponding author – email : Mrshenjie@126.com

The key feature of existing major hedging facilities,
fixed refuge chambers, and movable rescue capsules is
the internal life-support system—the main function ofwhich is to provide a safe space for the hedging
personnel waiting for rescue underground (Moncef etal., 1996). In contrast, the main function of theemergency rescue relay cabin is to provide materials andenergy supply for the mine rescue personnel andhedging personnel so as to ensure the continuity of the
rescue and hedging actions. Overall, the proposed relay
cabin provides temporary protection for the rescue
workers and hedging personnel.
2.2 Comparison of application objects
The application object of existing major hedging
facilities, fixed refuge chambers, and movable rescue
capsules is primarily the underground personnel (Gao etal., 2011; Jin et al., 2012; Sun, 2011b; Gao, 2011). In
contrast, the emergency rescue relay cabin can not only
serve for hedge personnel, but also provide mine rescue
personnel with oxygen bottles, self-help equipment,
food, water, communication devices, batteries, andother essential hedging and rescue energy supplies.
2.3 Structure and dimensions comparison
The average dimensions of a movable rescue
capsule in existing hedging facilities are 23 m × 2.4 m ×
2 m, which can accommodate 30 people. The internal
structure is divided into transition area, living area andequipment area. The average dimensions of a refugechamber for 30 people are 25 m × 4.5 m × 3.5 m. Theinternal structure is divided into refuge chambers on
both sides and the hedging area in the middle. For the
emergency rescue relay cabin to provide energy and3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016supplies for 40 people, the overall cabin dimensions are
only 1.52 m × 1.30 m × 1.77 m, as shown in Figure 1.
The internal structure is divided into battery and powersource area, supply storage area, equipment replacementarea, and communication area, as shown in Figure 2.

Figure 2: Functional compartments of the relay cabin.
Figure 1: Internal structure of the emergency rescue relay
cabin.

The comparison shows that, for the same number ofpeople, the emergency rescue relay cabin has a smaller
size. Further, compared to the movable refugechambers, it can move flexibly along pre-laid tracks by
the roadway, allowing for rescue missions near andabove the work surface, and others near and outside of
the mining area along the roadway.

Table 1: Costs associated with hedging facilities.
Fixed

Items

Relay cabin

Movable rescue capsule

Material cost

263,000

2,000,000

3,000,000

Site Transfor - mation cost

300,000

1,500,000

4,000,000

Daily Maintenance fee /year

55,00097,000150,000

Total

618,000

3,597,000

7,150,000

Ventilation and rest space for more

Hedging

Hedging forthan 40 people

for 30 people

more than 30 people

Number of people

2.4 Comparison of system components
The life-support system of existing major hedging
facilities, fixed refuge chambers, and movable rescue
capsules primarily includes the following: fire andexplosion protection system, closed buffer system, aircurtain isolation system, oxygen supply system, coolingand dehumidifying system, monitoring and control
system, and communications systems (Sun, 2010). The
main function of the emergency rescue relay cabin is toprovide a temporary hedging place and supplies andenergy for the rescuers and endangered workers.
Therefore, its internal systems consist of a basic
protection system, pressure air supply system,
communication and lighting system, supply anddistribution system, and power supply system.
2.5 Construction cost comparison

refuge chamber

The cost of the emergency rescue relay cabin,which includes material cost, site transformation cost,and daily maintenance fee, as listed in Table 1, is far
less than that of current hedging facilities.

3. SYSTEM COMPONENTS
3.1 Exterior structure of the relay cabin
According to the features of the emergency rescue
relay cabin and the condition of the domestic
underground transportation equipment and roadway
sizes, the final shape of the emergency rescue relay
cabin is designed to be rectangular, with specificdimensions of 152 cm × 130 cm × 177 cm. The interior
dimensions of the cabin are 150 cm × 128 cm × 175
cm. The entire relay cabin is steel welded to ensure acertain degree of strength and weight, thereby
preventing cabin body inclination as a result of shock315

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
waves from the side (Han et al., 2011). In addition, thecompressive and tensile properties are good. The frontof the relay cabin has an explosion-proof door and an
emergency switch. Furthermore, necessary interfaces
are set up to enable connection with the outside, such as
the ventilation port connecting to external air supply
devices, water supply port, power supply interface,communication interface, and air vent.
3.2 System components of the relay cabin
The interior of the relay cabin consists of fivesub-systems: enclosed system, air supply system,
resource system, power supply system, and lighting andcommunications system.
Enclosed system. The emergency rescue relay
cabin has relatively low design requirements in terms ofguaranteeing the survival of personnel, but it must
provide protection. The entire cabin body comprises an
enclosed system consisting of the steel shell structure
and the explosion-proof door. The steel shell of thesystem body is built with steel welding technology. The
front panel located in the tunnel and the explosion-proof
door can withstand an impact of 0.3 MPa, and ordinary
shock waves. In addition, the relay cabin has a certain
degree of air-tightness to prevent infiltration of toxic
gases. After the personnel enter the cabin, a positive
pressure of +200 ±100 Pa with a relief rate less than 30±20 Pa/min is maintained, which is slightly less thanthat of refuge chambers and movable rescue capsules.
Airsleeve air supply system. This system ismainly used for personnel to replace supplies. The
airsleeve can be used to cover the upper body to form
positive pressure and prevent poisonous gases fromentering. In addition, the personnel can temporarily
hedge in the airsleeve. There are two oxygen supply
systems for the airsleeve air supply system: compressed
oxygen bottles and external oxygen supply. The overall
air supply system comprises compressed air bottles,
compressed air bottle connectors, external pressure air
ports, pressure regulators, airway, pressure gauge,
muffler, ventilation isolation bag, and oil-water
separator (Zhao et al., 2003; Zhang et al., 2009). The
cabin also has two airsleeves, although only one is used
when the equipment is being replaced. In emergency
situations, both can open to ensure the hedging of two
people.
Resource system. The emergency rescue relay
cabin can be filled with self-rescuer, water, food, andfirst aid supplies based on actual need. In this study, thenumber of emergency rescue personnel and the safety
factor were set to 40 and 1.2, respectively.
Self-rescuer. The emergency rescue relay cabin
has 50 chemical oxygen 45 self-rescuers (with a safety
factor of 1.2) meeting the equipment replacement
requirement of 40 people. The rescuers are placed on

the window. A consistent model specification for each
rescuer and field worker is maintained. The emergency
rescue relay cabin can also be used as a complementarymine warehouse to assure routine replacement (Gao etal., 2012; Jin et al., 2012).
Water and food. The emergency rescue relay
cabin should have enough water and food fortwo people to use for four days (with a safety factor of
1.5). The cabin should contain 30 L of purewater. Further, the port is connected to the external
water supply, which provides a significant amount of
potable water. Referring to the relevant standards, theemergency energy intake should be above 2000
KJ/day·per person; the shelf life should be no morethan three years. Further, 3 kg of emergency foodshould be stored in the compartment to provide food for
emergency hedging personnel.
First aid supplies. Essential rescue supplies
should be stored in the relay cabin, such as
explosion-proof flashlights and explosion-proof
batteries, for rescue workers to replace the rescue
equipment and, thereby, increase the scope and time ofrescue. According to the actual situations, the cabin canalso store toolboxes, first aid kits, medicines, and theequipment required in emergency situations.
Power supply system. In the emergency rescue
relay cabin, equipment such as lighting andcommunication devices require electricity supply. The
power storage has two explosion-proof power supplies(one is the backup power supply); battery life ismonitored regularly to ensure its electrical storage
capacity. At the same time, an external electricalconnection port is setup to ensure external power
supply.
The provided power supply needs to guarantee four
consecutive days of electricity supply.

4. EXPERIMENT AND ANALYSIS
A relay cabin air-tightness test and airsleeve air
supply test were conducted in accordance with thedesign requirements for a closed air supply system.
4.1 Relay cabin air-tightness test
This test determined the cabin air-tightness
performance by varying the gas pressure in the cabin.
Method. A compressed air bottle was connected tothe air ventilation port of the cabin, and pressure sensor
testing devices connected in the cabin; the pre-drilledholes in the cabin body were sealed with leak-proof
mud. The monitoring and control system were thenturned on, the data parameters adjusted, and the door
closed. This was followed by the opening of the airbottle valve and injection of air into the cabin at a
uniform rate of 1.5 L/min. Throughout the process, thecabin pressure was monitored using pressure sensors.
When the cabin pressure rose to 500 Pa, the CO2316

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
cylinders were switched off and the pressure recorded
every 20 s until the pressure dropped by 100 Pa, that is,
400 Pa higher than the initial value. The test was
repeated five times and the pressure relief rate
calculated.
Conclusion. As shown in Figure 3, the pressure
relief rate can be obtained using the equations
y = -0.4334x+500, R² = 0.930 (1)Conclusion. It can be concluded from Figures 4
and 5 that when the rate is 190 L/min, the time needed toreduce the carbon dioxide concentration to 1% isapproximately 54 s. From the formula:V = kStx(2)
where: V is the amount of air required, k is the safety
factor, S is the aeration rate, t is time, x is the number ofpeople.
The required amount of air is 10260 L.
According to Figures 4 and 5, at an aeration rateof 220 L/min, the time needed to reduce the carbon
dioxide concentration to 1% is approximately 44
s. According to the Formula 2, the required amount of
air is 9680 L.

Figure 3: Pressure variation over time.

The pressure relief rate per minute calculated fromthe formula is 26 Pa, which meets the design
requirements. The design models are therefore qualified
and can be used as the carrier of the airsleeve air supply
test.
4.2 Airsleeve air supply test
The airsleeve air supply test replaces poisonous
gases with carbon dioxide, thereby determining theamount of compressed air needed to replace theequipment.
Method. The CO2 cylinders, carbon dioxide
detectors, sensors, cameras, and corresponding pipes
were connected. The carbon dioxide detectors wereplaced in isolation airsleeves, simulating human head
position, and the flowmeter inserted into the airsleeve.
One camera was then focused on the meter reading, andanother on the carbon dioxide detector readings. Finally,
the cabin door was shut, the carbon dioxide cylinder
valve opened, and carbon dioxide injected at a uniform
rate through the backup port into the cabin. When theconcentration of carbon dioxide in the airsleeve reached2%, the carbon dioxide cylinder valves were adjusted tomaintain the carbon dioxide concentration at 2%. The
compressed air bottle was then connected to an external
air vent, the gas-regulating flowmeter opened to a flowrate of 190 L/min, and the time, T1, recorded.
Subsequently, the carbon dioxide concentration wasrecorded once every five seconds and, when the carbon
dioxide concentration had fallen to 1%, the isolation
airsleeve valve was closed and the test terminated. The
above steps and test were again repeated with a flow rateof 220 L/min. Finally, the test data were exported tofacilitate calculation of the wind pressure and enable thecorrect wind pressure rate to be chosen.

Figure 4 Carbon dioxide concentration-time curve for a rate of
190L/min.

Figure 5 Carbon dioxide concentration-time curve for a rate of
220 L/min.

Because of the small amount of air required at the
supply rate of 220 L/min, 220 L/min was selected as the
final aeration rate, with two bottles of 40L compressed
air used to meet the requirements.

5. CONCLUSIONS
The main difference between the mining
emergency rescue relay cabin and existing hedging
facilities are as follows: From the perspective offunction the former focuses more on providing a safe
environment for the rescuer and hedging personnel toreplace equipment and supplement supplies, it can serveboth rescue workers and hedging personnel, and thestructure and dimensions are simpler and more flexible.
In addition, it is more streamlined in terms of systemcomponents.
The exterior dimensions of the emergency rescue
relay cabin are 152 cm × 130 cm × 177 cm. The cabinconsists of five sub-systems: enclosed system, air317

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016supply system, resource system, power supply system,
and lighting and communication system.
The pressure relief rate of the relay cabin wasdetermined to be 26 Pa/min via a relay cabin
air-tightness test. The result obtained meets the
stipulated air-tightness requirements.
The air supply rate for the personnel to replaceequipment in the emergency rescue relay cabin wasdetermined to be 220 L/min via the airsleeve air supply
test. The total air supply volume was 9680 L. This air
supply volume requirement can be satisfied using
two bottles of 40 L compressed air, which is in line withthe relay cabin space-saving size requirements.

6. ACKNOWLEDGEMENT
This work is financially supported by the National
Natural Science Foundation of China (No. 51504017),
the Fundamental Research Funds for the Central Universities (No.FRF-TP-15-043A3), the China Postdoctoral
Science Fundation (No.2014T70039), the Doctor
Science Research Foundation of the Education Ministryof China (No.20130006120020), the China Postdoctoral
Science Fundation (No.2013M540666),
which is gratefully acknowledged.

Sun, J.P. (2010). Personnel Position Monitoring
Technology and System in Underground Mine. Coal
Science and Technology, Volume 38, pp. 1-4
Sun, J.P. (2011a). The key technologies of the
refuge chamber and rescue capsule in the undergroundcoal mine. Journal of China Coal Society, Volume 36,
pp. 713-717
Sun, J.P. (2011b). Research on emergency refuge
system in underground mine. Coal Science andTechnology, Volume 39, pp. 69-71
Wang, S., Jin, L.Z., Li, J. (2010). The present statesof overseas mine emergency refuge chamber
technology. Journal of Safety Science and Technology,
Volume 6, pp. 119-123
Zhang, D.M., Ma, Y.D., Ding, Y.D. (2009).
Research and design of mine refuge chamber. Journal of
Safety Science and Technology, Volume 5, pp. 94-98
Zhao P.S., Hu, J.F. (2003). Status Analysis on
Rescue Technology and Equipment for Personnel in
Difficult in Underground Mine. Coal Science andTechnology, Volume 34, pp. 33-36

7. REFERENCES
Gao, N., Jin, L.Z., Wang, L., You, F. (2012).
Research and application of oxygen supply system inChangcun Coal Mine refuge haven. Journal of China
coal society, Volume 37, pp. 1021-1025
Gao, N., Jin, L.Z., You, F., Wang L. (2011).
Research and experiment on fireproof anti-explosion air
tightness system of refuge haven in underground mine.
Journal of China Coal Society, Volume 37, pp. 132-136
Gao, N. (2011). Research and Application of the
Key Technology of the Permanent Refuge Haven of
Changcun Coal Mine. Beijing: School of Civil andEnvironmental Engineering University of Science andTechnology Beijing.
Han, H.R., Jin, L.Z., Gao, N., Wang Y. (2011).
Study on confined positive pressure system in mine
refuge station. Journal of Safety Science andTechnology. Volume 7, pp. 89-93
Jin, L.Z., Zhao, Y., Gao, N., You F., Wang L.
(2012). Study on oxygen supply system of mine refuge
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Li, R.S. (1989). Mine refuge chamber. Yunnan
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Krarti, M., Kreider, J. F. (1996).Analytical Modelfor Heat Transfer in an Underound Air Tunnel. Energy
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Refuge Chamber Construction of Coal Mine. Coal
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318

ISMS 2016

Paper No. 186

Chemical equipment failure probability correction model based on the Multilayer Grey Evaluation Method
Yue Zhanga, Wentao Yanga, Yuanyue Zhua, Kai Zhangbab

Safety Evaluation Center, China Academy of safety Science and Technology, Beijing, China, 100012
Special Grease Chemical Plant, Henan Jiaozuo Coal Energy Co.,Ltd, Jiaozuo, China, 454000

ABSTRACTAt present, the role of basic leak probability of chemical equipment cannot be distinguished from the influence ofmany other factors on failure probability in the petrochemical field. Due to the defects in other methods, in thisstudy, by applying Analytic Hierarchy Process (AHP) and introducing grey theories, the chemical equipment failure
probability correction model based on the multi-layer grey evaluation method was proposed. By applying AHP, six
first level indicators including safety management, production equipment, process, production environment, naturalenvironment, and personal quality were analyzed, as well as twenty-seven second level indicators. The influence ofvarious factors in the chemical equipment failure system was obtained. Then, the correction factor value wascalculated according to grey system theories, and the correction coefficient was applied to correct the failure
probability. By taking a vinyl chloride tank of a chlor-alkali company as an example, the results indicated that thecorrected factor value of failure probability for the tank was 3.335, the correction coefficient was 1.25, and theactual failure probability of the tank was larger than the basic leak probability. This method provides a new way tomeasure the failure probability correction, and has a theoretical significance and practical value on accurate
calculation of the quantitative risk evaluation.
KEYWORDS: chemical equipment; failure probability; multi-layer grey evaluation method; whitening weightfunction; index system

1. INTRODUCTION
With the development of China's industrial
economy, the safety situation of the petroleum
chemical industry is becoming more and more
serious (Wu, 2008). Therefore, quantitative risk
assessment in the petroleum chemical industry is very
important. The core of quantitative risk assessment is
the fitting together of the accident occurrence
probability and the accident consequence. The
accuracy of chemical equipment failure probabilities
can greatly affect the rationality and applicability ofquantitative risk assessment results. At present, thestatistical data of basic leak probabilities in the
petroleum chemical industry are mainly from abroad,which generally represent the industry, but do notreflect actual failure probabilities of particular plants.
The equalization of statistical figures makes effects
of many factors on failure probabilities
indistinguishable; therefore, these defects must be
corrected.
Although the calculation of failure probabilities
has been realized to a certain degree in the literature(Shi et al., 2011; American Petroleum Institute, 2000;
Qingdao Safety Engineering Institute of SINOPEC,
2007; Zhu, 2005; Liu and Li, 2007; Koutsourelakis etal., 2004; Au and Beck, 2001; Yuan et al., 2007), the*Corresponding author – email: zhangyue032@163.com

current methods are subject to many problems, suchas: some methods completely depend on experiences,calculation processes are too simple, the index
systems are not comprehensive, indicators are notprimary or secondary, and calculation processes arelong and complicated in order to improve calculation
accuracy. For these reasons, they could untruthfullyreflect actual failure probabilities of chemical
equipment, especially where there are greater
differences in the aspects of personal quality,
production
equipment,
process,
production
environment, and safety management.
Because the main chemical equipment of
petroleum chemical industries are large scale, highspeed, and complex, internal factors and risks are
only partially known. Therefore, it is very difficult torealize objectivity by applying traditional methods.
The method proposed in this study calculates failure
probability correction by the multi-layer grey
evaluation method, which combines the advantagesof AHP and the grey evaluation method, and has
better adaptability for complex systems with distinct
layers. This method not only makes full use ofexisting information and focuses on internal
connections among behavioural data in the internal
system, but also effectively corrects the lack of asingle evaluation method. This makes evaluation

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

results more accurate (Liu et al., 2004; Huang et al.,2015). Basing on the multi-layer grey evaluation
method, the multi-layer grey evaluation model of thechemical equipment failure probability correction
factor was established, and the model application was
illustrated with examples.

2. THEMULTI-LAYERGREY
EVALUATION
MODEL
OF
THE
CHEMICAL EQUIPMENT FAILURE
PROBABILITY CORRECTION FACTOR
2.1 Establishing evaluation index systems

According to accident analysis theories (He etal., 2000; Tian and Jing, 2009; Xu et al., 2012), andby combining properties and environment conditionsof chemical equipment, the evaluation index systemof the chemical equipment failure probability
correction factor was established.
Through the investigation of some petroleum
chemical production plants, and by combining withthe analysis situations of investigated relevant safety
accident statistics, as well as expert investigation,practical experiences of safety, and environmental
protection staff and technicians, the comprehensive
evaluation index system of the chemical equipment
failure probability correction factor was established,
as shown in Figure 1.

Chemical equipment failure probability
correction factor (U)Safety management(U1)

Production equipment(U2)

Process(U3)

Production environment(U4)

Natural environment(U5)

Personal quality(U6)

Safety production
responsibility system (u11)Equipment design(u21)

Process continuity(u31)

Plant layout (u41)

Bad weather (u51)Personal skill andexperience (u61)Equipment
manufacture (u22)Process stability(u32)

Vibration and noise
control (u42)Earthquake (u52)Personal safety
consciousness (u62)

Safety protection
system (u23)Process
advancement (u33)

Safety production education(u12)
Safety technology measureplan (u13)Safety production inspection(u14)
Safety production rules andregulations (u15)
Safety production management
institution and personnel (u16)

Accident statistic andanalysis (u17)Daylighting and artifitiallighting condition (u43)Personal physicalcondition (u63)Personal psychologicalstatus (u64)

Monitoring system(u24)
Equipment usage
condition (u25)Equipment repair
and maintenance(u26)

Hazard evaluation andrectification (u18)
Emergency plan and measure(u19)

Figure 1: The chemical equipment failure probability correction factor model.

2.2 Determining weights of evaluation indictors
The influence of factors on evaluation objects(chemical equipment failure probability correction
factors) was reflected by the weight set of evaluation
indicators. In this paper, by using AHP, the judgment
matrix was constructed by applying the scaling value
method, and weight values of factors were calculatedby the asymptotic normalization coefficient.

2.3 Set scoring criteria of evaluation indicators
Evaluation index grades were divided into “low”,“general”, “higher”, “high” and “very high”.
Corresponding values were 1, 2, 3, 4 and 5,
respectively. When the index grade was between
adjacent grades, the corresponding score values were1.5, 2.5, 3.5 and 4.5, respectively.

320

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2.4 Organizing evaluation experts to score andestablish evaluation sample matrixes
The evaluation expert number was supposed k,
k=1,2,3,…,p , that was to say, there were p evaluation
experts. According to the scoring criteria, the pevaluation experts were organized to score theevaluation index uij and filled the score table. Basing
on the score value dijk of the kth evaluator, theevaluation sample matrix D was obtained as follows: d111
d
 121
 
D=
 d 211  dij1

d112  d11 p  u11
d122  d12 p  u12

  

d 212  d 21 p  u21

  

dij 2  dijp  uij(4) “high” (e=4), the grey number ○× 4 was× 4∈[0,4,8], and the definite weighted
supposed ○function f4(dijk) was supposed as follows: dijk 4
dijk ∈ [ 0, 4]
f 4 ( dijk ) =( 8 − dijk ) 4 dijk ∈ [ 4,8]

dijk ∉ [ 0,8]0(5) “very high” (e=5), the grey number ○× 5 was× 5∈[0,5,10], and the definite weighted
supposed ○(1)function f5(dijk) was supposed as follows:dijk 5 dijk ∈ [ 0,5]=
f5 dijk
dijk ∈ [5,10]
 1
 0
dijk ∉ [ 0,10]( )i=1,2,…,m; j=1,2,…,n; k=1,2,…,p.
2.5 Determining evaluation grey-grades
This study used 5 evaluation grey-grades. The
evaluation grey-grade number was supposed e, sothat e=1,2,3,4,5. The corresponding grey number anddefinite weighted function were as follows (Wen,2010; Ren and Zhu et al., 2008).
× 1 was(1) “low” (e=1), the grey number ○X ije = ∑ f e ( dijk )p(2)

× 2∈[0,2,4], and the definite weighted
supposed ○(3)

For the evaluation index uij , the total grey
evaluation coefficient of each evaluation grey-grade
was recorded as Xij , then there was:p

X ij = ∑ X ije(8)

2.7 Calculate grey evaluation weight vectors andweight matrixes
All evaluators advocated that the grey evaluation
weight rije of the eth evaluation grey-grade was
rije=Xije/Xij, the grey evaluation weight vector rij of theevaluation index uij was:(9)
rij=(rij1,rij2,rij3,rij4,rij5)
So the grey evaluation weight matrix Ri of each
evaluation grey-grade was obtained, for the index uij
affiliated to Ui. Then there was: ri1 
r 
i2 
=
Ri =

 
 rij 

× 3 was(3) “higher” (e=3), the grey number ○× 3∈[0,3,6], and the definite weighted
supposed ○function f3(dijk) was supposed as follows: dijk 3
dijk ∈ [ 0,3]
f3 ( dijk ) =( 6 − dijk ) 3 dijk ∈ [3, 6]0dijk ∉ [ 0, 6]


(7)

k =1

k =1

× 2 was(2) “general” (e=2), the grey number ○function f2(dijk) was supposed as follows: dijk 2
dijk ∈ [ 0, 2]
f 2 ( dijk ) =( 4 − dijk ) 2 dijk ∈ [ 2, 4]dijk ∉ [ 0, 4]
0


(6)

2.6 Calculating grey evaluation coefficientsThe grey evaluation coefficient was recorded as
Xije, then there was:× 1∈[0,1,2], and the definite weighted
supposed ○function f1(dijk) was supposed as follows:
dijk ∈ [ 0,1]1
f1 ( dijk ) =( 2 − dijk ) 1 dijk ∈ [1, 2]dijk ∉ [ 0, 2]
0


(5)

(4)

 ri11r
 i 21  rij1

ri12
ri 22


ri13
ri 23


ri14
ri 24


rij 2

rij 3

rij 4

ri15 
ri 25 (10) 
rij 5 2.8 Comprehensive evaluation
The comprehensive evaluation results were:(11)
Bi=Ai·Ri=(bi1,bi2,bi3,bi4,bi5)
The grey evaluation weight coefficient matrix
was:

321

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

 B1 
B 
2
=
R =
 
 
 B5 

 b11 b12b
 21 b22b51 b52

b13
b23


b14
b24


b53

b54

b15 
b25  (12)
 

b55 

Therefore, Ui was made comprehensive
evaluation, and its results were recorded as B , thenthere was:(13)
B=A·R=(b1,b2,b3,b4,b5)
The comprehensive evaluation value W of Ui wascalculated. When each evaluation grey-grade was
assigned through “grey level”, then each evaluation
grey-grade value vector C was C=(1,2,3,4,5).
Therefore, the comprehensive evaluation value W ofthe evaluation index U could be calculated according
to the following formula:(14)
W=B·CTB
T
Where, C was transposition of each evaluation
grey-grade value vector.
2.9 Determining correction coefficients
Values of correction coefficients were as shownin Table 1. After the comprehensive evaluation value
W was obtained, according to Table 1 and W thecorrection coefficient of the failure probability wasdetermined. The product of the correction coefficientand the basic leak probability was the correctedchemical equipment failure probability.
Table 1: Values of correction coefficients.
Comprehensive
Value of the correction
evaluation value
coefficient r[4.5, 5.0]
＞2.00
[4.0, 4.5)
1.50～2.00[3.5, 4.0)
1.50
[3.0, 3.5)
1.25
[2.5, 3.0)
1.05
[2.0, 2.5)
1.00
[1.5,2.0)
0.95[1.0, 1.5)
0.90

judgment matrixes of six first level indictors in thecriterion layer were constructed by experts, whichwere shown as Table 2. The weight vector of eachfactor was calculated by the “scaling value
method”, and the consistency test was made.
Table 2: Values of correction coefficients
Criterion
U1
U2
U3
U4
layer
U1
1
3
4
7
U2
1/3
1
3
5
U3
1/4
1/3
1
3
U4
1/7
1/5
1/3
1
U5
1/7
1/5
1/3
1
U6
1/3
1
3
5

U5

U6

7
5
3
1
1
5

3
1
1/3
1/5
1/5
1

The
weightofU
was
A=(0.413,0.202,0.098,0.042,0.042,0.202),λmax=6.159, CR=0.026＜0.1, and the consistency test
passed.
In the same way, weights of the second levelindicators for the criterion layer were obtained asfollows:
A1=(0.019,0.052,0.288,0.090,0.037,0.026,0.128,
0.128,0.232);
A2=(0.068,0.111,0.289,0.035,0.192,0.306);
A3=(0.106,0.633,0.260);
A4=(0.143,0.571,0.286);
A5=(0.500,0.500);
A6=(0.584,0.286,0.080,0.050).
3.2 Organizing evaluation experts to score andestablish evaluation sample matrixes
According to score sheets filled by 10 experts,
the evaluation sample matrix D was obtained.

3. CASE ANALYSISIn order to illustrate the validity of this model, avinyl chloride tank of polyvinyl chloride (PVC) plantof a chlor-alkali company in China was taken as an
example. The tank was horizontal type, and its
volume was 112m3. There were 8 flanges withdifferent sizes on tank body connections. It was e,
and its volume was 112m 112mThe failure
probability was corrected based on the multi-layer
grey evaluation model.
3.1 Weight coefficient matrixes
The index weight of each layer was calculated
though AHP. According to the 1-9 scale method,322

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

1
 2

 2.5

1.5
1

1.5
1.5

1
 2

1

1.5
 2

 2
D = 1.5

 2.5
1.5

1.5

1.5
1

1
1

1.5
1.5

 2.5
1.5

1

 2

1
2

1 1
1
2 1.5 1.5

1
2

2
2

1
1

3
2

3 1.5 1.5 2
2
2 1.5 1.5 1.5 1.5

1
1

1
2
1

2 1.5 1.5 1.5
1 1
2 1.5
2 1.5 2
2

2
2
2

1
1
1

1.5 2 12 1.5 1.5
2 2 1.5 2.5 1.5 2

11

1.5 3 2 1.5 2
2 1.5
2 3 1.5 2
2 2.5 1
1.5 2 1.5 1.5 1.5 1.5 1
2.5 2 1.5 1.5 1.5 2.5 1.5
2 3 1.5 2.5 1.5 3 1.5
3
1.5
1.5
2
1
1
1
2
2
2.5
2
1
2

3
2
2
2
3
1
1
2
2
3
2
2
2

1.5
1.5
2
2
1
1.5
1.5
1.5
1.5
1.5
1
1
1.5

2.5 1.5
1.5 1.5
1.5 1.5
1.5 2
3
2
1.5 2
1.5 1.5
2
2
2
2
1.5 2
2
2
1.5 1.5
2 1.5

2.5
2
1.5
1
1
2.5
1
2
1
2
2.5
1.5
3

2.5
1
1.5
2
1.5
1.5
1
1
1.5
2
1.5
1.5
3.5

1.5 1.5
1 1.5
1.5 1 

1.5 1 1.5 1.5

2 1.5
1.5 1 

2 1.5
11

1 1.5

1.5 1 1.5 1.5
1.5 1 22
121 1.5 

1
2

1
1
1
1

2
2
1 1.5 

2
1
2
1

2.5 1.5 
1.5 2 2 1.5 21

3.3 Calculating grey evaluation weight matrixes
According to formulas 2-6, 9, and 10, calculated
results were as follows: 0.342 0.256 0.171 0.128 0.103  0.164 0.386 0.257 0.193 0.164  0.162 0.324 0.293 0.220 0.162  0.235 0.353 0.235 0.176 0.235  ;R1 =  0.259 0.342 0.228 0.171 0.259 
 0.211 0.364 0.243 0.182 0.211
 0.211 0.364 0.243 0.182 0.211

 0.235 0.353 0.235 0.176 0.235 
0.187 0.363 0.257 0.193 0.187 
0.187 0.350 0.265 0.198 0.187 
 0.163 0.349 0.279 0.209 0.163

 0.211 0.364 0.243 0.182 0.211 ;R2 = 

 0.163 0.361 0.272 0.204 0.163
 0.092 0.357 0.315 0.236 0.092 
 0.092 0.321 0.336 0.252 0.092 

0.235
R3 = 0.188
0.1880.305
R4 =  0.211
 0.381
0.140R5 = 
0.164

0.069
0.116R6 = 
0.259
0.0940.353 0.235 0.176 0.235
;
0.375 0.250 0.188 0.188
0.375 0.250 0.188 0.188
0.270 0.243 0.182 0.305
;
0.352 0.250 0.188 0.211
0.286 0.190 0.143 0.381

0.397 0.265 0.198 0.140  ;0.386 0.257 0.193 0.164 
0.368 0.322 0.241 0.069 
0.395 0.279 0.209 0.116  .
0.342 0.228 0.171 0.259 
0.363 0.304 0.240 0.094 

3.4 Comprehensive evaluation
Evaluation indicators affiliated to Ui were
evaluated. The results were recorded as Bi, where:
B1=A1·R1=(0.198,0.348,0.258,0.193,0.194)
B2=A2·R2=(0.143,0.347,0.292,0.219,0.143)
B3=A3·R3=(0.193,0.372,0.248,0.187,0.193)
B4=A4·R4=(0.273,0.321,0.232,0.174,0.273)
B5=A5·R5=(0.152,0.392,0.261,0.196,0.152)
B6=A6·R6=(0.099,0.373,0.301,0.226,0.099)
The grey evaluation weight coefficient matrix of
Ui for each evaluation grey-grade was obtained by Bi.
 0.198 0.348 0.258 0.193 0.194 
 0.143 0.347 0.292 0.219 0.143
 0.193 0.372 0.248 0.187 0.193
R=
 0.273 0.321 0.232 0.174 0.273
0.152 0.392 0.261 0.196 0.152 
0.099 0.373 0.301 0.226 0.099 
The evaluation weight vector of the failure
probability correction factor grey-grade for the vinyl
chloride tank was obtained, that was:
B=A·R=(0.167,0.356,0.271,0.203,0.166)
The comprehensive evaluation value of the tankfailure probability correction factor was:
W=B·CT=3.335
3.5 Determine the correction coefficient
The correction coefficient was obtained
according to W and Table 1,. The failure probability
correction coefficient of the vinyl chloride tank wasdetermined to be 1.25, which when multiplied withthe basic leak probability gave the corrected failure
probability.

4. CONCLUSIONS
By combining with actual situations of chemical
equipment and by objectively and reasonably
choosing evaluation indicators, the chemical
equipment failure probability correction model based323

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

on the multi-layer grey evaluation method wasestablished, and then was applied to the case study.
By using AHP to determine index weights, andapplying the multi-layer grey evaluation method, thefailure probability of the vinyl chloride tank in achlor-alkali company was corrected. Comprehensive
evaluation results showed that the failure probability
correction factor value of the vinyl chloride tank in
the chlor-alkali company was 3.335, and thedetermined correction coefficient was 1.25. So thefailure probability correction factor value of the tank
was between “higher” and “high”, and its actual
failure probability value was larger than that of thebasic leak probability. This model not only provides a
new approach to the correction of the chemical
equipment failure probability, but also has importantpractical significance with the accurate calculation of
the quantitative risk assessment.
The comprehensive evaluation of the chemical
equipment failure probability correction factor was avery complicated research topic. However, thedetermination of scientific and reasonable
comprehensive evaluation index systems andevaluation methods was necessary to correct failure
probabilities. Established models should constantly
be optimized.
5.

REFERENCES

American Petroleum Institute. (2008) Risk-based
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654p.
Au S K and Beck J L. (2001) Estimation of small
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He X., etc. (2000) Safety engineering. China
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Huang C., He S. and He L. (2015) Urban
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Koutsourelakis P S, Pradlwarter H J and
Schueller G I. (2004) Reliability of structures in highdimensions, Part I: Algorithms and applications.
Probabilistic Engineering Mechanics. Volume 19, pp.
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Liu S., Dang Y., Fang Z., and Xie N. (2004)
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Liu X. and Li Z. (2007) Using Monte-Carlo
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Qingdao Safety Engineering Institute of
SINOPEC(ChinaPetroleum &ChemicalCorporation). (2007) Quantitative risk assessment
guide for petrochemical plant. China PetrochemicalPress. Beijing, 210p.
Ren H. and Zhu L. (2008) Multi-hierarchicalgrey evaluation on the construction enterprises’
information level based on combinational weight.
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Shi C., Luo A., Chen W., Duo Y. and Wu Z.
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Wen J. (2010) Airline flight safety risk
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Wu, Z. (2008(s)) Several cognition andcountermeasure discussion to promote safety
development. Journal of Safety Science andTechnology. pp. 1-3.
Xu X., Zhang L., Duan L. and Zhang Y. (2012)
Research on reciprocating compressors safetyassessment system based on AHP. Industrial Safety
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Yuan X. and Lv Z. (2007) Markov chain
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Zhu J. (2005) The use of multi-hierarchical grey
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University of Technology. Hangzhou, 72p.

324

ISMS 2016

Paper No. 199

Mechanisms and applications of formatting unsafe behaviour motivation
Yuebing Zhang* Zhiliang Wang
North China Institute of Science and Technology, East Yanjiao 101601, China
Foundation item: the fundamental research funds for the Central Universities Fund (3142014014)

ABSTRACTThis paper aims to reveal the mechanism of work safety behaviours in order to effectively curb various unsafe
behaviours. For this, various motivations for unsafe behaviour are analyzed based on the work safety behaviour
features, application need, motivation, behaviour theory of psychology, the logic analysis method, and accident
cases analysis, as well as the source of need producing the motivations. The results show that the need comes fromthe source of human behaviour. To improve the level of people's safety needs and to appropriately weaken the levelof other needs is the basic measure of preventing unsafe behaviours. The main means to adjust the level of needs isto regulate the imbalance of corresponding conditions. For instance, "on-the-spot meeting for accident investigation"
can change the lack and imbalance senses of people’s safety conditions and improve the level of safety need.
KEYWORDS: unsafe behaviour; need;, motivation; accident prevention; safety psychology

1.

FOREWORD

Productive labor can be considered a process ofunderstanding and changing nature. In this process,each human has experiences countless painful lessons
due to error behaviour or "incompetence", such as
natural disasters, wars, accidents, and disease. Someof these disasters can be avoided, such as in the fieldof work safety. Statistics show that more than 90% of
accidents are caused by improper human behaviour,and can be considered a “responsibility accident”.
Each of the 30 major work safety accidents
announced during 2007-12-23 to 2012-08-28 in thewebsite of China’s State Administration of Work
Safety is a responsibility accident (Fu et al., 2013).
Theoretical derivation also shows that the vast
majority of accidents are people-related (Zhang et al.,2013), either directly due to improper humanbehaviour, or due to a wrong decision andmanagement. For example, in 2013 the devastating
Shandong "11 • 22" Sinopec Dong Huang oil pipeline
leakage and explosion accident was attributable to theimpact spark produced by the site disposal using
hydraulic breaking hammer punching in a culvert
cover plate. Similarly, the fatal Babao coal mine gas
explosion was triggered by the improper control ofcoal spontaneous combustion in a mined out area.
Therefore, it is of significance for work safety to
study the behaviour of humans, analysis, forecast andcontrol human behaviour, both theoretically andpractically.

2.

THE
HUMAN
MECHANISM

BEHAVIOUR*Corresponding author – email : zyb8562@126.com

Human psychology is a very complex
phenomena. Human psychological activity isexpressed through external behaviour, or people’s
explicit behaviour is controlled by implicit
psychological activity. All human behaviours(including unconscious behaviours) are dominated bypsychological activities, and in turn, psychologicalactivities are developed and expressed throughbehaviour (Shao and Wang, 2004).
Psychology thinks that human behaviour isdecided by needs and motivation; behind people's
behaviour there must be motivation, and motivation
comes from the people’s need, therefore, the need isthe original power of human behaviour (Chen, 2010).
However needs do not lead to behaviour directly, butinstead act through motivation as the direct cause ofhuman behaviour (Chen, 2010). Motivation is being
studied more and more extensively in the educationand law fields, such as in studies of learning
motivation (Gao et al. 2003) and crime motivation(Chen, 2010). The safety behaviour field has been
paid little attention, because no people subjectively
expect accidents to occur, and the motivation ofunsafe behaviour is indirect (Zhang et al., 2013).
Chen suggests intheir research on criminal
motivation that the occurrence of criminal behaviour
should have experienced a process of one passive
need and two active direction selections. That is,needs exist in everyone’s objectively, with no goodor bad. Instead, people can choose by themselves
whether or not or by what manner to meet a needaccording to the objective conditions, thus resulting
in the corresponding motivation. People also choose3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

whether or not to move according to a code of
conduct and ethical standards. This theory is also
applicable to other behaviours such as safety
behaviour.
Psychology says that needs produce thepsychological tension state, which is transformed into
motivation in a situation where the needs can be met.
People are stimulated to engage in certain activities
to achieve their objectives. When the objectives areachieved, the needs are met and the psychologicaltension state is removed.

3. THEUNSAFEBEHAVIOUR
MOTIVATION ANALYSISThe transformation of needs into motivation is avery complex process. In general, the actor will
weigh the advantages and disadvantages in thedecision-making process.
Based on the behaviour model of Chen Hong(2006), the behaviour control model can be proposed
as shown in Figure 1. It can be seen that thephysiological and psychological aspects of a lack andimbalance always stimulate the person’s needs at a
certain level (Chen, 2010). This need makes actor
selectively sense the environmental information,
judge and process the information based on their own
experience and knowledge, determine whether
conditions exist that can satisfy some need, and thentake some kind of behaviour to meet the needs.
Hence, the motivation occurs.

Figure 1: the human behaviour model.

The author argues that whether need istransformed into motivation depends on two aspects:
one is the need intensity; the other is the behaviour
cost to meet the needs. Human behaviour at first
perceives the information of the environment, andthen based on the human’s knowledge, sends out a
response. According to Maslow's theory of hierarchyof need, the needs of people can be divided into fivehierarchies, from low to high: Physiological needs,
Safety needs, Love and belonging, Esteem, and Selfactualization (Maslow, 1954). However Maslow
insists that only the needs at lower levels can be met.
Maslow argues that this hierarchy can only beestablished in the general case. Numerous cases showthat society, organizations, and people can adjust theneeds level by themselves, such as various

behaviours of laying down one's life for justice. Chen
Hehua thinks that need is a kind of lack andimbalance. Therefore, the author considers that thelevel of need is adjusted artificially or by eliminating
this lack and imbalance. For example, in the face of awar or death threat, the lack of living conditions
places the survival need at a higher level. Then,
morale sets up the ideal to improve Selfactualization.
The actor can perceive the information aroundsituations using the sensory organs. The amount of
the information that can be perceived is limited, so
perception is selective. Needs at higher levels willprompt the actor to input more attentional resources
to the information that can help to meet the related
need. At the same time, the strength of theinformation and whether there are significant
differences between the information and othersaround will also affect the information perception
selection. Then, the actor processes the informationaccording to his own experience and knowledge. If
he is assured that in this situation, he is able tocomplete a behaviour, and behaviour results can meetthe needs, the actor will feel the motivation to
implement the behaviour. Motivation has a clear
directivity, and is linked to means of behaviour tomeet the need.
Finally, the actor will further think if this kind of
behaviour may cause other results, make a trade-off
between costs and profit, and determine whether or
not to implement this behaviour. If he chooses toimplement, but the behaviour fails, the actor may
choose to give up or continue to work hard according
to the judgment of the task difficulty, and eventuallysatisfy the need or leave it unsatisfied and cause
mental stress. This judgment process, of course, is
not always very prudent, due to the complexity of
causality or due to time limits. Thus the actor will
also show impulse.

4. UNSAFE BEHAVIOUR MOTIVATIONANALYSISAND
PREVENTION
COUNTERMEASURES
4.1 Unsafe behaviour motivation analysis
There are many kinds of unsafe humanbehaviours. Appendix 7 of “The enterprise worker
casualty accident classification standards” (GB64411986) classifies the unsafe human behaviours into
four kinds: first, the ones because of inattention, theindividual physiological function defects which cause
behaviour mistake; second, the ones because ofactors’ lack of scientific understanding or theconsequences of the behaviour, not knowing theseriousness of the consequences, not knowing the326

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

uncontrollable consequences, or not knowing what
behaviour is beyond their ability. This kind of
situation sometimes is due to inadequate mastery ofenvironmental information, sometimes due to a lackof experience and knowledge. It can also be due to alack of serious judgment, namely the paralysis ofthought; third, when one knows thepossibleconsequences, but between the positive benefits andpossible loss a preference exists to save energy, timeor bravado; fourth, because one does not agree withthe system. There is no equal information between
system makers and system conformance.
From the theory of need-motivation-behaviour,
the occurrence of the above unsafe behaviours are all
due to the safety needs of the actor. And theirorganization causes a low-level relative to the otherneeds.
Generally speaking, in the enterprise’s worksafety, the physiological need of the actor is usuallyin a relatively high level, because the enterpriseshould make profits and the workers should earnsalaries, which causes the enterprises to generate themotivation and the behaviour of production, and theworkers to generate the motivation and behaviour offinishing tasks. In addition, since fierce market
competition leads to the growing shortage of living
conditions, the physiological need is in a higher level.
As for safety needs, although they are in an
inferior level, considering the conditions for worksafety, the actor rarely has an accident or is in
distress. Therefore, the lack and imbalance sense of
the safety conditions is low, and thus the safety needis in the lower level.
Social needs, esteem needs, and selfactualization needs are in the higher hierarchy. These
need levels can be increased because of thecorresponding lack and imbalance.
4.2 Preventive measures of unsafe behaviours
In order to prevent the unsafe behaviour of thepeople, the fundamental method is to improve thelack and imbalance senses of the safety conditions,and to reduce the lack and imbalance senses of otherneeds, thus to put the actor’s safety needs in a higher
level. Only in this way can the actor pay more
attention to the work safety, reduce the formation of
the motivation and the implementation of theunsafe behaviours. Meanwhile, it can also help
employees learn safety knowledge and skills.
(1) Improve the level of safety needs
To improve the level of the safety needs mainly
relies on improving the lack and imbalance senses ofthe safety conditions. The improvement of this kindof lack and imbalance senses is not to literally reducethe conditions for work safety but to make people
feel the seriousness and importance of safety

problems. On-the-spot accident meeting is a goodway by which employees feel the seriousness of thesafety problems and the accident consequences, thus
their lack and imbalance senses of the safety
conditions are enhanced. Of course, for the company
alone, the accident probability is low, so it is helpfulthat the company should hold some meetings about
the near-miss accident, or play some videos of theaccident scene.
(2) Reduce the level of other needs
Risk-taking is a typical unsafe behaviour.
Although it can bring injuries, it give psychologicalsatisfaction and easy profit. It can meet the
Physiological needs and Esteem needs. According tothis situation, enterprises can cultivate safety culture
to form a belief that risk-taking is shameful and thatobserving discipline is glorious within the enterprise.
They can implement activities to satisfy theemployees’ esteem needs by observing discipline.
Meanwhile, to exercise workers’ stamina andendurance, they should reduce the labor intensity andtime, thus to lessen the lack and imbalance senses offatigue and the level of physiological need.
The performance of violation conformity
sometimes is to meet the Love and belonging needs.
For example, under circumstances where others are
not wearing a seat belt, the actors tend not to wear
one either. Enterprises can solve the above problems
by strengthening the communication among theemployees and enhancing the independence of safety
behaviour through publicity of public opinion.
Organizational citizenship behaviour exists tosatisfy the Self-actualization needs. These “extratasks” sometimes are beneficial for safety, andsometimes not. For example, three women in Jilin
Province managed to stop a train and prevented amajor traffic accident, but conversely, the collieries
removal of a miner’s lamp may lead to a gas
explosion.
The actor here means decision-maker,
management, or executive. For the decision-maker,
making decisions is their behaviour, like decisions
concerning work safety investments and safetymeasures. The nuclear field offers many examples of
how “external” errors or omissions have beensignificant contributing factors to accidents (Mosey,
D. 2014). As for the management, their behaviours
are planning, implementing, checking and improving
the system, crystallizing, detailing, programming thefinal policy, and implementing it. They must arrange
for someone to do some tasks, prepare materials andequipment, coordinate among different departments,and set up effective control systems like checking
and supervising behaviours and correcting them. As
for the executives, they need to execute the tasks
given by the management according to the relevant

327

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

regulations. Obviously, these behaviours are
influenced by the need level of the actors. Enterprises
should strengthen publicity, establish the values ofbeing people-oriented, and improve the level ofsafety needs to reduce the acceptable level of risks.
Meanwhile, to make the management realize theexpectations from the grassroots, the grassroots
should know the management’s policy. Effective
communication is a prerequisite that is necessary forthe improvement of the safety needs level, and thevalue everyone places on safety.

5.

CONCLUSIONSNo behaviours can exist without motivations,and needs are the source of behaviours. It is oftheoretical and practical significancefortheprevention of work safety accident to study themechanism of the theory of need-motivationbehaviour.
To prevent the unsafe behaviours of the people,
the fundamental method is to put the actors’ safety
needs in a higher level. Only in this way can theactors pay more attention to the work safety, actively
learn the safety knowledge and skills, reduce theformation of the motivation and the implementationof the unsafe behaviours.
In order to improve the level of the safety needs,
one must mainly improve the lack and imbalance
sense of the safety conditions, and reduce the lackand imbalance sense of life conditions, social
conditions, esteem condition and self-actualization
conditions. Methods include having meetings at thescene of accidents, increasing the employees’
income, exercising workers’ stamina and endurance,
reducing the labor intensity and time, enhancing
communication between the staff, and establishing
the right values. All these measures can change theneediness and the sense of imbalance.

6.

GB6441-1986, Standard for classification ofcasualty accidents of enterprise employees, National
standard of the people's Republic of China.
Maslow, A (1954). Motivation and personality.
New York, NY: Harper. p. 236. ISBN 0-06-0419873.
Mosey, D. (2014), Looking beyond operator,
NEI
Magazine,
http://www.neimagazine.com/features/featurelooking-beyond-the-operator-4447549/
SHAO Hui, WANG Kaiquan. Safety psychology(2004). Chemical Industry Press, 65p.
ZHANG Yue-bing, WANG Kai, WANG Zhiliang (2011). Theoretical research on hazards and it's
application in accident prevention. China Safety
Science Journal, Volume 21, pp. 10-16
ZHANG Yue-bing, ZHANG Chao, WANG Zhiliang. (2013). Research on Safety Behavior Featuresand Its Applicatio. China Safety Science Journal,
Volume 7, pp. 3-7.

REFERENCE

CHEN He-hua. (2010). Origin, Character andFormation ofCrim inalMotivation. Journal of
Political Science and Law, Volume 2, pp. 21-27.
CHEN Hong. (2006) Research on unsafe
behaviors of coalmine fatal accidents in
China.Beijing：Science Press, pp. 122-141.
FU Gui, YAN Wen-tao, DONG Ji-ye, et al.
(2013) Behavior-based accident causation: the“2－4”model and its safety implications in coal mines.
Journal of China Coal Society, Volume 7, pp.11231129
GAO Yi-hong, ZHAO Yuan, CHENG Ying, etal. (2003) Motivation Types of Chinese College
Undergraduates. Modern Foreign Languages,
Volume 1, pp. 28-38.

328

Paper No. 205

ISMS 2016

Examining safety and sustainability in longwall coal mining through casestudies of disasters and reviewing global trends in environmental stewardshipBen de Wit a, Xinglong Zhao b, Malcolm Scoble aa

NBK Department of Mining Engineering, University of British Columbia, 6350 Stores Road, Main Office Room 517,
Vancouver, BC, Canada V6T 1Z4bSchool of Mines, China University of Mining and Technology, No1, Daxue Road, Xuzhou, Jiangsu, 221116, China

ABSTRACTThe coal mining industry has struggled recently with numerous operations being closed due to poor market
conditions and profitability. In spite of these low prices however the industry is seeing longwall projects develop
and continue operations, which seems to present an opportunity that can be economical and sustainable.
This paper examines longwall coal projects and what makes them successful. The topic of safety is a primary focus,
with coal mining disasters highlighted and operational challenges addressed. It includes summary root-cause
analyses that may serve as a risk register to highlight significant issues and challenges facing the industry.
The paper discusses sustainability and the influence longwall operations could have on the future of the coalindustry, while also highlighting global trends in environmental stewardship and fossil fuel reduction.
KEYWORDS: Coal; Safety; Mine Disasters; Root Cause Safety Analysis; Fossil Fuels; Sustainability

1. CURRENT COAL DOWNTURN ANDSLUMP RESILIANT LONGWALL MINESThe coal mining industry has been facing
challenging operating conditions the past few years
and in combination with a global shift towards
renewable energy and a focus on sustainability, theviability of coal mining has been impacted. The
effects of these conditions have been seen through theclosure of numerous coal operations, the shelving of
projects, and companies restructuring and selling
assets to adjust to new market conditions.
The effects of low coal prices can be seen bylooking at the traditionally active coal mining regionof North East BC where 5 mines have closed andmore than 1,300 employees are out of work.
Communities such as Tumbler Ridge have been
impacted, where the town’s mayor estimates its
population has decreased from over 3000 to just 2000
(Cryderman 2015).
The severity of market conditions was
highlighted in 2015 when Anglo American
announced it would cut its workforce of 135,000 by
85,000 in response to continued low prices (Saunders
2015). Anglo also announcement its intentions to sell
numerous assets and focus on priority assets.
"Negative cash flow assets will either be closed,
placed on care and maintenance or sold," Mark
Cutifani, CEO Anglo American (Saunders 2015).
Despite low coal prices Anglo American
announced that its longwall coal mines, Moranbah
and Grosvenor, were not for sale and would continue

Corresponding author-email: mr.bendewit@gmail.com

operations (Saunders 2015). "Together with theadditional material capital, cost saving andproductivity measures announced, we are setting out
an accelerated and aggressive strategic restructuringof the portfolio to focus it around our 'Priority One'assets, being those assets that are best placed todeliver free cash flow through the cycle and that
constitute the core long-term value proposition of
Anglo American," Mark Cutifani (Saunders 2015).
The statements from Anglo’s CEO highlight theadvantages of longwall coal mines, primarily low
operating costs, and the ability to stay cash positive
during periods of low prices. Unfortunately, longwall
mines are restricted by geological conditions and theyrequire large up-front capital expenditures, however,once established a longwall mine can be very
valuable.

2. SAFETY PERFORMANCE IN THE USA
The risks associated with underground mines aremuch greater than surface mines, which is evidenced
by the higher accident and fatality rates inunderground mines. In 2015 for example, the US coalindustry had 11 fatalities, 7 of which were inunderground mines, with 4 of the 7 attributed to roof
or wall failures (CBC 2015). By reviewing thestatistics from the Mine Safety and Health
Association’s (MSHA) 2015 report, it is evident thatin the USA citations and orders are generally being
reduced. By reviewing Table 1 from MSHA 2015 it
can be seen that with the exception of 2010, when theUpper Big Branch disaster occurred, the fatality rate
has remained relatively constant around 0.016
fatalities per 200,000 hours worked, which is roughly
50% higher than in metal and non-metal mines. (Ifthe Upper Big Branch disaster is excluded from 2010
figures, the fatality rate is approximately 0.152).

It is also interesting that the number of citations
ordered is higher in coal mines, even though there are
6 times more metal and non-metal mines. Also, there
are roughly 3 times as many workers at coal mines,
which could be a contributing factor through issues
with congestion and communication.

Table 1: Safety Performance at Coal Mines in the USA (MSHA 2015).
Coal Mine Safety and Health

2008

2009

2010

2011

2012

2013

2014*

Number of Coal Mines

2,129

2,076

1,944

1,973

1,871

1,701

1,632

Number of Miners

133,828

133,089

135,500

143,437

137,650

123,259

116,010

Fatalities

30

18

48

20

20

20

16

Fatal Injury Rate (per 200,000 hours worked)

0.02370.01480.03840.01480.01590.01760.015

All Injury Rate (per 200,000 hours worked)

3.89

3.69

3.43

3.43

3.16

3.11

3.11

Coal Production (Millions of Tons)

1,172

1,075

1,086

1,095

1,018

984

1,000

Citations and Orders Issued3

106,793

101,904

96,352

93,07778,857

63,217

62,684

S&S Citations and Orders (%)

32%

30%

32%

31%

27%

26%

26%

Dollar Amount Assessed (Millions)

111.5

96.5

110.7

120.2

89.5

64.9

61.2

3.

SAFETY PERFORMANCE IN CHINA

Coal mines are common in China because of
how widely used coal is for energy production. From2000 – 2015, approximately 70% of China’s totalenergy consumption was from coal, and prior to 2000
it was even greater (Bloomberg 2015). However,mines in China have experienced many issues withsafety and the future of coal mining in China is
uncertain.
Information compiled by Askci (2013) indicatesthat China’s coal production accounted for roughly
half of global production from 2012 to 2014. Thishigh production rate contributes to higher accident
rates in that because of scarcity, marginally profitabledeposits are exploited and small margins can cause
operators to take greater risk. These risks could
include failing to implement certain safety measures
to reduce costs.
An article by Xi (2015) highlights China’s poor
safety record and cites that in 2009 China had thehighest number of fatalities globally, with 2,631. The
figures indicate that total fatalities in China have been
decreasing, but fatalities per unit produced are still 15
times greater compared to figures from US mines.
However, though there are a significant numberof safety incidents and fatalities in Chinese mines,
research by Chen and Zhao (2012) indicates that the
majority of accidents can be attributed to ownership.
The research divides China’s coal mines into 3 types
including state-owned, local, and private enterprises.
State-owned refers to mines controlled by
China’s federal government. These mines are large,
have high yields and production rates, are highlymechanized, and have generally strong safety

records. Local refers to mines controlled by the local
government without influence from the state, and are
generally smaller than state-owned mines. Private
refers to mines that are individually owned andoperated without influence from the government.
These mines are relatively small, with low yields andproduction rates, low level of mechanization, andhave very poor safety records (Zhang et al., 2007).
Table 2: Safety Incidents in Chinese Coal Mines from 2001
– 2010 (Chen and Zhao, 2012).
Coal
Mine Number of %total%totalOwnership
Accidents
accidents
casualties
Private
6911
87.7
90.2
Enterprise
Local
938
11.9
9.2
government
State
35
0.4
0.6
government

These statistics indicate that state-owned mines
account for less than 1% of incidents, with the
majority occurring in mines that are privately owned.
However, relative values can be misleading andinvestigating total fatalities shows a significant
number occurring at state-owned coal mines. A
contributing factor to this is the sheer number ofmines, where in 2008 for example, there were 16,000
active Chinese coal mines. However, a telling
statistic of how bad times were previously is that in2001 to 2005 China had on average 6,000+ fatalities
annually (MAC 2006).
Recent reports indicate that annual fatalities,
which peaked in 2002 at over 7000, have been
decreasing with less than 1000 reported in 2014
(Lelyveld, 2015). However, figures show that330

China’s coal industry is still experiencing severe risks
and there is discussion about the validity of reportingby the Chinese government.
China Cuts Coal Mine Deaths, But Count in Doubt.
In a 2006 article for the Jamestown Foundation
research organization, energy expert Jianjun Tu
argued that official reports understate the real totals,"as mine owners routinely falsify death counts inorder to avoid mine closures or fines."
The highest accident category of 30 or moredeaths automatically triggers an investigation led by
the State Council, or government cabinet, the Hong
Kong-based China Labour Bulletin said.
In what may be the worst recent case involving
the accident definitions in 2013, a State Council
probe found that operators in northeastern Jilin
province understated the death toll from a gas
explosion to avoid falling into the 30-or-morecategory.
The Babao Coal Mine Co. reported 28 deaths
and 13 injuries from the accident, although the real
death toll reached 36 (Lelyveld 2015).
A good example of strong safety at a Chinese
coal mine is the Daliuta mine owned by ShenHua
Group. The Daliuta mine was the world’s largest
underground coal mine in 2011 and at the time ofreporting the mine had an ongoing record of 7 years
of safe production with no fatalities (Daliuta 2011).
The Chinese coal industry faces many
challenges with safety, and the high number ofaccidents and fatalities highlights the need for
improvement and transformation. Overall, it seems
state-owned mines can have safety performancecomparable or superior to mines in the USA, but it isdifficult to separate these from the local and private
mines.

4.
LONGWALLSTUDIESDISASTERS:

CASE

Sadly, there are numerous cases of undergroundcoal disasters throughout history. It seems to be arepeating cycle. Below are three summaries of root
cause investigations.
4.1 Soma Mine Disaster (Turkey)
On May 13, 2014 an electrical malfunction
created an explosion and fire in the Soma coal minein Eynez, Turkey. An analysis of the disaster isoutlined in the report by Kilic (2014). A fire started
in the mine shaft which rapidly depleted oxygen andalso created smoke. Smoke was blown into the mineand resulted in 301 miners dying of carbon monoxide
poisoning, and 162 others being injured.
Investigations revealed the mine was a “DeathTrap” with numerous cases of gross negligence. A

root cause analysis by Kilic (2014) and Ultas (2014)
found:
1. There was no refuge chamber in the mine andworkers were not provided functioning gas masks.
2. There were faults in the electrical system andmany issues found in the weeks prior to the accident.
3. Plans for the electrical layout were not sent toregulators for inspection and approval.
4. The mine's gas sensors had not been inspected
5. The ventilation system did not meetrequirements and there wasn’t an adequate supply offresh air or removal of polluted air.
6. Workers were unable to exit the mine because
exit routes were being used for production, andbecause no escape plan had been created.
7. The communication system used in the mine
was not suitable for an underground mine.
8. Production was 2.5 times greater thanoriginally planned with more workers were present.
However, the ventilation system was not adjusted toprovide the increased volumes of clean air required.
9. Employees were not trained adequately before
beginning their work.
The Kilic report concluded with “Our group is of
the opinion that there were many negligent practices,and that this accident was avoidable.”
4.2 Upper Big Branch Disaster (USA)On April 5th, 2010, the Upper Big Branch Minein West Virginia exploded and killed 29 miners,
making it the worst mining disaster in the US since1970. As outlined by McAteer et al. (2011) the
methane and coal dust explosion is believed to havebeen ignited by a spark created as a shearer cut into
the sandstone roof at the mining face. The shearer
was equipped with water sprays designed to douseflames like these at the point of ignition, however, theinvestigation found that the water sprays were
ineffective because they had either been removed orwere clogged with dust.
McAteer et al. (2011) determined the root causes
to be:
1. Water sprinklers and methane detectors were
not properly maintained and failed to extinguish thesmall ignition that led to the massive explosion.
2. Massey failed to remove accumulated coal
dust which allowed the explosion to propagate.
3. The ventilation system did not function
adequately, allowing explosive gases to build up wellbeyond safe levels. Stoppings and seals had been
removed that could have controlled the spread of fire,
but instead blocked the mines escape route.
4. Many pieces of faulty equipment indicatedthat maintenance of safety equipment was not apriority. A misaligned conveyor belt allowed coal
dust to accumulate at the face and created a huge331hazard.
Massey Energy had a history of incidents prior
to this disaster with 25 other workers being killed in
Massey mines from 2000 to 2010 (Stickeler, 2012).
The unsafe conditions were well known and in 200926 citations were issued for coal dust accumulationand for failure to adequately apply rock dust. In the
15 months prior to the incident, the mine received 40
citations with the majority classified as substantial.
Massey received federal indictments and as
outlined by Biggers and Nelson 2010, the company
entered into guilty pleas for 10 criminal violations ofmine safety and agreed to pay $2.5 million in fines.
Also, over 1,300 citations were issued which resulted
in another $1.7 million in civil penalties. In 2015,
former Massey Energy CEO Don Blankenship was
found criminally guilty for a conspiracy to willfully
violate the Mine Safety and Health Act.
4.3 Jiangjiawan Coal Mine Dsaster (China)
On April 19, 2015, 24 miners were killed at the
Jiangjiawan mine when a shaft flooded (Mkaq,2015). 247 workers were inside the mine when theaccident occurred, of which 223 made it out safely
while 3 trapped workers were rescued (Mkaq, 2015).
According to Mkaq, on April 14, water flow
increased very suddenly at the mining face but themine didn’t stop production to investigate the hazard.
Instead, the mine continued production by installing
pumps to drain the water, rather than evacuating
workers. On April 19, the flooding accident occurredat the mining face, and 24 miners were killed.
The Mkaq 2015 report determined root causesas:
1. The Mine failed to take effective measureswhen water flow increased suddenly at the mining
face and did not respond to the new risks adequately.
2. Failed to evacuate workers effectively whenwater flow increased at the mining face.
3. Controlled caving in the gob area createdfractures in the rock above the coal seam. The
fractures allowed surrounding groundwater to flood
into the working area very rapidly.
4. Detailed exploration was not conducted prior
to mining, which caused the accumulated water
above the active mining face to go undetected until
its inflow.

5.

IS COAL MINING WORTH THE RISKS?

It is clear that there are risks associated with
longwall coal mining and past disasters can beheeded as warnings to its dangers. However, there aremany cases of successful longwall operations andwith proper planning these mines can be successful.
In the case studies outlined in this paper all of
the disasters were preceded by cases of negligence. In

hindsight it is easy to identify the root causes, buttragically the problems did not receive the necessary
attention, and focuses of production and profitability
surpassed safety and sustainability.
Current and future coal mines are greatly
affected by each disaster and it raises the question“are coal mines, particularly underground coal mines,
worth the risk?” The global shift towards renewable
and clean energy, along with increasing focuses onenvironmental and social stewardship has impacted
all fossil fuel projects and it is challenging to
generate positive attitudes and excitement about
projects.
Coal’s decline is perhaps best illustrated by the
Dow Jones U.S. Coal Index, which has decreased
more than 95% from 2011 to 2016 (Finance, 2016).
Clearly times are tough, and a fundamental shift
seems to be occurring with alternative energy looking
to replace fossil fuels.

6. GLOBAL SHIFT FROM FOSSIL FUELSIn November 2015 the government of Alberta
announced that by 2030 they plan to close all 18 of
the coal-fired power plants that generate around 55%of the province’s electricity, with two-thirds of thatpower replaced by renewable sources (Wilt, 2015).
Alberta’s decision follows a trend of moving
away from coal, which is highlighted by comments
made by the Environmental Protection Agency (EPA)
administrator Gina McCarthy. “We know in the U.S.
that we are transitioning away from coal because coal
is no longer marketable. We have cleaner natural gas,
and we have opportunities for low-carbon sources
like renewables and using energy efficiency to lower
energy demand.” (Henry 2015)
The UK has also pledged to close all 12 of its
coal power plants by 2025, and research by Levey(2015) found that “to achieve the international goal of
limiting global warming to less than 2°C above preindustrial revolution averages, the least expensive
way of doing so is to close a significant number ofcoal power stations by 2030”. Also, the Levey
research shows that some of the lowest cost
scenarios involve eliminating coal power by 2030,
even if that means shutting down generators earlier
than planned.
However, demand in Asia still makes coalmining feasible and using safe and sustainable
methods is paramount for coal to be an option. The
New York Times reported in 2015 that China has
underreported its use of coal. “China Burns Much
More Coal than Reported, Complicating Climate
Talks” said Lin Boqiang, a Research Director at
Xiamen University (Smith, 2015). While in India asenior government official explained “Paris climate
deal won’t affect plans to double coal output,” and332

that India still plans to double coal output by 2020
because no alternatives are available (Wilkes andDas, 2015).
Coal reserves in Asia are slowly depleting andmore remote deposits are being mined with advanced
technology. With North American mines shipping
coal to Asia, a global connection is already in place.
This promotes coal’s development in North America
even if there is no local market. Demand in Asia canbe expected to continue because of the high costs ofalternatives, and the infrastructure already establishedin North America facilitates opportunities for Asiancompanies to extract coal from overseas.
Ontario phased out coal fired power plants in2014. The transition’s costs and challenges are
explained in the report by Cundiff (2015). The costfor Ontario to transition to alternative energy wasestimated at $9.2 Billion. These prices were relatively
high, as much as 3.5 times for solar and 2.0 times forwind compared to the US average, because
infrastructure was not already established and private
power generators with higher prices were relied upon.
These high costs were rebuked by presenting costsavings through less pollution, including savings ofover $1 Billion in Health Care and improved
productivity. Savings of $10 Billion were estimatedwhen accounting for loss of life, pain, and suffering.
However, it seems Asia will be coal dependent
until prices for alternatives become morecompetitive. The transition away could be initiated byprices increasing through depleted reserves, higher
extraction costs, or relying on imports, however,
because many places are phasing out coal, andsustained low prices indicate an oversupply, it seems
that Asia’s transition away could be driven byenvironmental stewardship.
Pollution has been a major problem in China
and though costs are accounted differently in eachcountry, if Ontario was able to show that up to $10
Billion could potentially be saved annually by
eliminating coal power plants, China could be able toshow exponentially higher savings because its
population is roughly 100 times greater than
Ontario’s and its pollution levels are much more
severe.

7. LOOKING AHEAD: FOCUSING
SAFETY AND SUSTAINABILITYON

Longwall coal mining is common in China andapplying the method to deposits in more places seems
like a natural progression. However, the current coalmining industry faces risks with regards to safety,
sustainability, and economics, and aligning a coalproject within a larger framework of long-term
growth and development can be challenging.

An operating coal mine can stimulate an
economy locally and regionally by providing manyhigh paying jobs and numerous opportunities forindirect employment. Once a longwall coal mine isestablished its operating costs are relatively low and
it is more capable of staying cash positive during adownturn compared to other methods, and this is very
advantageous for long term stability and overallsustainability. Advances in clean coal technology
also provide the opportunity to increase efficiency
and reduce pollution, particularly in regions that do
not have access to viable alternative energy sources.
Alternatively, there are many risks associatedwith longwall coal mines and it is critical to identify
the contributions and impacts a project may have.
The risk of a mining disaster is always present, andeven though safety practices have advanced theindustry has a long and sad history of disasters.
Statistically, coal mines have injury and fatality rates
approximately 50% higher than metal and non-metal
mines, and the increased risks need to be considered(MSHA, 2015). The increased risk could potentiallybe offset with comprehensive safety programs, andthe costs funded through the lower operating costs
and increased margins. There are also environmental
risks, such as pollution, waste, subsidence, andimpacting water resources, which can greatly affectthe local region, while extracting fossil fuels impacts
pollution levels and global warming. Understanding
these risks is critical before developing a project,along with identifying and reviewing project specificrisks.
There are many opportunities and benefits of
having a mine operating, particularly when the coalmining industry has been struggling, but concerns
over safety, local and regional participation in the
project, and long-term viability remain. Finding abalance is key and keeping safety at the forefront is
critical if coal mines are going to be successful infuture.

8.

REFERENCES:

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Mine
Approvals
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Pollution
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Fatalities
At
RecordLow"
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Cryderman (2015). "How The Collapse Of Coal
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achievement,” Ontario Clean Air Alliance Research
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334

ISMS 2016

Paper No. 215

Research on Safety Incentive Model of Coal Miners and Strategy Analysis
Cao Qinggui a, Xie Changzhen a,*, Zhang Shouming a,b, Zhang Sai a , Liu Weihua aa Department of Mining and Safety Engineering, Shandong University of Science and Technology, Qingdao, China, 266590
b Zibo Mining Group Co., Ltd., Zibo, China, 255120

ABSTRACT
Based on the safety incentive theory and safety incentive mode, the system dynamics model of safety incentive
for coal miners is established, and the simulation of the model is provided. The research shows that the effect ofimproving reward measure and environmental conditions are the most significant. According to the influence to thesafety incentives, other measures are in the following order: technical equipment, safety culture, enterprise goals andpunishments. The safety incentive strategy of coal miners is put forward with the simulation results.
Keywords: Safety, Behavior, Incentive, Miners, System dynamics, Simulation, Strategy.

1. INTRODUCTION
A large number of statistics shows that morethan 80% of coal mine accidents are related toworkers’ unsafe behaviors(Chen Hong, Song
Xuefeng, 2006). Workers' unsafe behaviors arecaused by many factors, such as psychology,
physiology, environmental, etc. According to therelated theories of organizational behavior, people's
behavior is dominated by the motivation. Moreover,people's inner desire and motivation is inspired byincentive. So the research of incentive can help us
find the effective way to guide the safety behavior ofworkers.
Since 1920s, many experts and scholars in theworld have made researches on the incentive, and put
forward different theories of incentive. Generally,
these theories are divided into three categories (Shi
Jutao et al., 2003; Li Jizu, 2009): Content-based
Motivation Theory (e.g. Hierarchy of Needs Theory,
ERG Theory, Two-factor Theory), Behavior
Transforming Incentive Theory. (e.g., Frustration
Theory, Attribution Theory) and Process Incentive
Theory (e.g. Equity Theory, Expectation Theory,
Goal-Setting Theory).
Many Chinese experts and scholars have alsostudied the safety incentive. Li Hongxia (2001)
studied the safety incentive system, and put forward
three types of safety incentive methods: Educational
effect, Economic effect and Power effect. On thebasis of motivation theory, Huang Mingxia (2006)
described the incentive methods in safety
management, such as work incentive, achievement
incentive, criticism and encouragement incentive,
training and education incentive. Mao Xiaoxin (2013)
put forward the positive incentive scheme of safety*Corresponding author – email: changzhenxie@hotmail.com

behavior, and it was discussed from material
incentive and spiritual incentive. Liu Haibin et al.
(2015) established the incentive mechanism of coalmine safety production based on the research ofunsafe behavior. Combining with three types of
incentive theory (Content-based Motivation Theory,
Behavior Transforming Incentive Theory and Process
Incentive Theory), Zhang Lili (2008) put forward the
incentive mechanism of safety production
management. Liu Ying and Shi Shiliang (2009)
constructed the coal mine safety behavior incentive
system.
The studies of the safety incentive is on
theoretical level, and some are still in the period ofexperience. There are few studies on specificemployee safety incentive mode. Moreover, there arefew quantitative analysis of employees’ behavior andpsychology . In view of this, based on the theory andmethod of system dynamics ,the incentive model ofcoal miners safety behavior is researched, and to seek
the strategies and effective ways to control the unsafe
behaviors of coal miners.
2.

SAFETY INCENTIVES AND SAFETYBEHAVIOR IMPROVEMENT

Safety incentive refers to inspiring people in thesystem reasonably, and guiding and controlling the
behavior of people to make sure that their behavior
meets the safety standard (rules), with the integrated
use of management, economics and other modern
scientific principles and methods. The aim of safety
incentive is to prevent system from accidents anddisasters, and to ensure that system is at an
acceptable safty level. It ensures not only theindividual safety but also the safety of the3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

organization (enterprises), environment and society(Liu Ying and Shi Shiliang, 2009).
In the process of development enterprise should
guide the employees’ behavior by incentive method.
According to the source of need, the incentive
method can be divided into material incentive andspiritual incentive (Liu Haibin et al., 2015). The
former refers to the bonus, salary, welfare and othermaterial incentives while the latter refers to thecorporate
goals,
leadership,
interpersonal
relationships, group cohesion, job satisfaction, etc.
At present, coal miners’ safety awareness is
improved by material incentive factors such as
rewards, compensation and punishment. These
incentives may have a good effect in a short time, but
the enthusiasm of the workers will be changed
alongside the disappearance of the reward or
punishment. So the enthusiasm of the workers cannot
be sustained. In addition, it is difficult for coalmining enterprises to make appropriate safety
incentive measures to reduce the unsafe behavior of
employees, so as to achieve the proleptic incentive
effect. Therefore, in this paper, the safety incentivemode of coal miners is studied by the system
dynamics simulation.

3. SD SIMULATION OF SAFETY
INCENTIVE MODE
System dynamics (SD) is a science that scientifictheory of system science and computer simulation are
integrated to study system feedback structure andbehavior. It is used to study and deal with complex
system problems by qualitative analysis andquantitative analysis (Zhong Yongguang et al., 2012).
The commonly used system dynamics software are
STELLA/iThink, Vensim, Powersim, Anylogic, etc.
Vensim is the most widely used among them. In thispaper, Vensim will be used for the research.
3.1 Establishment of the stock flow chart of safety
incentive mode
According to the actual situation of coal minesafety management, the safety incentive model ofcoal miners is analyzed and established. The stockand flow chart of safety incentive model of coalminers is established with "Safety performance level"
as the measure of safety incentive effect (As is shownin Figure 1).

Fig.1: Stock and flow diagram of coal miners' safety incentive model
Table 1 Set of SD simulation variable
Variable type

NumberVariable name

Level Variables

1

Safety performance

Rate Variables

2

Enterprise security objectives, Production accident loss

Auxiliary
Variables

18

Work participation, Job difficulty, Individual effort, Group cohesion, Group pressure, Individual
objective, Safety work satisfaction, Safety reward, Safety investment, Pay fairness, Safety
punishment, Economic benefit, Violation operation, Safety management, Work ability,
Education and Training, Diminishing incentive effect(Zheng Guoduo. 2005), Safety attention

Constant

12

Family factors, environment, Technical equipment, Safety culture, The influence of leadership,
Organizational commitment, Development opportunity, Job match, Interpersonal relations,
Reward measures, Punitive measures, Enterprise goals

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The mode includes level variables, rate variables,
auxiliary variables and constants (Zhong Yongguang etal., 2012) (As is shown in Table 1). The constant inTable 1 is the standard or the desired goal which isset by the system, and the initial value is determinedby the author and the coal mine enterprise experts.
3.2 Determination of parameters of SD model
The determination of the parameters in the SD
mode is mainly about the weight coefficient of the
independent variable to the dependent variable. In
this paper, the parameters are determined by AHP
and expert estimation (Tian Shuicheng et al., 2014;
Wu Liping, 2006; Wang Lianfen, Xu Shubai, 1990).
Due to space reasons, take safe working
satisfaction and its related variable, for example, tointroduce the determination of weight coefficient.
The variables related to safety job satisfaction(L) are:individual objective (a1), interpersonal relations (a2),safety punishment (a3), safety reward (a4), job match(a5), job difficulty (a6), environmental (a7) and pay
fairness (a8), so the set of variables is:
U={a1,a2,a3,a4,a5,a6,a7,a8}. Three engineers who
engaged in safety supervision in coal mine
enterprises were invited to discuss with the author. So
the judgment matrix is established by expert
evaluation and the scaling method of 1-9 Grade(WuLiping, 2006). It is:1
1 
1 4 1
5
3 1
3
5
7
7

1

1
1
1
1
1
1
1
5
7
2
3
7
8
 4
3 5 1 1
1 
5
3 1

3
2
4


1
1
5 7 3
1
5
4

;
2
3
A=

 15 2 15 15 1 1 2 1 6 1 7 


1
1 
1
3 1
2
1 1
3
4
5
6
 3
7 7 2
2
6
5
1 1 
2

 7 8 4
3
7
6
2
1 
In the study, the consistency test and sensitivity
analysis of the judgment matrix A are made. Resultshows that the maximum eigenvalue of the matrix
is: λmax (A ) = 8.6486 , and the eigenvectors is:
WA=[0.145,0.047,0.238,0.385,0.063,0.093,0.500,0.71
7]T. The consistency index is: CI=0.09266,
CR=0.06571; Both CI and CR are less than 0.1, so
the consistency passed test.
The weights are calculated by the AHP: W={0.073, 0.023, 0.111, 0.172, 0.032, 0.047, 0.22,
0.323}.
Given judgment matrix A with a small
perturbations, the perturbation matrix is B.

1

1

3
 2

1
B=

1

1

1

 1

1

2

1

1

1

1

1

1

4

2

1

1

1

1

1

1

1

1

1

1

5

1

1

1

3

1

1

3

1

1

1

3

1

1

1

1

1

1

3

4
2

3

2
1

5

4

1

1 1

1 1
2 1
3 

1 1

1 1

1 1

1 1
1

3

4

The matrix C is a Hadamard product of A and B.
(Wang Lianfen, Xu Shubai, 1990)
1

1
 4
9
 2

5
C=

 15

1
 3
7

 7

2

2

1

1

5

1

1

7

3

1

5

1

1

9

2
2

1

9
5

5
3

1
1

1

5
7
3

5
4

5

3

1

2

2

1

5

9

7
7

5

3

1

5

4

1

1

3

1

3

1

2

2

8

2
3
6

7

2

3

6

5

1

8

4

3

7

6

2

1 
7
1 
8
1 
4
1 
3

1 
7

1 
6
1 
2
1 

Result shows that the maximum eigenvalue ofmatrix C is: λmax (C) = 8.810 .and the eigenvectors is:
WC=[0.138,0.044,0.255,0.366,0.062,0.094,0.523,0.70
3]T. Compared with the maximum eigenvalue andeigenvector of matrix A, the change is small. The
weight set of matrix C is: W’= {0.063, 0.020, 0.117,
0.168, 0.028, 0.043, 0.239, 0.322}, Compared withthe weight set of A, the ranking of each factor does
not change, and the numerical difference is verysmall. According to the above algorithm, given A
with different small perturbations, and the results arestable. So, it is considered that the sensitivity of thejudgment matrix A is within the acceptable range.
Therefore, the weight set obtained from thejudgment matrix A is reasonable. So the relation onsafe working satisfaction is:
L=0.073a1+0.023a2+0.111a3+0.172a4+0.032a5+0.047
a6+0.22a7+0.323a8
3.3 SD simulation and result analysis
After the parameters of the SD model are
determined, Vensim is used to simulate the model on
the basis of the stock and flow chart. The simulation
period is set to 72 months, the simulation step is set
to 1 month, and the initial value of safety
performance is set to 10, so as to analyze the longterm trend of safety incentive effect in 6 years.

337

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The main positive feedback loop in the model is:
Safety performance→Safety reward→ Individual
objective→ Safety work satisfaction → Individual
effort → Enterprise security objectives → Safety
performance. The main exogenous variables that
affect the positive feedback loop are: Enterprisegoals, Safety culture, Environment, Reward
measures, and Punitive measures. The main negative
feedback loop is: Safety performance→ Diminishing
incentive effect→ Production accident loss→ Safety
performance. The main exogenous variables that
affect the negative feedback loop are: Environment
Reward measures and Technical equipment. In
addition to the simulation of the original model, theeffect of exogenous variables on safety performanceis studied by changing the initial value of 6

exogenous variables in turn, and the 6 exogenous
include these: Enterprise goals, Safety culture,
Environmental conditions, Reward measures,
Punitive measures and Technical equipment. The
simulation is divided into 3 groups
In the first group of simulation, the researchobtained the level of safety performance through theSD simulation by increasing the initial value of oneof the exogenous variables 1 units, and the initialvalue of the other exogenous variable remainunchanged. The second group and third group wereincreased separately by 2 units and 3 units.
Comparing the simulation results of the three groups,
it is found that the trends of the safety performance
are the same. Table 2 shows the average value ofsafety performance of 72 months.

Table 2: Average value of the safety performanceFirst group
Second group
Third group

Original
model
49.70849.70849.708

Rewardmeasures55.36562.76472.732

Technical
equipment
53.51057.311
61.112

Second group of simulation was selected forfurther analysis. The simulation results of the second
groups are shown in Table 3, and the change trend ofsafety performance can be see from Figure 2.
The simulation results of the original model canbe seen from Figure 2 and Table 3. The safety
performance increased gradually from start to 30thmonth, it shows that the positive feedback loop plays
a leading role in the model, that is, the safety
incentive factors in the model play an incentive role

Environment
55.33960.70966.601

Safetyculture52.76455.81958.875Enterprisegoals
51.78453.86055.936

Punitivemeasures49.95750.20550.454and lead to the growth of enterprise security
objectives, which promote the level of safety
performance. It reaches the minimum value at 54thmonth, and then it showns an upward trend to 72thmonth, but it does not reach the maximum value in30th months. It shows that the negative feedback loop
plays a leading role, that is, the incentive effect ofsafety incentive is weakened in the model and theloss of production accidents increases, which leads tothe decrease of safety performance level.

Table 3: SD results of simulationTime
0
6(month)Original
10.000 25.321
model
Reward10.000 25.742
measures
Technical
10.000 28.324
equipment
Environ10.000 29.762
ment
Safety10.000 27.706
cultureEnterprise
10.000 26.918
goals
Punitive10.000 25.512
measures

12

18

24

30

36

42

48

54

60

66

72

37.700 49.281 57.518 72.888 55.466 60.588 54.567 35.770 45.541 64.555 71.866
40.331 56.215 69.295 94.040 73.439 81.781 74.742 44.477 57.134 85.282 100.014
43.044 56.445 66.068 83.595 64.156 70.102 63.357 42.068 53.208 74.866 83.199
45.612 59.937 70.250 88.910 68.341 74.702 67.557 44.935 56.794 79.845 88.717
41.979 55.186 64.615 82.040 62.457 68.305 61.527 40.274 51.350 72.898 81.185
40.593 53.412 62.523 79.552 60.221 65.889 59.210 38.374 49.199 70.268 78.369
38.046 49.776 58.117 73.686 56.036 61.223 55.123 36.082 45.979 65.239 72.645

It can be known from Figure 2, Table 2 andTable 3 that, with the initial value of the reward
measures increases, the safety performance level
increased significantly. It shows that the reward

measures are most sensitivities. The safety
performance level increases the smallest after
increasing the initial value of the punishment
measure, and it shows that the punishment measure is338

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the least sensitive. The safety performance also
increases after increasing initial value of theenterprise goals, safety culture, environment andtechnical equipment. It shows that these incentives
can effectively improved safety behavior of coalminers. So the safety incentive effect of variables canbe obtained by SD simulation. The sequenceaccording to the effect of the incentive factors is asfollows : reward measures, environment , technicalequipment, safety culture, enterprise goals andpunishment measure.

120

Safety performance

100
80
60
40
20
0
0

6

12 18 24 30 36 42 48 54 60 66 72

Time(month)
Reward measures
Environment
Technical equipment
Safety cultureEnterprise goals
Punitive measures
Original modelFig. 2: Trend of simulation result
As it mentioned above, the judgment matrix A
passed the sensitivity analysis, and the result isrelatively stable after a small perturbation.
Accordingly, simulation is made by reducing theweight of compensation rationality, and remaining
the ranking of the weight coefficient, the simulation
result is shown in Figure 3.

Safty performence

80
60
40
20
0
0

6 12 18 24 30 36 42 48 54 60 66 72
Time(month)
Adjust A
Original modelFig. 3: The simulation results after adjusting weights
It can be seen that the trend of simulation result
does not change too much. According to the same
method, the simulations are provided after adjustingother variables, and the trend of simulation result also
does not change too much. It shows that the model isstable and the parameters are quite reasonable,and theconclusion is reasonable and credible.

4. SAFETY INCENTIVE STRATEGY OF
COAL MINE WORKERS
According to the SD simulation results, thefollowing strategies are put forward to inspire coalminers and to promote their safety behavior
1) To combine material incentive with spiritual
incentive. SD simulation results show that reward
and other material incentive measures,safety culture,development opportunities, enterprise goals and otherspirit incentives can improve the safety performanceof enterprises. Therefore, it should be taken to create
a good development opportunities for the miners andother measures should be taken to enhance the levelof spiritual motivation, and to promote miners safety
behavior effectively with the help of the material
incentives.
2) To establish a fair and reasonable system of
rewards and punishments. Simulation results showthat the reward measures to improve the safety
performance is the most sensitive, and its incentive
effect is more significant than that of punishment
measures. Therefore, coal mining enterprises should
implement positive reinforcement in the safety
management, be cautious to use negative
reinforcement, and establish a fair system of rewards
and punishments. To give reasonable rewards andpunishments to miners
3) To improve coal mine’s environment andtechnical equipment. The simulation result showsthat, in the early stage, improving environment canlead to the fastest growing safety performance,technical equipmen also works out. Therefore, coalmining enterprises should improve the environmental
and technical equipment of coal mines, so that miners
have a safe and comfortable working environment,
and miners' enthusiasm for production safety can be
improved.
4) To establish a harmonious and effective
enterprise safey culture. Enterprise safety culture canmake all employees operate voluntarily, avoiding
unsafe behaviors. It is initiative technical measure in
the enterprise security management, and it should bevigorously promoted in the coal mine enterprise.
5) To establish a reasonable enterprise security
objectives. Coal mining enterprises should consider
the employee's individual needs, completing ability
and enterprise's actual situation , etc, develop a clear
and reasonable security goals,and guide the miners
complete the security objectives voluntarily andactively339

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

6) Strengthening the pertinence of safety
incentive. Because of different characteristics of coal
coal enterprises and each employee, safety incentive
should be targeted, and different incentive measures
should be taken according to different production
systems or post, so as to guide the safety behavior ofminers.

5. CONCLUSIONS
1) The system dynamics model of safety
incentive system for coal miners is established, which
can be used to simulate and analyze the safety
incentive effectively.
2) SD simulation results of safety incentivemodel for coal miners show that the effect of reward
measures and environment is the most significant.
According to the influence to the safety incentives,
other measures are in the following order: technicalequipment, safety culture, enterprise goals andpunishments.
3) The safety incentive strategy for coal miners
is put forward, which can provide reference for theestablishment of safety incentive system and safety
management of coal mining enterprises.

6. ACKNOWLEDGEMENT
The authors acknowledge the National Natural
Science Foundation for supporting reach. Thanks thedoctoral students Zhou Lujie and Wang Linlin forproviding advice and help in modeling.

7. REFERENCES
Chen Hong, Song Xuefeng. (2006) Study on
unsafe behavior of major accidents in China Coal
Mine. Science Press, Beijing, pp. 27-29.
Huang Mingxia. (2006) Motivation in safety
management. Journal of Safety and Environment.
Volume 06, pp. 57-59.

Li Jizu. (2009) Safety behavior. Machinery
Industry Press, Beijing, pp. 117-133.
Liu Haibin, Wang Qingqing, Huang Hui. (2015)
Based on the incentive mechanism for safety
production of coal mine employees unsafe
ACTS//.Proceedings of the second International
Conference on safety and security management.
Beijing, China: 4p.
Li Hongxia. (2001) Analysis of safety incentive
mechanism .Mining Safety and Environmental
protection. Volume 03, pp.8-9.
Liu Ying, Shi Shiliang. (2009) Study on behavior
incentive mechanism of coal mine accident
prevention. China Safety Science Journal. Volume
02, pp. 85-91.
Mao Xiaoxin. (2013) The study and scheme
design Safety behavior positive incentive scheme
design. Capital University of Economics andBusiness, pp. 38-39.
Shi Jutao et al..(2015) Organizational behavior.
Petroleum Industry Press, Beijing, pp 74-75.
Tian Shuicheng, Li Guangli, Li Tingjun,etal.(2014) Simulation on Miners' Unsafe Behavior
Intervention Model Based on SD. Safety in Coal
Mines, Volume 08, pp. 245-248.
Wu Liping. (2006) The Study on Fuzzy
Comprehensive Evaluation and its application.
Taiyuan University of Technology, pp.33-39.
Wang Lianfen, Xu Shubai (1990) Introduction of
Analytical Hierarchy Process, China Renmin
University Press, Beijing, pp 114-148
Zhang Lili. (2008) Study on incentive
mechanism of safety production management.
Jiangxi University of Science and Technology, pp.
42-43.
Zheng Guoduo. (2005) Theory of enterprise
incentive. Economic and Management Press, Beijing,pp. 59-87.
Zhong Yongguang, Jia Xiaojing, Li Xu. (2012)
System dynamics. Science Press, Beijing, pp. 3-9.

340

ISMS 2016

Paper No. 223

A new Virtual Reality training system for underground coal mines
Hui Zhang a,c,*, Xueqiu Hea,b, Baisheng Niea, Hani Mitric,daFaculty of Resource and Safety Engineering, China University of Mining and Technology (Beijing), Beijing, China, 100083
Faculty of Civil and Environmental Engineering, University of Science and Technology Beijing, Beijing, China, 100083
c
Department of Mining and Material Engineering, McGill University, Montreal, Canada, H3A 0E8dFaculty of Civil Engineering, Henan Polytechnic University, Jiaozuo, China, 454000b

ABSTRACT
Virtual Reality (VR) technology in mining is a new field of research. The successful application of VR to mining is
critical to mine safety and production. Based on different input/output devices that are used in the VR system, thecurrent VR mining system can be divided into three types: screen-based general system, projector-based customized
system, and Head Mount Display (HMD)-based intuitive system. Based on a VR headset, a smartphone and a Leap
Motion, an HMD-based intuitive VR training system was built and tested by 10 students who tried both the HMDbased system and a normal screen-based system to experience the difference between the two systems. The results
showed that the HMD-based system can give a better user experience, and is easier to use. In the future, with theemployment of more intuitive input devices and improved system software, the VR training system for mines could
play a much more important role in mine training.
KEYWORDS: Virtual Reality; training; Head Mounted Display; tracker; immersion; intuitive

1. INTRODUCTION
Virtual Reality (VR) technology is based oncomputer graphics, and can build a virtual scene,
which could be interacted by users through input
devices, and seen, heard, touched, even smelt throughoutput devices (Mazuryk and Gervautz, 1996; Burdea
and Coiffet, 2003; Zhao, 2009). With a well-designed
virtual reality system, people can feel almost likethey are in the real world. Burdea and Coiffet(Burdea and Coiffet, 2003) raised the three I’s
conception – imagination, immersion, and interaction– of VR.
IMMERSION

I3
INTERACTIONIMAGINATION

Figure 1: The three I’s of virtual reality (Burdea and
Coiffet, 2003).

VR is used in many fields, such as military,
aerospace, medical, entertainments, etc. After
decades of developments, a lot of theoretical andpractical experiences have been suggested. Stone(2012) raised some basic rules and principles fordeveloping serious games of military; Burdea and*Corresponding author-email: hndfzhanghui@gmail.com

Coiffet (2003) and Stone (2012) discussed theimportance of considering the factors of users. Others(Bertram and Moskaliuk et al., 2015) have studied
the effectiveness evaluation of VR training systems.
Though VR has been studied for several decades,
there are still many things need to be studied in the
future, especially with the rapid development of the
input and output devices in recent years. Nowadays,
there are many kinds of Head Mounted Display(HMD) devices on the market, such as the separated
devices – Oculus Rift, HTC Vive, etc., or the VR
headset plus smartphone solutions.
In many mining countries such as Australia, theU.S., Canada, South Africa, the U.K., and China,
many researchers in the past two decades have been
studying the possibility of using virtual reality (VR)as a tool for operator’s training (Bukowski and
Sequin, 1997; Squelch, 2001; Kizil, 2003; Foster and
Burton, 2004; Tichon and Burgess-Limerick, 2011).
Dozens of prototypes have been developed and someof them have become popular products(ThoroughTec, 2010; CAE-Mining, 2012; QinetiQ,
2012). The current popular mature VR mine training
systems are mainly composed of a multi/curved
screen projector, which could provide someimmersion to the trainees, and customized operation
platform.
Just like other VR systems, the VR mine training
system also contains 5 components: input/output (I/O)
Devices, VR Engine, User, Task, and Software &Databases (Figure 2).

Tasks

Virtual Reality System
Data

OutputDevices

Data

Software&Database

Hardware

Sense

Input
Devices

VR Engine

User

Operation

Figure 2: Components of VR system, adapted from
(Burdea and Coiffet, 2003).

2. INPUT AND OUTPUT DEVICES
Among the 5 components in the VR minetraining system, the I/O devices are critical as they
are the exclusive way through which users caninteract with and sense the virtual. As a result, all theavailable I/O devices for the VR systems are
summarized in this paper.
2.1 Input devices
Based on previous studies (Mazuryk andGervautz, 1996; Burdea and Coiffet, 2003; Mihelj
and Novak et al., 2014), the common input devices
can be classified into two types: physical input
devices and automatic track devices, as shown in
Table 1. It can be seen that all the automatic trackdevices are more intuitive and easy to use, while thegeneral type of physical devices such as keyboard
and joystick are less intuitive and more difficult touse.
Table 1: Summary of VR input devices.
CategoryType

Physical General
Customized
Automatic Body tracing

Devices
Keyboard, joysticks, etc.
Customized operational
platform
Camera, IR sensor, depth
camera, etc.

Intuitive Difficulty
Level
level
Medium/High
Medium/Low/
High
Medium
Low

High

Low

Movement
capturing

Data gloves, gyroscope, etc.

High

Low

Voice control

Microphone

High

Low

2.2 Output devices
A VR mine training system must have output
devices so that the users can “sense” the virtual world.
According to Mazuryk et al. (1996) and Kizil et al.
(2001), visual sense and auditory sense only takecharge of 70% and 20% respectively of the total
sensing for human beings, and other three kind senses– tactility, olfaction, and taste sense – only take theremaining 10%. As a result, visual sense is the mostimportant one for users of the VR system.
Based on previous studies (Milgram and Kishino,
1994; Stothard and Squelch et al., 2015), the common
visual output devices can be classified as screens,projectors, Head Mounted Displays (HMD), andholographic devices (immature technology) (seeTable 2). It can be found that HMD devices are theonly available devices that provide the full immersion
and at a low/medium cost.
Table 2: Summary of VR display devices.
Category Type
Immersion Numberof Costuser
ScreenNormalNone
SingleLow
screen3D screen
None
SingleLow
Projector Flat
screen Partial
Single/multiple Medium
fabricCurved/multi- Partial
Single/multiple Highscreen fabric
HMD
Small high- Full
SingleLow/medium
res screen
Small optical Full
SingleMediumprojector
Holograms Holographic Full
Single/multiple Invalid
emitter

2.3 Different VR mine training systems
Based on the classification of the input andoutput devices, a new taxonomy of VR mine training
systems, which contains three kinds, is raised asfollows:(1) Screen-based general VR mine training
systemThe screen-based general system uses a desktop
monitor as the output device, and general physicaldevices, such as keyboard, joystick, etc. as the input
devices. The whole system has little/no immersion,and is mainly used to develop the basic VR minetraining systems.
(2) Projector-based customized VR minetraining system
This is currently the most popular VR minetraining system, and there are many commercial
products in the market (CAE-Mining, 2012; QinetiQ,
2012; ImmersiveTechnologies, 2015). The output
devices for visual sense are projectors with different
kinds of screen fabrics – flat, multiple, curved,
domed, etc. At the same time, a lot of customized
operational platforms based on the real equipment areused in this kind of system. With the help ofprojectors and large screen fabrics, this system could
provide some immersion to the users.
(3) HMD-based intuitive VR mine training
systemThe HMD-based intuitive system means that thehigh immersive visual output devices (Head Mounted
Display) and intuitive input devices (auto tracing &capturing devices) are employed in the system. In thiskind of system, trainees can feel full immersion, andinteract with the virtual environment and equipment
naturally and intuitively. For now, the immersive
natural system is not wildly developed and used, but342

it is the most advanced system and the future of mine
VR training system.

3. AN INTUITIVE VR MINE TRAININGSYSTEM
In this paper, a new VR mine training system,
which is a HMD-based intuitive system, was built for
drilling scenario training in coal mines. In this system,
the movement track device was used to capture thetrainee’s hands’ movements and gestures, and the
HMD was used as the visual output device throughwhich the trainee can feel full immersion. At thesame time, a screen-based general system was also
built as a control system. The HMD used in thissystem, was composed of a VR headset and a
NEXUS 6P smartphone. When the smartphone isinserted into the headset and turned on, the HMD isready to use, and the user could see the virtualenvironment through the lenses of the headset. With
the help of the sensors build-in the smartphone, suchas the gyroscope and the accelerometer, thesmartphone could track the user’s head turning, andthe pictures in the HMD could update along with thehead’s movement.
The intuitive input device used in this system
was a Leap Motion movement tracker with IR
camera built-in. The Leap Motion was glued in thefront cover of the HMD as shown in Figure 3(b), andit had a valid tracking angle of 135°, which is
sufficient to track the user’s hands (Figure 3(c)).
At the same time, a screen-based general system
was also built as a control system.

Head Mounted Display

VR Headset

Smartphone(a) Composition of the HMD

Leap Motion(b) Input device and Output device
Figure 3: HMD and Leap Motion as I/O devices.

As for the software & database and VR engine
parts, the Blender and Unity 3D software were
employed: the virtual miner model was built in
Blender, and the underground coal mine scene, thetrigger and interaction rules between the user and thevirtual environment, etc., were developed and coded
in Unity 3D.

(a) Screen-based general VR training system(c) User’s hands’ recognization(b) HMD-based intuitive VR training system
Figure 4: Two different training systems.

In Figure4, the pictures on the left show the realutilization situation of each system, and the pictureson the right show the graphics that the user could see
from the screen or the HMD. It can be seen that in thescreen-based general system (figure 4 (a)), the user iscontrolling the character to drill by using a joystick,and the screen shows the third person view of thedrilling scenario, which means that the immersion of
the system could not be high. In the HMD-based
intuitive system (figure 4 (b)), the user canexperience the first person view through the HMD,
and at the same time, thanks to the gyroscope built inthe smartphone, the turning of the head could bemonitored, and the sight in the HMD could change inreal time. What’s more, the user could manipulate thevirtual miner’s hands directly, instead of the whole343

virtual character, and through the previous mentioned
Leap Motion device, the user could control thefingers respectively, which means the user could dosome more complicated movements and gestures tointeract with the virtual drill in the virtualenvironment.

4. RESULTS AND DISCUSSION
In order to evaluate the effects of each mining
training system, ten students tested both training
systems. After that, they filled out questionnaires
about the two systems to evaluate the levels of
immersive, intuitive, interactive, easy to use, andeasy to learn. Each aspect was evaluated in fivegrades. The results are shown in.
Through the results, it can be seen that the
HMD-based intuitive VR training system has adramatically higher immersive grade (4.8) than thescreen-based general system (1.3), and 1.5 to 2 times
higher grade of intuitive, interactive and easy to use,
this means that the HMD-based system has a better
user experience than the screen-based system. As tothe easy to learn – the training results of each system– the screen-based system is only a little lower thanthe HMD-based system, which means that both
systems have quite good training results, and the
HMD-based one is a little higher. After experiencing
both systems, 9 of 10 students prefer the training
experience of the HMD-based system, and would liketo use it in the future.
HMD-based intuitive system0immersive
intuitive
interactive
easy to useeasy to learn

1

Screen-based general system
2

3

4

5
4.8

1.3

reduce the immersion of the system, because whenpeople see they are touching something in the virtualenvironment, they could not feel the tactile sense in
the real world.
(4) The users found that they could only interact
with the drill, but could not interact with other thingsin the virtual environment, which is due to thelimitations of the current software.
The points mentioned above are the main
limitations of the current HMD-based VR system,
and most of them are due to the limitations of the
hardware and software used in the system. With thedevelopment of the VR input/output devices, and the
updates of the HMD-based VR training system, thelimitations of the current system might be solved in
the future.

5. CONCLUSION
This paper classifies the input and output devicesof mine training VR system into screen-based generalsystems, projector-based customized systems, andHMD-based intuitive systems. Using the Head
Mounted Display as the output device which iscomposed of a VR headset and a smartphone, and a
Leap Motion as the input device, an HMD-based
intuitive VR training system was built. Users can feelfull immersion through the HMD and control thevirtual character’s hands to manipulate the drill justby moving their own hands. After 10 students had
tested both the HMD-based system and a controlled
screen-based system, they found that the HMD-based
system is more immersive, intuitive, interactive, andeasy to use, and most of them believe the HMDbased system is better and would like to use theimmersive system in the future.

4.3

2.1
2.6

6. ACKNOWLEDGEMENTS

3.8
4

2.5
3.7

4.4

The authors would like to thank China
Scholarship Council for financially supporting thefirst author of this paper to study at McGill
University – Mine Design Laboratory.

Figure 5: Evaluation of both training systems.

The students also suggested some limitations of
the current HMD-based intuitive VR training system,and the main ones are as follows:(1) In the HMD-based system, a user could not
move the character through moving his own body,instead he must use other devices such as keyboard or
joystick to move the character in the virtualenvironment, which will lower the immersion of thesystem.
(2) With long-term utilization, the user could
feel tired or suffer from motion-sickness.
(3) For the current system, the Leap Motion
device is used to track the user’s hands, while theuser could not feel any tactile sense, which will also

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345

Paper No. 227

ISMS 2016

Study of roadside packing to go with gob-side entry retaining technology on
crisp surrounding and blasting face in the Xinzhuang mine
Ya-ge LI a,b,, Wei-xiang WANG a,b, Long-zhe JIN a,b, Shu WANG a,b, Jiang LU caSchool of Civil and Environmental Engineering, University of Science and Technology Beijing, Beijing, China, 100083
Mine Emergency Technology Research Center, Beijing, China, 100083
cHenan Shenhuo Group Co.,Ltd., Yongcheng, China, 476600b

ABSTRACT
In order to improve the recycle rate of coal resources, extend the service-life of the mine, and alleviate the tensionsof excavation-replacement in the Xinzhuang mine, this paper presents a high-water material for roadside packing togo with gob-side entry-retaining technology on crisp surrounding rock and blasting working face. Based on theconditions in the field, the authors analyzed the utility of the filling structures of the 12011 machine roadway. On thebasis of the engineering analogy method and laboratory experiments, the authors determined the ZKD new
high-water material ratio of each component and the filling process parameters. The results show that when four
conditions are met—rectangular packing is used; water cement ratio of the new high-water material is 1.8:1; the Φ
18 mm × L 3400 mm anchor bolt is imbedded in the filling body; and supplementary support, which consists ofanchor bolt, wire rope, and steel beam, is applied—the average contraction rate of the roadway section is 13.38%,
achieving a satisfactory effect. Compared with gob-side entry driving, it can improve the indirect profit by 9.86
million yuan; compared with digging a new roadway, it can increase the profit by 5688.5 yuan per metre.
KEYWORDS: gob-side entry retaining; high-water materials; observation of mine pressure; contraction rate ofsectionWith the increase of mining service-life, theXinzhuang coal mine now faces the problem of
running out of coal mine resources, and the pressureof excavation-replacement is becoming increasingly
great. In order to reasonably exploit existing coalresources, improve the mining rate of coal resources,
extend the service-life of the mine, and alleviatetensions of excavation-replacement in the Xinzhuang
coal mine, this paper presents a high-water material
for roadside packing to go with gob-side entry
retaining technology on crisp surrounding rock andblasting working face. This is based on the features of
blast mining technology, a crisp and dry coal seam,and the fact that blasting vibration may cause theroadway wall to cave into the Xinzhuang coal mine at
the three (3) 12011 working face.
To date, the new high-water rapid-hardening
material for roadside packing to go with gob-side
entry-retaining technology has been applied indifferent coal mines with satisfactory results. Tao Yi
coal mine, Heng Jian coal mine, and Guo Er Zhuang
coal mine of Handan Mine Group and Qiu Ji coalmine and Wang Lou coal mine of Lin Yi Mine Groupare examples of this. It is worth mentioning that
although the technology implemented in the
aforementioned coal mines has unique characteristics,
Corresponding author – email: 86592800@qq.com

there are still significant differences between thesemines and Xinzhuang coal mine. The working face
implements a blasting excavation process, and coalseam is crisp and dry; the blasting vibration may
cause the roadway wall to cave into Xinzhuang coalmine. These features bring great difficulties to theimplementation of gob-side entry retaining
technology in Xinzhuang coal mine.

1. SURVEY OF GEOLOGICAL AND
PRODUCTION CONDITIONS ON 12011
MACHINE ROADWAY
Xinzhuang coal mine three (3) coal 12011
machine roadway is located in the west wing of three(3) 12th mining area. The elevation of this roadway is
between 246.5 m and 162.6 m below base level, andthe strike length is approximately 525 m. Three (3)coal seam is revealed in this region, and the thickness
is 1.2 m to 1.8 m, with the average thickness being
1.3 m. The average dip angle is 9°, and hardness ratio
f is 1.5. The stratification and joint is developmental
and the immediate roof is mudstone, which has athickness of 3 m to 3.5 m. The fissures are developed
and hardness ratio f is 2. The floor is mudstone with athickness of 3.15 m. It is gray and black, containing
plant fossils. The fissures are developed, and hardness

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
ratio f is 2. There exists about 0.5 m carbonaceous
mudstone, soft and broken, under the coal floor. The
section of 12011 roadway is rectangular; it has a net
width of 4000 mm and clear height of 2600 mm.

2. FILLING MATERIALAs necessitated by roof activities, at the
beginning, the activity of the roof is mainly based on
rotation and subsidence where the load is small, andthe utility of the filling structure is primarily tobalance the weight of the immediate roof. When theworking face continues to move forward, theimmediate roof and a range of old roof collapses andbreaks up. In order to reduce the time of the presenceof the old roof and the deformation of thesurrounding rock, it is required that the filling
structure has enough support resistance. When the
support structure of old roof rock mass breaks up, theroof activity comes to an end, and the filling structureis there to maintain the stability of the structure.
Therefore, it is required that the filling structure
is to be of high strength in the early stages, andincreasing resistance as time passes. It is to be stable
and reliable with high load bearing capability. ZKD
new high-water filling material is better at meetingthese requirements. This material consists of two
components, A and B. Component A, based on
special cement clinker, is made from suspension
concentrate and a compound super-retarding agent.
Component B is mixed with lime, gypsum, andcompound accelerator. Both component A and B canbe used at mass ratio of 1:1. According to thestandard tests in the laboratory, the basic properties of
the new high-water material are shown in Table 1.
Table 1: Basic properties of the new high-water material.
uniaxial compressive strength (MPa)initial setting
time (min)
2h
24 h
7d
28 d
3–20
≥2.0
4.2
8–9
10–11

The experimental results show that thecompressive strength of the filling body, which
consists of new high-water filling material, isgenerally more than 20% when the anchor bolt is
placed in the filling body. The longitudinal and lateral
deformation of the filling body can reach up to 7%
and 10% respectively when there is no anchor bolt in
the filling body. The whole anti-deformation capacityof the filling body can be increased by 6% to 28%.
The placement of the anchor bolts can significantly
improve the overall strength and stability of thefilling body.

3.1 Field filling technology
Combined with geological conditions in the
Xinzhuang mine and based on engineering analogy
methodology, this paper adopts the American MTS
815 rock mechanics test system to measure rocksamples derived from different rock strata. Thesesamples were compared to standard test specimens of
new high-water material that have different
proportions, taking the cost, equipment selection,
operation flexibility, and requirements of the roadway
support resistance into consideration. The water
cement ratio was determined as 1.8:1, and under thiscondition, the average compressive strengths of the
new high-water filling material are 1.7 MPa, 3.8 MPa,
4.9 MPa, and 5.9 MPa at the time of 6 h, 1 day, 3days, and 7 days.
According to the production status of blasting
mining face in three (3) coal 12011 roadway, thepumping station is planted at the corner of the
roadway in three (3) coal 12 mining area. The
schematic diagram of equipment layout in the fillingchamber is shown in Figure 1. As is shown, materials
are transported by a hydraulic injection pump that is
specified for coal mine operations. The filling pipe iscomposed of a high-pressure hose with a diameter of
40 mm and seamless tube with an inner diameter of
40 mm. There are two feeding pipes: one for material
A and one for material B that separately convey thematerials from the pumping station to the filling point.
To make the filling technology more convenient andreliable, a high-pressure hose is used between thefilling pump and the tube, and between the filling
pipe and the external tee mixer. The mixing pipe
utilizes the high-pressure hose, with the innerdiameter being 55 mm. A quick coupling was used
between the rubber hose and steel pipe.
Considering the characteristics of thesurrounding rock and the requirements for retaining
roadway section in the Xinzhuang mine, it isdetermined that the filling body should be entirely
arranged in the goaf, and the rectangular filling bag
should be used with a size of 2400 mm × 3000 mm ×2600 mm. Its height and width can be adjusted
according to the actual conditions. The diameter ofthe feed hole is 100 mm, and the length of the feed
tube is less than 550 mm. There are six anchor holes
in the filling bag, with the diameter being 25 mm, andthe length of anchor bolt that is exposed on both ends
being 150 mm.

3. FIELD APPLICATION

347

Figure 1: Schematic diagram of equipment layout in filling chamber.

3.2 Control of the stability of the filling bodyAccording to field observation, the average dip
angle of three (3) coal 12011 working face is 9°;
however, parts of the area have a larger angle. Thereis a step between the roof and the floor with a heightof 1.3 m. The filling body was placed along theangular surface with a large angle. In order toprevent the lateral deformation of the filling body,which leads to instability affected by the load fromthe goaf side or affected by the force from the sideof the working face and the roof, an anchor bolt wasplaced in the filling body. The anchor bolt has two
thread ends of sizes Φ 18 mm × L 3400 mm. Afterthe shaping of the filling body and dismantling thebasic template with dimensions of 2400 mm × 200
mm × 30 mm and dismantling the front templatewith dimensions of 3200 mm × 200 mm × 30 mm,
the anchor bolt was fixed with light steel tape,which is suitable for roadway support at both ends.
The nut and tray has dimensions of 300 mm × 250
mm × 50 mm. This too, enhances the strength andstability of the filling body. Results from the field
application showed that the resistance of the anchor
bolt improved the overall strength and stability of
the filling body significantly, and the effect ofreinforcement became obvious. Figure 2 is aschematic diagram of the roadway beside the filling
support.

caving resulted from the tunneling process resulted
in an ultrahigh roadway segment of 30 m length by
3.4 m to 6.0 m height. Because the roadway was
subjected to a blasting vibration influence before
implementation of the gob-side entry retaining, thedegree of surrounding rock fracture in this part was
further increased, and the ultrahigh segment became
the most difficult area in gob-side entry retaining. In
view of this situation, the reinforced support of theroof of roadway and the east side of the coal wall
was decided to be implemented before the working
face, 50 m in front of the retained roadway. In theoriginal position between the two rows of anchor
bolts, 2 anchor cables were added in the middle ofthe east side of the roadway, and the anchor cableused the steel strand with dimensions Ф 18 mm × L
5000 mm. The row spacing was 1.4 m and thecolumn spacing was 1.5 m. At the same time, theflange beam was used to connect the anchor cable
along the vertical direction, to form the structurethat consisted of cables and beams to limit wallcaving. At the bottom, from the 3.0 m baseboard, at
an oblique upward angle of 5° to 10°, one steel
strand cable was set, the size of which was Ф 18
mm × L 5000 mm. Two parts of it were fixed withthe tray, the dimensions of which were 350 mm ×
350 mm × 10 mm. Then, depending on the distance
between the anchor cable hole and roadway floor,
two or three anchors were set under the anchor cable.
To ensure enough supporting force and the integrityof the coal wall, the spacing of anchors was not
more than 800 mm. The spacing between the anchor
bolt and the anchor cable was not more than 1000
mm, and the spacing between adjacent two rows of
reinforce support was not more than 1.6 m.

Figure 2: Schematic diagram of roadway besidethe filling support.

4. ANALYSIS ON THE EFFECT OF MINEPRESSURE OBSERVATION AND GOB-SIDE
ENTRY RETAINING
For this study, many measured control points
were set. On these points, single cross wiring method
was used to measure the surface displacement of the

3.3 Reinforce support of gob-side entry retaining
The crisp surrounding rock in three (3) coal
12011 machine roadway and the significant roof
Corresponding author – email: 86592800@qq.com

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
roadway. Beside the roof and bottom of filling bodythere were set control points forming a baseline along
the vertical direction. On the middle of the filling
body, a transverse steel pole was installed in advance.
Its exposed end was fixed, then a tape measure wasused to measure the distance between the two basepoints and the variable length of the exposed end. Thechange of displacement over time of the roadway at
various locations is shown in Table 2.
From Table 2, it was concluded that the

maximum and the average displacement of roof andfloor were 239 mm and 222 mm. The maximum andthe average displacement of the roadway’s sides were
255 mm and 212 mm. The maximum and the average
displacement of the filling body were 136 mm and100.5 mm. The maximum contraction percentage ofroadway section was 14.49%, and the averagecontraction percentage of roadway section was
13.38%. The effect is better and can meet therequirements of secondary use.

Table 2: Summary of roadway section contraction percentage.
roof and floor
roadway’s sides
surveythethe averagethethe average
sectiondisplacement
displacement
displacement
displacement(mm)
rate (mm/d)(mm)rate (mm/d)
16#
222
6.94
229
7.16
17#
207
6.27
243
7.36
18#
214
6.48
255
7.5
39#
230
6.97
227
7.09
40#
214
6.11
241
7.09
41#
228
6.33
251
7.17
58#
202
6.73
174
5.8
59#
224
7.22
188
6.06
60#
239
7.47
208
6.5
83#
217
7
167
5.06
84#
235
7.34
178
5.23
85#
228
6.91
185
5.29
average
222
6.81
212
6.44

Compared with digging a new roadway,
gob-side entry retaining can increase the profits by
5688.5 yuan per meter; as opposed to gob-side entry
driving, gob-side entry retaining reduces the
excavation work significantly, cuts down the work
time, alleviates tensions of excavation-replacement,
prevents fire disaster, extends the service-life ofmines, and improves indirect profits by 9.86 million
yuan. To summarize, it results in substantial
economic as well as social benefits.

5. CONCLUSION
This study adopted the new mine-fill whosewater cement ratio is 1.8:1. The size (length × width× height) of rectangular filling bag was 2400 mm ×3000 mm × 2600 mm, and the size of anchor bolts
which were imbedded in the filling body were Φ 18
mm × L3400 mm. Moreover, the supplementary
support, which consisted of anchor bolts, wire rope,and steel beams, was used to ensure the stability of
the lateral supporting force in the roadway, which hada crisp and dry coal seam. It was impacted by blasting
work, and had ultrahigh height, with the size of wirerope being Ф 18 mm × L 5000 mm. These measures
restricted the displacement of the coal wall, andfilling bodythethe average
displacement
displacement(mm)
rate (mm/d)
100
3.12
109
3.30
136
4
112
3.5
103
3.12
101
2.97
92
3.07
96
3.10
96
3
96
2.91
85
2.5
83
2.37
100.5
3.08

contraction
rate ofsection13.77%
13.55%
14.08%
14.02%
13.76%
14.49%
11.78%
12.91%
13.91%
12.17%
13.09%
12.99%
13.38%

improved overall strength and stability of the fillingbody.
The result of the mine pressure observation
survey showed that the maximum of roadway section
contraction percentage was 14.49%, and the average
roadway section contraction percentage was 13.38%.
The effect of gob-side entry retaining netted marked
improvement and demonstrably met the requirementsof secondary use.

6. ACKNOWLEDGMENTSFirst, I would like to extend my deepest
gratitude to my supervisor, Dr. Long-zhe JIN, whoprovided valuable guidance in every stage of writing
for this thesis. I also extend thanks to barmaster Jiang
LU for his support. Furthermore, I would like tothank my friends Shu WANG and Wei-xiang WANG
for their help and encouragement. Finally, I gratefully
acknowledge the experts who reviewed this thesis
and others who strive to make this international
symposium a success.

7. REFERENCES
Bai J. (2006).Surrounding Rock Control of Entry
Driven along Goaf. Xuzhou, 171p349

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
Bai J., Zhou H., Hou C., Tu X., and Yue D.
(2004).Development of support technology besideroadway in goaf-side entry retaining for next sublevel.
Journal of China University of Mining andTechnology. Volume 33, pp.183-186
Bu T., Feng G., and Jia K.(2010).Gateway Side
Backfilling Support Technology of Goaf Side
Gateway in Fully Mechanized High Cutting Longwall
Mining Face. Coal Science and Technology. Volume38, pp.41-44
Chen Y., Bai J., and WANG X. (2012). Support
technology research and application inside roadwayof gob-side entry retaining. Journal of China Coal
Society. Volume 37, pp.903-910
He T. (2012).The breaking place prediction offace end main roof flap top in the gob-side entry
retaining. Journal of China Coal Society. Volume 25,
pp.28-31
Hua X.，Ma J., and Xu T. (2005).Study on
controlling mechanism of surrounding rock of
gob-side entry with combination of roadside
reinforced cable supporting and roadway bolt
supporting and its application. Chinese Journal ofRock Mechanics and Engineering. Volume 24,
pp.2107-2112
Hua X., Zhao S., and Zhu H. (2006) .Research on
combined support technique of gob-side entry
retaining. Rock and Soil Mechanics. Volume 27,
pp.2225-2228
Ju F., Sun Q., and Huang P. (2014).Study ontechnology of gob-side entry retaining in thin seamsurrounded by soft roof and floor. Journal of Mining
and Safety Engineering. Volume 31, pp.914-919
Li J., Feng G., and Ning S. (2009).The
technology and application of roadside supporting forgob-side entry retaining in full-mechanized mining.
China Mining Magazine. Volume 18, pp.77-79
Qian M., Shi W., and Xu J. (2010).Miningpressure and strata control. Xuzhou, 374p
Tang J., Hu H., and Tu X.（2010）.Experimental
on roadside packing gob-side entry retaining forordinary concrete. Journal of China Coal Society.
Volume 35, pp.1426-1429
Xie W., Da J., and Feng G. (2004).Mechanism ofcontrolling surrounding rock around gob-side entry
retaining in top-coal caving mining face. Journal ofCentral South University (Science and Technology),
Volume 35, pp. 657-661
Xu J., Zhu W., and Li X. (2006).Study of theTechnology of Partial-Filling to Control Coal Mining
Subsidence. Journal of Mining and Safety
Engineering, Volume 2, pp.6-11
Zhang D., Miao X., and Mao X.
(2001).Simulation on Roof Activities of Gob-Side
Entry Retaining in Fully-Mechanized Top-Coal

Caving Faces. Journal of China University of Mining
and Technology. Volume 30, pp.261-264

350

Paper No. 228

ISMS 2016

Optimization of bit nozzle parameters of reverse circulation sampling used incoal mines
Kang Jianning a, b, Hu Qianting c, Zhang Rui b, *a

Shandong University of Science and Technology, Qingdao, China, 266590
Chongqing Research Institute of China Coal Technology & Engineering Group Corporation, Chongqing, China, 400037
c
Chongqing University, Chongqing, China, 400044b

ABSTRACTThe coal mine air reverse circulation sampling technique is important for improving the accuracy of direct
determination of gas content. The sampling drill is an important structural element to realize this technique. The
embedded annular ejector and external nozzle of the drill are the main structures that can achieve reverse circulation.
The external bit nozzle divides the mine compressed air into two parts. One part is used to wash the drill hole inorder to prevent hole collapse, and the other part can press cuttings at the hole bottom into the drill pipe center tube
and provide the transmission power. Bit nozzle dip angle and position are studied by numerical simulation, and theresults are proved by the filed test. The results show that when the dip angle of the nozzle is 15° and the position isappropriate away from the drill cutter, the reverse circulation is better and the sampling depth increases. This
improves the quality of sampling and prevents damage to the drill bit and buried drill accidents.
KEYWORDS: Coal mines; reverse circulation sampling; bit nozzle; numerical simulation

1. INSTRUCTIONS
The air reverse circulation sampling technique is
widely used in the geological prospecting industry in
China and other countries, as it is a kind of samplingtechnique with large sampling depth, high sampling
rate, spot sampling, low sample contamination rate,and strong representation. In this technological field,
Jilin University has formed a series of specifications
for reverse circulation drilling equipment (Zhang etal., 2007). Due to the advantages of the technique,from the year 2005 to 2010, the CCTEG Xi’an
Research Institute in China and the Commonwealth
Science and Industries Research Organization(CSIRO) in Australia used it for coal sampling inmines, in order to improve the accuracy of direct
determination of gas content of coal seams. Because
the drilling cuttings stress state and the mine airpressure in the coal seam borehole is different fromthe geological prospecting borehole, the sampling
depth of the underground coal mine air reverse
circulation equipment has not been able to effectively
break through 60 m (Yuan et al., 2011; Yuan et al.,2014; Hu, 2011). From the year 2011 to 2015, theChina Coal Technology Engineering Group
Chongqing Research Institute (Referred to as
Chongqing Research Institute) developed the SDQ
type deep hole fixed-point sampling device (Li, et al,2014 and Zhang, 2014), increased the depth of coalmine air reverse circulation sampling to 120 m,
which has provided the technical and equipment*Corresponding author – email : red_rui@163.com

support for the accurate determination of gas content
in large inclined long coal mining working faces. The
sampling drill designed by Chongqing ResearchInstitute leads the drilling cuttings from the bottom of
the hole into the double-wall drill pipe inner tube by
the effect of center tube extraction under externalpressure (Zhang et al., 2014). The external bit nozzle
is an important structure for providing the externalpressure. Based on computational fluid dynamics(CFD) and field tests, this study will probe into the
optimum design of the dip angle and position of theexternal nozzle, in order to enhance the effectivenessof reverse circulation sampling.

2. THEMECHANISM
OF
THE
UNDERGROUNDREVERSECIRCULATION SAMPLING BIT
A sampling bit with internal and external jet flow
control (air flow) functions is developed withreference to the air reverse circulation sampling bit in
the geological exploring industry and previous
research results and according to the characteristics
of drilling sampling in current underground coalseams, as shown in Figure 1. The sampling bit adopts
a composite design, that is, the annular ejector withan internal injection function is embedded in theinside of the drill bit, a positive pressure injection
orifice with external injection function is installedoutside the side wall, and the end head designed to be3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

a cutting structure of cuttings granularity control withan anti-blocking type. This structure can make thefresh cuttings automatically adjust to be the gas-solid
two phase flow with appropriate solid-gas ratio andflow rate, according to the change of drilling
resistance, under the triple control of external
collection, internal extraction, and hole wall shunting.
The fresh cuttings then enter the center pipe of
double-wall drill pipe to form the reverse circulation.
The principles of underground reverse circulation
sampling are shown in Figure 2.
1

3. PARAMETERS
OPTIMIZATIONRESEARCHOF
SAMPLINGBITNOZZLE BASED ON THE NUMERICALSIMULATION
3.1 Modeling
Because the longitudinal section of the sampling
bit is symmetrical, it can be used to study half of thesample structure when researching the parameters of
the external bit nozzle. A two-dimensional model
was established in order to study the influence of theexternal nozzle parameters on the reverse circulation
effect, as shown in Figure 3. The grid was divided byusing gambit. The air inlet is the inlet of compressed
air, where the pressure is 0.2 MPa. The outlet1 andoutlet2 are for export, and the pressure is theatmospheric pressure.

1-annular space, 2- center pipe, 3- jet nozzle, 4-annular ejector, 5drilling cutter, 6-coal wall, 7- bit body, 8- external bit nozzle, 9gap between the drill bit and hole wall

Figure 1: The structure of sampling bit with internal andexternal jet flow control.

External bit
nozzleCompressed
air in mine

Double-wall
drill pipe

Hole-bottom(drill
cuttings)

BoreholeSlagdischarge

Center pipeSlagdischarge

Figure 3: The simplified model and mesh of sampling bit.

Annular gap inbit body
Few airflow

Internal bit
nozzleDrill cuttings
suctionFigure 2: The mechanism of the underground reverse
circulation sampling.

As can be seen from Figure 2, the borehole wallshunts compressed air after it flows through theexternal bit nozzle. A portion of the gas stream
continues to flow to the hole bottom, providing
positive pressure power for making the drill cuttings
get into the center pipe and cooling the drilling cutter
at the same time. Another portion of the gas flows to
the nozzle, carrying the residual cuttings to avoid theoccurrence of buried drilling accidents. With thegradual increase of the drilling depth, the slag
discharge resistance of the drill hole and center pipe
increases gradually. It is easy to cause problems suchas drilling difficulties, low service life of drill bits
and poor effects of reverse circulation sampling, if
the air distribution of the two air-return slag
discharging space is unreasonable. Therefore, thispaper takes the dip angle of the external bit nozzle
and hole position as the research object, through a
combination of the Fluent numerical simulation andfield test method to optimize the two parameters, inorder to further improve the effect of reverse
circulation sampling under the premise of normal
drilling.

3.2 Dip angle optimization of the external bit nozzle
3.2.1 The internal flow field of the model withdifferent dip angle
As shown in Figure 4, α refers to the dip angle ofthe external bit nozzle, which is defined as the angle
between the central axis of the external bit nozzle andthe normal which is vertical to the hole wall.

Figure 4: The dig angle of external bit nozzle.

With reference to the design experience of thecommon drill in the drilling tool industry, the modelof different dip angles of the external bit nozzle was
set up, with the dip angle α set as 0°, 15°, 25°, 35°,45°, and 55°. Numerical simulation was carried out
using Fluent software, and the distribution ofcompressed air velocity in the internal flow space ofthe model was obtained, as shown in Figures 5-10.

352

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016a rebound off of the borehole wall. With the increaseof dip angle of the bit nozzle, the airflow into thebottom increases gradually.
(2) With the increase of the dip angle of theexternal bit nozzle, the pressure on the hole bottom
increases gradually, but the air flow velocity
decreases.
Figure 5: The flow field when dip angle is 0°.

3.2.2 The analysis of airflow velocity on the holebottomAs shown in Figure 11, the center cross sectionof the drilling cutter near the bottom of hole is taken
as the analysis object. The cross section is the mostconcentrated area of drilling cuttings when cutting
coal.

Figure 6: The flow field when dip angle is 15°.

Figure 7: The flow field when dip angle is 25°.

Figure 11: The location of center cross section of thedrilling cutter.

The velocity distribution of different locations(range of 0-48.5 mm at hole-bottom line) in thecenter cross section of the drilling cutter under
different dip angles of the external bit nozzle isshown in Figure 12.

Figure 8: The flow field when dip angle is 35°.

Figure 9: The flow field when dip angle is 45°.

Figure 10: The flow field when dip angle is 55°.

The following observations are made from
Figures 5 to 10:(1) Compressed air jets out from the external bit
nozzle flow to the orifices and bottom of drill hole byFigure 12: The velocity distribution of different location in
the center cross section of the drilling cutter.

It can be concluded from Figure 12 that:(1) When the dip angle of the external bit nozzle
is in the range of 0°-15°, the velocity distribution on
the center cross section of the drilling cutter is more
uniform, and the air flow is wider through the crosssection, which can carry most of the drilling cuttings.
(2) When the dip angle of the external bit nozzle
is in the range of 25°-35°, the velocity of air in thecenter section of the drill cutter reaches a maximum
but the distribution is not uniform, and the airflow
velocity decreases near the wall of the hole.
(3) When the dip angle of the external bit nozzle
is 45° and 55°, the center cross section of the drill353

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

cutter becomes smaller and the velocity becomes lessthan 15 m/s in most locations, The drilling cuttings at
the hole bottom are not easily disturbed at thisvelocity.
In conclusion, when the external nozzle angle isin the range of 0°-35°, it is conducive to form thereverse circulation which can carry cuttings from thebottom of the hole. However, when in the range of
0°-15°, the air flow in the cross section of the drill
cutter is uniform. On the one hand, this is conducive
to cooling the drilling cutter, but on the other hand,
high-speed airflow can completely cover the area ofthe hole bottom, giving the drill cuttings easier accessto the center pipe to form the reverse circulation.
3.2.3 The analysis of outlet flow rate
As shown in Figure 13, the rate of air flow whichflows to the bottom is defined as positive, while flow
to the nozzle is negative. According to the simulation
results, the air flow rate of outlet1 and outlet2 under
different dip angles of the bit nozzle are found, as
shown in Figure 14.

Figure 13: The flow direction in the model inner.

Figure 14: The flow rate of outlet1 and outlet2 changed
with the dip angle of the external nozzle.

The following conclusions can be drawn from
Figure 14:(1) When the outlet pressure is the same, the air
flow through the external bit nozzle is the outflow
from outlet1 and outlet2. When the dip angle of the
bit nozzle is 0°, the flow rate of the two exits is thesame. With increases of the dip angle, the amount of
air flowing through outlet1 decreases gradually, andthe air quantity flow through outlet2 increases
gradually.
(2) When the dip angle of the external bit nozzle
is 35°, the air quantity flow through outlet1 is 0.
When the dip angle is greater than 35°, outlet1 not
only does not discharge the wind, but snifts the wind.

When the dip angle is greater than or equal to 35°,
the air quantity flow through outlet2 increases, but inpractical application, it is not conducive to thedischarge of the hole wall residual cuttings and thephenomenon of buried drill or clamp drill are likely
to occur.
3.2.4 The analysis of outlet flow velocity
Figure 15 is the variation diagram of averagevelocity of the outlet with the change of the dip angleof the external bit nozzle, obtained from thesimulation results.

Figure 15: The flow velocity of outlet1 and outlet2 changed
with the dip angle of the bit nozzle.

It is can be concluded from Figure 15 that:(1) When the dip angle of the external bit nozzle
is more than 30°, the average velocity of flows
through outlet1 is less than 15 m/s. In practicalapplications, the speed is less than pneumaticconveying speed which is the minimum suspension
speed of cuttings, therefore, this dip angle is notconducive to the discharge of residual cuttings, andmay cause the phenomenon of buried drill or clamp
drill.
(2) When the dip angle of the external bit nozzle
is about 10°, flows through outlet1 and outlet2 havethe same average velocity. The energy of wind in thisangle has reasonable allocation and utilization forcarrying drilling cuttings.
Based on the above numerical simulation results,
it is concluded that when the dip angle of the external
bit nozzle is in the range of 0°-15°, it can form thereverse circulation which is favourable to carry the
drilling cuttings. When dip angle is about 10°, theenergy of the air flow is reasonably allocated andutilized. Taking into account the actual application
process, the smaller the dip angle, the greater the gas
etching by the air flow. Dip angles close to 0° are notconducive to the maintenance of the molding andstability of drilling, and should therefore be avoided.
At the same time, based on the purpose of sampling
which expects to discharge more cuttings throughoutlet2, practical applications should make the air
quantity through the outlet2 slightly greater thanoutlet1, so the dip angle should be greater than 10°.

354

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

By comprehensive analysis, the range of the dip
angle of the external bit nozzle should be 10°-15°.
3.3 The determination of location of external jet
orifice
On the basis of the optimization of the dip angleof the external bit nozzle, a physical model of the bit
nozzle in different locations is established, as shownin Figure 16. The internal flow field of three kinds ofsituations model was simulated in order to determine
the position of the bit nozzle which is the mostbeneficial in promoting the formation of reverse
circulation at the bottom of the hole.
Location①

Figure 19: The velocity images when bit nozzle is inlocation ③.

Data from the analysis of the air flow rate andthe average velocity of outlet1 and outlet2 are shownin Table 1. The flow rate through outlet2 is about
65% of the total flow at location ①, about 60% at
location ②, and about 66% at location ③. Regardlessof the location of the jet orifice, the flow of outlet2 isdominant, while the average velocity of outlet1 andoutlet2 is greater than 15 m/s, which can satisfy thetransportation conditions of drilling cuttings.
Therefore, on the basis of the optimization of the dip
angle of the external bit nozzle, the position of theexternal bit nozzle has little influence on the effect of
the reverse circulation.

Location②

Table 1: The air flow rate and the average velocity of outlet
in different location of the bit nozzle.
Location③

Figure 16: The bit nozzle models of different location.

The velocity images of compressed air in themodel are obtained by numerical simulation, as
shown in Figures 17 to 19.

Location①②③

Flow rate/m3/s
outlet1
outlet2
0.53
1
0.61
0.9
0.51
1

Velocity/m/s
outlet1
48.1
55.4
46.1

outlet2
62.8
56.2
65.1

The flow lines of space velocity and effective air
flow rate are analyzed as shown in Figure 20. Whenthe external bit nozzle is in the three positions, theflow field in the hole bottom are not the same. Whenthe external bit nozzle is at location ①, the vortex
area of the hole bottom space is small, and the
direction of the air flow velocity is very smooth.

Figure 17: The velocity images when bit nozzle is inlocation ①.

When the external bit nozzle is at location ②, thevortex area of the hole bottom space becomes larger,
the effective air flow line is mainly concentrated in
the vicinity of the coal wall in the hole bottom, andthe flow line compression phenomenon is generated.
When the external bit nozzle is at location ③, thevortex area of the bottom space is small, but thedirection of the airflow velocity is not more smooth

Figure 18: The velocity images when bit nozzle is inlocation ②.

than with the bit nozzle at location ①.
In summary, models can be obtained through thesimulation of the internal flow field under three kindsof external bit nozzle locations. At the same dip angleof the external bit nozzle, the influence of bit nozzle
location on the distribution of the air outflow rate of
the model is small, and the outlet velocity can meet
the transmission speed of the cuttings. The vortex
area of the bottom space has an increasing trend,
which is not conducive to make the drilling cuttingsfrom bottom-hole get into the center pipe space toform an effective reverse circulation, when the bit355

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

nozzle location is moved forward. Compared with thesimulation results, it is concluded that the reverse
circulation of the hole-bottom drilling cuttings can bebetter realized when the bit nozzle location is far
away from the drilling cutter.

in location ②. The field test is consistent with thenumerical simulation results.
Table 3: The sampling effect of drill bit with different
locations of the bit nozzle.
Investigation
targets

Sampledepth/m

Location

Location ①

Location②

4. FIELD TEST
In order to verify the correctness of thenumerical simulation results, the diameter of a 95
mm drill was processed according to the above
conditions for a real coal mine reverse circulation
sampling test. The range of sampling depth, theaverage sampling quality of single drill pipe, and thedrilling situation in the sampling process wasinvestigated, as shown in Tables 2 and 3.
Table 2: The sampling effect of drill bit with different dip
angle of the bit nozzle.
Sampledepth/mDip angle (°)
080~11015

90~120

25

80~90

35
45
55

50~70
20~45
20~30

①

90~1205.7②

80~1102.4③

90~120

4.9

Location③

Figure 20: Velocity vector diagram and flow chart of bit
nozzle in different position.

Investigation
targets

Average
Drilling situation
sampling
in sampling
quality of single
process
drill pipe /Kg

Average
Drilling situation
sampling
in sampling
quality of single
process
drill pipe /Kg
good slag
4.2
discharge
good slag
5.7
discharge
good slag
4.5
discharge
2.1
buried drill
2.2
buried drill
1.7
buried drill

Note: the largest quality cuttings of single drill pipe drill
were about 9.3Kg.

According to the field test, it is known that when
the dip angle of the external bit nozzle is 15° theinspection parameters are all optimal. At the sametime, with the dig angle of the external bit nozzle
become larger, the phenomenon of buried drill often
happens because the normal drilling in the sampling
process cannot be guaranteed. Therefore, thesampling depth is shallow and the sampling quality islow. When the external bit nozzle position is in thethree kinds of situations, the sampling depth of the
field test is better, but the quality of the sample is lessgood slag
discharge
good slag
discharge
good slag
discharge

5. CONCLUSIONSThe external bit nozzle of tge sampling bit cansplit the compressed air in the mine into the holebottom space, which is the key configuration for
promoting the anti-cyclical effect in the process ofsampling, guaranteeing normal drilling slag
discharge, and cooling the drill cutter.
The dig angle and the position of the external bit
nozzle of the sampling bit was studied through theuse of numerical simulation and a field test. The
results show that when the dig angle of the external
bit nozzle is 15°, the drill cutter can make thesampling bit produce a better anti cyclical effect,
increase sampling depth, improve the quality ofsampling, prevent bit damage, and prevent theoccurrence of buried drill accidents.

6. ACKNOWLEDGEMENT
This study was financially supported by Special
Foundation of Liang Jiang Scholars Program.

7. REFERENCES
Hu Z.Y. (2011). Research and application of air
reverse circulated drilling tools in mining seam. CoalEngineering, No.4, pp. 116-118.
Li J.G., Lv G.C, Long Q.M, and Hu J. (2014).
Application effects research on deep hole fixed-point
fast sampling technology in gas content
measurement. Industrial Safety and Environmental
Protection, Volume 40, No. 11, pp. 5-7, 51.
Yuan L., Xue S., and Xie J. (2011). Study andapplication of gas content to prediction of coal andgas outburst. Coal science and technology, Volume
39, No. 3, pp. 47-51.
Yuan L. and Xue S. (2014). Theory andtechnology of coal and gas outburst prediction by gas
content in coal seam. Science Press, Beijing, 174 p.
Zhang Y.G., Yin K., and Wang R.S. (2007).
Design and experimental study of the air jet bit of356

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

reverse circulation continuous sampling. West-china
Exploration Engineering, No.3, pp. 77-79.
Zhang S.T. (2014). Key technology for gas
content direct determination method in undergroundmine. Journal of Mining& Safety Engineering,
Volume 31, No. 2, pp. 328-332.
Zhang R., Long Q.M, Li J.G, and Li Q.L. (2014).
Research on nozzle parameters of annular ejector
embedded in sampling drill. Zhong zhou Coal, No. 5,
pp. 77-80.

357

ISMS 2016

Paper No. 208

Electrical equipment certification in Canadian underground coal mines –problem solved?
Ronald (Ron) F. King, P.Eng.a, Peter Cain, Ph.D., P.Eng.b*ab

R.F King and Associates, Brentwood Bay, BC. Canada, V8M 1A8
Director of Engineering, DMT Geosciences Ltd., Calgary, Alberta, Canada, T2R 0E4

ABSTRACT
Certification of electrical equipment for underground coal mines in Canada is problematic. EX protected electrical
distribution equipment to Group 1 standards is not manufactured in Canada, and even if it were, there is no facility
in Canada that is accredited to certify it. The Canadian Federal laboratories previously tasked with the job are now
closed. Provincial regulations require certification by either a now-defunct facility or by the US authorities (MSHA).
Unfortunately the underground coal legislation in the US is significantly at odds with Canadian Provincial
legislation and equipment approval requirements, which presents problems with equipment certified there.
Although the underground coal mining industry in Canada is small, the western Provinces are blessed with
substantial resources of high quality steel-making coal, much of which can only be accessed by underground mines.
There are perhaps half a dozen large underground projects awaiting a price revival in Alberta and British Columbia,
and it was the authors’ experience at one of these projects that led to this paper.
The project in question was owned by a Chinese company that wanted to use Chinese electrical distribution
equipment certified in China to IEC equivalent standards. The process of convincing the Provincial regulators that
the Chinese equipment was safer than the equipment that would be allowed under Canadian standards was arduous,
but ultimately successful. The next step was to seek changes in the Canadian electrical standard applicable to mines
so that the benefits could be felt across the country. This has recently also been accomplished.
This paper examines the problem through an important aspect of electrical safety in underground coal mines protection against electric shock and arcing. It compares the requirements of the Canadian legislation, US, and UK
legislation and IEC standards used by other countries.
It concludes that the levels of safety against shock and arcing afforded by IEC-certified multi-point systems can beorders of magnitude better than the single point systems mandated or traditionally used in Canada. Additionally,
multi-point systems may be better suited to protect high voltage equipment beginning to be deployed in large open
pits than the current Canadian protection standards. The recommendations arising for changes to Canadian standards
await ratification, and the authors are hopeful that they will be adopted by Provincial regulators as soon aspracticable.
KEYWORDS: ground fault protection, equipment certification, hazardous locations, electrical standards.

1. INTRODUCTION
The Canadian underground coal mining industry
has a long history, although currently it is almost
extinct. However, Nova Scotia and the western
Provinces of Alberta and British Columbia still holdvaluable resources of steel-making coal, much ofwhich can only be accessed from underground. There
are perhaps half a dozen large underground projects
awaiting a price revival in Alberta and British
Columbia, and it was the authors’ experience at oneof these projects that led to this paper.
The major underground mining Provinces, Nova
Scotia, Alberta and British Columbia have developed
their own safety legislation in response to their
history of mining tragedies and the idiosyncrasies of
their underground mines. These safety codes rely on*Corresponding author – email : peter.cain@dmt-group.com

underlying safety standards developed and updated as
required by stakeholder committees struck by the
Canadian Standards Association. The safety ofelectrical installations in mines, including
underground coal mines, in Canada is governed by
CAN/CSA M421-11 “Use of Electricity in Mines”(CSA, 2011).
M421 sets out the standards which electricalequipment must achieve and requires that equipmentused in underground coal mines either be certified bya certification organization accredited by theStandards Council of Canada in accordance with therequirements of a CSA Standard (or anotherrecognized document when an applicable CSA
Standard does not exist) or it must meet therequirements of the authority having jurisdiction.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Provincial regulators require that the certification beissued by the long extinct UK Ministry of Fuel andPower, the Canadian Explosive Atmospheres
Research Laboratory, which no longer provides
certification services, or MSHA in the USA.
Thus, certification of electrical equipment forunderground coal mines in Canada is problematic.
EX protected electrical distribution equipment toGroup 1 standards is not manufactured in Canada,
and even if it were, there is no facility in Canada thatis accredited to certify it. The Canadian Federal
laboratories previously tasked with the job are closed.
Unfortunately the underground coal legislation in the
US is significantly at odds with Canadian Provincial
legislation and equipment approval requirements,
which presents problems with equipment certified
there.

2. BACKGROUND
An underground coal project in NE BC provided
the initial impetus for a re-assessment of theCanadian standards and certification requirements.
The Chinese owners wanted to import Chineseequipment to use in the mine. The equipment wascertified in China to Explosion Protected IEC Group
1 Standards (gassy mines) by laboratories in China
accredited under ISO/IEC Standard 17025.
Certification to IEC Group 1 (gassy mines)
Standards can be achieved using most internationallyrecognized explosion protection technologies, forexample: explosion-proof or flame-proof“d”;
intrinsically Safe “i”, or increased Safety “e”,
among others.
The electrical classification of underground coalmines internationally is varied. In some jurisdictions
a zoning system is required and is defined, in general,to similar requirements of Section 18 of the CEC,
although there can be differences dictated by theauthority having jurisdiction; other provinces in
Canada and other countries allow only equipment
certified to Group 1 standards to be installed inunderground coal mines. In 2004, Alberta allowed
the application of the CEC zoning system to be
applied in underground coal mines.
The Canadian Standards Association has adopted
these technologies and applies them to their surface
hazardous location (Group 2) certification
requirements. The technical requirements of thesecategories are detailed in the CSA and IEC 60079
series of Standards.
There are significant differences between MSHA
and other international “Explosion Protection”
standards for Group 1 applications, although in
general they achieve the same levels of safety;
MSHA only recognize “explosion proof” and“intrinsically safe” technologies in underground coalmines, although they do legislate a form of“increased safety” and apply it to battery installations
on “permissible” machines. The underground coalmine is divided into two areas or zones, namely“permissible” and “non-permissible”. Equipment
inbye of the last fresh air cross-cut is required to becertified to their EXP and I.S. standards while
equipment outbye in the fresh air is generally toindustrial standards.
The British Columbia Health, Safety and
Reclamation Code for Mines (HSRC, 2008) only
accept equipment certified for use in gassy mines by
the Canadian Explosive Atmospheres Laboratories(NRCAN) and the Mines Safety and HealthAdministration in the United States (MSHA). Since
NRCAN no longer certify electrical equipment for
use in gassy mines, and EX protected electrical
distribution equipment to Group 1 standards is not
manufactured in Canada, and the underground coallegislation in the US is significantly different to
Canadian provincial legislation and equipment
approvals, it has proved necessary to review otherinternational standards for equipment produced andimported from countries other than the US.
Notwithstanding the fact that the Chineseequipment had not been certified by authorities
recognized by the Provincial regulators, there werealso questions raised about the ground fault
protection methods used on the equipment whichwere very different from those which have becomecommonplace in Canadian underground coal mines.
This prompted a detailed review of the ground fault(earth leakage) protection systems incorporated into
the switchgear and transformer assemblies todetermine if it could be used under a variance tosafety codes on the grounds of “equal or greater
safety”.

3. GROUND FAULT PROTECTION
Ground fault protection systems in undergroundcoal mines have been developed to a far greater
degree of safety than the rest of the mining industry
due to the many hazards associated with mining in
gassy atmospheres; the sophistication, sensitivity andspeed of operation of the two systems discussed
below are designed to eliminate the electric shock
hazard produced by ground fault voltages completely
and to limit ground fault energy levels to reduce thepossibility of gas ignitions due to damage or malfunction of electrical equipment.
The two systems are:
1. Single point (SEL)
2. Multi-point (SEL)
Both systems have been used extensively inunderground coal mines since the early 1960’s andhave proven to be reliable and effective in reducing359

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

electrical incidents; the systems are unique andcannot be interconnected or mixed in any way
without affecting their safety levels and/or rendering
the protection systems inoperative.
The review of IEC certified equipment from
China recently installed in a BC underground coalmine shows significant differences of electricalprotection technology when compared to Canadianrequirements set out in the Canadian mining
electrical standard (CSA M421-2011). While theCanadian requirements generally apply themselves tosingle point high resistance neutral grounding
systems, specifically referenced to achieving limits toground potential rise due to ground faults, theChinese earth leakage protection systems are basedon the principals of a multi-point grounding system,
developed in the 1960’s by the National Coal Boardin the U.K. These systems achieve greater sensitivity
and speed of operation than the requirements ofM421, and thus have a greater degree of safety ingassy atmospheres where incendive sparking fromdamage to electrical equipment is a distinct hazard.
The single point and multi-point grounding
protection systems are described below andcompared to the requirements of the Canadianstandard.
3.1 Single Point Systems
The single point system of protection has, overthe past 40 years or so, been adopted in Canada in thecoal mines in Nova Scotia, Alberta, and British
Columbia, and uses UK manufactured FLP
transformers and switchgear. Some of thisequipment, with protection systems based on theearlier relay technology, is still in use at the Quinsam
Mine in Campbell River, BC.
Figure 1 shows a protection unit for highimpedance single point earthing systems andincorporates an earthing or grounding impedance
directly coupled to the transformer secondary star
point. The original value of this impedance was set tolimit fault current to 0.25 ampere with a “solid” earth
fault. The systems imported into Canada were
designed to operate with a 5 to 10 amp current
limiting reactor connected to the star point of the FLP
transformer. When an earth or ground fault occurs on
the system, the flow of current to ground unbalances
the three-phase system and the resulting unbalanced
currents are detected by a core balance transformer,
or zero sequence current transformer, causing theprotection unit to trip.
Of note is the search circuit or look ahead circuit,which prevents closure onto an existing fault after theunit has tripped.

Figure 1: Typical Single Point Earthing System (after
NCB, 1976).

3.2 Multi-Point Systems
In multi-point systems the transformer neutral isleft “free” and is not directly grounded (Figure 2);
each transformer secondary and each section switch
and motor control switch protection unit is fitted witha starred impedance connected across the power
conductors and the star point or artificial neutral isconnected to ground through a further highimpedance.
When a ground fault occurs on the system, return
paths for the fault current are provided by the ground
conductors on the system and the derived neutral
impedance of each protection unit, and there are as
many ground return paths as there are units on eachsystem. The fault currents are limited to a level thatcannot produce heating and any incendive sparking is
confined to the area of the fault, and reduces thepossibility of a shower of sparks. The ground fault
current will pass through every detection circuit ineach unit in operation on the system at the time thefault occurs; it can therefore be expected that every
unit will trip, although this does not always occur in360

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

practice. The unit feeding the ground fault isprevented from being re-energized onto the fault by alock-out or look ahead circuit which cannot be reset
if the fault still exists; other units operating on thesystem which may also have tripped can be restarted
without any reset.

less than 1 s if the ground fault current exceeds 20%of the prospective ground fault current. It should be
noted that the standard refers to a “device” not a
resistor, although another section of the Standard
requires a “neutral resistance”.
An interpretation of certification requirements
was that “neutral resistance” had to be a resistor leadto the initial rejection of the Chinese equipment
proposed for use underground.

5. NEXT STEPS

Figure 2: Typical Multi-Point Earthing System (after NCB,
1976).

The Chinese IEC certified units proposed for use
in Canada utilize a starred impedance and signal
amplifying system that is used to trip the primaryswitch feeding the transformer. They also include anearth leakage test facility built into the system which,when operated, connects a phase to ground through a
1K ohm resistor and facilitates regular testing of theprotection system.
Both systems meet the standard. Given the
superiority of the multi-point system and the lack offacilities to certify any overseas systems in Canada, astrong case is made to expand the scope of theCanadian standards so that Canada is not left behind.

4. SYSTEM COMPARISONThe CAN/CSA M421-11 standard requires thatground fault protection, where required, is provided
through a neutral grounding device that limits ground
fault voltage to 100 V or less and is de-energised in

Presented with two problems, namely an
unfamiliar earth fault protection system andequipment that had not been certified by a listed
agency, a program was developed to provide a meansof allowing the BC Chief Inspector to allow theequipment to be used on the grounds of “equal or
greater safety” under a process known as a “variance”
to the written code.
This process involved visits to China bycompany consultants and inspectors working for the
Chief Inspector. Meetings were held with equipment
manufacturers, testing facilities, underground mines
and regulators. The certification and testing standards
were thoroughly reviewed and compared to theappropriate IEC standards.
During the analysis of the information, theCANMET Report “Equipment Approval Guide for
Underground Coal Mining Equipment” (CERL
Report 2009-19 (TR) was used to develop an
approval process for the Chinese equipment thatwould ensure that it met the high levels of safety
enshrined in the Canadian standards.
This guide specifically states that making a direct
point-by-point comparison of the two certification
schemes (IEC & MSHA) for explosion-proof
protection is not easily accomplished. Each isconsidered an effective system, despite being
developed independently. Although the approaches
are dissimilar, both are technically valid and have ahistory of successful application, although thedifferences in approach to explosion-proof andflameproof standards, as well as the single and multipoint protection systems dictate that the two systems
cannot be mixed.
Establishing that the approaches were technicallyvalid was a major step in obtaining the variance.
Perhaps more compelling was the argument that
although M421 limits ground fault voltages inunderground coal mines to 50 V with a maximum
tripping time of 1 second when fault current exceeds
20% of the prospective ground fault current, theChinese system, which is performance tested to thespecifications of Chinese Standard MT/T 661 – 1997
limits ground fault voltage to less than 1 volt on361

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

systems up to 1140 V, effectively eliminating theshock hazard, and tripping times of less than 100 ms.
The 10.5 KV systems are limited to less than 25
V ground fault voltage, currents are limited to a
maximum of 6 amps, with tripping times of less than
100 ms.
The insulation (look ahead) monitoring system,
which is designed to prevent closure onto an existing
ground fault is set to trip at 20 k-ohms, and not allow
reset and restoration of power until the insulation
resistance has been raised to 40 k-ohms.
After a period of two years and much discussion,a variance to use the equipment in British Columbia
was obtained.

6. CONCLUSIONS
A comparison of the single and multi-point
systems discussed above does not favor one over theother; they are both proven technologies and have,for many years, operated throughout the international
mining industries.
The single point system has one fault limiting
device inserted directly into the supply transformer
star point, the failure of which would render theprotection system inoperable which is why neutral
grounding resistors are required to be continuously
monitored. However, the multi-point system has anumber of derived neutral grounding devices andground paths in the system and thus has a degree ofprotection against failure of one protection unit.
The objectives of the ground fault protection
requirements in CSA Standard M421-11 are to limit
touch potentials (ground fault voltages) to tolerable
levels (see Table 52 CEC) and to trip the supply inless than 1 second. Section 7.9.6 of M421 requiresthat ground fault voltage be limited to 50 V inunderground coal mines. There is no consideration
given to limiting the energy in ground faults to levels
that reduce the likelihood of incendive sparking.
As the use of electricity in surface andunderground mines expands and the size of
distribution transformers is increased, it is becoming
more difficult to achieve the GPR limits on single
point high resistance grounded systems because of
the increased magnetizing currents on the system
which dictate the limits of prospective ground fault
current. On some 72K V distribution systems tomining moveable equipment in Canada, due to thesize of the supply transformers, up to 150A is theminimum that ground fault current can be limited toin order to achieve the 20% ratio between prospective
current and trip settings.
Other difficulties are being experienced on
installations where the resistance of the return ground
path, due to the distances involved, cannot be
maintained to achieve the required GPR limits. The

Potash mines in Saskatchewan are experiencing thiskind of challenge and the “Petersen Coil” based
system is being investigated for possible use inmines. The theory behind this resonant system isbased on a tuned circuit and is widely used in Europe
for HV transmission systems, where the source star
point is grounded through a reactor sized to threetimes the system per phase capacitance. When there
is a ground fault, the reactor tunes with thecapacitance and the fault current is very small,therefore the GPR is small. For mining, ground
conductor monitoring can still be done, as the cables
are the same. Apparently these systems are used inmines in Europe and a few in the USA and arecertainly worthy of further investigation.
The Chinese equipment installed in BC is not
subject to the limits imposed by supply transformer
size and maintains resulting touch potentials from aground fault to less than 1 volt on the systems up to1140 V thereby eliminating this electric shock hazard
completely, and significantly reducing the potential
for gas ignitions from electric arcs or sparks in thearea of the fault. Tests conducted at the
manufacturers in China on the 1140 V systems
demonstrated tripping levels at less than 30 milliamps in less than 100 ms. Ground fault limiting
devices, which can include resistors, reactors,
transformers, capacitors, and other components
sometimes used in combination, are tuned to thecable range they operate on and can be adjusted tosuit changes in the distribution system to achieve themost sensitive tripping levels.

7. RECOMMENDATIONS
The requirements for grounding systems inunderground coal mines should be directed atlimiting fault current rather than ground potentialrise, where even at the present 50 V limit, current
levels of 25 amps and higher can meet therequirements of the Canadian standard.
The Canadian standard would benefit fromwording similar to the UK Approved Code ofPractice, which stipulates that for power systems
where there is a high risk of fire, shock, or ignition of
flammable gas, limitation of the maximum
prospective leakage fault current should be practiced.
The fault current and its duration should be limited toas low a value as is reasonably practicable tominimize the risk of shock or damage leading toincendive sparking or arcing.
In addition to this change, reference to“resistances” for ground fault protection should be
replaced by references to “current limiting devices”
All alternating current systems in undergroundcoal mines should be subject to a maximum
allowable ground fault current depending on their362

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

location in the mine and subject to any Zoning orelectrical classification requirements.

8. ACKNOWLEDGEMENT
The authors acknowledge the support of H.D.
Mining International Ltd. of Vancouver BC who
sponsored much of the review work described above.
The views expressed are those of the authors,and may not represent the views of their employers.

9. REFERENCES
CSA (Canadian Standards Association) (2011)
M421-11 Use of electricity in Mines, CSA,
Mississauga, 79p.
NCB, (1976) Colliery Electrician, National Coal
Board, London. 338p.
Lobay, G. (2009) Equipment Approval Guide for
Underground Coal Mining Equipment CERL report
2009-19 (TR) CANMET, Natural Resources Canada.

363

ISMS 2016

Paper No. 164

Improving shovel safety using SAFEmine’s situational awareness technology
Marco de Werka, Todd RuffbabEngineering, Aecon Mining, Fort McMurray, Canada
Product Development, Hexagon Mining, Tucson, United States

ABSTRACT
Mining operations involve risks that can be controlled through engineering and process control. The human factor
however, is extremely difficult to quantify and control. Best practices, proper rest, and a good work/life balance
contribute to safer operating conditions, but there is no way of predicting when an employee has had a bad day.
Impacts of external stressors that are beyond the control of the employer can be minimized by implementing safety
technology such as Hexagon Mining’s SAFEmine collision avoidance system. Technology is another layer ofprotection, but it does not give the desired outcome without proper implementation, business processes, andcontinuous effort to improve. Aecon has successfully completed a pilot project with the SAFEmine system and has
committed to operating a 5500 shovel and supporting dozer with the system. This paper aims to outline the process
and results obtained during the pilot project.
KEYWORDS: Collision avoidance; shovel pit safety; equipment safety; safety equipment

1. OBJECTIVE
SAFEMINEFOR

INSTALLING

Safety first is Aecon’s #1 core value and a recent
metal-to-metal contact incident has been driving
changes to mine pit safety. In a mining operation thepit involves the largest number of variables ingenerally the smallest physical space. A shovel,
dozer, trucks, and light duty vehicles all interact in acongested, but organized fashion. The cleanup dozer
is exposed to the highest risk factors in the pit, as it
works in close proximity to a large shovel that has
numerous blind spots. Operator situational awarenessplays a crucial role in pit safety, yet situationalawareness is greatly impacted by the operator’s stateof mind. External stressors that cannot always becontrolled or monitored by the employer are
impacting pit safety directly. Using technology toenhance the operator’s awareness and provide an
additional layer of protection can help mitigate manyof these risks. There are three main areas of risk thatwere looked at to be reduced by using a collision
avoidance system:
1.
2.
3.

Shovel and dozer interaction
Shovel and pit feature interaction
Light vehicle and shovel interaction

Proper business process controls can help define safe
movement of the dozer in relationship to the shovel;
however, the human factor can sometimes interferewith the business process. Reduced focus or constantrepetition of the same scenario can put the shovel

Corresponding author -email: mdewerk@aecon.com

operator at risk of moving the shovel towards thedozer when business process prohibits thismovement. At the same time, the dozer operator canenter the swing radius of the shovel without
following the established business process. If boththe shovel operator and dozer operator could be madeaware when such an event occurs it could prevent a
metal-to-metal contact.
The second risk is impact between the mining
face and the shovel body. Generally, every precaution
is taken to allow for sufficient room, but somesituations are challenging due to design constraints or
the sinking of a new bench. An experienced operator
will be aware of the swing radius, but the mining face
might contain ground water or frost that can cause
small collapses during regular operating of the
shovel. If such collapse occurs during the swing
motion of the shovel, it is nearly impossible for theoperator to recognize this. A system that can detectobjects and alert the operator about the changes in
his/her surroundings increases situational awareness,
reduces possible contact between equipment andsurroundings, and thereby increases pit safety andproduction.
Light vehicles enter the pit throughout the day
for surveying operations, shovel inspections andservicing. Light vehicles can easily be overlooked
compared to the size of the equipment around them ina mining operation. The shovel operator controls thepit and the access to the pit, however the shovel
operator cannot always see all the traffic that ismoving in the pit. If the shovel operator were toknow, at all times, where all light vehicles are thatenter the pit, this would help ensure that no lightvehicles are in the operating area of the shovel when
it starts moving after service, inspection, or a break.
The situational awareness gives the shovel operator
an additional layer or “last line” of defense.
The SAFEmine configuration selected by Aecon
does not require the complete fleet to be outfittedwith a SAFEmine system. While the focus was
mainly on the three scenarios described above, othervehicles, such as haul trucks, were also detected by
the system on the shovel. The radar portion of thesystem provides information on proximity at which
the trucks spot relative to the shovel. Once the shovel
swings towards the face, the radar on the near side of
the shovel will pick up if the truck is spotted too
close. This was a benefit of the system, but it was notpart of the scope of the evaluation.

2. SAFEMINE CAS SYSTEM
Hexagon Mining’s SAFEmine Collision
Avoidance and Traffic Awareness System (CAS)provides vehicle and equipment operators withinformation concerning the location of nearby
vehicles and provides an audible alarm if anapproaching vehicle is on a collision course.
Using GPS, the system determines the location,
speed, and heading of the vehicle in which it isinstalled, and transmits this information to othernearby vehicles, along with vehicle ID, using avehicle-to-vehicle radio network. Sophisticatedalgorithms constantly monitor vehicle traffic todetermine if a collision is likely. An audible alarm isgenerated only if two or more vehicles are at highrisk of collision, which greatly reduces nuisancealarms.
The system monitors the full 360° around thevehicle and vehicle locations are indicated on an
LED display (Figure 1) or on a graphical display
called ScopeScreen (Figure 2).

Figure 1: SAFEmine LED display showing vehicle
locations and distances (e.g. green LED indicates a vehicle
to the left at 100 m, red LEDs indicate vehicles behind andto the right at 50 m).

Figure 2: SAFEmine ScopeScreen showing TopView for
nearby traffic information.

The standard SAFEmine system consists of: 1)
an antenna unit that houses the GPS, vehicle-tovehicle radio, and WiFi antennas (Figure 4, top); 2)
the main processing unit and receiver (Fig. 4, left);and 3) the remote LED display (Figure 4, right).
These are the typical components installed on lightvehicles, haul trucks, and other secondary heavyequipment. For the Aecon application, light vehicles
and dozers were outfitted with this system.

Figure 4: Hexagon Mining SAFEmine system components.

The system provides two main functions: trafficawareness and collision avoidance. Traffic awarenessgives the operator an indication of nearby equipment,
but no audible alarms are generated. This information
is displayed using the LED display or ScopeScreen
and is meant to improve situational awareness(Figure 5). The collision avoidance function provides
audible and visual alarms when two or more vehicles
are on a collision course. This is determined using
Dynamic Safety Zones which extend in the vehicle’s
direction of travel and are adjusted according tovehicle size, type, speed, heading, and braking
distance. If two vehicles are approaching each otherand their Dynamic Zones intersect, then a collision
alarm is generated (Figure 6).

365Level 1: Traffic Awareness
Visual information = anticipate danger

representing that vehicle type, along with their ID
number. Typically all vehicles in the mine are
outfitted with the CAS system so collision avoidance
is functional everywhere in the pit. However,
Aecon’s situation as a contractor is unique in that
only Aecon-owned vehicles are outfitted. Other
contractor or mine-owned vehicles that do not have
SAFEmine installed are still detected by the
TrackingRadar system if they enter the body swing
radius of the shovel. An audible radar alarm warns
the shovel operator of this critical encroachment (Fig.
7). This way all vehicles are protected in the loadingarea.

Figure 5: Traffic awareness function provides the operator
with location and distance to nearby vehicles.

Level 2: Collision Avoidance
Audible alarm = call to action

Figure 7: Example of the ShovelCAS functions for
detecting a nearby dozer. Shovel operator receives shortalert when dozer enters the boom swing area. A fullcollision alarm is generated in the shovel if the dozer isdetected in the body swing radius.

4. EFFECTIVE SYSTEM
IMPLEMENTATION
Figure 6: Collision avoidance function provides audible
alarms and visual indicators when two vehicles are on acollision course as determined by their Dynamic Safety
Zones.

3. CAS FOR SHOVELSThe SAFEmine ShovelCAS system installed ona shovel at Aecon differs from the standard CAS
system in a few respects: a second CAS unit, called a
Beacon, is installed on the rear of the shovel toprovide improved heading information for machinesthat can rotate around a center point; radar sensors,called TrackingRadar, are installed around theperimeter of the shovel to provide precise location
information of nearby equipment in the shovel’s bodyswing radius; and the ScopeScreen is installed toshow vehicle location and ID, along with radar
alarms for body swing protection.
Other vehicles outfitted with the SAFEmine
CAS system components, such as Aecon dozers, areshown on the shovel’s ScopeScreen as an icon

A safety system is a risk mitigation system thatwill reduce the likelihood of an event occurring. It is
important to establish, prior to the project, what is
considered “successful mitigation”. Without putting astandard in place there is no measure of success.
One of the key elements that has to be recognizedwith a safety system is that it is only “a system”. The
operational processes associated with the system are
critical to a lasting change in operating safety.
Frequently, technology is seen as an answer tothe complete problem, but this is rarely the case.
With the SAFEmine system it is important to involve
all levels of the organization with the solution andensure that adequate checks and validations arecarried out on a frequent basis. Aecon had to change
its operational process by ensuring that all lightvehicles that enter the pit on a regular basis wereusing the mobile SAFEmine units. The radars areinspected daily for damage and any damage isreported immediately to ensure the system can be
repaired at the next available opportunity.

366

A system will only work if the operators are receptive
to the solution that is being installed. Operators weremade aware of the SAFEmine system prior to
installation and its functionality was explained indetail. Providing a transparent and open dialogue
about SAFEmine ensured that once the system wasinstalled operators would be willing to give it a fairtest. It is human nature to be opposed to change, but
Aecon succeeded with open dialogue to haveminimal hesitation by the operators to adopt theadditional system.
The SAFEmine system installation was planned
well in advance, minimizing delays during
installation. During a major outage all wiring was
pre-routed on the machine reducing the final
installation time down to nine hours. Performing the
installation in phases effectively eliminatedinterruption to production. The most important partof the installation is keeping in mind what repairs
could be required once the system is activated andhow to plan for simple replacements. Installing theradars on poles rather than welded plates for easy
access has proven to be a major time saving solution(Figure 8).

Figure 8: Rear mounting locations for TrackingRadar (justbelow counterweight).

When running the required communication
cabling, including connector locations, thought mustbe given to where the shovel will be disassembled fortransportation - this facilitates future moves. Runningwiring in locations where it will not need to be
touched for regular maintenance, including
component replacements, also decreases maintenancedelaysThe SAFEmine system was commissioned in aphased process to ensure that operators wereadequately trained and alarms where verified. The
initial deployment had all alarms silenced and daily
downloads were completed to check the frequency ofalarms. When radar alarms were excessive, radar
parameters where adjusted to bring the alarm
frequency down. After two weeks of adjusting andmonitoring, all alarms were activated in the shovel

and dozer. At the same time an engineer was on theshovel to coach the operator on the alarms and makeany required adjustments. It is critical to ensure thatthe alarms are meaningful for the operator so thatalarms are acknowledged. If the alarms are
configured incorrectly, the operator may ignore themand lose interest in the system, resulting in no
additional layer of protection.
5.

RESULTS AND KEY FINDINGSThe key objective of this project was to create asafer pit operation by providing the shovel and dozer
operator with improved situational awareness. The
system has been very well received by the operatorsfrom the start. The inclusive implementation strategy
resulted in minimal negative feedback. Minor
adjustments had to be made to the alarm settings toensure that alarms in both the shovel and the dozer
were meaningful and correctly indicated risk.
Since the implementation of the SAFEminesystem in January 2015, there have been no metal-tometal contacts involving the shovel and dozer. No
near misses have been reported either and no
maintenance has been required on the system. Only
semi-annual verification has been done on thesystem.
The largest impact that has been observed is thechange in shovel operator behavior. When truck
drivers spot the truck very close to the shovel, they
say that it increases production by reducing theamount of boom travel that is required per bucket
dumped. But this also increases the risk of contact. In
the months post-deployment, the radar system
detection range was slowly extended to allow for asafer separation distance (just beyond the counterweight swing radius); however, the observed alarm
frequency was reduced. This shows that shovel
operators are loading the trucks farther away from thecar body to avoid alarms and thereby reducing therisk of accidental contact between the truck andshovel. This change in behavior has had no negative
impact on production.
Using the GPS-based portion of the system, theshovel operators can see at all times where thecleanup dozer is located. The additional situationalawareness has been described by all shovel operators
as “a great tool” and “a must for all pits”.
The SAFEmine system has created a safer work
environment for Aecon, however it is absolutely
paramount that proper procedures are in place andadhered to. Any safety system adds a layer ofprotection, but it will not guarantee no metal-to-metal
contact.

367

ISMS 2016

Paper No. 183

An evaluation of Soma underground coal mine disaster with respect to risk
acceptance and risk perception
H. Şebnem Düzgüna *, Evren D. Yaylacı
Department of Mining Engineering, Middle East Technical University, Ankara, Turkey, 06800

ABSTRACTThe underground coal mine disaster that occurred in Soma-Eynez Mine (SEM), Turkey, is one of the largest coalmine disasters of this Millennium. A fire suddenly started in the mine and could not be controlled, resulting in 301
fatalities and approximately 100 injuries. Although the cause of the fire has not yet been determined and there arevarious hypotheses related to the ignition of the fire, most of the casualties were mainly due to decision-making
related problems in various hierarchal levels. Moreover, the decision making related problems in the emergency
management have cascading effects and impacts on the casualties, and are related to risk acceptance and perceptionof the mine management. In this paper, the casualties of Soma Mine Disaster (SMD) are analyzed in terms of risk
acceptance and risk perception in order to establish related guidelines for better decision-making practice in case of
emergencies in underground mines in Turkey. It is found that quite a high degree of risk was accepted for mine firesby the high-level decision makers, which led mine employees to have a false safety perception. This also resulted inalmost full ignorance of self-escape, inappropriate use of personal safety equipment, and unstructured emergency
management which yielded large number of mine staff to wait in the mine during the fire instead of a quick
implementation of the mine evacuation plan.
KEYWORDS: risk perception, risk acceptance, underground coal mining, Soma Mine Disaster

1. INTRODUCTION
Coal mining, especially underground operations,is still one of the leading sectors in terms ofoccupational incidents and illnesses, injuries, andfatalities. The US statistics show that fatality rate per
100 000 full-time equivalent workers in coal miningis almost 1.5 times more than in metal and nonmetal
mining and 6 times more than other industrial
activities. Additionally, coal mining has the highest
rate of non-fatal injuries among all types of mining
operations. More specifically Margolis (2010) states
based on Bureau of Labor Statistics in the USA in2007 that underground coal mining has considerably
more injuries than surface coal mining operations.
As compared to mine fires, explosions, use of
explosives, dust and colliery explosions result in ahigher number of fatalities in coal mines in the USA,as they are sudden onset incidents. For example,
10,390 fatalities were recorded as a result of 420
explosion related incidents. On the other hand, 727
fatalities were recorded in 35 mine fires in coal minesin the USA between 1900 and 2006 (CDC, 2009).
Between 1983 and 2013, 647 fatalities were recorded
in Turkey as a result of 18 major mining incidents(i.e. incidents causing more than three fatalities) andonly one of these incidents was a mine fire, caused 19
fatalities and occurred in a metallic mine in Turkey(Düzgün, 2015).

*Corresponding author – email: duzgun@metu.edu.tr

While the number of fatalities due to fires has
always been lower than the casualties of explosions
among mining accidents since the 20th century bothin Turkey and around the world, the Soma Mine
Disaster (SMD), which occurred due to a fire in theunderground coal mine and caused 301 fatalities, isunique in this respect and requires further
investigation. Considering the complex nature of the
SMD, where the fire resulted in cascading hazards,
various factors were involved in the high number ofcasualties. Among them, socio-technical factors like
unstructured organizational and human performanceas well as inadequate safety culture play critical roles(Leveson, 2011).
Risk perception is one of the key parameters insafety culture development as well as effective
human and organizational performance. In this paper
the role of risk perception and acceptance incascading hazards after occurrence of the fire in
Soma-Eynez Mine (SEM) and the amplified numberof fatalities in the SDM’s case are analyzed.

2. RISK PERCEPTION AND ACCEPTANCE
Although there are various definitions of hazard
and risk (e.g. ISO Guide 73:2009, UNESCO), in thispaper the definitions used in natural disaster risk areadopted due to the nature of the SMD.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

In quantitative risk assessment (QRA) risk is themultiplication of hazard and its consequences.
Hazard is the probability of danger for a given place
in a specified period of time. In the SEM case, hazard
can be simply defined as the frequency of annual
mine fires. The consequences of the mine fires can belisted as production and equipment losses, injuries,
and fatalities. Hence the level of risk is controlled by
the hazard and its consequences, which should beconsidered in determining effective risk assessmentand management strategies for a safe mine operation.
Risk assessment refers to the computation of risk andevaluation
of
it
based
on
certainacceptability/tolerability criteria (Düzgün andLaccase, 2005). Therefore, understanding the natureof mine fire risks and their systematic management aswell as associated uncertainties are key factors forrisk acceptance.
Risk perception plays a vital role in theestablishment of risk acceptance criteria for minesafety management, because an individual’s behavior
highly interacts with the degree on his/her perceptionof danger, professional and personal objectives, andhis/her contacts within the organization (Badri et al.,2013). Moreover, risk perception is highly relatedwith behavioral factors of mine executives andemployees in the framework of organizational safety
behavior (Zhao et al., 2016). Consequently,
understanding the behavioural factors is significant
for reduction of risks, as behavior based safety is oneof the major contributors to accident prevention andrisk reduction (Paul and Maiti, 2007).
Various hazard assessment methodologies basedon several parameters, such as machinery,
housekeeping, geotechnical data, age, experience,
frequency, physical and environmental conditions,etc. are proposed in the literature (e.g. Düzgün andEinstein, 2004; Sarı et al., 2004; Coleman and
Kerkerin, 2007; Margolis, 2010), as well as risk
assessment methods (e.g. Düzgün and Einstein, 2004;
Khanzode et al., 2014). Recent works on thedetermination of optimal evacuation routes in case ofmine fire for underground coal mines (e.g. Klote,2002; Adjiski et al., 2015) have potential fordevelopment of effective risk mitigation strategies formine fires. However, despite the well-developed
methodologies for hazard and risk assessment, therisk acceptance and perception is rarely taken into
account in underground coal mining, which also
plays critical role in risk mitigation.
Rohrmann (2008) defines risk perception as theindividuals’ judgments and evaluations of hazards.
The occupational risks and mitigation methods differ
for the sectors and sectorial stakeholders, including
the individuals, operational, and regulative
institutions/decision-making bodies.

Therefore, it should be expected that
understandings of each stakeholder are variable andsubjective (Rohrmann, 2008).
Hence, different
socio-psychological factors such as fear, culture,
education,
norms,
value
systems,society,experiences, and type of hazard and knowledge affectthe risk perception of individuals and organizations(Zhao et al., 2016; Rohrmann, 2008). Furthermore,these factors are highly related with the risk
acceptance and risk behavior of diverse stakeholders(Rohrmann, 2008).
Osei et al. (1997) and Renn (1998) lists factors
influencing risk perception and acceptance:• being voluntary vs. involuntary• controllability vs. uncontrollability• familiarity vs. unfamiliarity• short vs. long-term consequences• presence of existing alternatives• type and nature of consequences• derived benefits• presentation in the media• information availability• personal involvement• memory of consequences• degree of trust in regulatory bodies
Voluntary risks (e.g. cigarette smoking) tend tobe higher than involuntary risks (building a newchemical plant). Once the risk is under personal
control (e.g. driving a car), it is more acceptable than
the risk controlled by other parties (e.g. traveling as apassenger). In case of mine fires, for coal mines
having frequent fires due to spontaneous combustion
propensity of the coal, management may be more
willing to accept it. Hence mine management
experiencing frequent fires may have different risk
acceptance than those experiencing rare firesituations.
Moreover, having frequent mine fires andmitigating them successfully may lead to accepting
higher fire risks due to personal involvement andcontrollability. The risk acceptance also depends onfor example level of available information. Informed
mine workers can have better preparedness for minefires when they have fresh memories of theconsequences. In this paper, these factors are taken
into account in order to analyze perceived andaccepted risk for the SMD case.

3. BRIEF DESCRIPTION OF SOMA-EYNEZMINE (SEM) AND THE INCIDENT
Soma coalfield, located in the Aegean Region in
the western Turkey, is one of the first reserves with
Seyitömer coalfield, explored in Turkey after theestablishment of MTA in 1935 (Ediger et al., 2014).
The coalfield is one of the most economically369

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016valuable lignite resources with around 600 million
tonnes reserve in 11 different locations (Bilgin et al.,2015). Soma coalfield has higher calorific values
with Tunçbilek coalfield compared to other lignite
reserves in Turkey; the calorific values vary from2080 to 3340 kcal/kg (Ediger et al., 2014; Bilgin etal., 2015).
Soma-Eynez Mine (SEM) is one of theunderground mining operations in the Soma coalfield
and the mining activities have three operational
periods. The first one is the period of Turkish CoalEnterprises (TKİ), the state-owned mining company,
which covers between 1990 and 2006. In this period
the mining operations were conducted in seven
underground mines, including the Eynez operation.
The state-own period in the SEM ended in 2006 after
the privatization of the mine for a period of 10 years
with a planned production of 15 million tonnes(Union of Turkish Bar Associations, 2014). The
private company, Park Teknik A.Ş., operated theSEM between 2006 and 2009 (the second period).
After production of 0.852 million tonnes of lignite inthree years, the company applied for the terminationof the contract due to the technical problems andoperational difficulties in the SEM. As a result, thethird period in the SEM started in 2009 after signing
the transfer agreement among the parties with TKİ as
the license owner, Park Teknik A.Ş. as the company
willing to end its operations in the SEM, and Soma
Coal Enterprises A.Ş. as the private company willingto take over the SEM to produce the 14.1 million
tonnes of lignite for seven years (Union of Turkish
Bar Associations, 2014).
In this third period, the production is performedby conventional, semi-mechanized, and fullymechanized systems. Conventional and semimechanized systems have mostly short face lengthsof 40-70 m, and coal is extracted with pneumatic
hand drills and explosives and moved with the faceconveyors. The main difference between theconventional and semi-mechanized systems is thetype of support, where hydraulic and timber supports
are used in semi-mechanized and convectional
systems, respectively. Coal is extracted by a drum
shearer and loaded into armed face conveyor withlonger face lengths in the mechanized system (Sari etal., 2004).
The coalfield has three seams, namely, upperKP1, lower-KM2, and middle-KM3 (Hokerek andOzcelik, 2015) with thickness ranges of 7-8 m, 15-35
m, and 6-10 m, respectively. Because of the thicknessof the coal seams, longwall top coal caving (LTCC)
is adopted. The simplified mine layout is given in
Figure 1.
In 2014 the production in the SEM, were basedon five panels with 10 production faces. The mining

method, adopted in each face in the SEM, is given in
Table 1.

Figure 1: Mine layout for the SEM.
Table 1: List of the mining method in each face in SEM.
Panel
Face
Type
A
A1
Semi-mechanizedA
A2
Fully-MechanizedH
H1
Semi-mechanizedH
H2
Semi-mechanizedS
S2 upperSemi-mechanizedS
S2 lower
ConventionalS
S3 upperSemi-mechanizedS
S3 lower
ConventionalR
R7 (East)
Fully-mechanizedK
140
Conventional

Due to the spontaneous combustion propensityof the coal, ventilation rate was kept around 2300
m3/min. Moreover, coal seams in Panel A contained aconsiderable amount of methane (Erdoğan, 2015).
The SEM worked in three shifts with approximately
800 workers per shift.
On May the 13th, 2014, a fire started between
14:40-14:45 in the roof of the main road (Figure 1)
and ignited the wooden pieces used for fixing steel
sets. Due to the existence of methane, the upper partof the belt conveyor also ignited. The possible
location of the mine fire (Figure 1) is the point where
the conveyor number 4 conveys materials to the belt
number 3. The airflow was quite slow to the point ofalmost being stagnant and there were no methane
detectors in this area. Therefore, it is not possible tofind out whether there was an accumulation of
methane here that would trigger or contribute to thefire before it broke out.
The outbursting smoke and the smoke from theopen flaming fire that broke out in the gallery
combined and spread in a short time moving withhigh pressure through all the main roads to the A andH panels and in the main road to the S panel in themain ventilation direction of the mine. By the time
the fire started (14:40-14:45) there was an electricity
blackout in U3 area (Figure 1), belts stopped, and370

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

intense smoke appeared on the main road of the belt
conveyor number 4 and evacuation team wasrequested to the accident scene. At around 15:00
smoke appeared in the A panel and at approximately
15:10 smoke first appeared in the main road of the H
panel going to the S panel. At 15:20 smoke arrived at
the first floor of the faces in the S panel. At this point
fainting and deaths began. At around 17:00 the minemanagement decided to change the direction ofventilation, which was changed at around 17:30. Dueto this change, 142 workers, who accumulated at the
A panel area, where smoke was not effective, started
fainting and some died. At around 20:20-20:30 themine rescue teams reached the A panel area. The
search and rescue operation took almost three days
and the mine management was unable to announce
the number of fatalities until the research and rescue
operations were finalized.

4. ANALYSIS OF THE SMD BASED ON
RISK PERCEPTION AND ACCEPTANCE
In order to understand the accepted risk levels
and risk perception by the SEM management, thedecisions made during the onset of the fire as well as
the emergency management activities should beconsidered. Moreover, the mine layout and mine
operational conditions indicate risk perception of themine management and organizations that approveand audit the mine operations.
4.1. Risk Perception and Acceptance Related to
Decision Making and Emergency Management
Based on the testaments of the survivors in thecase files, it can be clearly stated that the minemanagement did not make a decision of evacuation
for the whole mine; rather, the decision of evacuation
was made only for some parts of the mine. Almost allof the survivors of the SMD, were those who
received an order to evacuate the mine based on thenews of the fire and who left the mine immediately.
Those who did not leave the mine and stayed behindlost their lives.
The principle of self-escape in coal mining,
especially in mine fires, proves its validity. Although
there were no records of the exact location of
fatalities who were found by the rescue staff, basedon the distribution of locations where the rescue
teams accumulated the bodies for taking them tosurface, the distribution of the fatalities in the minelayout can be predicted (Table 2).

Table 2: The distribution of bodies according to where they
were collected before they were taken to the surface.
Panel
Number of Victims
S Panel and around209
R Panel and around10
140 Face4
A and H Panels and Fire Zone
78
Total
301

Since the S Panel is located remotely in the minelayout (Figure 1) and clearly separated from otherpanels, it is obvious that most of the bodies kept here
belonged to those who worked in this panel and its
surroundings. Accordingly, 209 people lost their lives
in this panel and its surroundings (Table 2). On theother hand, 78 people lost their lives around A and H
panels. The low numbers of casualties in the R panel
and around the 140 Face was because fewer people
worked in these panels and those who worked there
could evacuate the mine immediately after the fire
broke out.
It can also be decisively said that the decision forevacuation of the S Panel, where the biggest numberof deaths occurred (209), were not made. As it can beseen in the statements of the surviving victims in thecase file, the safety engineers responsible for the S
Panel did not allow workers in this panels to leave
the panel. The main reason for not evacuating the S
panel is related to the factors of familiarity andcontrollability. As the mine experiences frequent fires
due to spontaneous combustion propensity of thecoal, the mine management considered this case to be
similar to previous cases and assumed they would be
able to control it in a short period of time.
However, mine management ignored the locationof the fire in the SMD, where it started in one of themain roads handling ventilation air intake withprobable methane in the environment. The majorityof the fires experienced in the past took place in the
production faces, which were easier to mitigate. As
these fires are always controlled, the fire of the SMD
was also considered to be the one that could becontrolled easily.
For this reason the engineers responsible for thesafety of the S panel were not given inadequate
information about the severity of the accident by thecontrol center and the top management. Moreover,the ventilation of the S panel was serial ventilation,
which does not allow the workers to take analternative safe escape route. Under such a mine
environment with the assumption of thecontrollability of the fire, the decision for keeping
workers in this area rather than evacuating the mine
was considered to be the best option.
This decision is in fact related to the risk
acceptance parameter of the presence of existingalternatives (unavailability of alternative escape371

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

route), and derived benefits (assumption of safer
faces than the main road full of smoke). It was mostprobably thought that the fire would soon be taken
under control, so the workers should wait. It was
assumed that the workers might be exposed to smoke
while evacuating the mine before the fire wascontrolled, and their masks would not function
sufficiently during evacuation.
For this reason, the engineers fought against thesmoke by blowing clean air to the faces in the S panel
using the compressed air pipes so that the workers in
the S panel faces would not get affected by thesmoke. However, they all died during this action.
The information availability and personal
involvement aspects of risk acceptance emerge when
the actions of executive mine management are
examined. All the top management bodies that had
heard about the fire entered the mine and were trying
to reach the scene of the fire, in order to increase thelevel of information availability. This prohibited theeffective application of an organized emergency
management and evacuation plan.
In other words, instead of focusing on evacuating
the mine safely and implementing emergency
management, they tried to respond to the fire, which
is directly related to personal involvement of the risk
acceptance. In fact, some of the workers of thefollowing shift, who did not know about the fire,
entered the mine and lost their lives due to inefficient
emergency management.
4.2. Risk Perception of the Mine Management andOrganizations for Approval of the Mining System
The S and H panels are ventilated by means ofserial ventilation. The workers, who were working at
the H panel, learned about the fire since they werevery close to the fire were informed about thedecision to evacuate the mine. This decision wasprobably conveyed to the H panel by the safetyengineer, who was in that area and took the firstprecautions to ensure the safety of workers after theoutbreak of the fire. Some of those workers working
in the H panel could not leave because of the smoke,
but they waited safely first in the A panel area andthen in this area, which were nearby and ventilated
through parallel ventilation.
Construction of a second ventilation gallery for
the S panel was planned in 2012, but this was notrealized. Without doubt, if this gallery had existed at
the time of the incident, workers could have beensaved. As A panel was ventilated by parallel
ventilation system, it allowed safety engineers tomake a shirt circuit with the use of ventilation doors
in the A panel area to protect workers in this zone
from the smoke. Since the H panel was close to A
panel, the workers of the H panel were able to reachthis safe zone. It was not questioned by supervising
institutions why this gallery, which had been plannedin the mine since 2012 but had not been constructed.
Although risk assessment and emergency drills
were conducted in the SEM, a fire that might occur inthe main roadway was not among the anticipatedrisks. An effective drill in which all of the mine was
evacuated was never performed. Therefore, theliability of all the institutions that checked andapproved the risk assessment cannot be overlooked.
In the SEM, the production increase (from 1.5
million ton/year to 3 million ton/year) was realized
before the ventilation system was improved. Hence,
all the institutions who approved such a production
increase, before the ventilation conditions were
improved in the mine, accepted a high level of risk,
which is mainly associated with the short/long-term
consequences. The long-term consequences of sucha decision were ignored and trust for the regulatory
bodies led all the organizations to take a high level ofrisk.
The production increase also brought about
increases in the labor force in the mine since theproduction was mainly dependent on semimechanized and conventional systems. Among the 10
production faces, only two operated in a fullymechanized system. Risk is the combination ofprobable losses when a hazard occurs. In otherwords, even if the danger is slight, the risk is stillhigh if the losses that will occur are significant.
Therefore, the high number of workers in the S panel
had already increased the risk level of the SEM.

5. RESULTS AND DISCUSSION
The production with high risks in the SEM wasin fact supported by the legislation prior to theaccident. The legislation was renewed shortly before
the SMD and details about the actions to be taken forsafety were removed. The new legislation had some
general statements that stipulated that the mine
enterprise should take any precautions necessary.
With this legislation, internal and external bodies
making audits in the mine were also unable to reportproblems related to mine systems threatening safety.
Though there are such legislations available aroundthe world, standards or protocols have beendeveloped for their implementation. Hence audits are
performed based on whether these protocols arefollowed or not.
In Turkey, specific sections in the old legislation
were taken out without developing such protocols forboth coal mining and other types of mining, and thelegislation containing the general statements valid
before the accident resulted in risks being taken moreeasily. Unfortunately, the amendments made in thelegislation following the disaster are not sufficient to372

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

improve the safety conditions in current coal mines.
Besides, any type of legislation enacted to improvesafety cannot achieve the expected outcome without
developing the standards or protocols, which has
never been taken into account during legislation
changes.

6. CONCLUSION
The reason why there was an extraordinary
number of fatalities in the SMD was not the fact thata fire started in the mine, rather the decisions taken in
the mine after the fire broke out. These decisions
were made under the perceived risks, which were
accepted despite their high level and caused acascading impact of the fire due to the adopted
mining system and management in the SEM. This
also resulted in almost full ignorance of self-escape,inappropriate use of personal safety equipment, andunstructured emergency management that led a large
number of mine workers to wait in the mine during
the fire instead of implementing the mine evacuation
plan. Therefore, regulations based on research on risk
acceptance and perception of the mine management
and organizational bodies is required for effective
risk management in underground coal mines.

7.

ACKNOWLEDGEMENT

The authors thank to Research Commission of
the Grand National Assembly of Turkey, Turkish Bar
Association and Chamber of Mining Engineers ofTurkey for providing access to the data related to theincident, İlke Arıcan and Mahmut Çavur for their
help in organizing the data and Bilge Çelik forediting the paper

8.

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374

ISMS 2016

Paper No. 71

From operational hazards to organizational weaknesses: changing the
focus for improvement
Georges Loisellea, Dragan Komljenovic b*, Mustafa Kumral caEngineer; Hydro-Quebec Production, Canada
Researcher; Hydro-Quebec Research Institute (IREQ), CanadacProfessor; McGill University, Mining Engineering, Canadab

ABSTRACTThe daily operations in the mining industry are still a significant source of risk with regard to occupationalsafety and health (OS&H). Various research studies and statistical data world-wide show that the numberof serious injuries and fatalities still remains high despite substantial efforts to decrease those numbers put
in place by the industry in recent years. This paper argues that the next level of safety performance will
have to consider a transition from coping solely with workplace dangers, to a more systemic model taking
organizational risks into consideration. In this particular aspect, lessons learned from the nuclear industry
may be useful, as organizational learning processes are more universal than the technology in which they
are used. With the notable exception of major accidents, organizational performance has not received all
the attention it deserves. A key element for reaching the next level of performance is to include
organizational factors in low level events analyses, and approach management as a risk control system.
These factors will then appear not only in event analysis, but also in supervision activities, audits, change
management and the like. Many recent event analyses across various industries have shown thatorganizational factors play a key role in creating conditions for triggering major accidents (aviation,
railway transportation, nuclear industry, oil exploitation, mining etc.). In the following paper, we will
present a perspective that may be used in supervisory activities, self-assessments and minor events
investigations. When ingrained in an organizational culture, this perspective has the highest potential forcontinuous safety improvement.
KEYWORDS: Occupational safety and health, safety culture, organizational performance, risk analysis andmanagement

1. INTRODUCTION
The business and operational environment
has changed considerably for the majority oforganizations. One of the peculiarities of thischange comes from the integration of various
industrial, technical, political, economic,
environmental, and financial pressures withregulatory adjustments ensuing from it (OECD,
2009, Homer-Dixon, 2011, Rzevski 2011,
Komljenovic et al, 2015). The operation of these
sectors, which were previously relatively
autonomous and independent, becomes more
complex as the number of stakeholders increases,
including the advent of new technologies andinterrelations between entities that are notanymore isolated and independent. A directconsequence of these changes is the nature of theevents which continue to occur. While theaccidents which arose previously generally foundtheir cause in known and assumed factors,

modern events find their origin in unforeseeninteractions between elements without visible
links. The linear story-telling of events is thus
less suited for improvement in conventional andpublic safety (Carrillo, 2011; Dekker et al, 2011;
Homer-Dixon, 2011; Leveson, 2011). Thisdiagnosis is not limited to major accidents but
also applies to other types of events (such asprocess disruptions or bankruptcy). In this paper,
we discuss the evolution of the nature of thecausal factors, and talk about approaches andtools developed and used in the nuclear industry
to take into account the complexity of its
operational environment. This experience can betransposed to other industries, including mining.

2. THE CLASSIC VIEW OF AN EVENT:FAILURE OF A WEAK LINK
We are accustomed to simplistic story-tellingof significant events and accidents. It is natural

Corresponding author: dragan.komljenovic1@videotron.cato identify a barrier, which if it had worked
adequately, would have prevented the undesired
occurrence. The barrier analysis allows us to
identify the less than adequate performance ofdefences and to propose specific corrective
actions. Even more elaborate methodologies,
such as MORT (Johnson, 1975), stands on theidentification of independent administrative
barriers in complicated organizational systems,
but not necessarily complex interactions. Thisview of an event supposes some linearity (a timeline) which could be representative of reality to acertain extent. Even if some aspects were notreflected by the analysis, the identification ofsome weak barriers remained good enough foreffective actions. Today, for most situations,such a linear approach is insufficient to allow acomplete and useful understanding of the stakes
and challenges regarding safety (Carrillo, 2011;
Dekker et al, 2011; Leveson, 2011).

3. A NEW SOURCE OF RISK IN THE 21ST
CENTURY: THE ORGANIZATIONOur understanding of events has changed forone main reason: the nature of its contributory
factors. The main source of risk today is theorganization itself (DoE, 2009; Leveson, 2011;
Kahneman, 2012; IAEA, 2013). Indeed, we cannotice that many industrial accidents haveessentially organizational components, such as
the company’s culture, safety culture,communication between groups, decisionmaking by people in authority, centralization anddecentralization, organizational clarity, andseveral other attributes which are more a matterof collective than individual work (Perrow, 1999;
DoE, 2009; Carrillo, 2011; Dekker et al, 2011;
IAEA, 2013; Mosey, 2014). These new
characteristics are consequences of the evolutionof two things: the type of barriers which ensure asafe environment, and the new interrelations
between entities that were previously isolated
and practically independent. Barriers enablingsafety of the operational activities evolved withboth the complexity of the tasks and themultiplication of involved persons. The mainconsequence is to change redundant barriers into
dependant and interrelated ones, and to make it
difficult to anticipate weaknesses in thesebarriers, leading to failures. This trajectory iswell pictured by the metaphor of the slices ofcheese, where degradation propagates throughholes in lines of defence. This picture is stilladequate, but a sequential display of such an
event is not so representative of the underlying
reality anymore; lines of defence have no more

the same redundancy. A more appropriate model
would rather present the situation as adegradation of margins, which locally would be
individually acceptable but which, collectively,
have important consequences that could not be
anticipated by a local analysis.
This peculiarity brings us to certain
characteristics of complexity. Complexity of theoperational
environment
asks
for
an
organizational answer adapted to face new stakes
and challenges.

4. NEW STAKES AND CHALLENGES:COMPLEX INTERFACES
The technological evolution brings animportant source of complexity. The automationof several processes conveys more opacity, withmany control rules and new information
technologies involved. One of the consequencesof this situation is the necessity of increasing thetechnical training for the operator. This training
is taken for granted during commissioning but
invariably undergoes dilution in time, the inservice training being reduced to certain aspects
more critical to health and safety.
Maintenance is another domain wheretraining is often neglected. We usually believethat the procedures of maintenance prove thequality of the tasks output. This hypothesis is notunreasonable at the beginning of the operation of
new equipment or system. However, experience
shows us that we observe a degradation ofconformity with time, with staff developing local
adjustments and the management taking certain
liberties with regards to the maintenanceschedule.
We
slowlydeviatefrommanufacturer’s requirements without providing a
new technical basis for changes. Indeed, because
a decrease of maintenance does not necessarily
cause immediate declining in performance, these
deviations are tolerated and even sometimes
reinforced because of their short term advantage.
The last element of the impact of thesechanges is the difficulty for the workers toanticipate the global behavior of all the systems
components in interaction. The complexity isthus a matter of interactions between simple andrelatively autonomous systems, which brings
unexpected reactions of the whole, often
amplified by the operator’s actions erroneously
adapted to those situations (Perrow, 1999; DoE,
2009; Carrillo, 2011; Dekker et al, 2011; Mosey,2014).

5. COUPLING, COMPLEXITYNORMAL ACCIDENTS

AND

376

This reality brings us to the concept ofcoupling and complexity introduced by Perrow(1999). In this model, the various types ofindustries have their characteristics mapped on
two axes: complexity and coupling (Figure 1).

Figure 1: Interactions/coupling (Perrow, 1999).

Key attributes of complexity are related to
the nature of interactions (interdependent
components, common mode vulnerabilities,
numerous feedback loops, multiple interacting
controls, nonlinear reactions, phase transitions,indirect
information,
adaptability,
phasetransitions, etc.), and couplings (short delays,
intolerance to variation, uniqueness of thesequence of actions, etc.). Thus, the complexity
is associated with the strength of linkages
between several autonomous constituent
elements of a system that yield interactions thatare difficult to grasp and anticipate. It creates an
emergent system behaviour which is influenced
by uncertain cause-and-effect relationships andunscheduled discontinuities (OECD, 2009;
Dekker, 2011; Homer-Dixon, 2011; Rzevski,
2011; Komljenovic et al, 2015). Thoseinteractions and characteristics create bothsignificant uncertainties and overall opaqueness,
which consequently make the operator dependent
on indirect information reducing his capacity for
immediate analysis and ulterior action.
These peculiarities highlight the importanceof an organized situational awakening, which canbe described as the capacity to estimate theanticipated effects in the short term following
actions, and to at least ensure that obvious
anomalies are quickly detected and corrected.

6. IMPACT OF THE NATURE OF RISKON THE FUNCTIONS OF THE
ORGANIZATION
Figure 1 shows that mining is an activity
having complex interactions but loose coupling.
This statement does not always apply to the
management of tailing dams or underground coalmining, which may have tight coupling as an
attribute. The characterization of an industry on
Perrow’s diagram also gives an indication of its
organizational structure and work process
requirements. An organization operating in acomplex and strongly coupled operational
environment has to pay attention to centralizationand decentralization of the decision-making
process (Rzevski, 2011). Considering the uniqueand irreversible character of particular event
initiators, some decision-making in the fieldcannot allow delays. The chain of authority has
to then be modified to allow a timely reaction,reflecting a global direction already known by
the organization members (system behavior is
too complex to enable a centralized real-time
control). Thus, organization should have enoughflexibility to be applicable in a large number ofdifferent and unanticipated situations. Such ”onthe-spot“ decision-making has to be supported bytransverse (cross-functional) functions. The latter
involves a participation of several ad hoc
specialized units which can act in unison torealize an analysis by taking into account all the
relevant aspects while facing an unforeseen
situation.

7. HUMAN AND ORGANIZATIONAL
PREFORMANCE MODEL
An organizational and human performancemodel has to be coherent, adapted and universal.
The advantage of such a higher level model
consists in enabling to share a taxonomy, whichis common to event analyses, supervision, andplanning an even safety and organizational
culture. Indeed, operating experience can benefit
a lot from a model that can be used in all
activities, a must in pre-job briefings for theinfrequent evolutions.
Strength of the model resides also in its
capability to present events as complex
interactions with several potential influences andnot limiting itself to a unique sequence. It goesbeyond the "simple" approach of redundantbarriers, which gives a very linear reading of theevents.
To err is human: The basic premise ofhuman performance is that everyone is willing to377

perform adequately and tries to fulfill his tasks tomeet expectations. However, we all makemistakes and this cannot be avoided. Theseerrors are basically predictable and controllable
in many ways. Thus, their frequency may be
reduced. An improvement in human performancemeans reducing the factors favourable to error
occurrences. Given that they cannot becompletely eliminated, one should limit theirconsequences (DoE, 2009; IAEA, 2013). Figure
2 provides an illustration of the elements thatexist before a typical event occurs. Breaking thelinkages may prevent events.

Figure 2: Anatomy of an event (DoE, 2009).

For events involving human performance,
the most interesting aspect is the error itself. Not
as a cause of an event, but as the event itself. In
fact, both success and failure share the samemental processes and only the outcome differs.
An error is considered as such because of theunwanted result it brings. The human error which
generates an event is only a symptom for which
we have to find the cause. In this context, ananalysis will have to determine why the event
happened (direct cause) and why it was notprevented(fundamental
cause).
That
fundamental cause should question and target theorganization (expanded fundamental causes).
The direct cause is associated to preventive
barriers, mitigating barriers, and error precursors.
The function of a preventive barrier is topreclude errors or lapses. Procedures, training,
qualification, work practices are all preventive
barriers and aim at reducing the number of
errors. Mitigating barriers, on the other hand, aim
to limit the consequences that may follow an
inadequate action. Steel cap boots or inflatingbags in cars are mitigating barriers to limit
consequences of mistakes.
Precursors are sneakier. They include moreor less subtle elements in the working
environment, or invisible constraints within thetask. Abnormal configurations or pressure to
execute a task with tight deadlines are allconditions which have a direct or indirect
negative influence on the cognitive processes
required for the safe execution of a task (DoE,2009; Kahneman, 2012; IAEA, 2013).
Both supervision and the organizationaloversight are processes designed for validatingthat barriers are adequate and efficient. Such as
mentioned above, people in positions ofauthority ensure the adequacy of the measures inplace to allow the orderly, secure and effective
completion of the tasks assigned to the staff. Thisadequacy must be verified by an ongoing process
to make sure that the required measures are wellorganized, that expectations are communicatedand met, and that nothing invalidates theorganizational hypotheses. Supervision is the realtime twin of audit and oversight. If gaps aredetected between expectations and observations,additional error prevention tools should beconsidered.
We call “organizational” the various factors
that
imply
a
collective
behaviour.
Communications, organizational clarity, andcentralization of decision-making are examples
of such factors. The weakness of one or severalof these factors can compromise the quality of
the activities and their products.

8. IMPORTANCE OF A MODEL FOR
EVALUATING DEVIATIONS
As noted earlier, the notion of deviation or
anomaly can vary significantly from anorganization to another. However, this concept
implies inevitably a model of conformity (todefine non-compliances). For example, a losttime accident will initiate a formal causal
analysis. The expectation then may be to identify
failures and improvement opportunities under the
influence range of supervisors. We shall thus ask
the analysts to evaluate conformity in terms ofprocedure adherence, use of protective
equipment, fitness for duty, and employees
motivation. This first evaluation can then becompleted by the evaluation of the qualificationand the staff training, the profile of the actors(individual capacity to realize the tasks which areassigned to them) or the workload.
Such an approach thus considers implicitly
an occupational incident as a possible althoughunwanted situation. Indeed, it does not question
the organization and represents an implicit model
which does not exclude such events because wealready are expecting to handle such situations.
We call that first loop learning, because the event
does not indicate a loss of control (as it was378

considered possible) and does not challenge theorganization.
On the other hand, second learning loop
involves investigating why an event was notprevented and what the organizational(fundamental) cause of the mishap is (Argyris.
and Schön, 1996). This part is a real challenge
for management as it requires introspection andis often perceived as a self-blaming exercise.
Nevertheless, it is an inescapable for root cause
identification.

9. CASE STUDY
We will use the official MSHA report onUpper Big Branch Mine Accident to illustrate themodel discussed above. On April 5, 2010, at
approximately 3:02 p.m., a massive coal dust
explosion occurred at the mine, killing 29 miners
and injuring two (MSHA, 2011; NRC, 2012).
The physical conditions that led to the explosion
were the result of a series of basic safety
violations and were entirely preventable. Whenviolations of particular safety standards led to theconditions that resulted in the explosion, theunlawful policies and practices implemented by
the owner were the root cause of this tragedy.
First, the preventive and mitigating barriers
were not adequately implemented or maintained.
Corrective action program (CAP) weaknesses led
to understating assessed hazards. The basic
training in non-compliance, hazard recognition,and prevention of accidents, roof control,
ventilation, and new tasks was less thanadequate. Tests for dust and methane were notconsistently carried out. Those barriers, required
for worker’s health and safety protection, were
not effective.
Precursors,
on-the-spot
factorsthatfacilitates committing errors, were also
numerous. For instance, conditions like not
performing adequate pre-shift, on-shift, or
weekly examinations were observed frequently.
Numerous existing hazardous conditions were
not identified, hence not corrected. Multi-gas
detectors were often not energized, leading toless than adequate air measurements. Log wall
shearers were not kept in safe operating
conditions (worn bits on the face ring). Cleaning
and rock dusting (90% of samples were noncompliant) were not satisfactory. Clogged water
sprays were impacting particle detection. Finally,
there was a significant accumulation of loose
coal, coal dust, and float coal dust.
Validation processes (audits and CAP) did
not report safety problems. Employees werediscouraged from listing hazards, hence notcorrecting them. For instance, there werenumerous non-compliances to the approved
ventilation plan.
As for supervisory activities, it was notedthat advance notice was given to personnel of
MSHA presence on site. Correcting and fixing
hazards was a priority only prior to MSHA visits.
False measurements were recorded on numerous
times. Hazardous conditions were not correctedor even posted as hazards.
As for decision making, even if for safetyconcerns it should be a decentralised, the right ofworkers to participate in their own safety was notrecognized.
The accident of Upper Big Branch alsobrought a comment from the NRC about
weaknesses in safety cultural attributes expectedin an organization with a solid safety culture.
They mention among other missing attributes
leadership in valuing safety, identification,
processing and issue resolution of safety
problems, work processes, continuous learning,and questioning attitude (NRC, 2012).

10. CONCLUSION
Initiatives in human performance arepercolating from nuclear power industry andhigh risk organizations, where they were usedsuccessfully in the last decades, to other types ofindustries. For instance, the NERC initiated theimplementation of a methodology of event
analyses directly borrowed from INPO (Instituteof Nuclear Power Operators). This initiative
doubtlessly reflects the thinking on the lessons
learned from the loss of North-East Grid in 2003
(NERC, 2011).
The nuclear industry developed multiple
tools to integrate human performance into thedaily activities of operation. Human factors,
initially a technical speciality centred on
ergonomics and man-machine interfaces, became
a set of fundamentals of the everyday life usedby all the actors and agents of the organization.
This implementation succeeded because thebasic statement was that the working
environment was essentially complex and that
attributes of complexity must be taken into
account.
Considering the evolution of the industrial
environment characteristics, we believe thatthese approaches and tools can and should be
used as a more global methodology for analysesof accidents and low level events (LLE), and fortheir inclusion in a general frame oforganizational culture. Recent events illustrate
the presence of these factors and the advantages379

to recognize their harm and the potential
consequences of organizational failures, which
can be detected in a preventive way with a LLE
analysis process.

11. REFERENCES
Argyris, C. and Schön, D. (1996),
Organizational learning II: Theory, method andpractice, Reading, Mass: Addison Wesley.
Carrillo, R.A. (2011), Complexity andsafety, Journal of Safety Research 42 (2011)
293–300
Dekker, S., Cilliers, P., Hofmeyr , J-H,
(2011), The complexity of failure: Implicationsof complexity theory for safety investigations,
Safety Science 49 (2011) 939–945
Department of Energy, DoE, (2009), Human
Performance Improvement Handbook, vol. 1,
DOE
Standard,
Washington
D.C.,
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November 2015)
Homer-Dixon, T., (2011), Complexity
Science, Shifting the Trajectory of Civilisation,
Oxford Leadership Journal, Volume 2, Issue 1,
2-15
IAEA,
(2013),
Managing
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Vienna,pub.iaea.org/MTCD/Publications/PDF/Pub1623_
web.pdf (accessed on 25 November 2015)
Johnson, W.G., (1975), Accident/Incident
Investigation Manual, U.S. Energy Research andDevelopment Administration, Division of Safety,
Standards, and Compliance
Kahneman, D. (2012), Thinking, Fast and
Slow, Farrar, Straus and Giroux, New York,
533p.
Komljenovic, D., Abdul-Nour, G. andPopovic, N. (2015), An approach for strategicplanning and asset management in the mining
industry in the context of business andoperational complexity, Int. J. Mining andMineral Engineering, Vol. 6, No. 4, pp.338–360.
Leveson, N.G. (2011), Engineering a Safer
World, Systems Thinking Applied to Safety, TheMIT
Press,
Cambridge
MA;
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Mosey, D. (2014), Looking beyond operator,
NEI
Magazine,
http://www.neimagazine.com/features/featureloo
king-beyond-the-operator-4447549/, (accessedon 26 November, 2015)
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Investigation,(2011),
Fatal
Underground Mine Explosion, April 5, 2010:

Upper Big Branch Mine-South, Performance
Coal Company, Montcoal, Raleigh County, West
Virginia,
IDNo.
46-08436,
http://www.msha.gov/Fatals/2010/UBB/Perform
anceCoalUBB.asp;
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2015)
NERC, (2011), Cause Analysis Methods for
NERC, Regional Entities, and Registered
http://www.nerc.com/files/CauseEntities;
Analysis-Methods-Version1-2-Oct10.pdf(accessed on 26 November 2015)
OECD Global Science Forum, (2009),
Application of Complexity Science for Public
Policy; New Tools for Finding UnanticipatedConsequences and Unrealized Opportunities,
Erice,
Italy,
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2015)
Perrow C. (1999), Normal Accidents: Livingwith High Risk Technology, Basic Books, NewYork.
Rzevski, G. (2011) A practical methodology
for managing complexity, E:CO Issue Vol. 13
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NRC,(2012),
SafetyCultureCommunicator, Case Study 4: April 2010 Upper
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9A003.pdf (accessed on 26 November 2015)

380

ISMS 2016

Paper No. 141

Risk management in the mining sector through complex systems
Maria S. Q. Domingues a, Adelina L. F. Baptista b, Miguel T. Diogo a,*a

CERENA – Centre for Natural Resources and the Environment, Faculty of Engineering of the University of Porto, Rua Dr.
Roberto Frias, s/n, 4200-465 Porto, Portugalb
Universidade Lusíada do Norte, Edifício da Lapa, Largo Tinoco de Sousa, 4760-108 Vila Nova de Famalicão, Portugal

ABSTRACT
There is a wide diversity of concepts related to complexity. What the Santa Fe Institute (USA) calls “systemic”
corresponds to what Morin (Morin, 2006) calls “complex”. Mariotti (2000) outlines the need for a unified
terminology. When understanding complexity, it can be perceived as a fabric (what is woven together) of
heterogeneous inseparably associated constituents (…) (Morin, 2006). According to different authors, the main
drivers of complexity can be found in human behaviour and in uncertainty. This structural of dynamic complexity
can be organizational, technological, or nested in human relationships. The complex interrelationship that exists
between individuals within an organization or project and its influence on competitiveness can be studied byindividual emotional intelligence and organizational behaviour (Love, Edwards, and Wood, 2011).
According to ISO 31000:2009, risk management “refers to a coordinate set of activities and methods that is used todirect an organization and to control the many risks that can affect its ability to achieve objectives”. Whenconcerning any sector, industry, services, project, or activity, the use of models or theories are required as
guidelines. Therefore when its basic elements comprehend human behaviour and/or uncertainty, in order for risk
management to be effective and adapted as much as possible to reality, it must be operational within complex
systems, as already demonstrated in different R&D environments. Risk management faces particular challenges
when approaching more specific needs, such as in the mining sector. The ILO convention (C175, 1995) concerning
Safety and Health in Mines, establishes “that workers have a need for, and a right to, information, training andgenuine consultation on and participation in the preparation and implementation of safety and health measuresconcerning the hazards and risks they face in the mining industry”, and furthermore recognizes “that it is desirable
to prevent any fatalities, injuries or ill health affecting workers or members of the public, or damage to theenvironment arising from mining operations”. In this context, risk assessment of integrated operations can be
improved by complex risk models and dynamic environments (Grøtan, Størseth and Albrechtsen, 2011).
Hence, complex systems can provide decision makers with a supporting tool comprising a three axis analysis model.
Each of the three axes (X, Y and Z) comprehends a multi-variable linear function f i: X: f_1 (management variables
related to mining); Y: f_2 (variables related to risk management systems) and Z: f_3 (variables related to complex
systems. Designing, developing, and testing a risk management decision-making model within complex systems,
transversal to other hazard sectors of all economic activities, may provide organizations with sustainable andintegrated risk management indicators.
KEYWORDS: complex systems; risk management, uncertainty, human behaviour, high hazards

1. INTRODUCTION
Risk management is an important tool for any
business sector. In an economy of global scale andhigh volatility due to the uncertainty of markets, thistool is even more important because through it highproductivity gains can be obtained.
In some industries risk management has to betaken particularly seriously because of the effect ofproject failure on public safety or on theenvironment, e.g. in the mining sector due to risk
perception,
feasibility
decision-making,anduncertainty.
Technical
andsocioeconomic
complexity and organizational culture are among the*Corresponding author – email: tatodiogo@fe.up.pt

main characteristics of complex systems. In the same
sense the mining sector is by nature complex, andmajor hazards, socioeconomic impacts and resource
nationalism must all be considered.
The present study intends to present the
aforementioned variables in a multi-variable linear
function analysis methodology approach throughcomplex system modelling, and effectively
correspond to a risk management tool in the mining
sector.

2.

COMPLEX SYSTEMS

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

In physical sciences when joining or connecting
a large number of systems, the macroscopic orcollective properties of the outcome system are notgenerally related with the properties of theirindividual constituents. In this case, the resulting
system is a complex system. Complexity, as incollaborative design, comprehends the interaction ofmany participants working on different elements ofthe design (Klein et al., 2003), such as in diverse
economic activity sectors, i.e. the mining sector.
2.1 Complex thought
The complex thought is an instrument of change
and resilience, and is a method in the sense of
Descartes. Its main objectives are laid out in Table 1(Mariotti, 2010).
Table 1: Objectives of complex thought.
ID
Description
1
Understand the uncertainty and learn to live with it
2
Learn to deal with paradoxes and situations thatcannot be resolved by the binary logic
3
Provide more thinking flexibility
4
Better understanding life, the nature systems andthe systems created by man
5
Provide better relationships in the natural world6
Better understand the ego and learn to deal with itin a less self and hetero destructive mode

Contrasting a dynamic and ever-changing world,
human mental models support decision-making
processes, which are normally conservative andnarrow-minded. “Like organisms, social systems
contain intricate networks of feedback processes,
both self-reinforcing (positive) and self-correcting(negative) loops” (Sterman, 2006).
2.2 Complexity as a diversity of concepts
Complexity is far from being a simple concept ora single point of view: from the Santa Fe Institute(USA) “systemic” designation, through to the Morin(2006) “complex” classification, to the need for a
unified terminology claimed by Mariotti (2000),
complexity overlaps multiple labels and approaches.
According to Morin (2006) complexity must be
perceived as a “fabric” (what is woven together) of
heterogeneous inseparable associated constituents(…). In general, complexity is defined in terms ofpotential states in a system or a number ofcomponents (Sterman, 2006), and what is particularly
important to identify is the origin of complexity, its
level, and its implications (Ameen and Jacob, 2009).
Human behaviour and uncertainty are the keystone ofbasic research in complexity, as established by many
authors.

Figure 1: Feedback process of learning (Sterman, 2006).

2.3 Complex systems and complex projects
A complex system implies software, cultural andpolitical issues, and people and organisations that canaffect the whole or a part of a system (Marashi andDavis, 2006). With more complex systems, more
control must be exerted on the local environment(Sayama, 2003). Knowing the nature and ways of
expression of complex systems in organizations canbe an important tool for managers (Amaral and Uzzi,
2007).
Each different context (simple, complicated,complex, or chaotic) requires different managerial
responses (Snowden and Boone, 2007). In this sense,the ‘soft’ world of systemic thinkers is complex,
chaotic and ever changing, but it is also true that aprocess of questioning can be a suitable learning
system (Checkland, 2011).
Organizational behaviour and individual
emotional intelligence may support studies
concerning the complex interconnection between
individuals in an organization or a project team andcompetitiveness (Love, Edwards, and Wood, 2011).
Cognitive systems engineering maintains that anindividual’s cognitive system is capable ofcontrolling their behaviour using information about
the self and the situation, where prior information(competence, knowledge) can be applied to a specificsituation (feed-back, indicators) and constructs(hypotheses, assumptions) (Hollnagel, 1998).
The discussion about complex behaviours of asystem at different scales does not explain why thesystems are simple or complex, however, a profile
that
quantifies
therelationshipbetweenindependence, interdependence, and scale ofcollective behaviour may accomplish this (Bar-Yam,1997). When a complex system adapts to disruptions
and changing conditions, this is called resilience.

382

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Resilience is also understood as an emergent property
of complex systems (Dahlberg, 2015).
Resilience engineering (for safety management)
exists to help people to deal with complexity underpressure in order to achieve success (Hollnagel,
Woods, and Leveson, 2006). To understand thecomplex systems approach in the design andimplementation phases, one must recognize the manydifferences between the traditional practices ofengineering and the natural evolutionary process(Bar-Yam and Kuras, 2003). The response ofhierarchical control structures, control and central
planning are limited and inadequate as a solution tocomplex social problems in the functioning ofcomplex organizations (Bar-Yam, 2003).
Marashi and Davis (2006) propose a systemic
methodology based on negotiation and argumentation
to help in the resolution of complex issues and to
facilitate evaluation options during design of systems.
The decision-making processes supported by thequantification of complex areas are reinforced
because they help set priorities and direct
management efforts (Sivadasan, et al, 2010).
To deal with ambiguity and interdependency,
people seek a plausible sense of resolve that makes
sense (Weick, Sutcliffe and Obstfeld, 2005). The
multiple perspectives related to complex situations
are supported by the combination of two methods:“multiple criteria decision making” and “techniquesfrom soft systems” (Petkov, et al, 2007).
Research has shown that the complexity of
projects is imperative to establish exceptional
preventive measures (Domingues, 2012). In order toobtain a measure of project complexity, Fitsilis andDamasiotis (2015) study the effect of time, cost, andquality, as well as the three in combination. This
analysis shows that project complexity can have alogical and valid representation.
Other researchers present a framework for
project complexity that identifies both technical andorganizational complexity. For Bosch-Rekveldt et al.
(2011), the majority of the elements in the technicalcategory of the proposed framework have a structuralcharacter, like the number of goals, largeness ofscope, number of tasks, and dependencies between
tasks, and uncertainties in goals and methods arecovered in the elements of the technical category.
Further, the stakeholder’s multiplicity and multiobjectivity are covered in elements like goalalignment (technical category) and the number ofstakeholders and the variety of stakeholder’s
perspectives (environmental category) (BoschRekveldt et al., 2011).

3.

COMPLEX RISK MANAGEMENT

Complexity offers an interesting theoreticalframework for the interdisciplinary studies ofintegrated safety management and risk management
methods (Le Coze, 2005). A risk management
strategy must be developed in order to identify as
many potential risks as possible and then to decide
how to deal with them. Risk analysis is an important
process of risk management that can identify andevaluate risk that has to be controlled, minimized or
accepted. This is essential information for theidentification of threats, and is a vital element for
decision-making (Bosch-Rekveldt et al., 2011).
The focus of engineering is on the risk factors,
development, and implementation of the measures ofcontrol; from design, construction, operation
processes, systems maintenance, and operation limit
states such as emergencies, and start/stop processes(Domingues et al., 2013).
Traditional risk analysis is not sufficient torecognize the heterogeneity of the input criteria(wildness in wait) because it does not recognize thedifference between the assumptions aimed at
emerging order nor the possibility of heterogeneity ofcriteria to be incorporated in such apparent order.
“Hence, (…) Risk Assessment (as part ofGovernance) should be recognized as a (social)knowledge practice (…)”, (Grøtan, Størseth andAlbrechtsen, 2011).
Perminova et al. (2008) explained the link
between uncertainties and risk management andintroduced a new perspective on how to manage
uncertainties
inprojects.
Traditionalriskmanagement assumes risk as uncertainty, while theauthor understands risk as one of the implications of
uncertainty. They define uncertainty as “a context forrisks as events having a negative impact on the
project’s outcomes, or opportunities as events thathave beneficial impact on project performance”(Perminova et al., 2008).
Risk management needs to be thoroughly
defined; such is the case in ISO 31000:2009, whererisk management “refers to a coordinate set of
activities and methods that is used to direct anorganization and to control the many risks that canaffect its ability to achieve objectives”. In a similar
context, an important change related to risk
perception can be found in ISO 9001:2015. The risk
management integration approach is now a major
component of the organisational culture.
According to Afgan, and Veziroglu (2012) thechange of social elements (health hazards) is aproperty of complex systems. Some of these socialchanges are an inherent characteristic of a system,
therefore, mutual interaction between the system andits surrounding are imminent and changes in theirinteraction rate will affect it safety. If these processes383

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

are in steady state, the system is considered safe. It isof interest to investigate the essential characteristics
of construction site systems (or other hazardous
sectors like the mining sector), which may lead toresilience changes.
In the prevention domain, the most effective
elements of a safety program are the support of top
management commitment, the selection of humanresources (own or outsourced) and strategic
management. In turn, the least effective factors are
the records, accident analysis, and planning of
emergencies (Hallowell and Gambatese, 2009). The
role of safety technicians and the need for training
concerning the impact of maintenance activities in
the industrial process have been specified for the oil
refining industry (Cardoso et al., 2014).
In order to demonstrate how risk can be managed
in high-risk workplaces, one may utilize an analysis
of communication gaps (Rasmussen and Lundell,2012). Jaafari (2001) states that risk management
should have a strategy-based project management
approach, using life cycle objective functions as themain drivers for risk reduction and value addition.
Systematic management of complex projects requires
important information skills and decision support
systems which can combine the management of“hard” and “soft” aspects, and facilitate decisionevaluation on a real time basis (Jaafari, 2001).

4.

DISCUSSION

Guidelines for risk management need the supportof models and/or theories in every sector, industry,
service, organization, or project. Thus, in order toachieve effectiveness and adaption to reality, risk
management as a consequence of its basic elements,
human behaviour and uncertainty, must be
operational within complex systems, as alreadyapplied in various R&D environments.
Risk management faces particular challenges
when approaching specific needs. In the mining
sector, “workers have a need for, and a right to,
information, training and genuine consultation on
and participation in the preparation andimplementation of safety and health measuresconcerning the hazards and risks they face in themining industry”, as established by ILO convention
C175 (1995) concerning Safety and Health in Mines.
The same ILO regulation furthermore recognizes“that it is desirable to prevent any fatalities, injuries
or ill health affecting workers or members of the
public, or damage to the environment arising frommining operations”. Risk assessment of integrated
operations is enhanced by dynamic environments andcomplex risk models (Grøtan, Størseth andAlbrechtsen, 2011).

The mining sector faces unprecedented
challenges due to unexpected internal factors (lack oftrained people and frequent equipment failures) andexternal factors (mineral commodity prices, market
volatility, increasing regulations, dwindling profits,
and changing global demand) and inadequate risk
management can lead to failures in production oreven serious injuries to people and the environment.
These events can interrupt projects and even cause
the complete loss of the business (Kumar, 2015).
Badri (2015) “puts into perspective the complexity of
the challenge of integrating OHS into industrial
project risk management” and emphasizes that theinterdisciplinary nature of this problem must be thestarting point of any research (Badri, 2015).
The mining industry is complex due to thenumerous operations; however, its principal concern
is safety. Haas and Yorio (2016) consider the
performance of a health and safety management
system (HSMS) “a critical and pressing issue fororganizations”. Their study analyses the state ofcurrent HSMS methods, recommending reports basedon threemetriccategories:
organizational
performance, worker performance, and interventions.
Nelitz, at al. (2015) consider the principal
environmental stressors in this field to be: human
intrusion in ecosystems, gas emissions, noise anddust in the air, soil disturbance and contamination,
linear infrastructure, traffic and solid waste in land,
and water pollution. These vectors must be
considered for any risk management analysis in themining industry.
5.

CONCLUSIONS

Complex systems can be a supportive tool for
decision-makers. An algorithm proposal is designed
based upon a three axis ( X , Y , Z ) analysis model.
Each of the three axes represents a multi-variablelinear function f i :X : f1 (mining management variables);Y : f 2 (risk management systems variables);Z : f 3 (complex systems variables).
A risk management decision-making model,
designed, developed and tested within complex
systems, aimed at being transversal to other hazard
sectors in any economic activity, may provide
sustainable and integrated risk management
indicators for organizations.

384

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 2: Variables proposal.
VECTOR ANALYSISXYM Mining

RMS

f1 related
tof2

miningmajor
x1 hazard

y1

Z

Risk
Management
Systems
related torisk
managementsystems
Risk
perceptionCS

Complex
Systemsf3

relatedtocomplexsystemsz1

technicalcomplexity
Organiz
ationalcultureindustryx2 Resourc
e

y2

z2

nationali
sm
socio
x3
economic
impacts

feasibility
decisionmakingy3

uncertaint
y

z3

yn

xn
XY : ( f1 , f 2

PLAN ANALYSIS
M vs RMS

XZ : ( f1 , f 3

M vs CSYZ : ( f1 , f 3

RMS vs CS

socio
economiccomplexityzne.g.: (Haas andYorio, 2016)
e.g.: (Nelitz, atal., 2015)
e.g.: (Badri,2015)

VOLUME ANALYSIS
M vsRisk Management
XYZ : ( f1 , f 2 , f 3 )RMS vsWithin Complex
CS
Systems in Mining

The analysis methodology proposed above is
supported by a three-dimensional scope, F =( f1 , f 2 , f 3 ) (complex systems, risk management,
mining sector), with F being a comprehensivemodel of analysis that can be used to determine
scenarios among different options, where several
objectives can be set, such as “zero accidents”. The
mining sector can thus be thought of as a complex
system and the risk involved in the sector understoodas a management variable and integrated through therisk management function.
6.

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386

ISMS 2016

Paper No. 135
Application of Cognitive Task Analysis in mining operations
Serenay Demir*, Elie Abou-Jaoude and Mustafa Kumral
Department of Mining and Materials Engineering, McGill University, Montreal, Canada, H3A 0E8

ABSTRACT
Through the advancement of human-machine interactions in various fields, understanding beyond the technicalcomponents has become prominent. Traditional methods for analyzing human behavior in a work setting, whichmostly centralize in identifying material and observable traits, don’t seem to fit modern technology and systems
used in various industries today. The concept of Cognitive Work Analysis (CWA), in this regard, has gained interestin academic and business settings in the last few decades. A cognitive analysis expands the observation of worker’s
interactions to a more cognitive and behavioural level and sets a safety standard for a well-designed project. This
research essentially aims to fully comprehend the five steps of CWA through the examination of cases and finally,
seeks possible applications in the mining industry, where accidents due to human error are impactful. In this paper,an initial proposal of a CWA model for the mining industry is developed based on an existing model of quantifying
human error in maintenance in various industries.
KEYWORDS: cognitive work analysis, work domain, human behavior, safety.

1. INTRODUCTION
Many industries operate in hazardous fields,
including but not limited to nuclear power,
manufacturing, aircraft operation, and mining. While
the successful human-computer interaction is
generally ensured, there are still a number ofconcerns and room for improvement when
uncertainties are taken into consideration. While
there are many possible reasons for industry
accidents, human error is considered to be one of themain causes. Furthermore, the mining industry, being
acknowledged as a particularly hazardous industry,
experiences numerous accidents caused by neglect,lack of knowledge, or simply by a combination ofhuman error factors. In order to better comprehend
the design process of such hazardous and complex
systems, a number of cognitive analysis tools havebeen introduced, such as Cognitive Work Analysis(CWA).
This analysis is defined as a “conceptual
framework that makes it possible to analyze theforces that shape human-information interaction” byFidel and Pejtersen (2004). Therefore, thepsychological and cognitive thought of a worker areimportant factors. Interview processes and analysis
tools are used to uncover the operator’s approach to ahuman-machine system, beyond the formal training.
Qualified workers can sometimes be unaware of theiractions, despite their motivation to fully complete thetasks. This might occur due to a number of conditions
such as mental and physical state, work environment,
and the equipment’s design. Later on, the steps ofthe analysis will reveal that through document

analysis, interviews, and observations, besides
cognitive processes, the cognitive work system
includes five different aspects. The focus of thepresent study is to discuss the application of an
improved cognitive work analysis to a mine
environment. The paper firstly elaborates on the
background of the research and its reflections in therelated literature; this is followed by the steps forcognitive analysis data collection; and finally basedon those data, an initial cognitive analysis model isformed in order to quantify the cognitive work
quality of a mine.
2. RELATED WORK
Behavioral researchers in different fields address
issues such as analyzing the process of decisionmaking under uncertainty (Kahneman & Tversky,1979) and the effect of cognitive and motivationalbiases on the output of risk analysis (Montibeller &Winterfeldt, 2015). More specifically, engineeringsystems have also tried to comprehend the factors
affecting human performance and potential ways toimprove it (DoE, 2009). Among many others, someof the techniques and concepts mentioned in these
papers, such as Skills-Rules-Knowledge Taxonomy
and Strategic Analysis, are related to the specificconcept of Cognitive Work Analysis, which is thebasis of this paper.
The domain of human factors engineering started
in the 19th century during the industrial revolution,
where physical tasks were repetitive and required
none of the cognitive ability necessary in today’s*Corresponding Author – email: serenay.demir@mail.mcgill.ca

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

work domains. As such, the first forms of task
analysis simply question the best possible and only
way to perform a task (Vicente, 1995). However, inthe case of unanticipated events taking place, thistype of analysis would not be prepared since it only
involves the completion of a specific task.
Through the late 20th century, when the need fora more adaptive tool arose in order to meet thedemands of a more complex system, the concept ofcognitive task analysis was introduced. CWA wasthen developed by Rasmussen in 1986, in order toprovide a more general approach that examines thetask, the work domain, the strategies, and thecognitive processes all at the same time. Also, it was
identified that nuclear power plants are extremely
vulnerable domains in the sense that they are fairly
complex systems, and accidents mostly occur when
the incident is unfamiliar to operators (Vicente,1995).
Starting from 1989, the cognitive work analysis(CWA) changed its scope towards a different
framework called Ecological Interface Design, whose
focus is to design the interfaces in complex sociotechnical systems (Naikar, 2011). The concept foundapplications in process control systems of various
domains, such as petrochemical and nuclear power,
addressing both small and medium-scale problems. In
the following decade, this concept was applied toquestions regarding training needs of systems inmany different domains (Pawlak & Vicente, 1996;
Jamieson, 2007; Lau et al., 2008).
Therefore, the development of CWA started withthe consideration of nuclear power plants but cansurely be adapted to many other hazardous industries
where conditions are similar. Hazardous industries
with high levels of human-machine interaction anduncertainty, such as mining, would surely benefit
from further applications of Cognitive Work
Analysis.
3.

COGNITIVE ANALYSIS DATAThis section aims to elaborate the five steps of
the Cognitive Work Analysis (CWA) to be used in
the mining industry, and also, introduce general data
structure for the model in the next section. Each stepof this analysis serves a different purpose ofelaborating on more detailed aspects of datacollection.
3.1. Work Domain Analysis
Having defined the scope and purpose of the
CWA, the first step is to apply Work Domain
Analysis, which illustrates the domain where the task
is performed. All, the purposes are determined andthe functional units are illustrated. The mining
domain can be described as complex, combining

together different operations such as drilling andblasting, materials handling, loading-hauling orconcentration, mineral processing, equipment
reliability, and so on.
It is essential to fully comprehend the aspects of
the work domain and define the external constraints
to be faced. The Work Domain Analysis helps torealize what the system is supposed to do rather thanwhat it is actually doing. In this step, therecommended tool is Abstraction Hierarchy, alongwith Abstraction Decomposition Space (Jenkins etal., 2008). Through the examination of documents,
operation manuals, and interviews with subject
matter, the functional purpose, the elements and theconstraints in the system are revealed.
3.2. Control Task Analysis
This second phase takes the analysis a stepfurther and evaluates the required task in the working
system. The necessary task/operation to be performed
to meet the functional purposes are examined indetail. For example in drilling-blasting operations
cognitive experts should understand, from a humaninteraction perspective, the following information:
drilling geometry, drilling equipment maintenance,
drill bit replacement, bit-rock interaction, explosive
storage, type and placement, operator performance,
and inventory management.
The acquisition methods are Cognitive WalkThrough and study of work practices (Lintern et al.,2004), and the tools recommended for this step byVicente (1999) are either Decision Ladder orContextual Activity Template. These steps reveal the
relevant detailed information regarding thecomprehension of the task, the steps to make adecision, and which levels of knowledge the operator
uses.
3.3. Strategies Analysis
Strategies Analysis constructs the third phase of
the CWA. After outlining the work domain and therequired task in previous stages, the strategies
analysis moves towards the specific factors that may
prevent the task from completion and what are themost efficient ways to complete it. All human factors
affecting a mining operation are documented.
The acquisition methods are Critical Decision
Methods, Interaction Analysis and Verbal Protocol
Analysis (Lintern et.al, 2004). After gathering thenecessary information, the recommended tool fordemonstration is Information Flow Map (Vicente,1999).
3.4. Social Organization and Cooperation Analysis
The fourth step of the CWA is Social
Organization and Cooperation Analysis. As the name388

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

suggests, this step investigates how the teammembers interact with each other within theconstraints that are posed on the team as a whole.
This stage moves from individual to team, with theanalysis being conducted in terms of teamperformance.
The acquisition method is Communication andInteraction Analyses (Lintern et al., 2004), whichmainly discovers the relationship of actors throughverbal processes.
3.5. Worker Competencies Analysis
The final phase of the analysis is Worker
Competencies Analysis. It aims to discover thefactors affecting the behaviors of actors within a
specific workplace, when different situations are inquestion. Through the review of previous steps suchas the Decision Ladder and Repertory Grid Analysis(Lintern et al., 2004), a specific tool called Skills
Rules Knowledge Taxonomy is formed (Vicente,1999).
When a specific strategy for a specific task is
considered, The Skills, Rules, Knowledge (SRK)
Taxonomy demonstrates both the SRK informationand the information about the activity and how
different they are in each knowledge state (Jenkins etal., 2008). The SRK Taxonomy classifies humanbehavior in relation to various restrictions in aworkplace. As a result of this analysis, Vicente(1999) suggests that the most important parts ofcognitive processes can be awakened and used for the
betterment of the design. Furthermore, according to
Kilgore and Cyr (2008), the SKR inventory can also
refer to the worker competencies that are essential fortask completion.
It is important to mention that this paper
attempts to provide a different approach by including
the analysis of physical and mental fitness of theworkers as well. These elements are specificallyfound important in the sense that the cognitive factors
for the workers strictly depend on these conditions.
This will be introduced in the following sections
where the model is presented.
4.

COGNITIVE ANALYSIS MODELLING

4.1. Cognitive Work Quality Factors
In an attempt to form an applicable and similar
tool in mining to quantify the CWA explained in theprevious section, some related research issummarized here. One of the most significant papers
develops a method to quantify human error usinggraph theory and matrix approach (Kumar and
Ghandi, 2011). The current study adopted thismethod and combined it with the extensive

framework of CWA as an effective tool in assessing
mining reliability.
In an attempt to understand the complex
structure of the mining domain, Cognitive Work
Quality (CWQ) is computed as a percentage
describing the qualities of the mine domain, such as
its management, safety, and feasibility. The
information derived from the cognitive analysis data
in Section 3 forms the CWQ factors. Each factor has
different characteristics, each of which was assigned
a quality rating ranging from “Excellent” to “Poor”.
4.2. Quantifying the Cognitive Work Quality Index
In order to calculate the cognitive work quality
index for a task, it is crucial to determine the severity
value of each factor, as well as the influence between
these factors. First of all, each of the eleven CWQ
factors mentioned in Table 1 (See Appendix 1) has aweight (ranging from 0 to 1) attributed to it, which
represents the role and importance of a factor for thestudied task. The total sum of the weight should beequal to one, such as:
WCWD+ WMD&E+ WTD+ WTI+ WSA+ WS+ WMC+
WT&C+ WPR+ WP&MF+ WCDT = 1
The higher the weightage of a factor, the moresignificant it is in the assessment of cognitive work
quality.
Secondly, as seen in the table in the appendix,
each factor has different attributes, “Cognitive work
characteristic”, associated with it. Each of thosecharacteristics is rated from a scale from 5-excellent
to 0-poor. For each factor, the sum of its
characteristics ratings corresponds to the level value,
Li. As an example, to know the level value of the“Tools Design” factor, we would need to sum therating assessed for its characteristics such as: “Design
Compatibility”, “Efficiency for Task Completion”
and “Availability of Equipment”.
Based on the weightage (Wi) and the level value(Li) of each factor, Quality value, Qi is formed asfollowing:
Quality value, Qi= Wi·Li
Finally, the influence between two factors, Fij,
with a scale from 5 to 0 such as 5- Strong Influence,
3- Medium Influence, 1- Weak Influence, and 0- No
Influence, are assessed. These weightages andinfluences between factors are assessed by experts
using human reliability analysis techniques. These
techniques, such as THERP, CREAM and NARA set
an error probability to the execution of necessary
actions taken by the workers at every cognitive work
quality factor. Many aerospace industries, such as389

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

NASA, use these techniques to considerably reduce
operational and procedural errors (NASA, 2010).
The quality values Qi and the influence values
Fij are placed in a matrix as followed, with thepermanent of this matrix being the cognitive work
domain quality index.
𝑄1
𝐹12 𝐹1𝑀𝑄2 𝐹2𝑀�
CWQindex= Permanent of � 𝐹21
𝐹𝑀1 𝐹𝑀2 𝑄𝑀
With M being the number of factors involved for thework domain of the mine.
4.3. Cognitive Work Quality Results
The cognitive work domain quality index isturned into a percentage by computing the index forthe ideal case work quality and for the worst work
quality, such as:
CWQ (%) = CWQIndex-CWQIdeal / CWQIdeal-CWQworst
Table 1 shows the range and signification of the
Cognitive Work Quality percentage obtained.
Table 1: Cognitive Work Quality Ratings andRecommendations.
Rating
Cognitive
Recommendations
range
Work Quality85-100
ExcellentMine domain does not
requireanymajor
adjustment.
70-85
Good
Minor adjustments areneededtoattainexcellency in the minedomain.
60-70
Average
The mine domain is
efficientbutmajorchanges are needed to
improve its quality.
45-50
Poor
Enhance the management
system by seeking advice
from suitable experts.
0-45
Insufficient
The mine requires major
update in its system.
Should close until a safeand feasible environmentis attained.

As can be observed, this tool can be used toevaluate the standing point of a mine site through athorough examination of all its subsystems andfinally, forming a set of recommendations in which
the weakest parts would be improved. Furthermore,this tool can also be used to determine which of thefactors contribute to the final rating more, with asimple regression type analysis.
While there are a number of other design
solutions that can be provided within this framework,
specific recommendations to improve working

performance may need further attention. According
to the rating range in which the mining system is in,some adjustment can be made to the work quality ofoperators regarding the task performance. Therefore,
today, many mining companies track the workers’
general performance such as the production targets
achievements,
computertracking,
safetyperformance, reported injuries, safety procedureflaws, daily physical/mental state observation by thesupervisors, meeting the task deadlines, and drug
testing when required, all with the purpose of
reducing human error.
Finally, the prospect theory by Daniel
Kahneman explains that decision-making appears
subjective for every human worker, and so, assessing
probabilities to errors (weightage and influences)
could lead to biases in the cognitive work quality
results (Kahneman & Tversky, 1979). Also, theexperts’ judgments may lead to biases on choosing
thecharacteristics
rating.
The
field
of
neurotechnology could be used in the future todirectly connect the consciousness of an individualwith equipment and improve human-machineinteraction in the mine site.
5.

CONCLUSIONThe Cognitive Work Analysis (CWA) is arelatively new and powerful tool in assessing theworkplace in every aspect. Taking its roots from 19th
century ergonomics research, this type of analysis
evolved from traditional terms and finally, has room
for cognitive research as well. The method allows thedesign to be prepared for unanticipated events bydetecting the constraints on task completion. As it
analyzes aspects independent from the task and theactor, CWA provides a more flexible andcomprehensive point of view. Furthermore, analyzing
all the different aspects simultaneously leads tounderstanding and forming strong interactions
between these aspects, which is beneficial for thedesign.
As a highly risky industry with constant humanmachine interaction, the mining industry is a goodcandidate for the application of the CWA in order toimprove its system. After data gathering andmodeling, the Cognitive Work Quality was assessedusing probability factors. The quantified quality
found is associated the mining system state andpossibly,canpresent
some
specific
recommendations. Furthermore, factors affecting theworkers are better addressed than in Cognitive Work
Analysis, simply because mining is found to bedifficult to manage in terms of human factors andreliability, moreso than any other industry. Mining
systems and many other hazardous industry domains
can benefit from the introduction of this framework390

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

in quantifying and improving the quality of design inthe work environment. Since this is only the initialstage of this research, a case study should be
conducted on an actual North American mine to test
its efficacy.
6.

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Kumar, V. N. A. & Gandhi, O. P. (2011).
Quantification of human error in maintenance usinggraph theory and matrix approach.. Quality andReliability Eng. Int., 27, 1145-1172.
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ecological displays for the secondary subsystems of aboiling water reactor plant simulator. IEEE
Transactions on Nuclear Science, 55(6), 3597-3610.
Lintern, G., Cone, S., Schenaker, M., Ehlert, J.,
and Hughes, T. (2004) Asymmetric Adversary
Analysis for Intelligent Preparation of the Battlespcae(A3-IBP), United States Air Force Research
Department Report.
Montibeller, G. and Winterfeldt, D. (2015),
Cognitive and Motivational Biases in Decision andRisk Analysis, Risk Analysis, 35 (7): 1230-1251
Naikar, N. (2011). Cognitive work analysis:
foundations, extensions, and challenges (No. DSTOGD-0680). Defence Science and Technology
Organisation Edinburgh (Australia) Air Operations
Div.

NASA (2010, September), NASA Human Error
Analysis. National Aeronautics and Space
Administration, Washington D.C.
Pawlak, W. S., & Vicente, K. J. (1996).
Inducing effective operator control throughecological interface design. International Journal of
Human-Computer Studies, 44, 653-688.
Vicente, K. J. (1995, October). Task Analysis,
Cognitive Task Analysis, Cognitive Work Analysis:
What's the Difference?. In Proceedings of the Human
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Vicente, K.J. (1999). Cognitive Work Analysis.
Mahwah, NJ: Lawrence Erlbaum Associate391

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Appendix 1: Cognitive analysis modeling table for the quantification of the Cognitive Work Domain Quality (CWQ).
Cognitive Work Quality Factors(CWQi)

Cognitive Work
Characteristics

Characteristic Rating
5-Excellent; 3-Good; 1-Average ;0-PoorMINING DOMAIN
Characteristics Of Mine Domain (CWD)

System Functionality
Defining the function and the purpose of the system and creating a work environment accordingly.
Constraint Management

Target Attainability.
Mine Design And Environment (MD&E)

Mine Planning And Scheduling
Safety Precautions (Mine And
Assets)Operation System

Effectively managing the environmental, legal and technical constraints posed on the working
domain.
Achieving the defined common goals and targets of the domain.
Meeting long range planning goals by creating an efficient mining production plan.
Ensuring a safe environment for employees and equipment (i.e. Ground support, geotechnicaldesign).
Attaining optimal operation system. Creating the most time-efficient schedule to meet production
deadlines and targets.

CONTROL TASK ANALYSIS
Tools Design (TD)

Task Implementation (TI)

Design Compatibility
Efficiency for Task Completion
Availability of Equipment
Guidelines and Procedures of Task
Performance Criteria Well-Defined

The equipment suitability for the required task.
How efficient is the current set of tools for the task completion (quality, safety, productivity andso on).
Having an easily accessible and available equipment for the task completion.
Ensuring the accessibility of information sources and data.
How well-defined is the criteria for assuring outstanding performance.

STRATEGIES ANALYSIS
Strategy Analysis (SA)Management of Uncalculated Event

Handling unanticipated events and being prepared for novel situations.

Availability of Methods of Task
Completion

Ensuring the accessibility of available methods and different strategies pathways.

SOCIAL ORGANIZATION AND COOPERATION ANALYSIS
Supervision (S)Mining Culture (MC)Clarity of Instructions andProcedures

Excellent communication is necessary between the employees and supervisor in order to assure
optimal and safe performance.

Mine and Asset Sustainability
Time Management
Incentives

Maintain mine and assets quality to be fit for continuous activity.
Activities must maintain their time deadlines and ensure that tasks are completed on time.
Encourage good working habits by evaluation financial business and safety performance andrewarding with salary and bonus.
Workers participate in volunteering and community activities in the mine domain
The mine site is well-structured for any possible emergency situation, with specific plans andguidelines.
Roles and responsibilities for each actor is different and should be well-defined to comprehend
abilities and specializations.
Information flows freely according to the organizational structure of the mine domain, and thedifferent workers have access to that information by efficient communication system.
The activities of the workers require a certain level of coordination and feedback mechanism.

Mining Community Involvement
Safety and Emergency Plan
Teamwork and communication (T&C)

Roles and Responsibilities
Communication
Involvement and Coordination

WORKER COMPETENCIES ANALYSIS
Performance Requirements (PR)Formal/Continuous Training
Skill-Based Behavior
Rule-Based Behavior
Knowledge-Based Behavior

Physical And Mental Fitness (P&MF)

Cognitive Demand Of Task (CDT)

Arm, Leg, Back Strength And
Endurance Level.
Emotional Stability
Concentration Alertness And
MemorySelf-Satisfaction
Acute Sight
Logical Reasoning
Perception Skills And Knowledge
Stress Handling Capacity
Learning Skills and Experience.

Level of formal and professional training completed by the workers.
Automated responses to alerting events. Does not require much cognitive process. Mostly used inphysical processes, i.e, operating a machine.
The workers are able to verbalize their thoughts and generate behaviors through their experiences,i.e, following safety instruction for truck haulage.
More complex and demanding process where the workers take the individual and system goals
into consideration with analytical reasoning and problem solving skills
Physical condition to conduct any required task using mining equipment.
Stress management and handling unexpected situations. Mental health issues.
The workers are able to stay focused during task completion and memories important details andfacts.
The workers are confident in the abilities and satisfied with the way of task completion.
The workers have a great vision and a rapid reflex to any situation.
Dealing with novel situation by improving knowledge-based behavior and high level of logicalreasoning.
Perceiving a thorough outline of the task and applying knowledge to a problem with an extensive
perspective
Managing the stress facing a situation or a problem.
The ability to learn and adapt new and professional knowledge; level of experience of workers.

392

ISMS 2016

Paper No. 145

Avoiding workplace accidents: the importance of pre-job safety analyses
Colin Morrish
Safety Engineer, Westgate-on-Sea, UK, CT8 8PZ

ABSTRACT
Careful, thorough, individual and group pre-job safety analyses completed by knowledgeable and competent
individuals can significantly reduce workplace incidents. Benefits include: decreased costs, improved productivity
and morale of employees, and an increased perception by those outside of positive safety consciousness.
Pre-job safety analyses can be done either by a team of workers or by a solitary worker. In both cases these workers
need to be trained in the completion of pre-job safety analyses. Supervisors must check to see that these analyses arecompleted competently.
The current study presents pre-job safety analyses, namely the Neil George Five Point Safety system and aconstruction field level risk assessment. Workers may be guided by one of these systems to complete a pre-job
safety analysis but must also have access to safe work procedures, and equipment and area inspection reports.
Examples of accidents that were investigated during the author’s 18 years as a Saskatchewan mine inspector will be
discussed within the context of the above. The causes of the accidents will be explored with close reference to how
pre-job safety analyses could have prevented their occurrence.
KEYWORDS: safety; incident; worker; management; supervision; pyramid; domino; tool; analysis; morale; five;
field; mining; answering; construction

1.

INTRODUCTION

Incidents occur at mine sites, with some resulting
in serious injury. In order to reduce the number ofincidents that occur, the entire workforce of thecompany should work together in various ways toprovide a strong, integrated and constructive force.
One way to involve the entire workforce is for theworker to conduct a pre-job safety analysis. Twomeans of pre-job safety analysis are the Neil George
Five Point Safety System and Field Level Risk
Assessment.

2.

where there is an injury potential, not just thosecausing damage or injury. These investigations
would find the causes of the incident occurring. This
information could be used to help prevent similar
incidences from being repeated.

1

10
Minor Injuries

WORKPLACE INCIDENTS

Models developed using available data show that
historically, serious injuries occur less often thanincidents where nobody has suffered an injury. Thisis displayed in the pyramid model in Figure 1. The
accident data put into this model was based on
1 753 498 accidents reported by 297 companies to a
US insurance company; it was analysed by Frank
Bird. The actual ratio varies between industries,
circumstances, and the reporting of incidents.
However, a large discrepancy between “close-calls”
and “serious or disabling incidents” remains.
The incidents that occur with greater frequency
have less damaging outcomes. There is a potential
for the causes of incidents to produce outcomes ofdifferent severity. It is vitally important that incident
investigations should be carried out in instances*Corresponding author – colinmorrish@btinternet.com

Serious or Disabling
Injuries

30

600

Property Damage
Accidents
Incidents with No
Visible Damage or
InjuryFigure 1: Bird's Pyramid Model (Strahlendorf, 2008).

2.1 Preventing workplace incidents
Incidents occurring at mine sites range fromharmless to one where workers are seriously injured.
The more severe accidents occur less frequently. To
work towards a safe work place, the mining company

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

in which work is conducted must have a positive
health and safety culture. This is one where the aimof all employees is to have no incidents occurring. In
virtually all countries today, the workers of mining
companies have the legislative right to refuse workthat they believe poses a risk of injury to others orthemselves.
An accident causation paradigm is referred to as
the Edward Adam's Domino Sequence for Accident
Causation which is shown in Figure 2. The term
“Management Structure: defines the mining
company’s objectives, organization, and theoperations. The terms “Management Behaviour” and“Supervisor Behaviour” capture operational factors.
The term “Tactical Errors” describes unsafe acts andconditions. Accident/Incident represents all reported
incidents including those where nobody was injured.
Finally, Injury or Damage describes the outcome topersons or property.

Man
agem
ent
Stru
ct re

Man Supeage rvisorment
Beha Beha
io

Tacti
cal
Erro

Acci
dent/
Inci

Injur
y or
Dam

company which is sincerely concerned about
employee health and safety will be enhanced.

3. PRE-JOB SAFETY ANALYSISThe primary aim of an accident investigation isto learn from the incident that is being investigated tofind not only the causes but also how to eliminate thecause in the future. Management, Supervision, andWorkers all have roles within their category of
employment to identify aspects such as the safety of
the workplace and equipment, safety controls
initiated, and critical procedures necessary. An
accountable pre-job safety analysis can identify
potential accident causes and prevent them fromsurfacing before an incident occurs.
An adjustment of Edward Adam’s Domino
Sequence For Accident Causation depicts thepartnership of employee groups that must work
together to avoid Tactical Errors. This Pre-Job
Safety Analysis Domino Model is shown in Figure 3.

M
an
ag
e
m

Su
pe
rvi
sio

W
or
k

Tacti
cal
Erro

Accid
ent/Incident

Injur
y or
Dama

Figure 3: Pre-Job Safety Analysis Domino Model.

Figure 2: Edward Adam’s Domino Sequence for
Accident Causation (Strahlendorf, 2008).

Management and supervisors are responsible for
ensuring that the tools are in place to minimise unsafe
acts and conditions. A major responsibility of theemployer is to ensure that the minesite and the work
process are both safe. The workers are directly
exposed to the unsafe acts and conditions; theyshould conduct a pre-job safety analysis at theworkplace and work processes. As evident in theterm, pre-job safety analyses should be conducted
before beginning work.
Pre-job safety analyses may be conductedindividually or as a group. Unsafe conditions of thework environment or work process should be noted
and rectified to negate the risk to workers. The major
benefit from this should be decreased accident
frequency and their related costs. Production can behalted in order to investigate incidents that haveoccurred. Mining company employee morale would
improve this tool was used, and incident frequency
would decline. Finally, public perception of a mining

1. Management:
Management must be
involved to maximise the effectiveness of a pre-job
safety analysis system. They decide which system touse and must ensure it is implemented anddocumented. They monitor it by checking regularsummaries of the analyses. They can compare
incidents that have occurred with reference to thepoints noted in pre-job safety analyses. Pre-job
safety analyses are repetitive and workers canbecome complacent in their accurate and appropriate
completion; frequent management monitoring should
ensure proper attention is paid to them. In addition,
the pre-job safety analyses completed by workers
should be explored to see if there are any trends in
unsafe conditions. It would be advisable to have asection on the pre-job safety analysis where workers
can communicate safety improvement suggestions.
2. Supervision:
Supervision must ensure
workers are trained in how to complete pre-job safety
analyses effectively. All pre-job safety analyses
should be checked while the work shift is ongoing to394

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016see whether they have been completed adequately
and if not, further coaching must be given to thosecompleting them. Positive feedback provided bysupervisors for well-conducted pre-job safety
analyses can be a powerful incentive to reinforce theimportance of pre-job safety analyses. Management
must then respond to these observations. This would
help keep workers positively engaged in the healthand safety process.
3. Worker: Workers are required to focus on
pre-job safety analyses before beginning work.
Management has given them a tool and requires themto use it to make their workplace safe. Effective
supervision teaches workers how to use the tool tohelp them identify unsafe characteristics. The prejob safety analysis is completed by checking theworksite, equipment and applicable work procedures.
Any observations concerning the workplace,equipment, and work process is noted down. Any
safety improvement suggestions should also be noted.
To use this tool effectively, workers must be
thoughtful and not simply “tick-boxes”. Management
and supervisor may disseminate the data accrued
from past pre-job safety analyses if it is applicable toother workplaces; this data may be used effectively tosupport subsequent pre-job safety analyses.
If Management, Supervision, and Workers allfollow their responsibilities for the pre-job safety
analysis, the possibility of accidents/incidents
occurring will be significantly reduced. If an incident
should occur, the existence of a pre-job safety
analysis may also decrease the severity of theincident. All levels of the workforce must be
committed to pre-job safety analysis, communicationmust be maintained, and personal accountability to
how accurately it is completed be kept.
3.1 Neil George Five Point Safety System
This first pre-job safety analysis system wasdeveloped by Neil George in 1942 for the Ontario
mining industry. At the beginning of each shift theworker, in this case a miner, must inspect his
worksite by using the Five Point Safety System,
noting what was observed. This system is completed
by the miner at the area where the work is being
conducted. As the name suggests, miners must
consider five points before beginning work. These
points are:
1. Check the entrance to the place of work:
The miner must check his surroundings as entry to
the workplace is made. This includes travelling fromthe dry to the work place, and going between
workplaces.
2. Are working place and equipment in goodorder: The miner checks the working place andequipment to ensure it is safe. Checking the working

place and equipment may require checking specificchecklists. If there are records detailing when theworking place or equipment were inspected by aqualified professional, check to ensure the records are
current.
3. Are people working safely: The miner must
check that the required Personal Protective
Equipment (PPE) is being worn.
Is everyone
following safe work procedure? Ensure that thecorrect procedures are being followed by the crew ora risk assessment is being completed if warranted.
4. Do an act of safety: The miner should note an
act of safety accomplished by himself/herself.
During the course of completing work, an instancewill present itself where a safe act is required to do
the job safely or prevent a hazard from presenting
itself. It is a constant reminder for miners to think
about safety.
5. Can, and will, miners continue to work
properly: The miner must keep safe work in mind.
Before beginning the task, consider what is necessary
to complete the job safely in terms of personal
protective equipment, materials, equipment, andprocedures or risk assessment as the job progresses.
The miner must check to see if all that is required to
do the job safely can be accessed. If something newcomes to light during the course of work and themeans to do the job safely is not immediately
available, consider what must be done to ensure that
all workers remain safe.
The Neil George Five Point Safety System is astraightforward and structured means for miners toassess their workplace, equipment and work
procedures. It is used at the workplace immediately
before work tasks begin. It can be used at the
beginning of shift and stand as a pertinent reminderof health and safety issues throughout the shift. A
card is often carried by the miners with the five
points noted down for them to consider. Columns for
successive tasks to which the miners are assigned
during their shift are sometimes present. It is a
general card that does not have specifics and cantherefore be used at different workplaces. Mine
workplaces are dynamic and continually change. In
order to complete the Five Point Safety System, it isoften necessary to complete checklists and refer tomaintenance log books to ensure they are current.
They encourage independent thinking and real timeengagement because the miners must check theirworkplace, equipment, and required workplace
procedures and continue to do so throughout the shift.
3.2 Field Level Risk Assessments (FLRA)This second system is used on many construction
sites and involves teams of workers who work
together to assess risks at the workplace. Instances395

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

when this would be necessary include before
beginning work, when a new worker joins the crew,when work procedures change due to site conditions
or when new equipment is introduced, and when theactivities of others in the area may pose a risk. The
FLRA is completed by:
1. Noting hazards to which workers are
exposed: As work is being conducted it is necessary
to question what hazards are present to them and thesurrounding workers.
2. Assess the risk: Note and assess theprobability of the hazard causing an adverse outcome
and the possible severity.
3. Control those risks: Note the means to control
the risk by noting the hazards, the means to control
the hazards, who will control them, and who will
check if the controls are adequate.
4. Follow up: At this point, what follow-up isrequired after the job is completed. This would
include reactivating controls that were suspended to
conduct work and notifying any personnel withinterest of the work being completed.
Some forms or checklists may be used inconjunction with the FLRA such as hot work permits,
confined space entry, ground disturbance checklists,
working at heights checklists, critical lift checklists,
and mobile lift equipment checklists. These lists
combine assessing and effectively controlling risks.

4.

REAL LIFE EXAMPLES

Field Level Risk Assessments (FLRA) or the Neil
George Five Point Safety System as applied to reallife accidents:
4.1 Worker falling 20 metres
A worker fell 20 metres through a lifting well to
the ground. He, along with the rest of his scaffold
construction crew, were part of a team building a milltransfer tower which was 20 metres above groundlevel. He was a junior member of the crew. He hadcompleted a field level risk assessment for the crewby himself from ground level and the entire crew
signed it off even though they were not present at its
completion. Although it had been noted that fallarrest was required, the locations and job tasks when
the fall arrest should have been worn were not. The
worker was passing construction material from 20
metres above ground level to the more senior
members of the crew constructing the scaffold above.
He was not wearing fall arrest. He had to collectsome tubing from a collection area beside the lifting
well. He went around the collection area to fetch
tubing when he stepped into the open hole of thelifting well and fell 20 metres to the ground.

If the pre-job safety analysis had been completed
properly, the questions that need answering in thisexample are:1.
What would have been revealed if the entire
crew including more experienced members haddone the risk assessment at the elevation where thework was carried out?
2.
Would the open hole have been noticed ifthey were at the workplace 20 metres above
ground?
3.
If noticed, would the open hole have been
covered or would they have been wearing fallarrest while working around it to prevent themfrom falling through the hole?
4.2 Load-haul-dump vehicle driving into open stope
A miner drove a Load-Haul-Dump vehicle(LHD) into an open stope. He started his shift
working on the construction crew. During the shift, asupervisor assigned him to work on the production
crew for the rest of the shift. The job to which he
was assigned was to remove ore from a stope in thelower levels of the mine with an LHD. He was
performing this task but it was hot and dusty deep inthe mine. He drove the LHD to higher levels in themine to look for dust masks. For some reason, hedrove into the upper level of the stope from which he
was removing ore. There was a sign that prohibitedpassage past the point beyond which the ore wasbeing withdrawn from the stope from the level from
where he was working. This sign was on a rope thatwas meant to stretch across the cross-cut; the rope
was not connected across the cross-cut. He drove
past this point. It is thought there was a crust of rockover the stope for which the ore was being withdrawnthat he successfully drove over. When he drove overthis crust while returning, the LHD went through thiscrust.
If the pre-job safety analysis had been completed
properly, the questions that need answering in thisexample are:1.
Would the sign preventing entry on top of
the stopes had been noticed even though it was notconnected?
2.
Would the miner have been aware of thereason the sign was present?
3.
Should contact have been made withsomeone before driving anywhere near this stope?
4.3 Miner detonating drill hole
A surface driller drilled into a hole loaded with
explosives, causing the explosives to detonate. The
surface driller was assigned to clear drill holes ofmaterial that had sloughed into them by drilling fromsurface to an underground stope. These holes were
loaded. The resulting explosion expelled the drill396

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

string from the drill hole. Workers underground in
the cross-cut that was driven into the open stopewhere this incident took place were flattened by
percussion of the explosion.
If the pre-job safety analysis had been completed
properly, the questions that need answering in thisexample are:1.
Would the driller have checked for evidenceof the holes having been loaded?
2.
Would the underground miners havechecked what work was being conducted near thestope including any surface work?
4.4 Drill rig fireTwo workers inside a surface diamond drill rig
were burned. While the drill was operating, a hosecarrying hydraulic oil was transported detached froma nipple and sprayed the driller and helper with thehydraulic oil. It was an extremely cold day and theinside of the drill rig was being heated with an open
flamed propane heater. This open flame set theworkers alight.
If the pre-job safety analysis had been completed
properly, the questions that need answering in thisexample are:1.
Would the competence of the connections
have been tested?
2.
Would the preventative maintenance recordsof the drill rig been checked and noted as not up-todate?
3.
Would open-flamed propane heaters inside adrill rig have been identified as unsafe?

5.

CONCLUSION

6. ACKNOWLEDGEMENT
I am thankful to Professor M. Scoble (UBC) for
giving me encouragement to submit this paper to this
symposium. I am also thankful to my father, Alan
Morrish (retired Mine Manager) & my wife (Jennifer
Morrish) for giving me support and editing themanuscript.

7. REFERENCES
Carlson G.K. (2014): It’s not mine safety but
mind safety: a Henderson approach. 3rd international
symposium on block and sublevel caving. pp. 53-60
Cann N., Casey S., Mills R., Ross J. (2011):
Reducing mining and mineral processing plant
fatality rates. MetPlant 2011: plant design andoperating strategies: world’s best practice. pp.27-38
Davies F, Spencer R, Dooley K (2001).
Summary guide to safety climate tools. Offshore
Technology Report.
Pillay M. (2013): Disasters, accidents andsafety: a review of theory and applications foradvancing mine safety management. Proceedings ofthe 35th international conference of safety in mines
research institutes. pp.367-376
Strahlendorf, P.(2008): Accident Theory Study
Guide. Board of Canadian Registered Safety
Professionals Study Guide.
Towsey C.A.J. (2001): Managing occupational
health and safety risk in mining: implementing
behavioural change. Bull. Australasian Institute of
Mining and Metallurgy. no. 3. pp. 26-30.
www.safeopedia.com/definition/684/field-levelrisk-assessment, (2016)

Pre-job safety analyses are essential in helping toprevent incidents, which often have the potential tocause serious injuries. Incidents which have alreadyoccurred must be investigated to find their causes andthereby preventing a repetition.
For pre-job safety analyses systems to beeffective, Management, Supervision, and Workers
must all work together to make them operate
effectively. Management must implement anddocument a system as well as monitor it to ensure it
is working. Supervision must teach Workers how tocomplete pre-job analyses effectively and check to
see that they are being done competently. The
pivotal employees to make pre-job safety analyses
effective are workers: they must complete themcompetently.
There is no doubt that competent pre-job safety
analyses would have helped prevent the four serious
mining incidents discussed here.

397

ISMS 2016

Paper No. 148
Notification systems and risk management
Maria M. Antunes, Miguel T. Diogo*, Joaquim Góis

CERENA-Centre for Natural Resources and the Environment, Faculty of Engineering of the University of Porto, Rua Dr.
Roberto Frias, s/n, 4200-465 Porto, Portugal

ABSTRACTIn an occupational context, “Notification” understood as “the act of telling someone officially about something, or adocument that does this”, (in Cambridge Advanced Learner’s Dictionary & Thesaurus), may reveal a management
approach. The ILO Code of Practice on Recording and Notification of Occupational Accidents and Diseases
provides practical guidelines for establishing and use a national system for recording and notification ofoccupational diseases.
In the European Union, there is a legal obligation to report occupational accidents and diseases. Such is the case, e.g.
with RIDDOR making reporting certain incidents a legal requirement. The report informs the enforcing authorities
about deaths, injuries, occupational diseases, and dangerous occurrences. Mandatory notification procedures may
also arise from certain types of specific hazards, such as exposure to biological agents.
Also relevant are reporting procedures in non-compulsory management systems, namely the ILO Guidelines on
OH&S management systems, when considering performance monitoring and measurement, clearly states that
“Reactive monitoring should include the identification, reporting and investigation of: (a) work-related injuries, ill
health (including monitoring of aggregate sickness absence records), diseases and incidents (…)”.
Findings from a case study over a 5-year period, based upon a notification system from one organization alone with
736 records and 915 workers directly involved, supports a main conclusion. A notification system is not by itself
enough in prevention terms. The validity of the required information and the way it is demanded is also fundamental
to obtain the best adequate records. The statistical data treatment is a critical stage, for changes regarding preventive
actions and measures are based upon such findings and conclusions.
Statistical treatment of data is fundamental to achieve adequate use of the data collected. Multiple correspondences
analysis privileges tables of relevant size simultaneously comprising variables of distinct nature: quantifiable andqualitative. It helps in describing the complex relationships that may exist among variables, both independent anddependent (Dohoo, 1996).
The mentioned study comprises a total of 47 management variables and a set of multiple sub-variables, resulting
from the notification system analysed. The results obtained identify management variables that may be consideredtransversal to other economical sectors, from the workers’ point of view (gender, professional classification andothers) and specific to the sector if the employers’ point of view is considered (day of the week, type of accident,
communication procedures, contributing factors, etc.).
The present study aims to design, implement and validate a notification system as both a transversal and sectorial
information system in OH&S risk management. A notification system should provide effective and adequate flow of
information within a proactive prevention context.
KEYWORDS: notification systems; risk management

1.

INTRODUCTION

In an occupational context, “Notification”
understood as “the act of telling someone officiallyabout something, or a document that does this”, (inCambridge Advanced Learner’s Dictionary &Thesaurus), may reveal a management approach.
The International Labour Organization (ILO)
Code of Practice on Recording and Notification of
Occupational Accidents and Diseases provides
practical guidelines for establishing and use anational system for recording and notification of*Corresponding author – email: tatodiogo@fe.up.pt

occupational diseases. Not only at national level, butalso at the level of the enterprise, it establishes that
“6.2.1. The employer, (...), should set up
arrangements within the enterprise, in accordancewith national laws or regulations, to notify
occupational accidents, occupational diseases,
dangerous occurrences and commuting accidents, as
appropriate.”
In the European Union, there is a legal obligation
to report occupational accidents and diseases. Such isthe case with Reporting of Injuries, Diseases and3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Dangerous Occurrences Regulations (RIDDOR)
making reporting certain incidents a legal
requirement. The report informs the enforcing
authorities about deaths, injuries, occupational
diseases and dangerous occurrences. Mandatory
notification procedures may also arise from certain
types of specific hazards, such as exposure tobiological agents. The Directive 2000/54/EC of theEuropean Parliament on the protection of workers
from risks related to exposure to biological agents atwork establishes that “Art. 13 - Notification to thecompetent authority, Art. 14 - 4. The notificationreferred shall include (…) the name and capabilitiesof the person responsible for safety and health atwork and (…) the protection and preventive measuresthat are envisaged”.
Also relevant are reporting procedures in noncompulsory management systems, namely the ILO
Guidelines on OH&S management systems, when
considering
performancemonitoringandmeasurement, clearly states that “Reactive
monitoring should include the identification,
reporting and investigation of: (a) work-related
injuries, ill health (including monitoring of aggregate
sickness absence records), diseases and incidents(…)”.

2. ORGANIZATION PRESENTATIONThe organizational set for the present assessmentof an institutional Notification System, in the HealthCare sector, and for a five years period of theanalysis, has a human resources framework as shownin Table 1.
Table 1: Workers.
Year
N
N+1
N+2
N+3
N+4
Mean (5 years)

Number of workers
411
415
433
400
391
410

Over the five-year period, there is no significant
variation concerning the job categories amid theworkers. The most relevant job categories are
Operational assistants, representing in average 39%of the total number of workers; nurses are the second
job category, with 32%; the third professional groupare the Doctors (aprox. 18%) and the technicalassistants are the smallest group with 11%.
The workers’ age profile, as viewed in Figure 1,
identifies the higher percentage (19.22%) in the “5054 year” age group, followed by the “45-49 years”
age group, for the first three years, and a slight
reduction for the last two years.

Figure 1: Age groups.
Education is diverse and the largest percentageof workers holds a university diploma within the first
five years: (year N (41.12%); year N+1 (41.2%); year
N+2 (48.96%); year N+3 (51.25%) and year N+4(52.17%). The educational qualification has been
increasing in a general manner over the years.
Another variable, in a management point of viewis the working schedule.
working schedule/ no. of workers/
years
250
200

229
202
188
165

150

222
175

193
146

167
152

54

53

2
0

9
1

100
50
0

14
0

11
0

21
11
1

Figure 1: Working schedule.
(Note: blue (non-flexible); red (shifts); green(flexible); purple (lapse timetable) and blue (openschedule))
The non-flexible working schedule wasundertaken for the five years from year N to year
N+4, 49.15%, 55.18%, 51.27%, 48.25% and 42.71%
respectively. Working in shifts (three shifts)

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

represented in the same five years 45.74%, 39.76%,
40.41%, 36.50% and 38.87%.

ation

Near-miss
Incident event

3. CASE STUDY
A preliminary analysis was undertaken to assess
the potential of information flow and variables
correlation. A sample register procedure wasdesigned, including only ten (10) fields (variables)
considered crucial for a first rough analysis.
Table 2: Sample register procedure.
FieldContent

Remarks

Man
age
men
t

0

Notifica
tion

Counter

S

RegisterMonthly counter for the event &counter of number of persons
involved in the event (Year)

S

1

2

Date

Day of the week

M

3

Time

In a 24 hour

M

Morning4

Shift

Afternoon

M

Night
5

Location6

GenderDrop down menu of a inside mapof the establishing

M

FemaleW
Male

7

Professi
onal
CategoryDrop down menu of the legal
professional category

W/
M

8

Type of
Accident

Drop down menu of different
accident’s description

R

9

Accidentclassific

Accident
M
Incident

Unknown/Not assess

Note: S – system; M – management; W – worker
and R – Risk
The sample register procedure comprehends ten(10) fields (a subset from the total of forty-one (41)fields of the main notification system. These ten
fields are grouped into four (4) management criteria:
S – system; M – management; W – worker and R –Risk. For the five (5) years period of the study, Table
3 shows the figures related to total number of records(events); number of workers involved in those events.
Table 3: Case Study characterization.
Year
Number of
Number ofRecords
Workers(Workers)
Involved
N
93
101
N+1
126
166
N+2
165
199
N+3
183
235
N+4
169
214
Total
736
915

Total
Workers
411
415
433
400
391

Out the 915 workers exposed to events subjected
to register, over the five years period: 208 are nurses(22.73%); 17 operational assistants (1.86%); 18
doctors (1.97%) and 19 nursing students (2.085). The
remaining registers comprise different job categories
accounting for 15.74% of the total workers.
For analysis purposes, out of the five (5) years
period, one particular year was selected (year n+3).
Table 4: Year N+3.
Year
Number ofRecords(Workers)
N+3
183

Number ofWorkers
Involved
235

Total
Workers
400

Findings from a case study over a 5 year period,
based upon a notification system from one
organization alone comprehending 736 records and915 workers directly involved, supports a main
conclusion. A notification system is not by itself
enough in prevention terms. The validity of therequired information and the way it is demanded isalso fundamental to obtain adequate records.
The statistical data treatment is a critical stage,
for changes regarding preventive actions andmeasures are based upon such findings andconclusions400

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.

RESULTS=

Statistical treatment of data is fundamental toachieve adequate use of the data collected:- Combinatory analysis,- Multiple correspondences analysis (MCA),
privileges tables of relevant size comprisingsimultaneously variables of distinct nature:quantifiable and qualitative. MCA helps in describing
the complex relationships that may exist among
variables, both independent and dependent (Dohoo,
1996).
For the five years, Table 5 presents the numberof possible combinations ( n C p ) according to ten(10) variables of the sample register procedure.
Table 5: Case Study characterization.
n = 10No. ofcombinations

Total ofcombinations

=

p
=

3

nCp
=

120

165

p
=

4

nCp
=

210

375

In this set of a total of 375 combinations (45 (2vars) + 120(3 vars) + 210(4 vars)), there is an
essential aspect of always including field 00 (variable“Notification”) and field 01 (variable “Register”).
Thus the total number of 224 combinations (17(2vars) + 67(3 vars) + 140(4 vars)) as presented inTable 7.
Table 7: Year “N+3” combinations (Field 0 &1).
n=

p
=

2

p
=

No. ofcombinations

Total ofcombinations

nCp
=

17

17

3

nCp
=

67

84

4

nCp
=

140

224

nCp
=

45

45

3

nCp
=

120

165

p
=

2

p
=

4

nCp
=

210

375

p
=

p
=

5

nCp
=

252

627

p
=

p
=

6

nCp
=

210

837

p
=

7

nCp
=

120

957

p
=

8

nCp
=

45

1002

p
=

9

nCp
=

10

1012

p
=

1
0

nCp
=

1

1013

10

However the present study only analyses
combinations resulting from 2, 3 and 4 variables.
Table 6: Year “N+3” combinations.

pn = 10No. ofcombinations

Total ofcombinations

2

45

45

nCp

The register system under study, supporting thenotification system can be viewed has a global set in
the management cycle. It comprises a total of 47
management variables and a set of multiple subvariables, resulting from the notification systemanalysed. The results obtained identify a set
management variables such as: working schedules;
job categories and the accident’s description as
management variables essential in a risk assessment
procedure. Also crucial, is the legal framework ofaccident work-related classification of all the records.
The codification system adopted, pretends tohighlight the importance of a set of management
variables which may be considered transversal toother economical sectors, from the workers’ point ofview (gender, professional classification and others)
and another set which is specific to the sector if theemployers’ point of view is considered (day of theweek, type of accident, communication procedures,contributing factors, (…)).
This study aims to design, implement andvalidate a notification system as both a transversal
and sectorial information system in OH&S risk
management.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

A notification system should provide effective
and adequate flow of information within a proactive
prevention context.
Thus, the present study analyzed 736 records,
involving 915 workers. This set of records is howeverpart of a global notification system, not only workrelated accidents, but also comprising all type ofadverse events occurring, (total of 3763 records forthe 5 year period, involving 4636 persons for thestudied establishing)
5.

FINAL REMARKS

Besides the mandatory legal framework
procedure 1 “If workplace injuries or illnesses occur,
the employer constructor, or mine or mining plantowner, have the following duties to notify certain
people (…)”, notification systems, regarded as a fullcomponent of an OH&S management system,
provide employers as decision-makers with aprevention design management tool, in all economic
sectors in general, and in major risk sectors inparticular.
6.

Risk management has been described as “theadoptionoffinancial,technologicalandorganizational measures designed to modify the
relationship between the turbulence of anenvironment and the variability of the results
obtained therein”. Risk management is based
essentially on analysis and evaluation of all of therelevant information available (Badi, 2015).
The mining sector, despite considerable efforts inmany countries, remains the most hazardous
occupation when the number of people exposed torisk is taken into account. Decision makers need asustainable and consolidated reporting andnotification system in order to implement effective
improvements in the occupational and health safety(OH&S) management systems.
Table 8: Notification System: variables.
Health Care
Notification
Mining variables
Variables
variables
Legal framework

Notification

Mandatory

Date/time

Date/time

Date/time

Shifts (…)

Workingschedule

24 hours
production

PsychologicalrisksType of accident(risk exposure)Work-relateddiseases

REFERENCES

Dohoo, I., R., Ducrot,C., Fourichon, C., Donald,A., Humik, D. (1996). An overview of techniques for
dealing with large numbers of independent variables
in epidemiologic studies. Preventive Veterinary
Medicine, No. 29, pp.22 l-239.
ILO-International
LabourOffice.
1996.
Recording and Notification of Occupational
Accidents and Diseases. ILO Code of Practice,
Geneva.
RIDDOR-Reporting of Injuries, Diseases andDangerous Occurrences Regulations, 2013.
Directive 2000/54/EC of the European
Parliament and of the Council, of 18 September
2000, on the protection of workers from risks related
to exposure to biological agents at work.
ILO-International
LabourOffice,2000.
Guidelines on occupational safety and healthmanagement systems, (ILO-OSH 2001). Geneva,
ISBN 92-2-111634-4.
Badri, A. (2015) The Challenge of Integrating
OHS into Industrial Project Risk Management:
Proposal of a Methodological Approach to Guide
Future Research (Case of Mining Projects in Quebec,
Canada). Minerals 2015, No. 5, pp. 314-334.

In order for an action to be truly preventive or
corrective, hazards must be identified first on thebasis of rigorous analysis of information or data.
Such an approach and further procedure can create
conflict areas with a certain organizational
operational day-to-day basis. Several management
issues, such as financial, economic, social andoperational, may be constrained concerning data
sources (Badri, 2015).

402

ISMS 2016

Paper No. 12
Full-scale fire experiments in an underground mine
Rickard Hansen
Malmfältens Brandkonsult, Nyköping, Sweden, 611 67

ABSTRACTFew full-scale fire experiments have been performed in underground mines, therefore the information needed tovalidate calculations and estimations in preventive work, risk mitigation as well as incident planning is not readily
available. This paper presents two full-scale fire experiments involving a loader and a drilling rig in a mine drift in
Sweden. The heat release rate in the fire experiments was determined through oxygen calorimetry, i.e. by measuring
the mass flow rate, gas concentrations and temperatures at certain heights at the far end of the mine drift,
downstream of the fire source. The resulting heat release rate curve of the loader fire displays a fire that is initiallydominated by a sudden increase in heat release rate when the first tire is engulfed by flames and then by the slowly
declining heat release rates of the large tires of the vehicle. The calculated peak heat release rate of the loader was
15.9 MW and occurred approximately 11 minutes after ignition. The resulting heat release rate curve of the drillingrig displays a fire with high heat release rates and is relatively short lived – compared with the fire in the loader.
Practically all the combustible items were ignited in the early phases of the fire. The calculated peak heat release
rate of the drilling rig was 29.4 MW and occurred approximately 21 minutes after ignition. The fuel load of theloader consisted mainly of the tires, the hydraulic oil and the diesel fuel. The fuel load of the drilling rig consisted
mainly of the hydraulic oil and the hydraulic hoses. The heat release rate curves were validated by comparing thesummed up energy contents of the participating components with the integrated heat release rate curves.
KEYWORDS: Heat release rate, mining vehicle, full-scale fire experiment, underground mine

1. INTRODUCTION
Collecting information about relevant risks, fire
spread in mining vehicles and mobile equipment, andheat release rates for different types of fires isfundamental in preventive work, risk mitigation as
well as in incident planning. Few full-scale tests havebeen performed in underground mines and theinformation needed to validate calculations andestimations is not readily available. Studies haveshown that vehicles and mobile equipment are thedominating source of fire in underground hard rockmines (Hansen, 2009; De Rosa, 2004). The studies
have shown that better knowledge about fire
behaviour and fire spread is needed for service
vehicles, drilling rigs and loaders. Two full-scale fire
experiments on mining vehicles were conducted in anunderground mine in Sala, Sweden. The full-scale
fire experiments involved a loader and a drilling rig
and were conducted in order to provide much needed
data for future fire safety designs in undergroundmines.

2. INVOLVED VEHICLESThe loader in question was a Toro 501 DL, adiesel driven loader used for hauling iron ore. Table 1
presents an inventory of the combustible components
on the loader. The effective heat of combustion of thehydraulic hoses, low voltage cable and driver seat

was taken as the average value using results fromcone calorimeter tests. The effective heat of
combustion of the tires and rubber covers was set to
27 MJ/kg (Ingason, 2008). The effective heat of
combustion of the diesel fuel was set to 42.6 MJ/kg(Totten et al., 2003) and 42.85 MJ/kg for thehydraulic oil (Simonson et al., 1998). When summing
the energy contents of the individual components a
total energy content of 76,245 MJ was calculated.
The loader used in the experiments can be seen in
Figure 1.
Table 1: Combustible component inventory – loader.
Component
Estimated
Energy content
amount(MJ)
Tyres (rubber~1560 kg
42120
material)
Hydraulic oil
500 liters
16283
Hydraulic oil in
70 liters
2280
hoses
Hydraulic hoses~170 kg4905(rubber material)
Diesel
280 liters
10138
Driver seat
~10 kg
228
Electrical cables~1.5 kg21
Rubber covers~10 kg270*Corresponding author – email : malmfaltensbrandkonsult@bahnhof.se3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

relatively easy to install – in order to reduce thedependence upon expensive and sensitive gas
analysis instruments.
Assuming that the local gas temperature and the
local gas concentration correlate through the averagevalues over the cross-section (Ingason, 2006), theheat release rate can be calculated using thefollowing expression:
 M O2  ⋅ 1 − X H 2O , 013100 ⋅ ρ 0 ⋅ u 0 ⋅ A ⋅ 

M
a


Q =
 X O2 ,avg 
1 − X O2 ,avg ⋅ 
 1 − X CO ,avg 
0.1
2


+
X O2 , 0 1 − X CO2 , 0  
X O2 , 0 −  X O2 ,avg ⋅ 
 1 − X CO ,avg  

2




(

Figure 1: Loader used in the experiments.

The drilling rig in question was an Atlas Copco
Rocket Boomer 322, an electrically driven drilling rig
that is also equipped with a diesel powered engine
which is used when moving from one site to another.
Table 2 presents an inventory of the combustible
components. The effective heat of combustion of thehydraulic hose was also applied for the water hose.
The effective heat of combustion of the plastic covers(ABS plastic) was set to 30 MJ/kg (Tewarson, 2002).
When summing up the energy contents of theindividual components a total energy content of
45,758 MJ was calculated.
Table 2: Combustible component inventory - drilling rig.
Component
Estimated
Energy content
amount(MJ)
Tyres (rubber~155 kg
4185
material)
Hydraulic oil
350 liters in tank16283
and 150 liters in
hoses
Hydraulic hoses~390 kg11252(rubber material)
Water hose
~40 kg1154(rubber material)
Diesel
100 liters
3621
Driver seat
~10 kg
228
Electrical cables~450 kg
8735
Plastic covers~10 kg300

3. DETERMINATIONRELEASE RATE

OF

THE

HEAT

The heat release rate in the fire experiments wasdetermined through oxygen calorimetry, i.e. bymeasuring the mass flow rate, gas concentrations andtemperatures at certain heights at the far end of themine drift – downstream of the fire source - where
the fire experiments were conducted. The method
relies heavily on installed thermocouples at every
measuring point – which are inexpensive, robust and)[kW] (1)

Where:

ρ 0 is the ambient air density [kg/m ]3

u 0 is the cold gas velocity in a mine drift [m/s]

A is the cross-sectional area [m2]
M O2 is the molecular weight of oxygen [g/mol]

M a is the molecular weight of air [g/mol]
X H O , 0 is the mole fraction of water in the ambient2

air
X O2 ,avg is the average concentration of oxygen
X CO2 ,avg is the average concentration of carbon

dioxideX O2 , 0 is the mole fraction of oxygen in the ambientair
X CO2 , 0 is the mole fraction of carbon dioxide in theambient air
The average concentration of oxygen, carbon
dioxide and carbon monoxide are calculated using theabove mentioned correlation. In equation (1) it isassumed that 13100 kJ/kg is released per kg ofoxygen consumed and that the air mass flow rate of
combustion gases equals the ambient air mass flow
rate. Equation (1) has been used when determining
the heat release rate for a number of large scaletunnel fire tests (Ingason and Lönnermark, 2005).

4. THE EXPERIMENTAL SITE
The full-scale fire experiments were conductedin a dolomite mine in Sweden. The fire experiments
were conducted at level 55, an inactive part of themine. Nonetheless, the infrastructure was still inplace with power outlets, etc. The preconditions of
the potential test site were the following: an activemine with an intact infrastructure, the possibility to404

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016steer the smoke in one direction and through one
single exhaust, and accessibility for vehicles. Figure
2 presents a plan of the level.
As there was only one exhaust on one side of thetest site, all the smoke was ventilated out through thesingle exhaust, thus allowing for heat release ratemeasurements on this side of the test site. The intake
of air was from the entrance and the lower regions of
the mine.
Approximate dimensions of the mine drifts in thetest area were 6 meter in height and 8 meter in width.
The mine drift where the experiments took place
was approximately 100 meters long, approximately
150 meters from the entrance to the mine and 40
meters from the exhaust. There were practically no
differences in height between the entrance of themine and the exhaust.

Figure 2: Experimental area.

5. EXPERIMENTAL SET UP
At the end of the mine drift – where all the firegases would pass - the data needed for calculating theheat release rate was collected at a measuring station(see Figure 3 for the experimental set up in the mine
drift). The data was measured using six
thermocouples, four velocity probes and one gas
monitor (measuring O2, CO and CO2) positioned at
different heights. The temperature above each vehicle
was measured with a thermocouple attached to theceiling. A video camera was placed in the mine drift
aimed at the side the each vehicle in order to record
the fire behavior and the time of ignition of the
combustible items.
On each vehicle a number of thermocouples
were placed on the combustible components, i.e. thetires, hoses, cables and the interior of the cab. Fourplate thermometers were placed at the ground at eachtire during the tests in order to measure the heat flux
at the locations.

Figure 3: Experimental set up.

The existing ventilation flow in the area wasfound to be insufficient to ventilate all the smoke inone predetermined direction - in order to obtainadequate heat release rate measurements. Additional
ventilation resources were therefore needed and amobile fan with a capacity of 217,000 m3/h was usedduring the experiments.
Regarding fire initiation, a circular tray wasplaced underneath the fuel tank of each vehicle and it
was located close to at least one tire. The trays werefilled with diesel fuel in order to simulate a pool firecaused by leaking diesel from the tank.

6. EXPERIMENTAL RESULTS
6.1 Loader Experiment
After the completion of the loader experiment it
was found that the front tires had not been consumed
in the fire and were therefore intact. Also, thehydraulic hoses from the vertical hinge (the vehicle issplit into a front and a rear half which are connectedby a vertical hinge approximately at the middle of thevehicle) and forward and in some parts of the rear
section behind the rear tires also remained intact.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Other parts had participated fully in the fire. The
resulting heat release rate curve can be seen in Figure
4. The maximum heat release rate from theexperiment was 15.9 MW. The maximum heatrelease rate was reached approximately 11 minutes
after ignition. The resulting heat release rate curve
displayed a fire that was dominated by a sudden
increase of the pool fire and when the first tyre wasengulfed by flames and then by the slowly declining
heat release rates of the large tyres of the vehicle.
Still, the stop of fire spread from the vertical hinge
and forward clearly shortened the duration of the fireconsiderably.
HRR - Loader fire
18000
16000

Heat release rate (kW)

14000
12000
10000
8000
6000
4000
2000
0
0

20

40

60

80

100

120

140

160

180

200

220

50.5 GJ. The difference is most likely due to theuncertainties when estimating the amount of
combustibles available and the amount of
combustibles consumed in the fire.
6.2. Drill Experiment
After the completion of the drilling rig
experiment it was found that a small portion of thehydraulic oil did not participate in the fire. Except for
the hydraulic hoses approximately two meters infront of the cab and forward, some amount ofhydraulic oil as mentioned above, and a major part ofthe low voltage cable on the cable reel, the entire
vehicle had participated in the fire and the
combustible material had been consumed. The heatrelease rate curve from the experiment can be seen in
Figure 6. The maximum heat release rate from theexperiment was 29.4 MW and was attained after 21
minutes. The resulting heat release rate curve of thedrilling rig displays a fire with high heat release rates
and relatively short lived – compared with the fire in
the loader. Practically all the combustible items were
ignited in the early phases of the fire.

t (min)HRR - Drilling rig
35000

Figure 4: The resulting heat release rate of the loader.

Average gas temperature at measuring station - Loader

Average gas temperature (C)

70
60
50
40
30
20
10
0
30

60

90

120

150

180

210

240

25000

20000

15000

10000

5000

0
0

10

20

30

40

50

60

70

t (min)Figure 6: The resulting heat release rate of the drilling rig.

80

0Heat release rate (kW)30000

The maximum average gas temperature at themeasuring station (74°C) occured after approximately
11 minutes, which is the same time as the occurrenceof the maximum heat release rate. This latter
observation is expected, as the average oxygen andcarbon dioxide concentration correlates with theaverage gas temperature at the measuring station. The
average gas temperature measurements can be seen in
Figure 5.

270

300

t (min)Figure 5: The average gas temperature at the measuring
station - loader experiment.

The maximum average gas temperature at themeasuring station - 93°C - occurs after approximately
21 minutes, which is the same time as the occurrenceof the maximum heat release rate (see Figure 7 forthe average gas temperature at the measuring station).
When comparing the average gas temperature in
Figure 7 and the heat release rate curve in Figure 6 it
can be seen that the average gas temperature at themeasuring station correlates well with the measured
heat release rate.

Using the heat release rate curve the energy
content of the combustible materials consumed in thefire was calculated at 57 GJ. When summing theenergy contents of the materials participating in thefire the summation results in an energy content of406

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Average gas temperature at measuring station - Drilling rig
100
90

Average gas temperature (C)

80
70
60
50
40
30
20
10
0
0

30

60

90

120

t (min)Figure 7: The average gas temperature at the measuring
station - drilling rig experiment.

The energy content of the combustible materials
consumed in the fire was calculated at 30.9 GJ. Whensumming up the energy contents of the materials
participating in the fire the summation results in anenergy content of 32.5 GJ. The difference is most
likely due to the same uncertainties as in the case of
the loader.

7. DISCUSSION
The initial sharp rise and high heat release rate
for the first 20 minutes of the loader fire can be
explained mainly due to the pool fire and the fire in
the rear, right tire. The sharp drop after about 20
minutes was due to the pool fire burning off. The
burn off time of the diesel pool fire at the loader
experiment was calculated to be about 43 minutes(assuming a regression rate of 0.066 kg/s·m2 (deeppool)). Assuming a maximum heat release rate perunit area of 1.33 MW/m2 (Lönnermark et al., 2008)
for a thick fuel bed, the maximum heat release rate ofthe diesel pool fire was calculated to be 1.26 MW.
When studying the heat release rate curve in Figure
4, the decrease in heat release rate was about 8 MW
which was much larger than the calculated 1.26 MWof the pool fire. The difference can be explained by
the fact that the diesel tank of the wheel loader was
not equipped with a magnetic valve – as in the caseof the drilling rig – which suggest that the fuel hoses
in the proximity of the fuel tank could have been
burned off during the early stages, draining the tankand thereby increasing the size of the pool fire andconsequently the heat release rate of the diesel poolfire. Also, the pool fire was underneath the loader andthus the re-radiation back to the pool surface would
be much larger than for a free standing pool fire andthus the heat release rate would be larger. Thisobservation is further enforced by the fact that thecalculated burn off time of the diesel pool fire wasmore than twice as long as the observed burn off
time. The differences will have to be investigatedfurther in order to be fully explained.

The slow increase in heat release from about 20
minutes to about 50 minutes was due to the slow
flame spread along the surface of the rear, left tire.
The sudden – and temporary - decrease in theventilation velocities and heat release rate
approximately 10 minutes after ignition can be
related to the change of position of the mobile fan,where the fan was geared down temporarily during
the transport. The change of position was due toextensive backlayering reaching and passing theinitial position of the fan.
The plate thermometers positioned at the forward
tires did not record incident heat fluxes exceeding 14
kW/m2 (unfortunately the plate thermometer at theright, forward tire stopped functioning approximately
40 minutes after ignition) and were therefore in linewith the fact that ignition of the forward tires did nottake place - if assuming and applying a critical heat
flux of 17.1 kW/m² (Babrauskas, 2003) for natural
rubber.
Approximately two minutes after ignition bothrear tires of the drilling rig were ignited and the fire
spread further to hydraulic hoses in the rear, upper
part. About 12 minutes after ignition the right,
forward tire was ignited. At about the same time asudden increase in intensity occurred, most likely due
to the bursting of the right, rear tire. After 26 minutes
there was a second sudden increase in intensity, due
to the bursting of the right, front tire.
The temperature at the forward part of thedrilling rig boom – where the hydraulic hose did not
ignite and burn – exceeded 930°C approximately 25
minutes after ignition, when studying the temperaturerecordings of the thermocouple at the boom. It is
unclear why the hydraulic hoses did not ignite andburn. It could possibly and partially be explained by
the hydraulic hoses already being drained of all
hydraulic oil and thus decreasing the heat release rate
and the fire spread when initially ignited. The
incident radiation level was simply too low to
propagate the fire in the direction of the ventilationflow.

8. CONCLUSIONS
Two full scale fire experiments involving aloader and a drilling rig were carried out in an
operative underground mine in Sweden, in order toproduce total heat release rate curves forrepresentative mining vehicles.
It was found in the loader experiment that thefront part of the vehicle with front tires never ignited.
The maximum measured heat fluxes at the front tires
were found to never exceed the critical heat flux ofnatural rubber and was thus in line with the fact that
ignition did not occur.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The maximum heat release rate from theexperiment was 15.9 MW and it was reachedapproximately 11 minutes after ignition.
The resulting heat release rate curve of the loader
fire displayed a fire that is dominated initially by thesudden increase in heat release rate when the first tireis engulfed by flames and then by the slowly
declining heat release rates of the large tires of thevehicle. Still, the stop of fire spread from the verticalhinge and forward clearly shortened the duration of
the fire considerably.
Regarding the drilling rig fire experiment it was
found that except for the hydraulic hoses
approximately two meters in front of the cab andforward, some amount of hydraulic oil, and a majorpart of the low voltage cable on the cable reel, theentire vehicle had participated in the fire.
The maximum heat release rate from the drilling
rig experiment was 29.4 MW and it was attained after
21 minutes.
The resulting heat release rate curve of thedrilling rig displayed a fire with high heat release
rates and was relatively short lived, compared withthe fire in the loader. Practically all the combustible
items were ignited in the early phases of the fire.

P Custer, J R Hall and J M Watts, Eds.). NFPA,
Quincy, USA.
Totten G.E., Westbrook S.R. and Shah R.J.
(2003) Fuels and lubricants handbook: technology,
properties, performance, and testing, volume 1.
ASTM International.
.

9. REFERENCES
Babrauskas V. (2003), Ignition handbook. Fire
Science Publishers, Issaquah, USA.
De Rosa M.I.,2004. Analysis of mine fires for all
US metal/non-metal mining categories, 1990-2001.
NIOSH.
Hansen R., 2009. Literature survey – fire andsmoke spread in underground mines. Mälardalens
Högskola, MdH SiST 2009:2, Västerås.
Ingason H., and Lönnermark A. (2005). Heat
release rates from heavy goods vehicle trailers intunnels. Fire Safety Journal, Volume 40, pp. 646-668
Ingason, H. (2006). Correlation between
temperatures and oxygen measurements in a tunnel
flow. Fire Safety Journal, Volume 42, pp. 75-80
Ingason H., 2008. Fire test with a front loader.
SP report P801596, SP, Borås.
Lönnermark, A., Kristensen, P., Helltegen, M.,
and Bobert, M. (2008). Fire suppression and structure
protection for cargo train tunnels: macadam andhotfoam. ISTSS.
Simonson M., Milovancevic M. and Persson H.,
1998. Hydraulic fluids in hot industry: firecharacteristics and fluid choice. SP Report 1998:37,
SP, Borås
Tewarson A. (2002), Generation of Heat andChemical Compounds in Fires. In: The SFPE
Handbook of Fire Protection Engineering (P J
DiNenno, D Drysdale, C L Beyler, W D Walton, R L

408

ISMS 2016

Paper No. 201
Diesel exhaust exposures in an underground mine

Hugo Coulombe a, Guillaume Lachapelle b, Eve Neesham-Grenon c, Stéphane Hallé d,Maximilien Debia c,*
a Health and Safety, Westwood Mine (IAMGOLD), Preissac, Canada, J0Y 2E0
b Health and Safety, Agnico Eagle Mines, Toronto, Canada, M5C 2Y7
c Department of Environmental and Occupational Health, School of Public Health, Université de Montréal, Montreal, Canada, H3T

1A8
d Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, Canada, H3C 1K3

ABSTRACTThe mining industry is a major contributor to the Quebec and Canadian economy. In Canada, more than 400,000
workers are involved directly or indirectly in the mining industry. Health and safety challenges in underground mines
are unique due to the complexity of the environment. Exposure to diesel engine exhaust is a major concern inunderground mines due to the presence of off-road diesel-powered machinery. Diesel engine exhaust has been linked
to cardiopulmonary diseases and was classified as a human carcinogen by the International Agency for Research on
Cancer in 2012. Here we present the results of a preliminary study conducted in an underground gold mine in theprovince of Quebec in 2014-15 to assess diesel engine exhaust exposures among mine workers. The goal of this study
was 1) to compare three surrogates of diesel engine exhaust exposure (total carbon, elemental carbon and respirable
combustible dust) and 2) to assess diesel exhaust concentrations among the similar exposure groups and the variabilityof the exposures. Results were also compared to the Ontario and Quebec occupational exposure limits for compliancepurposes. Environmental and breathing zone measures were taken. Average environmental results of 0.31 mg/m3 in
total carbon, 0.24 mg/m3 in elemental carbon, and 0.17 mg/m3 in respirable combustible dust were obtained. Average
breathing zone results of 0.32 mg/m3 in total carbon, 0.19 mg/m3 in elemental carbon and 0.36 mg/m3 in respirable
combustible dust were obtained. The highest exposures were obtained in the conventional, scooptram and jumbo
workers. The average total carbon/elemental carbon ratio was 1.3 for environmental measures, and 1.9 for breathingzone measures. The variability observed in the total carbon/elemental carbon ratio shows that interferences from nondiesel related organic carbon can skew the interpretation of results when relying only on total carbon data. However,more data is needed to support this.
KEYWORDS: diesel; exposure; underground mine; respirable combustible dust; elemental carbon; total carbon;
similar exposure groups

1. INTRODUCTION
Exposure to diesel engine exhaust (DE) has been
linked to increased cancer risk and cardiopulmonary
diseases. DE has recently been classified as a humancarcinogen (group 1) by the International Agency for
Research on Cancer (IARC, 2012) and has become acontaminant of primary interest at the international
level. Vermeulen et al. (2014) reported that 6% ofdeaths from lung cancers could be linked tooccupational exposures to DE. Acute exposures to DE
have been associated with respiratory irritation andinflammation, and cardiovascular effects (Hussain etal., 2012; Kipen et al., 2011; Lucking et al., 2008;
Mills et al., 2005; Nordenhall et al., 2000; Salvi et al.,1999).
DE refers to the complex mixture of chemical
substances found in solid, liquid or gaseous states
resulting from the incomplete combustion of fuel. The
type of engine, fuel, oil, and operation are all factors*Corresponding author – email: maximilien.debia@umontreal.ca

that can affect the composition of DE. Carbon (monoand di-) oxides (CO and CO2), nitric oxide (NO),nitrogen dioxide (NO2), sulfur dioxide (SO2), water
vapour, sulfur compounds, low molecular weighthydrocarbons (e.g. benzene, 1,3-butadiene), andoxygenated compounds (e.g. aldehydes) can all befound in the mixture. Diesel particulate matter iscomposed of elemental carbon (EC) onto whichorganic carbon (OC) compounds and other particles(unburnt fuel, lubricant droplets, metallic additives,etc.) are adsorbed. The majority of the particles indiesel particulate matter are within the respirable
fraction (4 µm in diameter or less) and most are
ultrafine particles (100 nm in diameter or less) (Carex
Canada, 2015).
Occupational exposure limits (OEL) for DE vary
greatly between and within countries. In the provinceof Quebec, Canada, a limit value of 0.6 mg/m3 of
respirable combustible dust (RCD) applies to themining industry (Government of Quebec, 2016). The
Canadian province of Ontario has recently adopted aregulatory time-weighted value of 0.4 mg/m3 of total
carbon (TC) transposable to EC via a conversion factorof 1.3 (i.e. about 0.31 mg/m3 for EC) for the mining
industry (Government of Ontario, 2016). The U.S.
Mine Safety and Health Administration (MSHA) hasprescribed an 8-hour OEL of 0.16 mg/m3 of TC basedon recommendations and methods of the National
Institute for Occupational Safety and Health (NIOSH)(MSHA, 2008). There is currently no regulation for
TC or EC in the province of Quebec. However, a
proposition for the modification of the Quebec
regulation of 0.6 mg/m3 of RCD to 0.4 mg/m3 of TC
has recently been published in the Official Gazette ofQuebec (Éditeur Officiel du Québec, 2015). There iscurrently no time-weighted average Threshold Limit
Value proposed by the American Conference ofGovernmental Industrial Hygienists.
Underground mines pose great occupational healthand safety challenges due to their very unique work
environments. The presence of off-road, dieselpowered mobile machinery is one of these challenges,
which is briefly addressed in this paper.

2. METHODSThe DE assessment methods compared were the
NIOSH 5040 method (NIOSH, 2003) used forsampling the carbon fraction (EC and OC), and the
RCD method (IRSST, 2016). For the NIOSH 5040
method, 37-mm aluminum cyclones (SKC) were usedwith 37-mm quartz filter cassettes, SKC model 225-1
cassette holders, and SKC pumps (PCXR4 model).
Interferences from cigarette smoke, non-metal mining(e.g. coal) and oil mist are to be considered with thismethod. For the RCD method, 25-mm aluminum
cyclones (SKC) were used with 25-mm silver
membrane cassettes, SKC model 225-1 cassetteholders, and SKC pumps (PCXR4 model).
Interferences from oil mist and mineral dust (e.g.
sulfides in rock) are to be considered with this method.
Personal RCD and NIOSH 5040 samples were taken
during two separate periods of two to three weeks; theRCD samples were taken in November and December
2014 while the NIOSH 5040 samples were taken in
March 2015. Personal samples were taken 30
centimeters from the workers’ breathing zone during
their full 10-hour shift. Environmental RCD and
NIOSH 5040 samples were taken simultaneously inmain circulation routes (i.e. bypasses and ramps) overperiods of about 8 hours. The pumps were hooked to
the ground support at about 8 feet high to avoid
damage to the equipment.
Most samples were taken during the day shift.
Field observations were noted throughout the
sampling periods. The RCD samples were sent to SGS

Laboratories (Lakefield, Ontario, Canada) and thecarbon samples were sent to Galson laboratories (NewYork, USA).
Statistical analyses were done with IHSTAT(American Industrial Hygiene Association - Exposure
Assessment Strategies Committee). The geometricmean (GM) and geometric standard deviation (GSD)
were used for describing the exposure profiles. The
estimated arithmetic mean (AM) and thecorresponding 95% confidence limits were used forcomparing personal exposure levels to exposure limits
and for evaluating the cumulative damage fromexposure to diesel exhaust. Non-detected values were
replaced by the corresponding limit of quantification(LOQ) for the sample. Similar exposure groups (SEG)
were based on job titles and were pre-defined by thecompany.

3. RESULTS
3.1 Environmental measures
Environmental TC, EC, and RCD concentrations
are presented in Table 1. The average TC/EC ratio forenvironmental measures was 1.3.

Table 1: Summary of environmental TC, EC and RCD
measures.
TC(mg/m3)EC(mg/m3)RCD(mg/m3)

GM

0.31

0.24

0.17

GSD

2.00

2.22

1.90

N

5

5

5

TC: total carbon; EC: elemental carbon; RCD: respirable
combustible dust; GM: geometric mean; GSD: geometric standard
deviation; N: sample number

3.2 Personal measures
Descriptive and inferential statistics for personal
TC, EC, and RCD concentrations are summarized inTable 2. Personal TC measures were close to the
Ontarian OEL of 0.4 mg/m3 (AM = 0.32 mg/m3 [LCL
= 0.28; UCL = 0.38]). Personal EC measures were atabout half the Ontarian OEL of 0.31 mg/m3 (AM =0.19 mg/m3 [LCL = 0.15; UCL = 0.24]). The personal
RCD concentrations were at about half the Quebec
OEL of 0.6 mg/m3 (AM = 0.36 mg/m3 [LCL = 0.29;
UCL = 0.52]). The average TC/EC ratio for personalmeasures was 1.9.
Table 3 presents the TC, EC and RCD
concentrations according to the different SEG.
Conventional, scooptram and jumbo operators were410the most exposed. At the opposite, mechanics,
foremen and rock bolter operators were the least
exposed groups. As presented in Table 3, most of thegeometric standard deviations were around 2 or below.
The TC/EC ratio for the conventional and chisel
operators were higher than for other SEG (4.1 and 5.8,
respectively).

GM

LCL=0.28
UCL=0.38
0.30

LCL=0.15
UCL=0.24
0.15

LCL=0.29
UCL=0.52
0.25

GSD

1.53

1.87

2.41

N

30

30

36

95% CL

TC: total carbon; EC: elemental carbon; RCD: respirable
combustible dust; AM: estimated arithmetic mean; 95% CL: 95%
confidence limits; LCL: lower confidence limit; UCL: upper
confidence limit; GM: geometric mean; GSD: geometric standard
deviation; N: sample number

Table 2: Summary of personal TC, EC and RCD measures.
TC
EC
RCD
(mg/m3)(mg/m3)(mg/m3)
0.32
0.19
0.36
AM

Table 3: TC, EC and RCD results by SEG.
TC (mg/m3)

EC (mg/m3)

RCD (mg/m3)

GM

GSD

N

GM

GSD

N

GM

GSD

N

TC/EC
ratio

Shotcrete operators

na

na

na

na

na

na

0.51

1.59

2

na

Truck operators

0.28

1.37

6

0.19

1.47

6

0.19

1.80

3

1.5

Scooptram operators

0.36

1.52

8

0.21

1.54

8

0.30

2.20

8

1.7

Foremen

0.20

1.28

2

0.13

1.17

2

0.14a

5.80

2

1.5

Conventional

0.74

1.28

2

0.18

1.42

2

0.72

1.96

4

4.1

Electricians

na

na

na

na

na

na

0.21

1.63

2

na

Diamond driller operators

na

na

na

na

na

na

0.13

1.91

2

na

Jumbo operators

0.33

1.26

2

0.17

1.09

2

0.35

1.39

3

1.9

2.35

3

1.4

SEG*

Mechanics

0.19

1.29

2

0.14

1.36

2

0.11a

Chisel operators

0.29

1.37

2

0.05

10.01

2

na

na

na

5.8

Rock bolter operators

0.21

1.00

2

0.12

1.19

2

na

na

na

1.8

TC: total carbon; EC: elemental carbon; RCD: respirable combustible dust; GM: geometric mean; GSD: geometric standard
deviation; SEG: similar exposure group; N: sample number; na: not available*Only SEG for which there were two samples or more are reported
aOne value was <LOQ

4. CONCLUSION
In conclusion, as long-term risk indices, arithmetic
mean estimates and the corresponding upper
confidence limits did not exceed the Ontario andQuebec OELs for personal TC, EC and RCD
measures. More data is needed for each SEG to better
understand the exposure profiles and to make acomprehensive long-term risk assessment.
The variability observed in the TC/EC ratio showsthat interferences from non-diesel related organiccarbon can skew the interpretation of results whenrelying only on TC data. This was most obvious whencomparing the ratios between the different SEG. The
conventional and chisel operators had a higher ratio,
indicating greater interferences from non-diesel
related organic carbon, most likely from oil mist. Our

results question the use of TC as a measure ofoccupational exposure to DE. However, more data isneeded to validate this.
In future studies, direct reading instruments will be
used in addition to the integrated sampling methods
described in this paper, in order to better understandthe determinants of exposures.
Overall, this preliminary study gives an overview
of diesel exhaust exposures in an underground mine.

5. ACKNOWLEDGEMENT
The authors would like to thank all workers who
have participated in the study. This project was
financially supported by the Fonds de recherche duQuébec - Nature et technologies (FRQNT).

6. REFERENCES

411

Carex Canada. (2015). Diesel Engine Exhaust.
http://www.carexcanada.ca/en/diesel_engine_exhaust/.
Éditeur Officiel du Québec. Regulation
Respecting Occupational Health and Safety in Mines,
Chapter S-2.1, r. 14, SECTION IV 1.102(1)(a) Quebec
City, Québec, Canada.
Éditeur Officiel du Québec. (2015). Part 2:
Regulation modifying the Regulation Respecting
Occupational Health and Safety in Mines Official
Gazette of Quebec, 28 october 2015, 147th year, no43, 4085-4086.
Government of Ontario. Mines and Mining
Plants, Occupational Health and Safety Act, R.R.O.
1990, Regulation 854, PART VIII 183.1(5) (a).
Ottawa, Ontario, Canada.
Hussain, Sabiha, Laumbach, Robert, Coleman,
Jakemia, Youseff, Hatim, Kelly-McNeil, Kathie,
Ohman-Strickland, Pamela, Kipen, Howard. (2012).
Controlled exposure to diesel exhaust causes increased
nitrite in exhaled breath condensate among subjects
with asthma. Journal of occupational andenvironmental medicine/American College ofOccupational and Environmental Medicine, 54(10),1186.
IARC. (2012). Diesel and gasoline engine
exhaust and some nitroarenes IARC monographs on
the evaluation of carcinogenic risks to humans (Vol.
105). International Agency for Research on Cancer,
Lyon, France.
IRSST. (2016). Respirable combustible dust
(RCD)
analysis.
Method384.
http://www.irsst.qc.ca/en/laboratories/referencestools/guidestools/workplace-aircontaminant/substance/i/307.
Kipen, Howard M, Gandhi, Sampada, Rich,David Q, Ohman-Strickland, Pamela, Laumbach,Robert, Fan, Zhi-Hua, Madura, Kiran. (2011). Acutedecreases in proteasome pathway activity after
inhalation of fresh diesel exhaust or secondary organic
aerosol. Environmental health perspectives, 119(5),658.
Lucking, Andrew J, Lundback, Magnus, Mills,
Nicholas L, Faratian, Dana, Barath, Stefan L,
Pourazar, Jamshid, . . . Badimon, Juan J. (2008).
Diesel exhaust inhalation increases thrombus
formation in man†. European heart journal.
Mills, Nicholas L, Törnqvist, Håkan, Robinson,
Simon D, Gonzalez, Manuel, Darnley, Kareen,
MacNee, William. Sandstrom, Thomas. (2005). Diesel
exhaust inhalation causes vascular dysfunction andimpaired endogenous fibrinolysis. Circulation,
112(25), 3930-3936.
MSHA. (2008). Limit on Exposure to Diesel
Particulate Matter, Code of Federal Regulations Title

30, Part 57.5060(b),(3) (pp. 370-371). Washington,
DC.
NIOSH. (2003). Method 5040: Diesel Particulate
Matter (as Elemental Carbon) NIOSH Manual of
Analytical Methods, 4th Ed. (4th ed.). National
Institute for Occupational Safety and Health, Atlanta,
GA, USA
Nordenhall, C, Pourazar, Jamshid, Blomberg,
Anders, Levin, Jan-Olof, Sandstrom, T, & Adelroth,E. (2000). Airway inflammation following exposure todiesel exhaust: a study of time kinetics using induced
sputum. European Respiratory Journal, 15(6), 10461051.
Salvi, Sundeep, Blomberg, Anders, Rudell,Bertil, Kelly, Frank, Sandstrom, Thomas, Holgate,
Stephen T, & Frew, Anthony. (1999). Acuteinflammatory responses in the airways and peripheral
blood after short-term exposure to diesel exhaust in
healthy human volunteers. American journal of
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Vermeulen, Roel, Silverman, Debra T, Garshick,
Eric, Vlaanderen, Jelle, Portengen, Lützen, &Steenland, Kyle. (2014). Exposure-response estimatesfor diesel engine exhaust and lung cancer mortality
based on data from three occupational cohorts.
Environmental health perspectives, 122(2), 172.

412

ISMS 2016

Paper No. 125

Liquid-solid coupling analysis of tailings dam under complex engineering
conditions
Shuren Wanga,*, Haiqing Zhangb, Zhengsheng Zoua, Xiliang LiuaabOpening Project of Key Laboratory of Deep Mine Construction, Henan Polytechnic University, Jiaozuo, China, 454003
School of Engineering and Technology, China University of Geosciences, Beijing, China, 100083

ABSTRACTThe tailings pond, a place for stockpiling tailings, is a necessary facility for maintaining normal production of amine. On the other hand, the tailings dam is a major danger for metal and non-metal mines, because dam failure may
occur. The present study takes the flat land tailings pond of the Sanshan Island gold mine, Shangdong Province,
China, as an example. The tailings dam 3D numerical model was built using MIDAS/GTS and FLAC3D techniques.
The safety factor and the potential slide face of the tailings dam were calculated under different conditions using thestrength reduction method. It is concluded from the liquid-solid coupling analysis that there are three potential
failure modes of the tailings dam under preloading. Under the present conditions, the tailings dam meets the safety
requirements, however, it does not in the event of additional heaping. The height of the present heap must be cut tosatisfy the stability requirements under the condition of rain infiltration.

1. INTRODUCTION
The tailings pond is a necessary facility for
maintaining the normal production of a mine, and asa place for stockpiling tailings. On the other hand, thetailings dam is a major danger for metal and nonmetal mines, as dam failure may occur. In the case of
a possible tailings accident, it will cause not only
great losses and harm the safety of life and property
to the residents downstream of the mine, but also
serious environmental pollution.
Many scholars have studied the stability of thetailings pond and dam failure disasters. Shakesby andRichard (1991) studied the tailings dam accident in
Arcturus gold mine in Zimbabwe. They hypothesizedthat the dam failure resulted from the poor seepage
conditions of the dam foundation, as the dam slop
was too steep and the tailings were saturated underheavy rain. Through investigating the tailings dam
failure in America, Strachan (2001) held that the dam
failure was a result of flood overtopping, static ordynamic instability, seepage, internal corrosion andpoor foundation conditions. Chakraborty and
Choudhury (2009) investigated the behavior of
tailings earthen dam under static and seismic
conditions, and found that the dam deformation wasaffected seriously by seismic action. Additionally, theunderlying input acceleration of tailings dam had an
amplification effect along the height of dam. Bussière
et al. (2003) modeled the flow field characteristic for
exposed and covered tailings dams using the finite
element method (FEM). Valenzuela and Barrera(2003) analyzed the seismic stability of the dam up to*Corresponding author – email: w_sr88@163.com

a height of 195 m by the limit equilibrium method in
Los Quillayes copper mine in Chile, indicating that a
dam height of 195 m was feasible.
Li et al. (2012) summarized two instability
models based on the combination of the liquid-solid
coupling method with the strength reduction method.
One method concerned global instability and theother local instability, which is mostly caused by the
too shallow saturation line in the tailing dams. Chenet al. (2008) provided a comprehensive method toevaluate the tailings dam stability with numericalcalculation of the seepage stability, static stability
and dynamic stability of a specific project. Yin et al.
(2010) studied the change regularity of the saturationlines during normal and flood conditions, when thedam had been heaped to about two thirds of the totalheight of 120 m. Hu et al. (2004) analyzed the antislide stability of the upstream tailing by changing thedam height, saturation line conditions and thedrainage system operating conditions. Li et al. (2005)
analyzed the stability of a tailings dam using the
Sweden method and Bishop method, giving theinterrelated parameter of the stability and thecredibility of the dam structure when its level was
raised to 510-520 m. Lou et al. (2005) calculated thestress-strain isoline of the higher dam in the future byusing FEM, and evaluated the dam’s stability withthe residual thrust method.
The main causes of tailings dam failure include
flood overtopping, slope stability, seepage failure,
structural damage and seismic liquefaction. The
influence of the seepage field on the stability of thetailings dam cannot be ignored. The current study is3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

mainly based on a two-dimensional plane strain
assumption. In order to correct the lack of analysis ofthree-dimensional (3D) stability of the tailings
seepage and deformation, a 3D numerical model wasbuilt based on a flatland tailings pond project, toconduct the liquid-solid coupling analysis of thepotential risk due to successive preloading in front of
the dam. Afterwards, engineering countermeasures
were put forward according to the evaluated results.

2. ENGINEERING OVERVIEWAs shown in Figure 1, taking the flatland tailings
pond in China as an example, the pond covered anarea of about 0.22 km2, and had a catchment area of
about 0.21 km2. The ground level was about 3.1 m 4.2 m, and the reservoir elevation was about 3.5 m 20.7 m. The starter dam consisted of roller
compacted sand, with a height of 11.0 m, top widthof 3.0 m, and outer slope ratio of 1:1.8 - 1:2.5. Figure
1 shows the plan of the tailings pond and the mullock
heap.

Modelling range

Mullock heap

According to the survey results of drilling, thestratum was divided into three layers from top tobottom: mullock material, tailings material and thenatural formation. The mullock heap was mainly
gravel with silt. Tailings fill dam were mainly tailings
silt and silty clay. The original ground was composedof medium coarse sand of alluvial-diluvial andmarine deposit genesis and alluvial-diluvial silty clay.

3. 3D
MODEL
AND
ANALYSIS SCHEME

SIMULATION

3.1 Building the computational model
In view of the technical difficulties of FLAC3D
for complex 3D engineering modelling, the finite
element software MIDAS/GTS of South Korea wasadopted for geometric modeling of complex geologic
body and mesh generation, followed by model datatransformation from MIDAS/GTS to FLAC3D, tomake up for the pre-processing shortcomings of
FLAC3D and give full play to its powerful calculating
function.
Although the element shape of MIDAS/GTS isbasically the same as that of FLAC3D, the node
numbering rules and node order are different,
therefore, the element and node data exported from
MIDAS/GTS should be rearranged according to the
FLAC3D recognizable format and then be imported,
thus realizing data transformation between the two
programs. This can be achieved by programming.
The entire modeling process is shown in Figure 2.
CAD map of topographic
contours and soil stratum
Importing CAD data to
MIDAS/GTS

Tailings pond

Figure 1: Schematic of borehole layout and the calculation
range.

The waste rock heaped up from 2010 in thenorthwest corner of the tailings dam, with anaccumulation level up to 38.5 m, a height 11 meters
higher than that of the tailings stacking dam (statuselevation 27.5 m). The plane shape of the waste rockheap was approximately rectangular with an eastwest length of 260 m, and a 110 m length from northto south, covering an area of about 1.89 × 104 m2 andoccupying a volume of 36.67 × 104 m3. The mullock
heap was about 50 m wide in the south, and it
weighed on the north slope of the dam. The mullock
heap slide was unaffected until a natural repose slope
ratio of 1.0:1.1 - 1.0:3.0, and no obvious collapse or
crack was found during the site investigation.

Geological modeling and 3D
geometry meshing
Exporting data using
MIDAS/GTS
Data of nodes and elements(*.txt or .xls)

Data transforming andgrouping by MATLAB
programming

FLAC3D modle data(*.flac3d)
Importing data using
impgrid in FLAC3D
3D modling by FLAC3D
Boundary conditions,material parameters,
and construct process.
Numerical analysis by FLAC3D

414

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 2: Flow chart of three-dimension modeling process.

The tailings dam 3D numerical model (Figure 3)
was built following the aforementioned procedure,
corresponding to the scope of the blue dashed line in
Figure 1. A system of coordinate axes was definedwith the origin at the silty clay layer beneath thenatural ground of 34 m, with the z-axis pointing
upward. The model was approximately 280 m long,
250 m wide, and 38.5 m high in the x-, y-, and z-axis,
respectively. The present height of the waste rockwas 38.5 m, with a future height of up to 42.0 m.
The horizontal displacement of four lateralboundaries of the model were restricted, the bottom
was fixed and the top was free. To obtain the initialstress field, only the geomaterial dead weight was
taken into account. The material of the model was
made to meet the Mohr-Coulomb strength criterion,
and the physics and mechanics parameters wereselected as listed in Table 1.

ZYXGravel with silt
Section A (X = 100 m)

Tailings silty sandTailings silty clay
Medium-coarse loose sandMedium-coarse slightly dense sandMedium-coarse loose sandSilt
Silty clay

Section A

ZYFigure 3: 3D model mesh and its material sets.

X

3.2 Liquid-Solid Coupling in FLAC3D
The fluid-solid coupling behaviour involves two
mechanical effects in FLAC3D. First, changes in porepressure cause changes in effective stress of the solid.
Second, the fluid in a zone reacts to mechanicalvolume changes by a change in pore pressure.
The variables of fluid flow through porous media
such as pore pressure, saturation and the specificdischarge are related through the fluid mass-balance
equation, Darcy’s law for fluid transport, aconstitutive equation specifying the fluid response tochanges in pore pressure, saturation, volumetricstrains, and an equation of state relating pore pressure
to saturation in the unsaturated range. Assuming thevolumetric strains are known, substitution of themass balance equation into the fluid constitutive
relation, using Darcy’s law, yields a differential
equation in terms of pore pressure and saturation that
may be solved for particular geometries, properties,
boundary and initial conditions.
In summary, possible causes of tailings dam
failure include flood overtopping, slope instability,
seepage failure, structural damage, and seismicliquefaction. In general, the stability of a tailings dam
being influenced by the seepage field cannot beignored. The current study is mainly based on theassumption of two-dimensional plane strain. There iscurrently little literature on three-dimensional (3D)
stability of the tailings seepage and deformation, so a
3D numerical model was built based on a flatland
tailings pond project, to conduct a liquid-solid
coupling analysis of the potential risk due tosuccessive preloading at the front of the dam. Someengineering countermeasures are put forward
corresponding to the evaluation results.
3.3 Simulation Analysis Schemes
The numerical simulation consisted of four steps,
as follows:
Step 1: The initial seepage field and initial stressfield were calculated under the current operatingwater level of 27.0 m and then the displacements
were reset to zero.
Step 2: The heap process was divided into six
steps up to the present level of 38.5 m to analyze thedeformation characteristics of the tailings dam under
the current conditions.
Step 3: The heap height was increased with anadditional accumulation to 42.0 m high, and thedeformation characteristics analysis of the tailings
dam was repeated.
Step 4: The stability evaluation and potential risk
analysis of the tailings dam were carried out by using
liquid-solid coupling method considering different
preloading conditions, and the corresponding safety
factors were proposed.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Physics and mechanics parameter of the model.
No.

Name

Density/kg/m3

Elasticity
modulus /GPa

Poisson ratio Cohesion /kPa

Frictionangle / °Permeability
coefficient /cm·s-1

1

Gravel with silt

2250

50

0.32

1

35

0.134

2

Tailings silty sand

1710

15

0.40

3

25

2.93×10-3

3

Tailings silty clay

1910

8

0.35

19

8

2.3×10-6

4Medium-coarse loose sand

1950

70

0.30

3

30

1.7×10-2

5Medium-coarse slightly dense sand

1960

75

0.30

3

32

3.2×10-2

6Medium-coarse loose sand

1870

63

0.30

3

29

2.8×10-3

7

Silt

2190

47

0.32

30

20

1.2×10-4

8

Silty clay

2030

80

0.30

35

15

1.5×10-6

4. LIQUID-SOLID COUPLING ANALYSISOF TAILINGS DAM
4.1 Pore pressure distribution of the flow field undercurrent operating level
In order to facilitate the analysis, a vertical crosssection at x = 100 m (section A) was defined, as
shown in Figure 2. All of the results below are shownin section A under the current operating water levelof 27.0 m.
It can be seen from the pore pressure distribution(Figure 4) under the condition of the current
operating water level that the stable seepage line intailings dam extended from the embankment to theouter toe of the slope of the mullock heap, where
failure occurred more easily due to the seepage ofgroundwater.

Z

Y

X

Contour of Pore Pressure
Plane: on
Magfac = 0.000e+000
0.0000e+000 to 2.5000e+004
2.5000e+004 to 5.0000e+004
5.0000e+004 to 7.5000e+004
7.5000e+004 to 1.0000e+005
1.0000e+005 to 1.2500e+005
1.2500e+005 to 1.5000e+005
1.5000e+005 to 1.7500e+005
1.7500e+005 to 2.0000e+005
2.0000e+005 to 2.2500e+005
2.2500e+005 to 2.5000e+005
2.5000e+005 to 2.7500e+005
2.7500e+005 to 2.9128e+005
I t
l 25 004

4.2 Deformation characteristics of the tailings dam
under gradual accumulation

The calculation results of displacement fields are
displayed below, with Figures 5 and 6 corresponding
to the current elevation of the mullock heap (38.5 m)
and Figures 7 and 8 corresponding to the additional
heaped elevation (42.0 m). By comparative analysis it
can be seen that:
Apart from its consolidation deformation owing
to self-gravity under gradual accumulations of the
mullock heap, the outside ground surface, starter dam
and outer slope of tailings fill dam are loaded andcrushed with different deformation characteristics asa result of their different stiffnesses. The outer slope
toe of mullock heap is mainly surface settlement andlateral uplift. The tailings dam deforms inward underpressure with a certain lateral deformation that results
in a little uplift of tailings silty sand. From the viewof magnitude, the horizontal displacements toward
inner tailings dam are close to that in the opposite
direction.
The
aforementioned
deformations
developed significantly with the increasing height ofthe mullock heap.

Figure 4: Pore pressure distribution under the current waterlevel.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Z
Z

Y
Y

X

X

Contour of Y-Displacement
Plane: on
Magfac = 0.000e+000-1.9925e-001 to -1.5000e-001-1.5000e-001 to -1.0000e-001-1.0000e-001 to -5.0000e-002-5.0000e-002 to 0.0000e+000
0.0000e+000 to 5.0000e-002
5.0000e-002 to 1.0000e-001
1.0000e-001 to 1.5000e-001
1.5000e-001 to 2.0000e-001
2.0000e-001 to 2.2701e-001
I
l
0 002

Contour of Displacement Mag.
Plane: on
Magfac = 0.000e+000
0.0000e+000 to 5.0000e-002
5.0000e-002 to 1.0000e-001
1.0000e-001 to 1.5000e-001
1.5000e-001 to 2.0000e-001
2.0000e-001 to 2.5000e-001
2.5000e-001 to 3.0000e-001
3.0000e-001 to 3.5000e-001
3.5000e-001 to 4.0000e-001
4.0000e-001 to 4.5000e-001
4.5000e-001 to 5.0000e-001
5.0000e-001 to 5.0175e-001
Interval = 50e-002

Figure 8: Horizontal displacement field under the futureheight.

Figure 5: Displacement field and arrow under the current
height.

Z

Y

XContour of Y-Displacement
Plane: on
Magfac = 0.000e+000-1.7969e-001 to -1.5000e-001-1.5000e-001 to -1.0000e-001-1.0000e-001 to -5.0000e-002-5.0000e-002 to 0.0000e+000
0.0000e+000 to 5.0000e-002
5.0000e-002 to 1.0000e-001
1.0000e-001 to 1.5000e-001
1.5000e-001 to 1.7882e-001
I t
l 50 002

Figure 6: Horizontal displacement field under the current
height.

Z

Y

XContour of Displacement Mag.
Plane: on
Magfac = 0.000e+000
0.0000e+000 to 5.0000e-002
5.0000e-002 to 1.0000e-001
1.0000e-001 to 1.5000e-001
1.5000e-001 to 2.0000e-001
2.0000e-001 to 2.5000e-001
2.5000e-001 to 3.0000e-001
3.0000e-001 to 3.5000e-001
3.5000e-001 to 4.0000e-001
4.0000e-001 to 4.5000e-001
4.5000e-001 to 5.0000e-001
5.0000e-001 to 5.5000e-001
5.5000e-001 to 5.6021e-001
I t
l 50 002

Figure 7: Displacement field and arrow under the futureheight.

The results suggest three potential failure modesof tailings dam under preloading: (1) Compressive
shear zone in the outside ground is likely to induce
sliding failure through the outer slope toe of tailings
dam in cases where additional loadings arecontinued; (2) Local compression and shear failure
could appear during the deformation process oftailings dam under gradual preloading; (3) Uplift
failure might occur in tailings embankment as loadincreases with the increasing height of the mullock
heap.
4.3 Safety risk analysis of tailings dam under gradualaccumulation
According to Chinese technical codes, the safety
factor of the tailings dam in this example project
should not be less than 1.25 under normal operating
conditions. The internal shear strength reduction
method of FLAC3D was adopted to calculate thesafety factors of tailings dam with different heap
heights and to determine the potential slip surface
position. The safety factor of tailings dam was 1.28
under the present heap height of 38.5 m (Figure 9),
which would reduce to 1.23 when the mullock heap
height increased to 42.0 m (Figure 10). This would
constitute a lack of safety reserve, and therefore theheap height should not be increased.

Z

Y

X

FoS
FoS value is : 1.28

Figure 9: Potential slip surface and safety factor under thecurrent height.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Z

Y

X

FoS
FoS value is : 1.23

Figure10: Potential slip surface and safety factor under
future height.

5. CONCLUSION
It is concluded from liquid-solid coupling
analysis that there are three potential failure modes oftailings dam under preloading. Under present
conditions, the tailings dam meets safety
requirements whereas in the event of additionalheightened heap, safety requirements would not be
met.
According to the above results, these engineeringcountermeasures were put forward: The height of thepresent heap must be cut to satisfy the stability
requirement under the condition of rain infiltration.
Sound monitoring and regular inspections should beestablished to ensure the safety of the tailings pond
operation. The engineering practice showed that thesesafety measures achieved good results.

Li G.Z., Li P.L. and Xu H.D. (2005) Tailing dam
stability analysis based on structural confidence level,Gold, Volume 26, pp. 48-50.
Li Q., Zhang L.T., Qi Q.L., Zhou Z.L. (2012)
Instability characteristics and stability analysis of atailings dam based on fluid-solid coupling theory,
Rock and Soil Mechanics, Volume 33, pp. 243-250.
Lou J.D., Li Q.Y. and Chen B. (2005) Tailingdam math simulation and stability analysis, Journalof Hunan University of Science & Technology(Natural Science Edition), Volume 20, pp. 58-61.
Shakesby R.A. and Richard W.J. (1991) Failureof a mine waste dump in Zimbabwe: Causes andconsequences, Environmental Geology and Water
Sciences, Volume 8, pp. 143-153.
Strachan C. (2001) Tailings dam performancefrom USCOD incident-survey data, Mining
Engineering, Volume 53, pp. 49-53.
Valenzuela L. and Barrera S. (2003) Seismic
design of Los Quillayes tailings dams in Chile, In:
The 12th soil mechanics and geotechnicalengineering Panamerican conference, Massachusetts,
pp. 2235-2240.
Yin G.Z., Li Y., Wei Z.A., Jing X.F. and Zhang
Q.G. (2010) Regularity of the saturation lines' change
and stability analysis of tailings dam in the conditionof flood, Journal of Chongqing University (Natural
Science Edition), Volume 33, pp. 72-86.

6. ACKNOWLEDGMENTS
This work was financially supported by the
National Natural Science Foundation of China(51474188; 51074140; 51310105020) and the
Natural Science Foundation of Hebei Province ofChina (E2014203012), 2015 Endeavor Research
Fellowship and the Program for Taihang Scholars, allthese are gratefully acknowledged.

7. REFERENCES
Bussière B., Chapuis R.P. and Aubertin M.
(2003) Unsaturated flow modeling for exposed andcovered tailings dams. In: The Montreal ICOLD
Conference, Montreal, pp. 1-20.
Chakraborty D. and Choudhury D. (2009)
Investigation of the behavior of tailings earthen dam
under seismic conditions, American Journal ofEngineering and Applied Sciences, Volume 2, pp.
559-564.
Chen D.Q., Wang L.G. and Li G. (2008)
Analysis of tailing dam’s stability, Journal of
Liaoning Technical University (Natural Science),
Volume 27, pp. 349-361.
Hu M.J., Guo A.G. and Chen S.Y. (2004)
Reflections on anti-slide stability analysis of agangue dam, Rock and Soil Mechanics, Volume 25,
pp. 769-773.

418

Paper No. 111

ISMS 2016

Numerical analysis of Westwood Mine tailings embankment stability during
the restoration phase
Yaya Coulibaly*, Tikou Belem, Li Zhen Cheng
Research Institute on Mines and Environment (RIME)
Université du Québec en Abitibi-Témiscamingue (UQAT)
Tel: +1 819-874-8728 ext. 6233

ABSTRACT
Stability analysis of Westwood Mine tailings embankment performed using SLOPE/W and SIGMA/W codes
showed that the minimum factor of safety obtained is higher than the recommended value of 1.5 set by some authors
and the Quebec Ministry of Natural Resources and Wildlife for static loading and steady flow conditions. Porepressures that must be controlled are higher in bottom layers of the embankment, and these pressures move toward
the downstream side. In addition, low electrical resistivity values (by geophysical method) associated with the highwater content tailings layer, suggest its susceptibility to internal erosion.

1. INTRODUCTION
The mining industry is the lung of the economy
of any country possessing active mines, but it also
generates large quantities of solid wastes such as
tailings and waste rock that must be properly
confined either in a tailings storage facility (TSF) or
waste rock pile, respectively. The exposure of thesesolid wastes to atmospheric conditions could result inenvironmental pollution by acid mine drainage(AMD) or contaminated neutral drainage (CND).
When underground mining methods require that thestopes are artificially supported to allow full ore
recovery, backfilling is an effective way of solid
wastes management. Mine tailings are surrounded in
the TSF by embankments that must be monitored toprevent spillage of slurry tailings due to theirpotential failure. Failure is a physical process(mechanical or hydraulic) by which the embankment
can be broken by tearing off and dumps potentiallycontaminated slurry tailings and, consequently,
floods the downstream side of the dam. In general,
breakdown of embankment dams is via four classicalmechanisms (Mériaux et al., 2001): external erosion,internal erosion, external instability and liquefaction.
Runoff of rainwater can also be the cause of external
erosion. The settlement on the ridge causing cracking
and water infiltration into the dam can cause internal
erosion or slippage in an area of weakness.
Numerical analysis methods have been widelyused to solve complex problems of slope stability,
which otherwise would not be possible using
conventional techniques (Eberhardt, 2003; Barbour
and Krahn, 2004; Ormann et al., 2010; GEO-SLOPE
International Ltd., 2007). Also, the geophysicalmethod using electrical resistivity has excellent*Corresponding author – email : yaya.coulibaly@uqat.ca

potential, as the measured parameters (resistivity or
conductivity) are sensitive to the presence of water orcavities (Denahan and Smith, 1984; Ernstson and
Kirsch, 2006). Among other things, electricalresistivity method makes it possible to detect theinternal structure and cracks in the embankment.

Figure 1: Aerial view of the tailings embankment studied.

The Westwood Mine (owned by IAMGold
Corp.) aims at reusing their TSF #1 for solid wastes
storage, but on the other side of the Northwest
separation embankment is located a small polishingpond (Figure 1). Some sporadic and localized slumps
and slippage on the embankment have been reported.
The slippage occurs on the downstream side slope(external instability) and the upstream slope side forsome reason (e.g. liquefaction of the tailings or3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2. METHODS OF SLOPE STABILITYANALYSIS USING NUMERICAL CODES
2.1 Factor of safety (SLOPE/W)
In conventional methods of limit equilibrium
analysis, the factor of safety (FS) is defined as theratio between the resisting forces and the forcesleading to tilting movements (Krahn, 2007, in GEOSLOPE International Ltd., 2007).
FS =

∑ 𝑆𝑟
∑ 𝑆𝑚

(1)

FS =

𝑀𝑜𝑚𝑒𝑛𝑡𝑠 𝑟𝑒𝑠𝑖𝑠𝑡𝑖𝑛𝑔 𝑠𝑙𝑖𝑑𝑖𝑛𝑔
𝑀𝑜𝑚𝑒𝑛𝑡𝑠 𝑐𝑎𝑢𝑠𝑖𝑛𝑔 𝑠𝑙𝑖𝑑𝑖𝑛𝑔(2)

where Sr = resisting force due to friction andcohesion; Sm = driving force tending to drag theblock.
Alternatively, the factor of safety can also be
expressed as follows:

Amongst the most popular analytical methods oflimit equilibrium analysis (see Figure 2), theMorgenstern-Price method was chosen as theanalysis method (which is close to the Spencer’s
method), because it expresses two basic concepts fordetermining the factor of safety. The factor of safety
versus lambda (Lamé coefficient) indicates theminimum factor of safety at the point of intersectionof equilibrium moment and equilibrium force. From
Figure 2 the point of intersection of the moment andthe force corresponds to a factor of safety of 2.15,
according to Morgenstern-Price or Spencer methods.
In practice, the use of FS greater than 1.5 for static
analysis of embankment stability and steady flow
conditions is recommended (Eberhardt, 2003;
Ormann et al., 2010; Quebec Ministry of Natural
Resources and Wildlife).

Factor of Safety

foundation soil as a result of a probable low
magnitude seismic event).
The aim of this study is to assess theembankment stability by the means of numericalanalysis using SLOPE/W and SIGMA/W codes(from GEO-SLOPE International Ltd.) and ofgeophysical methods that use electrical resistivity andground-penetrating radar (GPR). The SLOPE/W codeis based on limit-equilibrium analysis, while the
SIGMA/W code is based on finite element method(FEM). The SLOPE/W code was used for assessing
the embankment slope stability analysis through thecalculation of the factor of safety (FS) based on thestrength reduction factor (SRF) method. The
SIGMA/W code was used for obtaining the stress andstrain distribution across the embankment. The
geophysical methods (electrical resistivity and GPR)
show excellent potential of correlating all the data
since the tailings dam properties (resistivity or
conductivity) measured are sensitive to the presenceof water or cavities. This paper presents the main
results obtained.

3.2
3
2.8
2.6
2.4
2.2
2
1.8
1.6
1.4
1.2
-1

MomentForce
BishopMorgenstern-Priceor Spencer

Janbu0
Lambda (Lamé coefficient)

1

Figure 2: Graphical plot of the factor of safety as a functionof Lamé coefficient for the moment and equilibrium force.

2.2 Stress-strain analysis (SIGMA/W)
The stress-strain analysis was performed by thefinite element method using the SIGMA/W
numerical code. The embankment slope stability wasassessed by the effective stress analysis and theMohr-Coulomb failure criterion was chosen:
𝜏 = 𝑐 ′ + 𝜎 ′ 𝑡𝑎𝑛𝜑 ′(3)where 𝜏 is the shear strength (kPa), 𝑐 ′ is the effective
cohesion (kPa), 𝜑 ′ is the effective internal friction
angle (°) and σ’ is the effective normal stress (kPa)which is given as follows:(4)𝜎′ = 𝜎 − 𝑢where u is the pore water pressure (kPa) and 𝜎 is thenormal or vertical total stress (kPa).
The reduction of the effective stress 𝜎 ′ will
reduce the shear resistance and this could promote
some instabilities. For each simulation, theconvergence of the calculations were be analyzed by
the unbalanced forces. An unstable model is usuallycharacterized by a non-zero value, often fluctuating;the maximum unbalanced force and increased
displacements (Eberhardt, 2003). Also, areas of low
stresses are favorable to the internal erosion (Ormann
et al., 2010).
2.3 Geophysical analysis by computed tomography
The computed images of the electrical
tomography using a freeware (RES2DINV software)
can be interpreted as an electrical conductivity map

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

showing that the conductive areas through theembankment are correlated with water saturated areas
where electrical resistivity values are low in favor ofa high conductivity.

3. RESULTS
3.1 Embankment stability analysis using SLOPE/W
The input parameters for each type of material
are: unit weight (γ), effective cohesion (c’) andeffective internal angle of friction 𝜑’ (cf. Table 1).
Figure 3 shows the result of the analysis thatindicates a factor of safety (FS) value of 1.833 which
is higher than the recommended value of FS = 1.5.
This value corresponds to the start of the tailings
impoundment filling which is the current state of theembankment. This result shows that the embankmentis currently stable (Figure 3). When 10 tons static
dead-weight is applied on the crest of theembankment, simulating a stationary truck during
waste rock damping, the factor of safety remains

above 1.5 but decreases to 1.754. When the tailings
impoundment is entirely filled the factor of safety
decreases slightly from 1.833 to 1.814.
To determine the effects of the change incohesion and the angle of friction of fill layers(rockfill and tailings), several simulations were
performed and the values the factors of safety are
shown in Table 2. One can observe that there would
be embankment failure when the tailings effective
cohesion c’ is zero and the effective internal angle offriction is 12° (FS = 0.755). Also, when the tailings
effective cohesion is zero with an angle of friction of
35° and a unit weight of 12 kN/m3, the factor ofsafety FS = 1.28 (which is lower than therecommended value of 1.5).
It should however be noted that these two
scenarios are unlikely because the tailings effective
angle of friction would be close to 30° while it is very
unlikely that the tailings can have a unit weight lower
than 14 kN/m3 (specific gravity of 2.67 and slurrysolid mass content of 50%).

Table 1: Values of parameters used in SLOPE/W simulations (from the report of the closure plan and restoration, 1999).
Type of material
Unit weight (kN/m³)
Angle of friction (°)
Cohesion (kPa)
Undrained shear strength (kPa)
Tailings
19.0
35
0
0
Upper silt
19.2
28
0
0
Lower silt
19.2
28
0
0
Silty clay
16.5
30
0
40
Rockfill
2042046Filling material
19
35
0
0

Figure 3: Stability analysis of the embankment slope showing a FS of 1.833 at the start of the tailings impoundment filling.

Data in Table 2 are used to construct different
graphs that are presented in Figures 4, 5, and 6 andillustrate the influence of the effective cohesion andinternal angle of friction on the factor of safety.
These figures show that the effective cohesion andangle of friction (which are the shear strengthparameters shown in Eq. 3) have a direct influence on

the factor of safety. In fact, FS increases with theincrease of the cohesion and the angle of friction. Fora similar range of variation of c’ and 𝜑’ the trend of
the factor of safety is more pronounced for thetailings than for the rockfill (Figure 6).

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
Table 2: Factor of safety when we vary the cohesion and the angle of friction of rockfill and tailings layers independently.
Type of material

Rockfill

Tailings

Cohesion (kPa)
0
0
0
0
10
20
0
0
0
0
0
0
0
0
10
20
0
0
0

Angle of friction (°)
20
42
60
42
42
42
42
42
42
42
12
35
53
35
35
35
35
35
35

Unit weight (kN/m³)
18.1
18.1
18.1
18.1
18.1
18.1
18.1
23.1
24.3
30
19
19
19
19
19
19
12
19
25

Factor of safety
1.856
1.964
2.072
1.964
2.013
2.064
1.964
1.848
1.824
1.729
0.755
1.964
2.582
1.964
2.222
2.391
1.28
1.964
2.349

Figure 4: Variation in the factor of safety as a function of a) the cohesion and b) the angle of friction of the rockfill layer.

Figure 5: Variation in the factor of safety as a function of a) the cohesion and b) the angle of friction of the tailings layer.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
Figure 6: Variation in the FS as a function of a) effective cohesion and b) internal angle of friction for rockfill and tailings.

pressure does not dissipate easily in short term, thetotal stress could increase progressively and put theembankment stability in question. The pore waterpressure was relatively high in the deeper layers,
particularly in the regions directly below theembankment (i.e. below the rockfill and tailings) andmoving toward the downstream side (Figure 7).

3.2 Stress-strain analysis using SIGMA/W
The input parameters to perform the stress-strain
analysis of the embankment using the SIGMA/W
code are listed in Table 3. The values are
representative of each material in the embankment.
The stress analysis shows that if the pore water
Table 3: Values of parameters used in SIGMA/W.
Parameters

Rockfill

Tailings

Upper silt

Silty clay

Lower silt

Filling material

Young’s Modulus E (kPa)

40000

7200

3895

9312

9800

3048

Unit Weight (kN/m³)

24.3

19

19.2

16.5

19.2

19

Poisson’s ratio

0.334
0.50010.334
0.50010.334
0.50010.334
0.50010.334
0.50010.334
0.5001

In situ pressure coefficient K0

1
8 F.
1 mate0 rial
0

Roc
kfill

Upper silt18

- 22 20
12
0 140
0
00
m
1
F.
0
mate
0
1
0

rial

a
)

Tailings layer

22 20 18
24
0 0 0
m

30
m

Silty
clay silt layer
Lower
layer

46
Roc m

b
kfill layer
Tailings
Upper silt)

Silty
Lower silt layer
clay
78
5
layer

1
m

m

Displace
ment ofpore
pressures

Figure 7: Illustration of the iso-value curves of pore pressure for a) current in-situ condition, b) filled state.

3.3 Geophysical tomography using RES2DINV
software
The geophysical method used was the electricalresistivity method in which an electric current is
injected into the embankment using different
electrodes placed at different locations, and then thepotential difference between a pair of potential
electrodes is measured. The apparatus used was theground penetrating radar (GPR). According to thesystem set up, a section of the apparent resistivity
was be calculated from the potential measurements.
Two measurement configurations were used: Wenner
and Wenner-Shlumberger (Syscal R1 Plus Switch 72)

in order to look at the variation of the resistivity
within the embankment related to its internal
structure. Figure 8 shows an inversion result fromdata
collected
withWenner-Schlumberger
configuration using the RES2DINV software. In thisfigure the blue color represents the low resistivity(i.e. high conductivity) and the red color represents
the high resistivity. The distribution of the apparent
resistivity outlines a layered structure of theembankment. An outcrop (observed in the field) at
the end of the profile on the right (at around 320 m)
corresponds to the highest resistivity area (darkbrown to purple). The resistivity variation with the423

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016depth correlates very well with the internal structure
observed from the geotechnical drilling F-95-1
observations performed by Golder and Associates in
1996; especially at the depth of the interface between
the moraine and the bedrock. Based on the drilling
data, the following lithological limits from top tobottom on the sections in Figure 8 were identified:
The rockfill layer (0 − 5 m approximately), withelectrical resistivity of between 65 and 117 Ωm;Tailings layer (5 – 26 m approximately),
electrical resistivity between 20 and 65 Ωm;
Upper silt, silty clay, lower silt, dense moraine
and bedrock (> 26 m of depth), electrical resistivity
between 117 and 1222 Ωm;

The bedrock is located in sub-surface to the rightend of the section and it might have the same
composition as that on the bottom of theembankment. Lateral variations in resistivity may
imply that there are resistivity heterogeneities within
the embankment in particular between the moraine
and the sub-surface rock (lowest resistivity area).
These heterogeneities may be due to cracks filledwith water (dark blue);In the pond (downstream of the dam), it seems
that there is a penetration of tailings drainage water
through the dam. It could be caused by small cracks
where there is a discontinuity of resistivity (reddashed cycle on Figure 8) of the embankment layersmaterialized by resistivity variations.

Drilling F-95-1

Rock

Rock
Zone of weakness
Heterogenious zone Lithological limits

Figure 8: Tomographic inversion image, Wenner-Schlumberger with 5m distance between electrodes.

4. CONCLUSION
Stability analysis performed was particularlyinteresting as a monitoring tool for the Westwood
Mine embankment. The calculated values of thefactor of safety were higher than 1.5, which meets thestandard recommendations set by some authors andby the Quebec Ministry of Natural Resources andWildlife for static loading and steady flow
conditions. In all cases of realistic geometricrepresentation of the embankment, the minimum
factor of safety was greater than 1.5, thus confirming
the stability of the embankment studied. The stressanalysis suggests that the pore water pressure ishigher in the layers directly below the embankment(i.e. higher in the upper silt, silty clay and lower silt).
The performed electrical tomography shows that it ispossible to distinguish the different structures of theNorthwest embankment of Westwood Mine tailings
storage facility without employing a destructive
method. The electrical tomography image shows thatthe conductive areas across the embankment correlate
well with water saturated areas such as tailings layer
where electrical resistivity values are low in favor ofa high conductivity. These water-saturated areas are
susceptible to the risk of internal erosion. The change
in electrical resistivity scale in the rockfill layer (5 m
depth) shows that it is unsaturated layer having alower electrical resistivity (approximately 65 − 117Ωm). These zones could reflect heterogeneity of theparticle size of these materials, which could cause
differential settlement in the long term.

5. ACKNOWLEDGEMENT
This research was financially supported by the
RIME (Research Institute of Mining andEnvironment) of UQAT. The authors would like toacknowledge them for this support. The authors also
wish to thank our mining partner, IAMGOLD
Corporation (Westwood Mine), including theSuperintendent of Environment Department, Mr.
Sylvain Lortie for their collaboration in this project.

6. REFERENCES
Barbour, S. L., and Krahn, J. (2004). Numericalmodelling – prediction or process? Geotechnicalnews, December 2004.
Denahan B. J., Smith D. L., (1984). Electricalresistivity investigation of potential cavities
underlyingaproposedashdisposalarea. Environmental geology and water sciences.
Volume 6, Issue 1, pp 45-49.
Eberhardt, E. (2003). Rock slope stability
analysis - Utilization of advanced numerical
techniques.
Ernstson, K., Kirsch, R., (2006). Geoelectricalmethods. In: Kirsch, Reinhard (Ed.), groundwater
geophysics. Springer. ISBN: 3-540-29383-3, pp. 85–
117.

424

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

GEO-SLOPE International Ltd. (2007). GeoSlope Office (Slope/W, Seep/W, Sigma/W,
CTran/W, Temp/W, Quake/W, Air/W). Geo-Slope
International Ltd., Calgary, Canada.
Mériaux P., Royet P., Folton C. (2001).
Surveillance, entretien et diagnostic des digues deprotection contre les inondations. Cemagref Editions,
191 p.
Ormann, L., Zardari, M.A., Mattsson, H.,
Bjelkevik, A., and Knutsson, S., (2010). Numericalanalysis of strengthening by rockfill embankments on
an upstream tailings dam.

425

Paper No. 213

ISMS 2016

Application of an economy comparison model for mine cooling systemtechnology
Miao Dejuna,b*, Chang Dehuaa,b, Tan Dongweia,baCollege of Mining and Safety Engineering, Shandong University of Science and Technology, Qingdao, China 266590
State Key Laboratory Breeding Base for Mining Disaster Prevention and Control, Shandong University of Science andTechnology, Qingdao, China 266590
b

ABSTRACTThe existing selection methods for mine cooling schemes are complex and have incomprehensive index values. In
order to rectify this problem in the specific circumstance of high temperature mines, this paper puts forwad 13
index values, including the machine power, project investment, operation cost, etc. A comparative model oftechnical and economic benefit of mine cooling systems is established by using the objective entropy weight and
TOPSIS method. Using objective entropy weight, the entropy weight of evaluation index and the weight decision
matrix are determined. Using the TOPSIS method, the ideal solution and the negative ideal solution are determined.
The optimal scheme can be determined by using the closeness degree calculation for the scheme sort. Optimization
calculation and comparisons are carried out for four cooling schemes in a mine. Scheme 4 is found to be the optimal
scheme for cooling systems.
KEYWORDS: Mine cooling; Technical and economy model; Scheme optimization

1. INTRODUCTION
With the increase of mining depth and theimprovement of comprehensive mechanical mining
capacity, high temperature heat damage has become
one of the problems that seriously restricts the safe
production of mines, and affects the economic benefitof the mine (Qi Yudong et al., 2014). Since thecauses of high temperature mine heat damage aredifferent, reasonable solutions should be chosen foreach individual mine. Miao Sujun (2010) puts
forward a mine cooling system scheme optimization
method to aid in choosing a mine cooling scheme.
Feng Xiaokai (2009) and Chen Xiaoyou (2013) haveresearched the economy of cooling projects, theeconomic benefit of coal mines, and constructed amine cooling system cost economic evaluation
method that focuses on mathematical analysis andscheme comparison. Zhang Hui (2009), Chen
Jianmei (2009), Jian Congguang (2008), and Li
Hongyang (2010) have optimized the economic andtechnological indexes of cooling systems andimproved the mechanical cooling system evaluation
method by comparing the economic costs in multiple
dimensions. Of the above schemes, some are very
complex, and need more experts to determine theweights. Therefore, it is necessary to build a mine
cooling system technology and economic benefit
model to improve the effectiveness and practicality ofscheme selection.

*Corresponding author – email: Junmdxh@163.com

2. ESTABLISHMENTOFMINETECHANICALANDECONOMIC
BENEFIT COMPARATIVE MODEL
In this paper, the mine cooling technical andeconomic benefit comparison model is based on theobjective entropy weight and TOPSIS method. Firstly,target decision matrix are constructed, andnormalized processing is carried out. Secondly, theentropy weight of the evaluation index is determinedaccording to the objective entropy weight. The
weighted decision matrix is constructed and the ideal
solution and the negative ideal solution aredetermined. Finally, the feasible scheme isdetermined. The feasible scheme makes the distance
between the scheme solution and the ideal solution
the smallest, and the distance from the negative ideal
solution the largest (Ma Zhipeng et al., 2009).
The decision rule of the scheme is found bycomparing the actual feasible solution with thepositive ideal solution and the negative ideal solution.
The close degree between the scheme and the best
scheme can be used as a basis for evaluation of themerits of each program (Yue Chaoyuan, 2003). Thiscan be found by calculating the weighted Euclidean
distance between a scheme, the best scheme, and theworst scheme. The calculation steps of the model are
as follows:
1) Formation of decision matrix
The decision matrix is formed according to theactual situation of the high temperature mine and themachine-operating power and investment costs. In

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the cooling schemes, the corresponding target
decision matrix is established. Set multiple target
decision scheme set as M=（M1，M2，… ，Mm），
the index set as C=（Cl, C2,…, Cn）, set the project
Mj to the index Ci value as xij （i=1,2,…,m; j =1,
2,…,n ), multi-objective decision matrix (A) is: x 11x
 21
A =  x31
 
 x m1x1n 
 x 2 n 
 x3n  
 x mn 


x12
x 22
x32

xm 2

bij =

（1）

j =1

4) Constructing the weighted decision matrix
Multiplying the normalized judgment matrix andthe weight of each index can obtain the weighted
decision matrix:（i=1,2,…,m; j=1,2,…,n）（9）5) Determining the ideal solution and negative
ideal solution（2）

xmax − xminn1− H j
ω
=
,
W
(
=
)
,
1
j 1×n ∑ ω j
n
j =1
n−∑Hj

R = (ri , j ) m×n , rij = w j ⋅ bij

Target decision matrix A is normalized and thenormalized judgment matrix B is obtained:

xij − xmin

ωj=

The value b ij is determined by the superior
degree of running power and investment cost index.
Specific performance is in the following two aspects:
x(i, j ) − xmin ( j )
bij =
（3）
xmax ( j ) − xmin (i, j )Choice criterion: the bigger the better index
x ( j ) − x(i, j )b ij = max（4）x max ( j ) − x min (i, j )Choice criterion: the smaller the better index
Where bij is normalized value of characteristic
value， x min ( j ) , x max ( j ) , the j evaluation indexes+

The ideal solution S and the negative ideal−

solution S of each scheme can be determined fromthe weighted decision matrix. The selection of ideal
solution and the negative ideal solution can be found
via the selection condition of each index in the design
scheme.
max{rij }, ( j = 1,2....., n)
1 ≤ i ≤ m
S +j = min{rij }, ( j = 1,2....., n)
1 ≤ i ≤ mmin{rij }, ( j = 1,2....., n)
1 ≤ i ≤ mS −j = max{rij }, ( j = 1,2....., n)
1 ≤ i ≤ m

(10)

（11）

6) Distance between the ideal solution and negative
ideal solution+

The ideal solution S and the negative ideal

are the minimum and the maximum.

−

2） H j determined by objective entropy weight
According to the definition of entropy, there arem schemes and n evaluation indexes. They candetermine the evaluation index of entropy.
Hj =m
� , m;  i = 1, 2, 
1(∑ fij ln fij ) � ,n 
− ln m i =1
 j = 1, 2, 

（5）In order to make ln f ij meaningful, it isnecessary to modify the f ij . It is defined as:

f ij ≠ 0 ， f = bij
ij

∑b
i =1

f ij = 0 ， f ij =（6）m

S d+i =∑ (s − r )(12)

S d−i =∑ (s − r )

(13)

n

j =1
n

j =1

+
j

−
j

2

ij

2

ij

In equations (12) and (13), i=1,2,…,m;
j=1,2,…,nij

1 + bij（7）m∑ (1 + b )i =1

solution S of each scheme can be determined fromthe weighted decision matrix. The selection of ideal
solution and the negative ideal solution can be found
via the selection condition of each index in the design
schemeij3）Establish entropy weight of evaluation index W

7) Calculation of cooling system close degree anddecision
According to the mathematical model, therelative closeness degree ξi can be calculated. Itsvalue is between 0 and 1. The values close to 1 showthat the evaluation objects will be closer to the
optimal level.

（8）

427

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Ui =

S d−i
−
di

S +S

+
di

(14)

In equation (14), i=1,2,…,mAccording to the size of value U i ，they can besorted. The project will be better if the U i is closer tothe ideal solution.

3. APPLICATION OF TECHNICAL AND
ECONOMIC BENEFIT COMPARISONMODEL IN MINE COOLING SYSTEMS
3.1 General Situation of Mine
The average geothermal gradient of a mine is
2.0°/100 m, namely, each 50 m increases by 1°. It
belongs to the normal temperature gradient zone. Dueto the complexity of the coal bearing strata lithology
combination, the general geothermal gradient ishigher than that of the non coal measure strata, withan average of 2.2°/100 m. The ground temperatureof the recoverable coal seam belongs to the normal
gradient (first and second grade high temperaturezone), the upper coal seam mostly in the first hightemperature zone, and the lower coal seam mostly insecond grade high temperature zone. Initial mining
was in 3 coal seams. In the north the groundtemperature is low, and near the southeast of F2 andF3 is a high temperature zone, belonging to thesecond grade high temperature zone and the rest
belonging to the first grade high-temperature zone.
The level of the mine is about -1000 meters. The
inlet air volume is 1200 m3/min. The original rocktemperature is 37°. Mechanical equipment in theworking face installed capacity is larger.
Underground heat damage is very serious in thesummer and mechanical cooling should be used atthat time.
3.2 Four cooling schemes for high temperature coalmines
According to the specific conditions of the mine,the four cooling schemes are ice cooling,
centralization on the ground, centralization
underground,dispersion
undergroundandcondensation heat centralization.
1) Ice cooling
Cold Source: low temperature water is madefrom a ground water chiller, transported to the ice
making machine, and made into ice.
Cold transportation: ice through the wind is sent
to the wellhead while cold water is sent to theunderground ice melting pool through the insulation

pipe. Melted ice is transported to the required cold
place through a pipeline.
Scatter cold: in order to reduce the inlet air
temperature of the working face, an air cooler isarranged on the intake airflow roadway. The methodof spraying cool. water is used in the working face.
Condensation heat emission: heat is discharged
via the cooling tower.
2) Centralization on the ground
Cold source: low temperature cold water ismade on the ground by a refrigerator.
Cold transportation: low temperature cold water
is sent to the underground high and low pressure heatexchanger through the insulation pipe along the shaft.
It is exchanged into low pressure chilled water to thevarious required cold locations.
Scatter-cold: in order to reduce the inlet air
temperature of the working face, the air cooler isarranged on the intake airflow roadway. Small air
coolers are arranged on the working face.
Condensation heat emission: it is discharged on
the ground through the cooling tower.
3) Centralization underground
Cold source: the cooling chamber can be built in
the well and equipped with a refrigeration unit. Coldwater is made from a refrigeration machine.
Cold transportation: chilled water is delivered toeach required cold locations through insulation pipes.
Scatter cold: in order to reduce inlet air
temperature of the working face, an air cooler isarranged on the intake airflow roadway. Small air
coolers are arranged on the working face.
Condensation heat emission: it is discharged to
the ground through the two pipes of the shaft.
4) Dispersion underground and condensation heatcentralization
Cold source: a local refrigeration machine isused to produce the chilled water.
Cold transportation: chilled water is delivered toeach required cold location through insulation pipe.
Scatter cold: a large air cooler is arranged on
the intake airflow roadway. Mobile cooling is usedon the working face.
Condensation heat emission: the cooling waterof the refrigerating machine is transported to thebottom of the well through pipelines by a high andlow pressure heat exchanger, Heat is discharged to
the ground of the cooling tower through the shaft
pipeline.
3.3 Comparison of mine cooling schemes
Using the above technical and economic benefit
comparison model, the four schemes of mine cooling428

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016and heat energy utilization are compared with 13
indexes, including the choice of power machine,engineering investment, annual operating cost, thelength of transmission line, the cold loss ratio,

comprehensive utilization of heat energy, thereliability of the system, pressure-bearing, heatemission, expansion capacity, load regulation
performance and shaft bottom occupancy space, andthe mining influence, as is shown in Table 1.

Table 1: Indexes of four design schemes.
Index value

OrdernumberIndex

4

Installed power（KW）
Engineering
investment(equipment cost,engineering
investment)（
Thousand yuan）
Annual operating cost（Thousand yuan）
Transmission line
length（m）

5

Cold loss ratio

1

2

3

Scheme 1：
ice cooling

Scheme 2：
centralizationon thegroundScheme 3：
centralized
underground

Scheme 4：dispersion
underground andcondensation thermal
centralization

Remarks

2374

2250

2180

2140

S

34700

32800

33500

31200

S

3500

2800

3000

2600

20020

22300

22300

22300

28%

24%

20%

10%

3

3

3

7

H

7

7

7

5

H
S

7

Comprehensive
utilization of heat
energySystem reliability

8

Pressure bearing
property

3

7

7

5

9

Heat emission effect

7

7

7

7

10

Expansion capacity

5

3

3

7

11

Load regulation
performance

3

5

5

7

12
13

Bottom space

7

3

5

3

Mining influence

1

1

1

3

6

In Table 1, S represents the smaller the better; H
represents the higher the better.
 2374 2250A=
2180
 2140


S
S
S

H
H
H
S
S

From the technical and economic benefit model, it iseasy to calculate the following values:

3470 350 20020 28% 3 7 3 7 5 3 7 1 3280 280 22300 24% 3 7 7 7 3 5 3 1 3350 300 22300 20% 3 7 7 7 3 5 5 1 3120 260 22300 10% 7 5 5 7 7 7 3 3 429

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 20160
0 1 0 0 1 1
 0

19
7
124
0 2
0 1 0
xij − x min

234
35
9
9
bij =
=
5
12
4
x max − x min 194
0
0 1 0
234
35
9
9
 1
1
1
0
1
1
0 0.5


Hj =

1

1

0.5 0.5 1 
1
1 0 

0 0.5 00 0 0.5
0

0

0

1

0
1

m
1
（∑ f ij ln f ij）= (0.9793 0.9421 0.9828 0.6966 0.8900 0.6966 0.9930- lnm i =10.9064 1 0.9064 0.9654 0.9687 0.9930)

0 0.0867 0.0320 0.0290 0.0065)

wj =1− H jnn − ∑H j= (0.0192 0.0536 0.0159 0.2810 0.1019 0.2810 0.0065 0.0867

j =1

0
0
 0

0
.
0102
0
.
0291
0
.
0124

rij = 0.0159 0.0184 0.0088
 0.0192 0.0536 0.0159

0.0867 0 0.04335
0
0
0
0
0
0
0.04335 0 0.0867

0.2810000.006500.022600.006500.045300.006500.1019 0.2810
0000.0065 
0.0160 0.0290 0.0065 
0.0160 0.0145 0.0065 
0.0320 0.0290
0 

S +j = (0 0 0 0 0 0.2810 0.0065 0 0 0.0867 0.032 0 0)

S = (0.0192 0.0536 0.0159 0.281 0.1019 0 0 0.0867 0 0 0 0.0290 0.0065)−
j

Table 2: Analytic solutions of 4 schemes
Index value
Scheme 1
Ideal solution
0.41034
Negative ideal
0.12896
solution
Closeness degree
0.23912

Scheme 20.29871

Scheme 30.29952

Scheme 40.128960.306200.302470.41034

0.502450.760875

0.50619

The analytical solutions of the 4 schemes can beobtained from equations (8) to (12), as shown in
Table 2.
As can be seen from Table 2： U1 < U 3 < U 2 < U 4
The closeness degree of scheme 4 is the largest,so scheme 4 is optimal. Scheme 4 is chosen by themine as the mine cooling project.

4. CONCLUSIONS
According to the specific conditions in heatdamaged coal mines, 13 index values are determined.
A simple and reliable comparison model of minetechnical and economic benefits is put forward basedon objective entropy weight and the TOPSIS method.
The model can be used to optimize the mine coolingscheme.
The mine technical and economic benefit
comparison model not only inherits thecharacteristics of multi-objective decision making,but also can easily and quickly select the best of thedesigned cooling schemes. The model is preferred to
avoid the serious problem of decision making
mistakes.
Calculations and analyses are conducted on fourcooling schemes for a high temperature mine and the
optimal scheme is determined. The selection of the
optimal scheme not only meets the requirements ofcoal mine safety regulations, but also reduces total
investment and saves cooling costs for the mine,
which verifies the feasibility and practicality of themodel.

5. ACKNOWLEDGEMENT
We are very thankful to The Natural Science
Foundation of Shandong Province (Grant No.
ZR2012EEM004) for sponsoring to publish thispaper.

6. REFERENCES

430

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Chen Xiaoyou. (2013). Research on CoolingTechnology And Economics in High Temperature
Deep Well. Anhui University Of Science &Technology. pp. 63-70
Chen Jianmei, Zhang Hui, Jian Congguang.
(2009). Research on economical operation of thecold-water mine cooling system. Mining &Processing Equipment. Volume 37,No. 24, pp.54-56
Feng Kai. (2009). The Research of the CoolingTechnology in High-temperature Mine and Its
Economic Analysis. Xi`an University of Science andTechnology.pp.42-53
Jian Congguang, Wei Xiujun, Yue Jun. (2008).
Ansys on economical operation of the ice
refrigeration and air conditioning syetem. Mining
Safety & Environmental Protection. Volume 35,No.
4, pp. 33-37
Li Hongyang. (2010). Technical and economic
analysis of mine cooling system .Safety in Coal
Mines. No. 3, pp. 93-96
Miao Sujun, Xin Song, Peng Peng. (2010).
Research and application optimization and decision
theory of mine cooling system. Journal of China Coal
Society.Volume 35, No. 4, pp. 614-618
Ma Zhipeng, Yuan Jianguo ,Shi Yunyun.
(2009). Grey Decision Model for Flood Control of
Cascade Reservoirs Based on Stochastic Weight
Assignment method. Water Resources andPower,Volume 27, No. 1, pp. 77-80
Qi Yudong, Cheng Weimin, Yu Yanbin. (2014).
Status Summarization and Progress of Heat Hazard
Control Technology in Coal Mine of China. Safety in
Coal Mines. Volume 45, No. 3, pp. 167-174
Yue Chaoyuan. (2003). Decision theory and method .
Science Press, 2003
Zhang Hui, Jian Congguang, Zhang Bo. (2009).
Econcmical performance of ice refrigeration and air
conditioning system in high temperature mine.
Journal of Xi'an University of Science andTechnology. Volume 29, No. 2, pp. 150-152431

Paper No. 217

ISMS 2016

Behaviour of cable bolts in shear: experiment and mathematical modelling
Naj Aziz, Ali Mirza, Haleh Rasekh, Jan Nemcik, Xuwei Li
Rock Bolting Research, School of Civil, Mining and Environmental Engineering, Faculty of Engineering and Information
Sciences, University of Wollongong, Wollongong, Australia 2500

ABSTRACTThe application of cable bolts for ground support is increasing in underground coal mines worldwide. Currently,
two methods of evaluating the performance of the cable bolt are favoured: the short encapsulation pull test, andthe shear test. The former method can be used both in the laboratory and in the field while the latter can beundertaken mainly in the laboratory. There are two methods of shear strength testing: single and double shear
tests. This paper examines the double shear testing of several cable bolts currently marketed in Australia undervarious pre-tension stresses. Both plain and indented wire cable bolts were tested. It was found that the shear
strength of the cable bolt was a function of the wire geometry and initial pre-tension. Indented wire cable bolts
were lower in shear strength than the plain wire cable bolts. A mathematical model was proposed to evaluate theshear strength of cable bolts using Fourier series and a linear relationship between shear and normal loads. The
model coefficients were determined based on the experimental results. The findings from the mathematicalmodelling tallied well with the experimental results.
KEYWORDS: cable bolt; short encapsulation pull test; shear strength; double shear testing; mathematical model;
Fourier series
planes, resulting in shearing loads across the cablebolts.
1. INTRODUCTION
Recently in Australia’s coal mining industry,
Cable bolts have been used for ground support
there has been increasing interest on the evaluationin mines worldwide since the 1960s. Cable boltsof cable bolt shear behaviour. Generally, there arehave been mostly used as a secondary support intwo main methods of testing cable bolts in shear,
addition to conventional rebar type primary support.
single, and double shear methods. Goris and Martin
Longer cable bolts act to reinforce strata above the(1996) reported on single shear tests conducted inprimarily bolted beam, and also to suspend thepairs of 0.025 m3 concrete blocks having joint
primary bolted beam to the higher competentsurfaces ranging from smooth to rough. The failure
stratification layers. Shorter cable bolts have alsoof cable bolt strands in the field may not occur inbeen used as flexible primary roof support, known
shear alone, but could be a combination of tensile
as FLEXIBOLT, replacing the ordinary rigid rebar
and shear due to the movement of bedded strata(Fuller and O’Grady, 1993).
formations in various directions.
Traditionally the mechanical integrity of cable
The understanding of cable bolt behaviour inbolts and rebar is evaluated for tensile strength andshear
is still in its infancy as there are various
axial load transfer assessed by the pull testing
practical
issues to be examined. Many theories andmethod. Various publications have reported on themechanisms involved are yet to be fully explored,
subject, covering studies undertaken both in thewhich could provide a better understanding of any
laboratory and field (Hyett et al., 1992; Hyett et al.,particular cable bolt’s behaviour in shear. The
1996; Clifford et al., 2001; Thomas, 2012). Pull tests
double shear testing study reported by Aziz et al.
are generally carried out to evaluate the axial(2004) used a three piece concrete block double
reinforcement behaviour of cable bolts as theshear apparatus to simulate the shear behaviour ofnecessary requirement for cable bolt application torock bolts in rock at the University of Wollongong.
strata support in underground coal mines. Cable
Aziz (2010) and Craig and Aziz et al. (2010a and b)
bolts are typically installed vertically above a coalused a similar but larger apparatus and examined themine opening, perpendicular to the sedimentary rock
failure behaviour of 28 mm hollow strand “TG”
bedding planes. Rock movement resulting from in
cable bolts taken to complete failure. Their findings
situ and mining intensified horizontal stresses often
demonstrated the symmetric characteristics of theoccurs along these horizontal bedding
double shear equipment with the cable bolt being
sheared to failure on each side of the sheared joints.
Analysis of the failure mode and loads achieved
indicated that the cable strand undergoes bending

Corresponding author-email: naj@uow.edu.auand crush the concrete surrounding the borehole atthe shear plane. This kind of behaviour of the cable
will not occur when the cable bolt is grouted in steel
pipes instead of rock, as the case of the single shear
method as recommended by the British Standard BS
7861-part 2 (British Standards 2009). The
equipment used in BS 7861 is a guillotine style tool,
where the cable bolt is sheared fully in the steel
frame (see Figure 1). Crushing of the rock will
enable a cable bolt to bend and subsequently load inboth shear and tension; hence, the British Standard
methodology using steel pipe is inappropriate andmay be misleading.

cause a reduction in the cable strand cross section,
leading to the loss of strength (see Figure 2),
including the failure in shear initiated at the indent.
The three types of cable tested to date included
hollow plain wire, PC plain wire, and PC indented
wire. Thomas (2012) reported on laboratory axial
pull tests of all the Australian cable bolts on themarket including the design variables of bulbs,
nutcages (birdcages), hollow, PC, multi-strand,
indented, and plain wires. It was requested of
manufacturers to provide the shear performance ofcable bolts with these multiple variables, andJennmar proceeded to test their cable bolts at the
University of Wollongong. The University has since
expanded upon the laboratory tests to include
mathematical modelling of the cable bolt behaviourin shear.

2. EXPERIMENTAL STUDY

Figure 1: Sectional diagram of double embedment shear
frame with the united being tested (BS 7661-2: 2009).

A total of six different cables were subjected to
double shear testing in 40 MPa concrete. Figure 3
shows the schematic view of various cables asassembled in concrete blocks. Each double shear
testing process requires three concrete blocks with
two outer 300 mm side cubes and a central
rectangular block 450 mm long. The casting of theconcrete blocks can be carried out either in a
specially prepared plywood mould or directly in theconfining steel frame of the double shear apparatus.
A plastic conduit 20 mm in diameter, set through thecentre of the mould lengthways, will create acentralised hole for cable installation in the concrete
blocks. Once the concrete blocks were allowed toset, and the plastic conduit was taken out, the hole ineach block hole was reamed to the desired diameter.
The concrete blocks were left immersed in a
concrete curing solution to cure for a minimum
period of 28 days.

With Australia having the largest variation ofhigh capacity, pre-tensioned and post-grouted cablebolts in the world, there exist a minimum ofliterature on shear testing of these products using arecognised shear testing methodology. While pull
testing of cable bolts can be practiced both in thefield and in the laboratory, testing of cable bolts inshear is normally carried out in the laboratory. The
difficulty of monitoring shearing process in holes
drilled in the ground formation in remote locations
renders testing in the field an inconvenient approach.
Further, Aziz et al. (2014) carried out acomparative study on 22 mm diameter plain andindented wire cable bolts, as the cable bolt surface
indentation remains an issue of concern, particularly
in shear. The study indicated that shear properties ofindented wire cables were inferior to plain wire
cables of the same type. The indentation appeared to

Figure 2: Tensile load / elongation profiles of both plain
and indented 5.5 mm wire from cable bolts.

433

Garford Twin-Strand

Non-Birdcaged Cables

Birdcaged Cables

Figure 3: Cross section of double shear blocks and cables.

The cured blocks are then mounted in the double
shear confining steel frames and the cable bolt
specimen placed into the borehole. Two 60 t loadcells were inserted onto each end of the cablefollowed by the typical cable bolt end fitting. The
load cells were connected to the data logger during
tensioning. Once the cable is pre-tensioned, thegrout was injected to the annulus between the cableand borehole through the intersecting small holes on
top of the block. Cables with hollow central tubes
were also filled with grout, and the grout or polyester
resin left to cure for at least 7 days. The top of theconcrete blocks were covered by the bolted steel
plates and the whole assembly was then mounted on
the carried base platform. The whole double shear
assembly and the base frame was then mounted on
to the 500 t compression testing machine for the
shearing process, as shown in Figure 4.

Figure 4: Arrangement of shearing apparatus oncompression machine.

The properties of the eight different cable bolts aredescribed in Table 1. The study focused on the main
cables in the market as supplied by Jennmar, withindented wire hollow cable included for additional
research. Cables were subjected to three different
values of initial axial load ranging from 0 to 25 t.
Three types of bonding agent were used in thisparticular study; Jennmar bottom-up grout (BU100),Jennmar top-down grout (TD80) and J-Lok standard
oil based resin. The values of shear and axial loads

434

versus shear displacement were monitored andrecorded. It is noted that the double shear test
delineates two times of the cable bolt shear strength.
Therefore, half of the shear load obtained from thedata tacker was considered in this study.
The process of double shear testing consists ofloading the central block vertically in the 500 t

compression testing machine (Figure 4). The 450
mm long middle section of the double shear
apparatus is then vertically shear loaded at the rateof 1 mm/min for the maximum100 mm verticaldisplacement. The rate of loading and displacement
are monitored and simultaneously displayed visuallyon a PC monitor.

Table 1: list of tested cables and the test environment.
Cable Bolt Properties
Test
No.

Cable
Product name

∅
(mm)

Wire
geometry

1

Superstrand

21.8

Spiral2

Superstrand

21.8

Plain

3

TG

28

Spiral

4

SUMO

28

Spiral

5

SUMO

28

Spiral6

Plain SUMO

28

Plain

7

Plain SUMO

28

Plain

8

Gardfordtwin-strand

15.2

Plain

Cable
crosssection
19 wire,PC strand
19 wire,PC strand
9 wires,hollow
centre9 wires,hollow
centre9 wires,hollow
centre9 wires,hollow
centre9 wires,hollow
centre2x7
wire, PC
strand

Drill
bit
(mm)

Cable
geometry
Nonbirdcaged
Nonbirdcaged

28
28

Bondingagent

Oil basedresin
Oil based
resin

Pretension
load(kN)/Peakaxial load

Peakshear load(kN)[½
doubleshear]

250

558

250

628

Nonbirdcaged

42

TD80
Grout

250

604

35mm
birdcage

42

TD80
Grout

250

414

35mm
birdcage

42

TD80
Grout

100

488

35mm
birdcage

42

TD80
Grout

250

711

35mm
birdcage

42

TD80
Grout

100

659

25mm
Bulbs

55

BU100
Grout

0

501

an =

2
2nπu
σ n cos(
)du
∫
T 0
T

(2b)

bn =

2
2nπu
σ n cos(
)du
∫
T 0
T

(2c)

T

3.

MATHEMATICAL MODELLING

The mathematical model was developed byassuming a linear relationship between the shear andnormal stresses:

S − N tan(ϕ ) − c = 0(1)where, S is the shear load, N is the normal load, φ isthe friction angle, and c is the cohesion.
The Fourier series concept as described below
is applied to replicate the variation of the normalload against shear displacement. Fourier series is amathematical technique incorporated to solve a large
variety of engineering problems mainly adopting theprinciple of superposition:

N=

∞
a0
2nπu
2nπu + ∑ a n cos(
) + bn sin()
2 n =1 
T
T 

(2a)

T

where, an and bn are Fourier coefficients, n is thenumber of Fourier coefficient, u is the shear
displacement, and T is the shearing length.
Introducing Equations (2a, b, and c) inequation (1) by considering a0 to a3, the shear
strength is obtained as:
3a0
2nπu 

S = ( + ∑ a n cos() ) tan(ϕ ) + c
2 n =1 T (3)The shear displacement at peak shear strengthis determined by taking derivation of the above435

relationship respect to the shear displacement andequating to zero as:

3a0
2nπu ) ) tan(ϕ ) + cd+ ∑ a n cos(
2 n =1 
T 
=0
du

concrete surface basic friction angle. The normalload subjected to concrete blocks started with 50 kN
and increased incrementally every 20 mm, reaching
to 250 kN at the end of the test. The value of shear
load against shear displacement was measured andsubsequently incorporated to calculate the concretesurface basic friction angle as shown in Figure 5.
The basic friction angle was indicated as 26.94°.

(4)
Thus, the peak shear displacement at peak
shear strength (up) is obtained as: − 4a + 16a − 48a a + 144a 2 
T
2
2
1 3
3

up =
cos −1 
2π
24a 3


(5)
Introducing equation (5) in equation (3), thepeak shear strength (Sp) is proposed as: − 4a + 16a − 48a a + 144a 2  
T
2
2
1 3
3


2nπ cos −1 
2π
24a 3

 
a0 3 
S p = ( + ∑ a n cos()) tan(ϕ ) + c
T
2 n =1 








(6)
The model coefficients including Fourier
coefficients (an), cohesion (C), and angle of friction(φ) were determined according to the measured datafor various conditions of cable type and pre-tension
as listed in Table 2. Generally, the values of Fourier
coefficients showed a decreasing trend with theincreasing the number of Fourier coefficients.
Above equation determines the total shear
strength of reinforced concrete blocks. This consistsof the cable bolt shear strength and the additional
shear force generated by the concrete surface
friction. In order to obtain the pure shear strength ofthe cable bolt, the frictional term should bequantified and subsequently deducted from the total
shear strength as indicated by equation 6.
The frictional force generated in the process ofshearing follows the Coulomb tribological equationas:(7)
S = N tan(ϕ b )where, φb is the concrete surface basic friction angle
determined by tilt testing.
Deducting equation 7 from equation 6, the pure
shear strength of cable bolt (Spb) is obtained as: − 4a + 16a − 48a a + 144a 2  
T
2
2
1 3
3

 
2nπ
cos −1 
2π
24a 3

3 
a

 
S bp = ( 0 + ∑ a n cos(
) )[tan(ϕ ) − tan(ϕ b )] + c
2 n =1 
T








(8)
Concrete surface basic friction angle
A double shearing test without cable bolt as thereinforcing element was carried out to determine the

Figure 5: test results of the concrete blocks sliding test.

Introducing the value of basic friction angel inEquation 8, the pure shear strength of cable bolt isobtained as: − 4a + 16a − 48a a + 144a 2  
T
2
2
1 3
3

 
2nπ
cos −1 
24a 3
2π

3 
a0

 
) )[tan(ϕ ) − tan(26.94°)] + c
S = ( + ∑ a n cos(
2 n =1 
T







b
p

(9)

4. RESULTS AND ANALYSIS
Figures 6 to 13 show the shear load and axial
load profiles against shear displacement for the tests
conducted in this study. The solid lines show theshear loads and dash line show the axial loads. The
initial changes in some of the shear load graphs after
the elastic state may be related to the barrel/wedge
settlement as the cable ends begins to take axial load
due to cable bending at the shear planes. Various
shear drops beyond the peak value are attributed toindividual cable strand failures. The larger shear
drop corresponds to the higher diameter strand
failure while the smaller ones are due to the small
strand failures. It is of interest to note that the
number of visible sudden drops in load upon shear
displacement is equal or slightly less than thenumber of failed strand, which might be due to two
strands snapping near the same time. The strand
failure in the cable at the shear plane was also436

observed as load drop at the load cells measuring
axial load near the end fittings. Figure 14 showssnapped strands of the tested cables. It is obviousthat the failures of strands in the cable are a mix oftensile and shear, depending on the location of thestrand in the cable cross-section, the direction of theTable 2: Model coefficients for different types.
Test No.
𝑎𝑎0
𝑎𝑎1
𝑎𝑎2

shearing and cable construction. For multiple mixed
wire diameter cables of the superstrand cable, it wasobserved that smaller diameter strands of the inner
layer appear to fail in tension with con and cup
pattern (Aziz et al., 2014 a, b).

𝑎𝑎3

ɸ

c

1

624.59-53.97-28.72

25.73

52.13

8.82

2
3

619.70636.82-7.87-67.87-77.06-14.88

65.73
18.57

51.41
37.53

0.27
0.16

4

387.5983.53-36.68

-5.05

51.23

67.8

5

335.31-27.32-62.84

40.02

61.7

0

6

534.76

3.47-75.64

55.49

59.56

12.66

7

449.78-136.34

16.39

-3.91

61.33

0.44

8

235.38-157.50

42.83

-4.21

47.61

137.89

Table 3 summarises the peak shear strength ofthe different cable bolt and testing configurations. It
is obvious from the results that the plain wirebirdcaged cables had higher shear strength whencompared to the indented wire birdcaged cables. The
shear performance of non-birdcaged superstrand andhollow TG cable was lower when wires wereindented, but the shear strength was still close to theUTS (Uniaxial Tensile Strength) of the cable bolts.
The lower shear behaviour of the indented wireof the same cable type was likely attributed to thefact that the indented wires have a small crosssection and the indent geometry forms a stress raiser
to initiate failure. The indented wire cable bolts
display lower deflection (stiffer) than the plain wire
equivalent type. No cable rotation was observed ineither the plain or indented strand cable bolts during
the double shearing tests.
As can be seen from Figure 15, the shear
strength values of cable bolted concrete blocks
subjected to shearing are in reasonable agreementwith proposed model results for different initialpretension load, bonding agents and cable bolt
typess. To verify the proposed equation for the pure
shear strength of cable bolts, two new double shear
tests were performed. In these tests, one test waswith concrete surfaces of the concrete faces being incontact with each other and the others without, thatis no frictional resistance. Other parameters such aspretension value, grout type, and concrete strength
were kept constant in both tests. To have cable bolt
shearing without contact between concrete blocks,
the double shear instrument was modified byinstalling two lateral braces on each side of theapparatus (Figure 16a). The lateral braces wereintended to impede subjection of normal load on
concrete blocks during shearing. To further assure

no friction between concrete blocks, a pair of Teflon
sheets with negligible fiction coefficient was
introduced between concrete joints, as illustrated in
Figure 16b. Table 4 compares the values of the pure
shear strength of cable bolts obtained from the
proposed equation and experiments. It is inferredthat the results of proposed equation fits reasonably
close with the experimental data.
In order to compare the method of double
shearing used in this study with single the shear testof British Standard, Superstrand cables bothindented and plane ones were also sheared assuggested by British Standards (2009). Figure 17
shows the comparison between the shear load
against shear displacement using double shear andsingle shear test methods. It is inferred that the single
shear testing method significantly underestimates
the shear strength of Super strand cable bolts. The
conspicuous difference between the value of shear
load in single shear and double shear tests can be
related to the fact that the single shear test is only ametal to metal shearing and does not carry any
pretension or axial load during shearing. Thus, all
the strands only experience shear failure without
having any tension failure as observed in double
shearing and shown in Figure 14. Nevertheless, inthe process of double shearing, the initial pretension
value is subjected to the cable before shearing andincreases upon shearing due to the cable
deformation. This profoundly increases the strength
at which cables can resist against shearing andsimulate properly the field conditions.

437

900

1200

800
700

800

600

Load (kN)

Load (kN)

1000

600
400

500
400
300
200

200

100
0

0
0

50
Displacement (mm)Figure 6: Shear behaviour of cabled concrete [test 1].

1400

100

Figure 9: Shear behaviour of cabled concrete [test 4].

1000

1000

800

Load (kN)

800

600

600
400

400

200

200

0

0

0

50
Displacement (mm)100

Figure 7: Shear behaviour of cabled concrete [test 2].

050
Displacement (mm)100

Figure 10: Shear behaviour of cabled concrete [test 5].

1400

1600

1200

1400
1200

1000

1000

Load (kN)

Load (kN)50
Displacement (mm)

1200

1200

Load (kN)

0

100

800
600

800
600

400

400

200

200
0

0
0

50

100

Displacement (mm)050Displacement
(mm)

100

Figure 11: Shear behaviour of cabled concrete [test 6].

Figure 8: Shear behaviour of cabled concrete [test 3].

438

1400

4
5
6
7
8

1200
Load (kN)

1000
800

414
488
711
659
501

600
400
200
0
0

50
Displacement
(mm)

100

Figure 12: Shear behaviour of cabled concrete [test 7].

1200

800
600
Figure 14: Strands snapped of the tested cables.

400
200

1200

0

1000
0

50
Displacement (mm)100

Figure 13: Shear behaviour of cabled concrete [test 8].

Table 3: Peak shear load for different cabled concrete
blocks.

Test Number

Peak shear load per surface (kN)

1
2
3

558
628
604

Shear load (kN)

Load (kN)

1000

Mode predictionl
Measured data

800
600
400
200
0
0

2

4
6
Test Number

8

10

Figure 15: Comparison between the model results andmeasured data.

439

Figure 16: Up to date double shear instrument (a) thewhole assembly inside compression machine (b) Teflon
sheet layers between concrete blocks.

Figure 17: Comparison between the double and single
shear method.
Table 4a: Comparison between the proposed model for the pure shear strength of cable blots and experimental data.

Test
No.
9
10

Product type

Bonding agent

Plain
Plain

Strata binder HS
Strata binder HS

Pre-tension
load (kN)
5
5Peak shear load perface (kN)
645.64442.16

Table 4b: Determination of shear load by the model.

Test

Plain
superstrand with 5
kN pretension
load
(with
friction)

Friction between
surfaceswithwithout

a0

a1

a2

a3

Model normalload (kN)

Tan ɸ

Tan
26.94°c(kN)

Measured peak
shear load perface (kN)

324.77182.37

18.65

3.04

366.316

1.47

0.508

88.61

441.006e)

5. CONCLUSIONS & RECOMMENDATIONS
The following conclusions are drawn from thisinvestigation:a) Spiral profiled strand wires combined withbirdcaging of cable bolts is detrimental to thecable shear performance.
b) Shear strength of non-birdcaged cables bolts
are less affected by spiral profiling of the wire.
c) It is likely that the reduced cross-section
reduces tensile strength and the geometry
forms a stress raiser to initiate failure.
d) A mathematical model was proposedincorporating a linear relationship between
shear and normal loads and Fourier series
concept to simulate the shear strength ofcabled concrete blocks. The model values
are in close agreement with the experimental
results.

The values of Fourier coefficients decreased
as the number of Fourier coefficients
increased.

Recommendations include:a) Due attention must be given to the study of thecable shear across closed and interlocking
sheared beds as well as across separated beds
with no contacts between sheared faces.
b) More experiments are suggested to calibrate
the model for practical purposes.
c) The double shear method in simulated rockhas proven to provide valuable insight into insitu performance. The British Standard BS
7861 (part 2)* cannot be applied to the studyof the shear behaviour of the cable bolt inrock. The equipment used in the BS 7861 (part2) is a guillotine style tool, where the cablebolt is sheared fully in the steel frame.

440Shearing of the cable bolt in rock normally
undergoes both shear and tension; hence, theBritish standard methodology is inappropriate
and may be misleading.

5.

REFERENCES

Aziz, N. (2014a). Double shear testing cablebolts for Jennmar Australia, a report of study prepared
for Jennmar Australia, School of Civil, Mining andEnvironmental
Engineering,
Universityof
Wollongong, May 27, 9p
Aziz, N. (2014b). Double shear testing of Secura
Hollow Groutable Cable-bolt (SHGC) for Orica
Australia Pty Ltd, a report of study, School of Civil,
Mining and Environmental Engineering, Universityof Wollongong, July, 9p
Aziz, N., Heemann, K., Nemcik, J. and Mayer,
S. (2014). Shear strength properties of Hilti plain andindented strand cable bolts, in proceedings Coal
Operators Conference (Coal 2014), Wollongong,
February 12-14, ISBN 978 1 925100 02 0, pp156-162
(Eds.
N
Aziz,
B
Kinninmonth),
http://ro.uow.edu.au/coal/509/
Aziz, N., Nemcik, J., Jalalifar, H. (2011). Double
shearing of rebar and cable bolts for effective strata
reinforcement, in proceedings 12th ISRM
International Congress on Rock Mechanics, Beijing,
China, 18-21, October. Pp 1457-1460. Published inHarmonising Rock Engineering and the Environment–Qian and Zhou (Eds), 2012 Taylor and Francis
Group, London, ISBN, 978-0-415-80444-8
British Standard BS 7861- Parts 1 and 2. (1996).
Strata Reinforcement support system components
used in Coal Mines-Part 1, Specification for rockbolting and Part 2: Specification for Flexible systems
for roof reinforcement
Clifford, B., Kent, L., Altounyan, P. and Bigby,
D. (2001). Systems used in Coal Mine Developments
in Long Tendon Reinforcement, 20th International
Conference on Ground Control in Mining. ICGCM,
http://icgcm.conferenceacademy.com/papers/detail.a
spx?subdomain=icgcm&iid=735
Craig, P. and Aziz, N. (2010a). Shear testing of
28 mm Hollow Strand “TG” Cable Bolt, inproceedings 10th Underground Coal operators
Conference, Wollongong, February 11/12, pp171-179(Ed.N Aziz and Jan Nemcik. 375 p),
http://ro.uow.edu.au/coal/303/
Craig, P. and Aziz, N. (2010b). Shear testing of
28 mm hollow strand "TG" cable bolt, In proceedings
29th International Conference on Ground Control in
Mining, ICGCM (pp. 169-174), (Publication
ID=35591),
http://icgcm.conferenceacademy.com/papers/detail.a
spx?subdomain=icgcm&iid=273
Goris, J.M., Martin, L.A.(1996). Shear
behaviour of cable bolt supports in Horizontal bedded
deposit. Laboratory pull tests of resin –grouted cablebolts, 15th International Conference on Ground
Control in Mining, Golden, Colorado, August 13-15,
pp.
511-521,http://icgcm.conferenceacademy.com/papers/paperlis
t.aspx?iid=407
Fuller PG, O’Grady P. (1993). FLEXIBOLT
flexible roof bolts: A new concept for strata control,
12th International Conference on Ground Control in
Mining, Morgantown, West Virginia, USA, pp. 2434,
http://icgcm.conferenceacademy.com/ebook/view.as
px?PaperID=1235
Hyett, A.J., Bawden, W.F. and Reichert, R.D.
(1992). The effect of rock mass confinement on thebond strength of fully grouted cable bolts, Int. J. Rockmechanics and Min. Sci. & Geomech. Abstr, 29(5),pp. 503-524
Hyett, A.J., Mossavi, M. and Bawden, W.F.
(1996). Load distribution along fully grouted bolts,
with emphasis on cable bolt reinforcement, Int. J. for
Numerical and Analytical Methods in Geomechanics,
20, pp 517-544
Thomas, R. (2012). The load transfer propertiesof post-groutable cable bolts used in the Australiancoal industry, 31st International Conference on
Ground Control in Mining, Morgantown, 10p,
http://icgcm.conferenceacademy.com/papers/detail.a
spx?subdomain=icgcm&iid=1011

441

ISMS 2016

Paper No. 101

Operating conditions of a mine fan under conditions of variable resistance
Zhang Yinghuaa, Chen Lia, b, Huang Zhiana, *, Gao YukunaaState Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing, 100083, Chinab
College of resources, Hebei University of Engineering, Handan, 056038, China

ABSTRACT
According to the basic fluid principles and ventilation laws combined with the ventilation network computing
method, this study proposes the concepts of relative sensitivity and absolute sensitivity, and studies these twosensitivities’ variation law under conditions of variable airway resistance. The result showed that when the
airway resistance increased, the fan air volume, relative sensitivity, absolute sensitivity and fan pressure’s
relative and absolute sensitivity tend to decrease. At the same time, fan pressure shows an increasing trend.
Conversely, when the airway resistance goes down, the above parameters follow the opposite trend. These
results provide a basis and guidance for adjusting the fan operation condition in the mine production process.
KEYWORDS: variable resistance, operating conditions, change rule, sensitivity
1.

INTRODUCTION

Mine Ventilation System is one of the basic
production systems that ensures the safety ofunderground work personnel life (Zhou et al., 2005).
In recent years, the mining strength, depth, and the
production level have all been increasing, whichleads to increasingly complex ventilation systems andexisting diagonal structures in the mine ventilation
system, which make the ventilation management
increasingly difficult. The actual production processneeds timely adjustment of volume, because theworking face to replace, wind resistance of roadways,
the network structure and the need to air volume areconstantly changing (Mi, 2009. Air conditioning is a
dynamic process, and the nonlinear changes not only
increase the difficulty of air volume adjustment forcomplex ventilation networks, but also have asignificant impact on production safety. Therefore,
mastering the complex network air regulation change
rules requires more and more attention. Zhou (1995)
put forward and illustrated the simple calculation
method of the adjustable resistance value, based on
the influence of the network. Zhao et al. (2003)
developed measures of increasing and decreasing theresistance to adjust the air volume on the individual
ventilation networks. Zhou et al. (2005) analyzed thesensitivity of the branch airflow to the wind
resistance and the natural wind pressure, in order tojudge the stability of ventilation networks. Jiao et al.
(2009) analyzed the partial ventilator regulating
ability and introduced the concept of air volume
adjustable tunnelling faces. Wu, (2011) used thesensitivity to quantify the selection criteria of the air
regulation point. Yan et al. (2011) studied the*Corresponding author – email: huang_za@qq.com

ventilation system air volume and wind resistancechanges between the superpositions. Hu et al. (2014)
explored the complexity of mine ventilation networkand fan control. There are few reports on air
regulation change law for complex ventilation
network. The present study examines the fan air
volume and air pressure change rules and regulationof sensitivity for the main branches of the complex
ventilation network system, in order to provide abasis and guidance for mine air regulation.

2.

MODEL OF THE VENTILATIONNETWORK SYSTEM
The set of the ventilation network nodes is

J = ( j1 , j2 ,, jm )where m is the number of nodes.
The set of the ventilation network branches is
E = (e1 , e2 ,, en ) ,where n is the number of branches.
The ventilation network can be expressed as

G = (V , E )A typical complex ventilation network that
included series, parallel, and angle type andcontaining eight nodes and twelve branches wasbuilt, as shown in Figure 1.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The wind resistance information of each branch
was as shown in Table 1. The basic information of
the fan was as shown in Table 2.

Figure 1: The ventilation network.

The wind resistance change of branch is definedas the variable resistance branch. When the variable
resistance branch of wind resistance changes the air
flow and pressure of the fan, this magnitude of the air
volume change is defined as the sensitivity of air
volume for variable resistance, called γ . The ratio of
the air flow (pressure) variation and the wind
resistance of variable resistance branch is defined as
the absolute sensitivity, called ψ . The formulas are
as follows:d (∆Q ) d Qij − Qi 0 （1）γq ==d (∆R ) d R j − R0

(
(

γq =

γf =

)
)

d (∆Q ) d (Qij − Qi 0 ) （2）=Rj
Rjd (∆H ) d (H ij − H i 0 ) (3)=d (∆R )d (R j − R0 )γf =d (∆H ) d (H ij − H i 0 ) （4）=Rj
Rj

Where: Qi is the fan branch air volume after
variable resistance of the j time measured in m3 / s ;H i is the fan branch of wind pressure after variable
resistance of the j time; Pa ; Qi 0 is the fan branch air
volume air volume after variable resistance of thej − 1 time measured in m3 / s ; H i 0 is the fan branch ofwind pressure after variable resistance of the j − 1time; Pa ; R j is the resistance value of the variable
resistance branch after the j time variable
resistance; R0 is the resistance value of the variable
resistance branch after the j − 1 time variable2

8

resistance measured in N .s / m .

Table 1: The value of the each branch wind resistance.
Branch number
Value of the wind resistance (N. s2/m8)
e1
0. 001e2
0. 026e3
0. 005e4
0. 065e5
0. 082e6
0. 099e7
0. 126e8
0. 048e90. 087e10
0. 032e11
0. 029e12
0. 134
Table 2: The basic information of the fan.
Fan model
FBCDZ-6-№20
Wind pressure( Pa)661-1917
Air volume (m3/s)
25. 9-65. 5
Motor model
YBF2-315S-8
Rated speed (r/min)
900
Rated power (kW)
2×55

3.

VENTILATION NETWORK SOLUTION

Network solution is one of the important ways toadjust and analyze the ventilation network. This istheoretically based on the three laws of ventilation,
which are the air volume balance law, the mesh airpressure balance law, and the law of resistance(Zhang, 2000).
(1) The balance law of air volume:
The mass flow of each branch that inflows andoutflows of a node algebraic addition is zero. The
formula is as follows:∑ M = 0 （5）i(2) The balance law of the mesh air pressure:
In a closed loop without a power source, theventilation resistance of the branches algebraic
addition is zero, while with a power source, theventilation resistance of the branches algebraic
addition is equal to fan air pressure of the loop. The
formula is as follows:∑ h = 0 or ∑ h = h （6）iif(3) The law of the resistance:
The resistance of the roadway is equal to the
product of the wind resistance and air flow square.
The formula is as follows:

h = RQ 2 （7）4433rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

By combining (5) to (7), the air volume wascalculated using the Scot-Hinsley algorithm. The
network solver is written using the VB. net platform.

4.

THE DISCUSSION AND ANALYSIS

e8 and e9 were selected as a branch of variable
resistance, which are parallel branches. e8 is theincreased resistance branch, while e9 is the reduced
resistance branch, resistance changed 20 times insuccession, and the network was calculated once theresistance changed. The computed results are asshown in Table 3.

Table 3: The computed results
Adjustment
times

Value of theincreased
resistance( N .s 2 / m8 ）

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

0.088
0.128
0.168
0.208
0.248
0.288
0.328
0.368
0.408
0.448
0.488
0.528
0.568
0.668
0.868
1.068
1.668
2.668
4.668
6.668

Pressure of thefan（ Pa ）The air
volume of thefan（ m3 / s ）Adjustment times

1183.079
1199.206
1210.512
1219.151
1226.125
1231.953
1236.946
1241.300
1245.152
1248.597
1251.708
1254.539
1257.133
1259.522
1264.768
1273.026
1279.335
1292.079
1304.128
1316.509

64.24264.01163.84963.72563.62463.54063.46863.40563.34963.29963.25463.21363.17563.14063.06462.94362.85162.66462.48762.304

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

4.1 The change rule of the fan air volume and airpressure
When the airway resistance changed, the fan air
volume and air pressure changed, as shown in
Figures 2 and 3. The figure shows that, when the
airway resistance increases, the fan pressure will
increase and the fan air volume will decrease; On thecontrary, when the airway resistance decreases, thoseparameters’ change follows the opposite trend. Thisis due to the changes of total wind resistance in theventilation network system caused by the airway
resistance.

Value of the
reducedresistance（ N .s 2 / m8
）
0.077
0.067
0.057
0.047
0.037
0.035
0.033
0.031
0.028
0.026
0.024
0.022
0.020
0.018
0.016
0.014
0.012
0.008
0.004
0.001

Pressure of
the fan（Pa ）1180.815
1178.297
1175.465
1172.222
1168.427
1167.583
1166.704
1165.787
1164.335
1163.310
1162.235
1161.1061159.915
1158.657
1157.324
1155.904
1154.387
1150.991
1146.940
1143.241Air
volume offan（m3 / s）64.27464.31064.35064.39664.45064.46264.47564.48864.50964.52364.53864.55464.57164.58964.60864.62864.65064.69864.75564.807

Figure 2: The changed curve of the fan air volume when
variable resistance.

Figure 3: The changed curve of the fan pressure when
variable resistance.

4.2 The sensitivity of the fan air volume and airpressure
The computed results were substituted into
formulas (1) to (4). The relative and absolute444

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016sensitivity of the fan air volume and air pressure werecomputed when varying the resistance, as shown in
Figures 4 to 7. The figures show that, when the
airway resistance increases, the relative and absolutesensitivity of the fan air volume and air pressure
showed a decreasing trend. The curve is initiallysteep before gradually slowing. When the airway
resistance goes down, the relative and absolutesensitivity of the fan air volume and air pressure
showed an increasing trend, with the relative
sensitivity stability increased gradually. The earlystage of the absolute sensitivity changes smoothly,
while the late stage increases suddenly. This suggeststhat the influence of the fan air volume and airpressure is obvious when the airway resistanceincreases in the early stage and the airway resistancegoes down in the later stage.

Figure 4: The sensitivity curve of the fan pressure whenincreased resistance.

Figure 6: The sensitivity curve of the fan air volume whenincreased resistance.

Figure 7: The sensitivity curve of the fan air volume whenreduced resistance.

5.

Figure 5: The sensitivity curve of the fan pressure whenreduced resistance.

CONCLUSIONS

The following conclusions can be drawn:
First, when the airway resistance increases, thefan air volume, its relative and absolute sensitivity,and fan pressure’s relative and absolute sensitivity,
tend to decrease. At the same time, fan pressure
showed an increasing trend. Conversely, when the
airway resistance goes down, the above parameterschange in the opposite direction.
Second, the influences of the fan air volume andair pressure is obvious when the airway resistanceincreases early on, and then gradually weakens.
Conversely, when the airway resistance goes down,
the influence of the fan air volume and air pressure
follow the opposite trend. These results provide abasis and guidance for adjusting the fan air volume inmines.
Finally, when increasing the resistance, even theappearance of the fan air pressure being too highshould be avoided, as it could cause unstable runningof the fan, and ultimately impact safe production.

445

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

6.

ACKNOWLEDGEMENT

It is with great pleasure that we acknowledge thegenerous financial support of National Natural
Science Foundation of China (project number:
51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).
7.

REFERENCES

Hu, H. H., Yang, G. Z. (2014). Quantified
calculation on complexity of mine ventilation
network and control force from main ventilator.
Journal of Safety Science and Technology,
Volume10, No. 7, pp. 152-157
Jiao, Y., Zhou, X. Q., Gong, W. (2009).
Network analysis of air volume adjustment in minetunnelling faces during the period of the normal
production. Mining Safety & Environmental
Protection, Volume 36, No. 6, pp. 76-78
Mi, X. K. (2009). Mine local air volume andtotal air volume adjustment. Coal Technology,
Volume 28, No. 5, pp. 107-108
Wu, F. L. (2011). Using sensitivity to optimize
mine air regulation point and parameter. Mining
Safety & Environmental Protection, Volume38, No. 5,
pp. 1-3
Yan, Z. G., Fan, J. D. , Wang, H. (2011).
Superposition features of air flow＇s changes in amine ventilation system. Science & Technology
Review，Volume29, No. 34, pp. 37-40
Zhang, G. S. (2000). Ventilation Safety. China
University of Mining and Technology Press, 85-92p
Zhao, D., Liu, W. H., Yao, L. Z. (2003).
Calculation and Regulation of the Local Air Volume
in Mine. COAL, Volume 12, No. 3, pp. 35-36
Zhou, J., Liu, J. and Jia, J. Z. (2005). Analysis
sensitivity of mine ventilation system. Journal of
Liaoning Technical University, Volume 24, No. 4, pp.
1-3Zhou, L. H. (1995). Calculation and analysis of
the air condition in mine ventilation network. J.
XIANGTAN MIN. INST, Volume10, No. 4, pp. 1418

446

ISMS 2016

Paper No. 132

Analysis of slag debris flow initiation based on laboratory tests of slag
Hongbiao Zeng, Hongming Yu
Department of Engineering, China University of Geosciences, Wuhan, China, 476400

ABSTRACT
Accumulated slags and waste in mines are major physical resources for slag debris flow, which are potentially majordisasters that threaten mine safety. Initiated by heavy rain, slag debris flow has happened in Ganjiang gully around
Luanchuan county, China. Studies have been carried out to further understand the formation and initiation
mechanism of slag debris flows. Slag samples with different fines content were collected from the gully and the slag
strength and permeability were investigated by direct shear tests and by falling head permeability tests, respectively.
The results indicate that the fines content has a significant impact on both the strength and permeability
characteristics of slags. With the fines content increasing, both the strength and the hydraulic conductivity of theslag decrease. The strength of saturated slag samples is extremely weak, meaning that water will easily soften theslag. In addition, as the fines content increases, the hydraulic conductivity would decreases at an accelerated rate,
down to a very small constant. Based on the current investigation, it can be concluded that two different types ofslag debris flow would form in the specific conditions: shallow debris flows are mainly dominated by surface
erosion, while deep debris flows are dominated by bottom tearing and suffusion erosion.
KEYWORDS: slag, debris flow, initiation, strength, hydraulic conductivity

1.

INTRODUCTION

Mine debris flow is different from the naturaldebris flow, also referred to as slag debris flow,which mainly occurrs in the fragile ecologicalenvironment of mountainous and hilly areas. With
the development of the mining industry, mine debris
flow is quickly becoming one of the major reasons
restricting mining and production safety. According
to Xu (2007), as of the end of 2005, mine debris
flows have occurred 247 times in the northwest
region of China, killing 426 people and causing direct
economic losses of $384 million. There is muchresearch on general debris flow; however, research
related to slag debris flow is currently lacking due tothe particularity of the material resource and dynamic
conditions.
Debris flow occurs in all regions with steep relief
and at least occasional rainfall, and tends to occur on
slopes that are geologically young, steep, andnaturally only marginally stable, (Jakob, 2005;
Anderson, 1995). The initiation of the debris flow isrelated to three issues of resources, water (rainfall),and underlying conditions. Cannon et al. (2008)
specify the significant role of rainfall in the initiationof debris flow by using a rain guage and response
data. Stoffel et al. (2011) studied the formation
mechanism of debris flow in the Alps of Switzerland.
Chen and Cui (2006) have carried out research on theformation process of debris flow through artificial
rainfall experiments. Jakob et al. (2012) studied theformation mechanism of debris flow induced by*Corresponding author – email : 806686130@qq.com

rainstorms. Mergili (2012) developed a GIS model tosimulate the initiation and movement of debris flows.
The related research on mine debris flow ismainly on the qualitative analysis of provenancecharacteristics, formation conditions, classification,and initiation mechanisms. Fang (2007) summarized
the material sources of mine debris flow, andconsidered hydrodynamic conditions to be theexternal factor that triggers the initiation. Waste anddump induced debris flows were classified into 5
types according to their formation mechanism: dump
outburst, bottom tearing, side eclipse, surface erosion,and other complex types (Ni, 2011). Deng (2009)
analyzed the development characteristics and theinitiation conditions of slag debris flow for one gully
in a gold mining area. Cao (2008) classified slag
debris flow into two types, slope flow and trench
flow, and studied their initiation mechanisms.
Other studies have focused on the penetration
characteristics of slag, and tried to analyze andpredict the mechanisms of mine debris flow throughthe use of quantitative methods. However, the impact
of slag strength and permeability characteristics on
the initiation of slag debris flow is still poorly
understood. This paper consists of two main parts.
First, the shearing strength and permeability of theslag with different fines content taken from Ganjiang
Gully, in Luanchuan county, are studied using
laboratory tests. Second, based on the test results ofthe shearing strength and permeability characteristicsof the slag as well as some previous initiation models

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2.

LABORATORY TESTSTest samples were taken from the slag heaps inGanjiang Gully, Luanchuan County, with thesample’s dry density (ρd) being 1.90 g•cm-3, specificgravity (Cs) being 2.86, and field moisture (W) being
3.2%. Three remoulded samples were prepared for
direct shear tests and variable head permeability tests.
The grading curves of the slag samples were asshown in Figure 1.
100
Original
Fines content of 18%
Fines content of 30%
Fines content of 40%

Percent Finer by Weight (%)

90
80
70
60

2.1.1 Shear Stress vs. displacement
The remoulded samples with fines content of
18% were chosen for explaining the variation ofshear displacement as the shear stress increased under
different saturations of 21%, 75%, and 100%.
110
100

400kPa90

Shear Stress/kPaof general debris flow, the initiation of slag debris
flow is analyzed.

80
70

300kPa60
50

200kPa40
30

100kPa

10
0
0

50

21%
75%
100%

20

1

2

3

4

5

6

Shear Displacement/mm

40

Figure 3: Shear stress vs. horizontal displacement under
different saturation (21%/75%/100%).

30
20
10
0
10

1

0.1

0.01

0.001

Grain Size (mm)Figure 1: Grading curves of original and remoulded
samples.

2.1 Direct shear test

Figure 2: The direct shear apparatus.

Direct shear tests were carried out to obtain thestrength parameters of the slag samples. The three
remoulded samples have different fines content of
18%, 30%, and 40%, with two different saturation ofnatural water contents: 50% and full saturation. The
test was conducted in the strain controlled direct
shear apparatus (Figure 2). The quick shearing test
was applied at a rate of 0.8 mm/min, with thesamples destructed in 3-5 minutes.

As Figure 3 shows, the slag samples of 21% and
75% saturation were mostly destructed with the peakhorizontal displacement between 3-5 mm, which
proved to be strain softening. When the shear stressreached a peak, shear failure occurred, and theshearing strength continued to decrease, with theshear displacement going down to a certain value ofresidual strength. While under full saturation (100%),
there were no significant peaks at different verticalpressure, which shows the characteristics of creep
deformation and strain hardening.
In the shearing process, the particles rearrange
on the shear plane with the effort of vertical stress,
and the shear dilatancy occurs when the pore pressurebuilds up in the undrained condition. Fully saturated
slag samples with high water content may have acertain plasticity flow, with fluctuating curves ofstress-displacement. In addition, it can be seen thatthe corresponding peaks of the curve declined withincreases in slag saturation level, and the shear stressof the saturated slag declined more sharply than theslag of 21% and 75% saturation, demonstrating thatthe slag strength is weaker in saturated states.
Rainfall results in slags reaching a saturated state,
which may accelerate the initiation of slag debris
flow due to the deterioration of stability.
2.1.2 Slag Strength vs. Fines Content
Shear tests for three samples with different fines
content of 18%, 30%, and 40% were conducted toinvestigate the relationship between slag fines
content and the shear strength, as shown in Figure 4.

448

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

13.0
12.5
12.0
11.5
11.0

Friction angle/°

13.5

10.5
10.0
40

30

18

Fines Content /%Figure 4: Relationship between fines content and φ.

Since the clay content of slag is very low, andthe cohesion measured from the test by Xie (2013) isclose to zero, in this study the tested slag wasconsidered sandy soil, without considering thecohesion. The Mohr-Coulomb theory was employed
to determine the shear strength of slag, using thefollowing equation (1):=
τ tan ϕ(1)
Where
φ is the internal friction angle;
τ is the shear strength.
In this study, friction angle (φ) is used to express
the strength of slag samples. As Figure 6 shows, it
can be seen that slag strength decreases withincreases in fines content, with the three different
slag samples all showing the same phenomenon.
Strength of the slag samples with 40% fines content
was 8.6%-15.6% lower than that of slag samples with
18% fines content. The fines content has a significant
influence on the microstructure of the slag, and theincreased fines content leads to weakening of theinteractions between the coarse particles, causing a
reduction of its shearing strength. In addition, it
shows an obvious decrease when the saturation ofslag with the certain fines content increases, and theinflection points of the curve are more apparent for
the 50% and natural saturation levels. While the slag
sample is in a saturated state, the friction angle
declines to a minimum, since the water in the slag
samples destroys the cementation of the particles ofslag.
The results indicate that the particle gradation
characteristics of slag have a limited effect on slag
strength, while the saturation level shows a more
important influence on shearing strength of slag.
2.2 Variable head permeability test
The South 55-type variable head permeameter
was carried out to obtain the slag permeability
characteristics, using three different fines content(18%, 30%, 40%) slag samples. In order to measure
the saturated hydraulic conductivity, the cutting ring
samples for testing are prepared and controlled atnatural saturation levels.
In order to determine the saturated hydraulicconductivity, the slag in natural states are prepared tofor testing using the vacuum saturation method. The
following equation (Darcy Law) was used (2):K = QL / Aht
(2)
Where
A=0.23758 cm2；
L=4cm, represents Penetration Path；
Q, h and t are obtained from the test records.
The test results are listed in Table 1, and graphedin Figure 5.
Table 1: Results of variable head permeability test.
Fines Content
18%
30%
40%
Hydraulic
Conductivity/cm·s-1
Hydraulic Conductivity k /(cm·s-1)

14.0
21%(Nature)
50%
Saturated

1.80

1.68E-04

7.22E-05

4.67E-05

× 10-4

1.60

Data points

1.40—— Fitting curve

1.20
1.00

y = 172.8x -1.60
R² = 0.999

0.80
0.60
0.40
0.20
0.00
10

20

30

40

50

60

Fines Content /%Figure 5: Fitting curve between fines content and hydraulicconductivity.

As shown in Table 1 and Figure 5, there is anapparent gap between the hydraulic conductivity ofslag samples with different fines contents of 18%,
30%, and 40%. The gap between the slag samples of
18% and 30% fines content is much larger than thatbetween the slag samples of 30% and 40% fines
content. The fitting curve between fines content andhydraulic conductivity, according to the distributionof data points, is expressed as the following equation(3) with a correlation coefficient (R) of 0.999:

y = 172.8x−1.60(3)
In which, y=K×104, x=C×102, where K and C
represent the hydraulic conductivity and fines
content, respectively. Equation (3) can then bechanged to the following equation (4):=K 1.0903E− 05C−1.60(4)With increases in the fines content of slag
samples, the hydraulic conductivity decreases, and449

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the trend of decline is such that the difference gap of
the hydraulic conductivity between the slag of 40%
fines content and one of 30% fines content is larger
than the gap between the slag of 18% fines content
and the one of 30%.
Meanwhile, from the trend of the fitting curve,
when the fines content of slag reaches a certain value,
the decline of hydraulic conductivity gradually
becomes weaker, and reaches an almost stable statewith values of more than 40%. Kong (2011) and
Wang (2012) have found similar sequences bystudying the variation of hydraulic conductivity ofsand. It can then be noted that the greater thehydraulic conductivity, the stronger the infiltration
ability, therefore, the slag will more easily reach asaturated state under certain rainfall conditions.

3. ANALYSIS OF SLAG DEBRIS FLOWINITIATION
3.1 Initiation Models of General Debris Flow
As Liu (2002) summarized in his overview offoreign debris flow mechanism models, the primaryclassical debris flow initiation mechanism models
that have been widely accepted include: Coulomb’s
particle flow model containing pore water pressure,
the Johnson model (1970), the Takahashi model(1978), the general viscous plastic flow model put
forward by Chen (1986), O’Brien’s dilated plastic
flow model (1993), and the mixed flow theory of
momentum conservation equation applied forcomplicated debris flows as proposed by Verson(1997).
In addition, many researchers have developed
diverse initiation mechanisms for debris flow withdifferent types of solid content and formation,
including:
1. Takahashi model
Takahashi (1991) proposed that the wash anderosion of the sediments in gully beds by water flow,
resulting from rainfall or underground water, is the
key factor causing the initiation of hydraulic debris
flow. After rainfall, runoff with a depth of h develops
and forms on the underground surface or on s brookwith an inclination angle θ. The shearing force
produced from water flow acting on deposits is τ, andthe shearing resistance of deposits is τL. According to
the relationship between τ and τL, the initiation ofdebris flow can be discussed. If the effect of flow
velocity on the deposits with a certain depth isignored, the total shearing force acting on thedeposits can be calculated using the following
equation (5):

τ = g sin θ [C∗ (ρ m − ρ )a + ρ (a + h0 )]

Where

(5)

C* is the volume concentration of deposits.
a is the layer thickness of deposits which ispossibly sheared and move, m.
ρm is the soil density of debris, g/cm3.
ρ is for the density of water (containing a small
suspended solids, ρ = 1), g/cm3.
g is the acceleration due to gravity, m/s2.
h0 is for the depth of surface flow, m.
The totally shearing force is made up of twoparts, the solid material in the flow and the water, as
shown in the equation.
The shear resistance τL of the deposits can becalculated using the following equation (6):

τ L = g cosθ C∗ (ρ m − ρ )a +

ρmd 
tan ϕ (6)cosθ 

When τ > τL, it is believed that debris flow islikely to form and develop.
2. Sediment movement model
Xie et al. (1993) established the mechanicalmodel for the initiation of deposits loosely piled up in
gully beds, based on sediment movement theory. It isbelieved that loose deposits in gully beds is critical indebris flow initiation, and deposits containing a lot ofwater show the characteristics of saturated slurry.
This is especially true for the deposits contractedwith the bottom of the gully bed. For hydraulicallydriven debris flow, the flow initiation theory can be
regarded as the sediment movement theory for bed
material flow initiation.
3. Hydrodynamic model
Tang et al. (2001) proposed a mechanical modelfor the initiation of deposits piled up in gully beds
based on hydrodynamic theory. This type of debris
flow initiation model mainly considers that the debris
flow is initiated by the fluid’s drag force on thedeposits. Therefore, it is called the drag-imitation
model. The drag force is determined according tohydrodynamic theory, and it is a key factor
influencing the initiation of deposits.

3.2 Analysis of slag debris flow initiation
Based on the findings above, the strength of slag
samples is greatly influenced by slag saturation state,
and is quite weak in a saturated state. Slag strength
has shown little sensitivity to grain-size distribution
characteristics. However, the hydraulic conductivity
makes a significant difference because of thedifferent fines content of slag. Therefore, slag debris
flow initiation can be analyzed according to thestrength and permeability characteristics of slag.
As Cui et al. (2003) studied, there is a direct
relationship between soil saturation and rainfall, andwith some initial rainfall, a slag pile reaches a certain
saturation state. In addition, antecedent moisture
content directly governs the hydraulic conductivity of450

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

partially saturated soils and also influences thestrength characteristics of the slag. Generally, withongoing rainfall, slag strength declines constantly. In
contrast, its weight would be increasing, causing thestability of the slag pile to become worse, andeventually causing damage.
Secondly, judging from the experimental data,slag strength is lowest when its hydraulicconductivity has the minimum fines content of 40%,for conditions where the stability of the slag pile isworst. It should be noted that a value of 40% for fines
content is already great, according to the analysis of
the particle composition of slag material collectedfrom different location.
Hereafter, if the fines content of slag, which isconsidered a quantitative evaluation factor, is high,the slag strength would be weak, while permeability
and infiltration capacity would be also weak with alower saturated velocity, that is, with a decreased
velocity of slag strength. Generally in this case, suchslag pile induced debris flow is initiated slowly, andwith conditions of continuous rainfall, both surface
flow and pore water pressure of the slag pile also
increase constantly, and shallow debris flows mainly
dominated by surface erosion may form easily. On
the other hand, the lower the fines content of slag, thestronger the slag strength, and the slag pile would be
more susceptible to damage in the same topographic
and rainfall conditions. While, there is a large
hydraulic conductivity among the slag pile andrainfall can quickly penetrate into the bottom of slag
pile through the void in particles, due to the higher
saturated velocity and the higher decreased velocity
of slag strength, such slag piles induced debris flow
generally initiates quickly. With ongoing rainfall,deep debris flows mainly dominated by bottom
tearing and suffusion erosion may easily form, which
would carry a larger amount of provenance and be
more dangerous than shallow debris flows.
3.3 A Field Case of Slag Debris FlowOn July 22 to 24, 2010, impacted by the typhoon"chan had", heavy rain occurred around Luanchuancounty in China, inducing a centralized outbreak ofdebris flow because of the torrential rains. The
affected slag pile had been accumulating in Ganjiang
gully, and had a lack of protection. The debris flow
initiation induced by the slag pile was analyzed
according to the strength and permeability
characteristics controlled by the particle compositionof the slag.
First, the fines content of slag pile in Ganjiang
gully was between 20% and 30%, and the slag
strength was relatively high. Correspondingly, due tothe large hydraulic conductivity, the slag pile was ina saturated state within a short time during the heavy

rainfall that occurred, and the slag strength decreased
quickly. Therefore, as the heavy rain continued,
runoff occurred and the hydrodynamic conditions
were prepared for the initiation of debris flow.
Finally, on July 24, 2010, the slag pile in the sourcearea of Ganjiang gully experienced outburst, forming
deep debris flows mainly dominated by bottom
tearing and suffusion erosion. This was accompaniedby shallow debris flows in the other partial area. The
following picture is the slag left behind after thedebris flow burst in Ganjiang gully, as shown in
Figure 6.

Figure 6: Slag left behind after the debris flow burst.

In conclusion, when the slag debris flow in
Ganjiang gully was evaluated, the main factors
affecting the initiation of slag-induced debris flow
were the fines content and permeability characteristicof slag, because particle size distribution is moresensitive to permeability characteristics than to slag
strength.

4. CONCLUSIONS
Based on the current study’s analysis of the slag
debris flow in Ganjiang gully in Luanchuan county,
the following main conclusions are obtained:
1) The fines content of slag is a significant factor
not only for the slag’s strength but also its
permeability characteristics. With fines content
increasing, both the strength and the hydraulicconductivity of the slag decrease. If the value of thefines content of the slag exceeds 40%, the hydraulicconductivity decreases constantly, with theacceleration of decline becoming more gradual, down
to an almost stable state.
2) Considering the change in slag strength andpermeability characteristics in conditions ofcontinuous rainfall, two different types of debris flow
can be induced: shallow debris flows, which aremainly dominated by surface erosion, and deep
debris flows, which are mainly dominated by bottom

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tearing and suffusion erosion. Fines content and thepermeability coefficient are the main factors that
affected slag debris flow in Ganjiang gully.

5.

ACKNOWLEDGMENTS

The work is supported by the research grant from
National Natural Science Foundation of China(Project Number: 41272377), Henan Scientific andTechnological Research Projects (Project Number:
122102310477).

6.

REFERENCES

Cannon, SH, Gartner, JE and Wilson, RC (2008).
Storm rainfall conditions for floods and debris flows
from recently burned areas in south western Colorado
and southern California. Geomorphology. DOI:
10.1016/j. geomorph.2007.03.019.
Cao Y.B (2008). Experiment of Initiation
Mechanism of Mine Debris Flow [D]. Chang’an
University.
Chen X Q, Cui P, Feng Z L, et al. (2006).
Artificial Rainfall Experimental Study on Landslide
Translation to Debris Flow. Chinese Journal of RockMechanics and Engineering. Volume 25, No. 1, pp.
106-117
Cui P, Yang K, Chen J (2003). Relationshipbetween occurrence of debris flow and antecedent
precipitation: taking the Jiangjia gully as an example.
Science of Soil and Water Conservation. Volume 1,
No 01, pp. 11 -15
Deng L.S, Fan W, Xiong W, et al. (2009).
Development features and risk of inducing slag
debris flow at daxicha gully. Journal of Engineering
Geology, Volume 17, No. 3, pp.415-420
Fang Q.J, Ren J.Q, Guo S.K (2007). Summary offormation conditions of mine debris flow.
Geotechnical Engineering World. Volume 11, No. 5,
pp. 66-67
Jakob M. and Hungr O. (2005). Debris–flow
Hazards and Related Phenomena. CA: Berlin
Heidelberg
Jakob M, Owen T and Simpson T (2012). A
regional real-time debris-flow warning system for theDistrict of North Vancouver, Canada. Landslides.
DOI: 10.1007/s10346-011-0282-8
Kong L.W, Li X.M and Tian H.N (2011). Effectof fine particles content on permeability coefficientof sand and its correlation with state parameters.
Rock and Soil Mechanics, Volume 32, No. S2, pp.
21-27
Liu X.L (2001). An Overview of Foreign Debris
Flow Mechanism Models.Journal of Catastrophology.
Volume 17, No. 4, pp. 1-7
Mergili M ， Fellin W ， Moreiras S ， et al.
(2012). Simulation of debris flows in the Central

Andes based on Open Source GIS：possibilities，
limitations ， and parameter sensitivity. Natural
Hazards. DOI: 10.1007/s11069-011-9965-7
Ni H.Y, Tie Y.B, Cui, P (2011). Classificationand disaster prevention systerm of debris flows
induced by wsate dumpes. Resources Industries.
Volume 13, No. 3, pp. 107-113
Anderson, Scott A and Nicholas, Sitar(1995).
Analysis of Rainfall-induced Debris flows. Journal of
Geotechnical Engineering. DOI:10.1061/(ASCE)
0733-9410(1995)121:7(544)
Stoffel M, Bollschweiler M and Beniston M.
(2011). Rainfall characteristics for periglacial debris
flows in the Swiss Alps：past incidences-potential
future evolutions. Climatic Change. DOI: 10.1007/
s10584-011-0036-6
Takahashi T (1991). Debris flow. Balkema,
Rotterdam, International Association for HydraulicResearch.
Tang H.M, Weng Q.N, Wang K, et al. (2001).
Research on substances start up types andmechanisms of debris flows in impact-deposit debris
flow valleys. Journal of Chongqing Jiaotong
University. Volume 20, No. 2, pp. 65-69
Wang Z.K, Zhang M, Zheng Q.L (2012). Impact
on permeability coefficient for fines content of coarse
sand. Heilongjiang Science and Technology of Water
Conservancy. Volume 40, No. 10, pp. 63-64
Xie K, Yu H.M, Peng Z.W, et al. (2013). Large
scale direct shear test of debris flow source soilin
Luanchuan of Henan. Journal of Mountain Science.
Volume 31, No. 6, pp.738-744
Xie M.S, Wang Y.J, Zhang H.J, et al. (1993).
The Deposite Analysis of Water Dynamic Conditions
to Form Debris Flow and to Set up Mathematical
Model in Debris Flow Valley. Journal of Beijing
Forestry University. Volume 15, No. 4, pp. 1-11
Xu Y N, He F and Chen H Q. (2007). Mine
Debris Flow and Its Distribution in Northwestern
China. Joural of Mountain Science. Volume 25, No.
6, pp. 729-736

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ISMS 2016

Paper No. 203

Hydrogeological challenges and strategies at McArthur River Operation
Xiaoyou Yuna,*, Baoyao Tanga, Greg Murdockb, Brian McGilla, Brian Mattieaab

McArthur River Operation, Cameco Corporation, Saskatoon, Canada, S7M 1J3
Rabbit Lake Operation, Cameco Corporation, Saskatoon, Canada, S7M 1J3

ABSTRACTHigh pressure, radon-bearing water has been identified as one of the most critical challenges in mining the highgrade uranium deposit at the McArthur River Operation, Cameco Corporation. The ore deposits are located between
490 m and 640 m below the surface and surrounded by water bearing Athabasca sandstone, a graphitic fault zone,
and highly altered ground. This paper introduces the inflow risk management program at McArthur River Operation
which includes various hydrogeological challenges and the corresponding strategies applied, such as risk based
probe and grout programs (geological, hydrogeological, and geotechnical), ground freezing programs, andcomprehensive ground control programs. These programs have being developed, tested, and proven successful overyears of mining practices. Working with this world-class deposit of high risk and low tolerance, the authors believethat these experiences might be beneficial to other mining operations with similar hydrogeological characteristics.
KEYWORDS: Inflow risk management; Geotechnical and development probe and grout programs; Groundfreezing; Ground control

1. INTRODUCTION
The McArthur River Operation is anunderground mine located in the eastern part of the
Athabasca Basin of northern Saskatchewan,
approximately 620 km north of Saskatoon, Canada.
As the world’s largest high-grade uranium mine,it has proven and probable reserves of 336.5 million
pounds U3O8 (Cameco's share – 234.9 million
pounds) with an average ore grade of 10.94 % U3O8
at December 31, 2015. Cameco is the operator of themine with 69.805% ownership in partnership with
AREVA Resources Canada Inc. who owns theremaining 30.195%. Multiple mining methods havebeen developed and approved and are being
employed at McArthur River: the first one is a unique
non-entry Raisebore mining method; the second one
is Boxhole mining; and the third is drill and blast
stope mining, which has the potential to be one of the
major mining methods in the future at McArthur
River. The ore is grinded into slurry at underground,and then pumped to surface where it is loaded into
special containers and shipped to Key Lake formilling. In 2015, the total ore production at McArthur
River was 19,782,596 lbs (8,973,235 kg) of U3O8.
As an underground high-grade uranium mining
operation, the protection of workers and theenvironment during the mining activities have been
the top priorities in all phases of the design,development, and operation of the mine. The mining
activity at this operation faces three major challenges:*Corresponding author – email: Xiaoyou_Yun@Cameco.com•

Hydrogeological: the ore is located in proximity
to water enriched sandstone with highhydrostatic water pressures.
• Geotechnical: mine openings have to be
developed in highly variable ground conditions
ranging from excellent rock to wholly
unconsolidated clays and gravels.
• Radiation protection: workers have to beprotected from radon bearing water andmineralization with high-grade uranium.
This paper intends to introduce thehydrogeological challenges at this Operation, andpresent the corresponding strategies that have beensuccessfully employed by the site to permit safe mine
operations.

2. MINE
GEOLOGY
MECHANISMSAND

INFLOW

The McArthur River uranium deposit is locatedin the southeastern portion of the Athabasca Basin,
within the southwest part of the Churchill structuralprovince of the Canadian Shield. The crystalline
basement rocks underlying the deposit are membersof the Aphebian Wollaston Domain metasedimentary sequence. These rocks are overlain byflat lying sandstones and conglomerates of the
Helikian Athabasca Group. These sediments are over
500 m thick in the deposit area.
High-grade uranium mineralization has beendelineated from surface drilling over a strike lengthof 1,700 m, occurring at or close to the unconformity,

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

which separates the overlying, horizontally bedded
sandstones of the Athabasca Group from themetamorphosed basement rocks, located between 500
m and 640 m below the surface. Underground
exploration drilling programs have covered
approximately 750 m of the 1,900 m strike lengthdelineated from surface. Ore body widths are variable
along strike but the most consistent, high grade
mineralization occurs proximal to the main graphitic
thrust fault around the “nose” of the up thrust
basement rock. Less consistent and generally lower
grade mineralization occurs down dip along this fault
contact between basement rock and sandstone.
Locally the basement rocks include pelitic gneisses
and significant quartzite units. Alteration ischaracterized by intense silicification of thesandstone with less intense clay alteration comparedwith other Athabasca deposits. The mineralization at
McArthur River is associated with a northeast
trending, southeast dipping zone of reverse faulting,along which the unconformity is displaced vertically
60 m to 80 m, as shown in Figure 1.
Hydrogeologically, the brittle, flat lying
sandstone has been highly fractured by the tectonic
forces of the thrust fault and these fractures are water
bearing. Drawdown testing has demonstrated that thefracture patterns, along with water bearing joints andbedding planes are directly connected to the surface
groundwater table. This indicates an unlimited
volume of high-pressure water is sourced within thesandstone, and significant flows could be produced if
the water is intersected by the mine development.

There are two major channels by which the water
could enter the underground openings:• Boreholes - grouted or ungrouted,• Geological formation - directly or indirectly
Underground probe/exploration holes are drilled
into all planned mining areas to collecthydrogeological and structural information prior tomining through it. These drill holes could intersectintervals, generally structural related, which contain asubstantial amount of high-pressure water. Any lossof control might result in these holes being conduits
for a significant inflow of water into the mine. To
minimize this risk, rigorous collar security standards
have been developed for all underground drilling.
There is a potential risk for encountering
ungrouted or poorly grouted surface holes during
underground excavation. Therefore additional
precautions need to be taken in the vicinity of asurface hole during design and development phases.
Any underground development within 8 m of asurface borehole is treated as high risk as per ENG01-09.
Water inflows into the mine could also occur if awater bearing geological structure was encounteredduring development or if the mine development
inadvertently breached the unconformity. In 2003, abreach of the unconformity in Bay 12 during
development resulted in a peak inflow of 1,069 m3/hr,
and then stabilized at 700 m3/hr.
In order to prevent high pressure and radonbearing water from entering the mine, several
different tactics have been developed and applied at
the McArthur River Operation:• Artificial ground freezing to form a frozen curtain
between the water bearing sandstone and the ore
body.
• Probe and grout drilling to evaluatehydrogeological and structural conditions prior todrift development and to reduce the water
conductivity of the surrounding rocks withpressure grouting, if no freeze wall protection
exists.
• Strategically locate the underground excavations
away from known water sources wheneverpossible.

3. GROUND FREEZING

Figure 1: Typical Zone 4 geological section.

Artificial ground freezing is an excavation
support method that involves the use of refrigeration
to convert in-situ pore water into ice. Over the last
several decades, many mining operations havesuccessfully utilized artificial ground freezing fordeep excavation support while shaft sinking.
McArthur River successfully maintains a very largescale ground freezing infrastructure. The resulting454

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

freeze walls act as barriers between the undergroundmine workings and the water bearing formations.
Freeze methods used consist of the following
three categories:
3.1 Freeze Wall Isolation
Freeze wall isolation consists of creating one ormore freeze walls to isolate an area from water
bearing ground. In order to be effective, the freeze
walls must be tied together and completely enclosed
or anchored into non-water bearing and nonpermeable ground. The lower portions of Zones 2
and 4 were isolated from the ground water bycreating three freeze walls (north, west and south)and by using the geometry of the thrust fault to takeadvantage of the non-water bearing basement rock toseal the top, east and bottom of the zone (Refer toFigure 2). More recently, freeze wall protection for
the upper portions of Zone 2 and Zone 4 haveincluded a frozen cap, as shown in Figure 3. The
freeze hole drilling for Zone 1 is currently in progress
and is based on this design.

Figure 3: Typical freeze wall insulation situation with top
freeze cap as well.

3.2 Mass Freezing
Mass freezing consists of freezing an entire area
to isolate it from water bearing ground. To date,mass freezing has been used at McArthur River only
for the Boxhole mining test at Zone 4 North. Thismight be considered as an option for the upper
portions of Zone 2 and 4 mining area due to thepresence of a massive clay zone right above the highgrade ore (Refer to Figure 4).

Figure 2: Typical freeze wall insulation situation with threefreeze walls.

Figure 4: Massive freeze insulation.

3.3 Freeze Shield Protection455

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Freeze shield protection consists of creating
freeze walls that are not completely enclosed incertain situations where potential water sources arestrongly dominated from one direction. They do notprovide full protection from water, but do help
mitigate the risks associated with developing nearwater bearing ground. Freeze shields have been used
for some 530 level development in the Zone 4Central Lower mining area. (Refer to Figure 5).
Freeze holes spacing is determined by various
factors such as geothermal properties, drilling
accuracy, schedule requirements, and cost. Holespacing has varied slightly, but is typically in therange of 2.5 to 4 m.
3.4 Freeze Drilling
A freeze hole drilling program is carried out
according to an approved engineering design. Eachhole typically begins with a 9 m long grouted
standpipe, which is pressure tested to ensure that it issecure and that there is no leakage to the mineworkings. The hole is drilled to depth and the outerfreeze rods are grouted to the rock. A second set offreeze steel is grouted inside of the outer steel. A
deviation survey is performed on the hole and thedata is entered into the drill hole database. The
location of the hole is compared to the adjacentfreeze holes to ensure that the final spacing is within
the design criteria. Infill holes are occasionallyrequired to fill gaps. At regularly spaced intervals
adjacent to a freeze wall, temperature monitoring
holes are drilled. Thermocouplers are inserted andgrouted at 5 to 10 m spaced intervals within each ofthese holes and the resulting temperature data isrecorded into a central database. This information isused to monitor the temperatures and to provide datafor 3D modelling of the freeze wall as it forms.

Figure 5: Freeze shield insulation situation.

3.5 Ground Freeze Commissioning
After the freeze holes are drilled off, the brine
distribution system is installed and the brine iscirculating, the freeze wall is left to develop for
approximately six months. The freeze wall is
considered to be in place when temperatures from themonitoring holes and results from the blockmodelling indicate that ground conditions meet theminimum criteria of -3°C or lower and a freeze
structure thickness of at least 4 m. Within theconfines of the freeze wall, the ground will contain
unfrozen water that remains at full hydrostaticpressure. A series of strategically placed diamond
drill holes, with full collar security, will target theunfrozen rock within the freeze wall. These holes
will dewater and depressurize the area before any
mine development or other production activities arecarried out within the freeze structure. Water flows
and pressures will be regularly measured to confirm
that the isolated ground is not recharging fromoutside the freeze wall. The results will be subjected
to a review and approval process before the freeze
wall is officially commissioned.
3.6 Ground Freezing Maintenance
After a freeze structure is established sufficiently
for mining operations to proceed, the wall willcontinue to grow. Ground temperatures are monitored
throughout the life of the freeze structure. This helps
the operation to monitor the freeze wall status, makedecisions on brine circulation rates, verify or refine
future freeze design criteria and assists in establishing
the baseline for the overall freeze loading capacity
requirements.
If temperature readings indicate

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unusual or unknown changes, an investigation will be
conducted to diagnose and resolve the problem in atimely manner.

4. PROBE AND GROUT PROGRAMS
All mine development will be assessed andassigned a risk level: low risk, medium risk, or highrisk based on the available hydrogeological,
geotechnical, and radiological information. Once therisk level for the proposed development area isassigned, a probe and grout design will be createdbased on the standards that have been established foreach risk level. The probe and grout coverage will
extend 10 m beyond the designed development end
and at least 5 m on either side of the proposeddevelopment. An extra probe hole might be required
to confirm the location of the unconformity. In thecase of water concerns encountered during normalprobe drilling for the upcoming development,
extensive probe and grout might be needed to seal off
the paths of water. A probe and grout program donewith a jumbo might be considered for covering shortdistances within low risk development.
Figure 6 is a typical example of probe and grout
patterns for high risk development.
Once a probe and grout program is completed, aformal review will be conducted to identify any risk
(geological, hydrogeological, and geotechnical) andproviderecommendations
forthefuturedevelopment.
Geologicalstructuresandhydrogeological information will be documented.
Geotechnical information will be assessed through aGround Hazard Model and Rock Mass Rating
system. The heading will be formally released fordevelopment with proper controls in place for
excavation and ground support.

5. CONTINGENCY DEWATERING OF
HIGH RISK DEVELOPMENT WITHOUTFREEZE PROTECTION
Any high risk development less than 15 m to theunconformity without ground freeze protection may
have risk of unknown water interception. In order tomitigate this risk, contingency plans have to be inplace to manage the risk, such as contingency
dewatering infrastructure including water hitch,drainage holes, and sufficient dewatering pumping
capacity.

6. CONCLUSIONSThe practices used for dealing withhydrogeological challenges at McArthur River
Operation are:
• Probe and grout drilling programs prior to any
development without freeze protection to collectdetailedgeological,hydrogeological,
geotechnical, and radiological information.
Results collected are formally reviewed and thenthe heading can be released for development withproper controls applied if required.
• Freeze walls have been used effectively to isolate
production areas from water enriched formations,such as Zone 2, Zone 4 Lower, Zone 4 North
upper, and Zone 4 Central upper.
• Freeze shield protection was used for the 5307300E Raisebore drift to allow for the mining ofZone 4 Central Low portion.
• Dewatering and pressure relief drilling were usedin Zone 2 Panel 5 and Zone 4 North Upper as partof the freeze wall commissioning process.
• Additional
precautions
are
taken
with
underground development in the vicinity ofknown surface drill holes. If a new development
without freeze wall protection from the water
source is located within 8 m of any ungrouted
surface hole, it will be considered as high risk
development.
• Before any hydrological high risk development
without freeze wall protection is allowed to takeplace, an emergency water handling plan must be
in place, such as water hitches or drainage holes,
etc. The corresponding mine dewatering capacity
must also be sufficient.

7. ACKNOWLEDGEMENT

Figure 6: Typical probe and grout pattern for high risk
development.

The authors would like to thank Cameco
Corporation for permission to publish this paper. The
authors would also like to thank all of those whohave contributed and have been involved in groundcontrol and related programs at McArthur River over
the years of operation.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 20168.

REFERENCES

Baoyao Tang, June, 2014, Interoffice Memo.
MCA Zone 4NU Freeze Wall Commissioning.
McArthur River Operation, 2014. ENG-08
Underground Dewatering and Groundwater Control
Systems Design Procedure.
McArthur River Operation, 2014. ENG-10
Ground Control Procedure.
McArthur River Operation, 2014. ENG-12
Ground Freezing Procedure.
McArthur River Operation, 2014, MOP-09-04
Freeze Hole Pressure and Leak Testing.
McArthur River Operation, 2015. GEO-03-07
Drilling Instructions for Freeze Hole.
McArthur River Operation, 2016, ENG-01-09
Underground Development Risk Classification.
McArthur River Operation Groundwater
Control, 2016.

458

ISMS 2016

Paper No. 95

Experimental Study on Bolt Pull-Out Property Coupled by Plate andShotcrete
Xiliang LIU a,*, Jiaqi GUO a, Long Wan b, Jianhua Wang aabSchool of civil engineering, Henan polytechnic university, Jiaozuo Henan, 454003, PR China
Yellow River Construction Engineering Group Co., Ltd, Zhengzhou Henan430071, PR China

ABSTRACT
Based on a self-developed multi-function bolt mechanical test system, axial pull-out loads were applied on samebolts under the different conditions, combining with a flat plate, a butterfly plate, a new-type plate and three kinds ofshotcrete(C15, C20 and C25 plain concrete). Experimental results showed that the relationship between bolt
elongation and drawing force has three stages, including elastic, yielding and strengthening. The strength of
shotcrete lining has an obvious influence on the bolt stiffness during the elastic stage i.e. the strengthening of theconcrete leads to the increase of bolt stiffness. The strength and width of the yield platform of the bolt reach the
maximum for the butterfly plate and the yield plate with C20 plain concrete lining. The butterfly plate and the newtype plate both have yield functions, and the latter one can effectively prevent the damage of shotcrete. The damageof shotcrete lining usually begins around the drill holes, when the interfacial stress between the initial shotcrete
lining and surround rock is higher than that in the initial lining and secondary lining. With the new-type plate used,the cracks in the secondary lining cut through along the same direction.
KEY WORDS: Pull-Out Test; Coupling Effect; Strain; Fracture Morphology

1. INTRODUCTION
Anchor bolt-spray has become one of the mosteconomic and effective support methods applied inunderground projects (WANG Jin-hua, 2007; Anders
Ansell, 2005). The main function of bolts in thebolting and shotcreting technology is to improve
deformation resistance of surrounding rock andcontrol the rock deformation, making the surroundingrock as a part of the support system. In recent years,
many scholars around the world have carried out
massive and in-depth theoretical researches about thebolts (HE Manchao et al, 2014; ZHAO Tong-bin etal, 2011; M.Cai and D.Champaigne, 2012). Shotcrete
lining plays an important structural roles in the
combined support system. Shi Ling analyzed thefunctions of shotcrete lining under the stress-control
and the structure-control mode (SHI Ling, 2011).
Wen Jingzhou developed the bearing model of thesurrounding rock-shotcrete lining structure (WEN
Jingzhou et al, 2011). Fang Shulin et al monitored thestress state of the post-shot concrete in a roadway( FANG Shu-lin et al, 2012). Xiang Wei et al.
investigated the deformation law and interaction
mechanism of surrounding rock and shotcrete lining
under freeze-thaw cycles (XIANG Wei et al, 2011).
Plates play significant roles during the loadtransmission between different parts of the support

system. Jiang Tieming analyzed the influence of theplate on the stress distribution in the surroundingrock after the pre-stressing of bolts based on the
FLAC (JIANG Tieming, 2008). Wang Jianzhi et al.
studied the influence of plates on the internal stress
distribution of bolts (WANG Jianzhi et al, 1989).
Kang Hongpu et al. studied the influence of a plate on
the bolt pre-stress field and its support effect on thesurrounding rock. Above-mentioned researches havevastly perfected the anchor bolt-spray support theory
and effectively promoted the massive application ofthis technology in engineering.
All the aforementioned studies focused on onlya certain bearing part or two in the whole bolt-spray
support system. Studies on the interaction between
plate and shotcrete, as well as the bolt stress behavior
under the coupled action of them, are still very
limited. Therefore, a self-developed multi-function
bolt mechanical test system was adopted to conductpull-out tests of the same type of bolts under different
combination conditions between plate types and plain
shotcrete linings with various strength values. Basedon the experimental results, the bolt stress state under
the coupled action of plates and shotcrete linings, andthe deformation and fracture behaviors of shotcrete
linings were discussed.

2. TEST SYSTEM AND METHOD*Corresponding author – email: xlliu@hpu.edu.cn

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2.1 Test system
Due to the limitation of maximum drawing force
and test range, commercially available bolt testingmachines cannot meet the requirements of themechanical performance testing of new types of bolts
such as high-strength bolts and large-deformationbolts developed based on pressure principle.
Meanwhile, they also cannot precisely simulate thein-site interaction between bolts and surroundingrock as well as the coupled action between plates andshotcrete linings. Hence, they are unable to meet therequirement of this study. The authors designed amulti-function bolt mechanical test system, as shownin Fig.1. The test system consists of counter force
frame, anchorage, loading device, measurement
device, control system and data acquisition andprocessing system. It can provide drawing force as
great as 600 kN, and the maximum pull-out stroke is
300 mm. It can simulate the in-site interfacialinteraction between the bolt and adhesive material,
and that between the anchoring body and surroundingrock. Moreover, it can also simulate axial/eccentric
pull-out property of bolt under the coupled action ofplates and shotcrete linings, and the deformation
behavior of surrounding rock and shotcrete lining. In
addition, it can realize the real-time acquisition,
dynamic displaying and paragraph preparation of test
data.

Fig.1. The self-developed multi-function boltmechanical test system

2.2 Test materials
Cast-in-situ shotcrete linings were used in thisstudy. The principal raw materials of the shotcrete
linings were cement, aggregate and water. The
cement used was 32.5# ordinary Portland cement
produced by Henan Jiaozuo Jiangu Cement Co.,
LTD. Coarse aggregates were gravels with diameters
ranging from 20 to 35 mm. The gravels were wellgraded, clean, dry and had crush indexes between
7.9% and 8.1%. Fine aggregates were river sand withhigh quality. The fineness modulus of sand was 2.63,
with the maximum particle size lower than 5 mm.
The sand was well graded, clean and dry. Plain
concretes with strength values of C15, C20 and C25,
were prepared according to calculation. The prepared
concretes were poured into shotcrete linings indetachable special mould made of Q235 steel plates.

9 pieces of C30 concrete substrate blocks withdimension of 500 mm ×500 mm ×300 mm werepoured in mould to simulate surrounding rock.
Left-handed ribbed high-strength bolts producedby Jiaozuo coal company of HNCC were selected inthis study. The bolts were made of MG400 bolt steel,with 3 m in length and 22 in diameter. Their yieldstrength is 400 MPa and ultimate tensile strength is
540 MPa. During testing, three types of plates, flat
plate, butterfly plate and new-type plate, were used,
as shown in Fig. 2.

(a) flat plate(b) butterfly plate and(c) new-type plate.

Figure 2. Plates used in tests

2.3 Test method and scheme(1) Preparation method of the plate and shotcrete
lining system: The shotcrete lining used in the pullout test had a dimension of 500 mm × 500 mm × 150
mm( JIANG Tieming, 2008), with a hole of 50 mm
in diameter reserved at the center as the anchoring
reserved hole for bolts. During pouring the shotcrete
lining, an initial lining with a thickness of 60 mm was
firstly poured and then a secondary shotcrete lining
with a thickness of 90 mm was poured. Whenpouring the secondary shotcrete lining, a square holewith a dimension of 160 mm ×160 mm was reservedat the center adjacent to the initial lining, in order toinstall the plate. After the installation of the plate,concrete was poured to both inside and outside thesquare hole to a certain thickness at the same time.
After that, the wood die for the square hole wasremoved and the square hole was poured to thedesigned thickness and vibrated. The pouring processof the shotcrete lining is illustrated in Fig. 3.

Figure 3. Pouring process of the secondary shotcrete lining,(a) before pouring, (b) after pouring.

(2) Test method of bolt pull-out under the
coupled action of plates and shotcrete linings: The
prepared detachable die was firstly fixed at one endof the test system. Then, substrate blocks andshotcrete linings were placed inside the die and fixed.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The substrate blocks and shotcrete linings wereconstrained by the die. Bolts were then anchored tothe drawing end and the shotcrete lining end throughthe reserved hole. The drawing end was the anchoredend and the spherical anchorage with 21 mm indiameter produced by Henan Yujian Mining
Technology Co., LTD was used. After the installationof the shotcrete-bolt support system, tests wereconducted under specific conditions, with the pull-out
load and bolt elongation recorded. When the loading
system reached its maximum stroke, the shotcrete
lining was seriously damaged or the bolt tail was
fractured, tests were ended. In this study, 9 sets ofpull-out tests with 3 kinds of plates and 3 strength
grades of shotcrete linings were carried out. To
analyze the strain features of different locations at thecontact interface between the initial lining andsurrounding rock, the contact interface between theinitial lining and the secondary lining, the externalsurface of the secondary lining during testing,
SZ120-50AA resistance strain gages were pasted onthese locations.

3. RELATIONSHIP CURVES OF DRAWINGFORCE AND ELONGATIONS

Bolt Drawing Force (kN)

Relationship curves between the bolt drawing
force and elongation under the different combination
conditions of plates and shotcrete linings are shownin Fig. 4.
250

Flat Plate

200
C15 shotcrete layer
C20 shotcrete layer
C25 shotcrete layer

150
100
50
0

0

50

100

150

200

250

300

Bolt Drawing Force (kN)

Bolt Elongation (mm)250

Butterfly Plate

200
C15 shotcrete layer
C20 shotcrete layer
C25 shotcrete layer

150
100
50
0

0

50

100

150

200

250

300

Bolt Drawing Force (kN)

Bolt Elongation (mm)250

New Plate

200
C15 shotcrete layer
C20 shotcrete layer
C25 shotcrete layer

150
100
50
0

0

50

100

150

200

250

300

Bolt Elongation (mm)Figure 4. Bolt drawing force-elongation relation curves
under different combination conditions of plates andshotcrete linings

According to Fig. 4 and related test data, we canfind that:(1)Under different plate/lining combination
conditions, the relation curves between the bolt
drawing force and elongation present similarvariation trends. By taking the combined influence ofplates and shotcrete linings, the bolt drawing process
can be divided into three stages with obvious
features, which are elastic, yield and hardening.
(2)With the same plate type, the intrinsic strength of
shotcrete lining has limited influence on the bolt
yield strength. The shotcrete lining strength hassignificant influence on the bolt stiffness at the elastic
stage, at which the bolt stiffness increases with the
improvement of shotcrete lining strength. Whenbutterfly plates are used, the bolt stiffness increases
from 4.45 MN/m to 4.86 MN/m when the shotcrete
strength increasing from C15 to C25. When flat
plates are used, the bolt stiffness increases from 6.42
MN/m to 9.22 MN/m, and the bolt stiffness increases
from 5.89 MN/m to 7.89 MN/m when new-typeplates are utilized. This is mainly attributed to thatthe influence of the shotcrete in the early bearing
stage of the shotcrete-bolt support system is more
dominant. In addition, above test results can also
explain the reason why exorbitant shotcrete lining
strength is not beneficial to the release of surroundingrock pressure and the play of the intrinsic bearing
capacity of surrounding rock in shotcrete-bolt support
systems. (3)With the same shotcrete strength, thecurve slope of the flat plate is greater than those of
the butterfly plate and new-type plate at the elastic
stage, due to the lack of pressure relief function of theflat plate. Thus, it is indicated that the flat plate is notbeneficial to the full development of the elastic
deformation stage of the shotcrete-bolt support
system, thereby affects the controllable release of
surrounding rock during the early excavation oftunnels or roadways. (4)When flat plates are used, thebolt yield strength under the coupled influence ofplates and shotcrete linings is not obviously affectedby the shotcrete lining strength, and the widths of theyield platforms are all 42 mm. However, after thebolt is yielded, the elongation slightly increases with
the improvement of shotcrete lining strength.
(6)When butterfly plates are used, the elongation andyield strength of bolts during yielding are almost thesame. But the yield platform width gradually
increases with the reduction of shotcrete lining
strength. Based on calculation, the yield platform
width of the C15 shotcrete strength is 1.24 times ofthat of C20 and 1.219 times of that of C25. Hence, it
is implied that the increase of shotcrete lining
strength when butterfly plates are used, is notbeneficial to bolt yielding.(7)When new-type plates
are utilized, under the coupled action of plates andshotcrete linings, the bolt yield strength firstly

461

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

increases and then decreases with the increase of
shotcrete lining strength. The bolt yield platform
widths and elongations during yielding are almost
similar.

4. SHOTCRETE LINING STRAIN UNDER
THE COUPLED ACTION OF PLATE AND
SHOTCRETE
The relation curves between the shotcrete lining
strain and bolt drawing force under different
combination conditions between C20 plain shotcreteand three types of plates are displayed in Fig.5. Since
the variation tendencies of shotcrete lining strain
corresponding to different combination conditions
between C15 and C25 plain shotcrete with different
types of plates, are similar to that of C20 plain
shotcrete, only the C20 plain shotcrete lining is
discussed here.

Bolt Drawing Force /t

25
20
20 mm outside the drill hole at the contact interbetween initial layer and secondary layer
20 mm outside the drill hole at the external surf
surof secondary layer
70 mm outside the drill hole at the external surfof secondary layer
120 mm outside the drill hole at the external suof secondary layer
20 mm outside the drill hole at the contact interbetween initial layer and surrounding rock
70 mm outside the drill hole at the contact int
between initial layer and surrounding rock

15
10
5
0

0

100

200

300

400

500

600

700

(a) Shotcrete layer strain under the coupled action of flat plated C20 hl25Bolt Drawing Force /t

2015
20 mm outside the drill hole at the contact interfac
between initial layer and secondary layer
20 mm outside the drill hole at the external surface
surfacof secondary layer
70 mm outside the drill hole at the external surfaceof secondary layer
120 mm outside the drill hole at the external surfaof secondary layer
20 mm outside the drill hole at the contact interfac
between initial layer and surrounding rock
70 mm outside the drill hole at the contact interfa
interfbetween initial layer and surrounding rock

10
5
0

0

100

200

300

400

500

600

700

(b) Shotcrete layer strain under the coupled action of butterfly plate

25

Bolt Drawing Force /t

20of the bolt drawing force. Around the drill hole, theshotcrete lining is obviously yielded at the lateloading stage. (2) For strain gages on the same lining,
the further they are away from the drill hole, thelower their strain will be. This phenomenon also
explains why the shotcrete lining often starts to breakaround the drill hole during pull-out tests under the
coupled action of plates and shotcrete linings.(3)The
contact interface between the initial lining andsurrounding rock has strain slightly greater than thatof the interface between the initial lining andsecondary lining, even their distances to the drill hole
are the same. The strain at the contact interface
between the initial lining and surrounding rock isgreater than that of the external surface of thesecondary lining, though they are equal far awayfrom the drill hole. Thus, it is indicated that the stressat the contact interface between the initial lining andthe surrounding rock is greater than those at thecontact interface between the initial lining and thesecondary lining, and at the external surface of thesecondary lining. (4)When butterfly plates are used,
the initial strain around the drill holes at the contact
interface between the initial lining and the secondarylining, and the contact interface between the initiallining and the surrounding rock is lower than those at
the same positions when flat plates or new-typeplates are used. But the strain will gradually increase
to the same value. This is attributed to that at theearly stage of loading, the center of the butterfly platecannot contact with the initial lining, and with theloading increasing, the butterfly plate deforms andcontacts the initial lining until the test ends. Thus, it
is demonstrated that the butterfly plate has thefunction of pressure relief. (5)When new-type plates
are adopted, the slope of the strain-drawing force
curve around the drill hole at the external surface ofthe secondary lining experiences a sharp increase.
This is caused by that with the increasing load, thenew plate deforms and introduces pressure on the
shotcrete lining, which hinders the further increase ofstrain. The new plate presents the property of limiting
the exorbitant deformation of shotcrete lining.

15
20 mm outside the drill hole at the contact interface
between initial layer and secondary layer
20 mm outside the drill hole at the external surfaceof secondary layer
70 mm outside the drill hole at the external surfaceof secondary layer
120 mm outside the drill hole at the external surfaceof secondary layer
20 mm outside the drill hole at the contact interface
between initial layer and surrounding rock
70 mm outside the drill hole at the contact interface
between initial layer and surrounding rock

10
5
0

0

100

200

300

400

500

600

700

(c) Shotcrete layer strain under the coupled action of new plate

Figure 5.Relation curves between the shotcrete lining strain
and bolt drawing force

Some results drawn from Fig.5 are as fellows: (1)The shotcrete lining strain increases with the increase

5. SHOTCRETE FRACTURE PROPERTY
Plain concrete possesses remarkable brittleness,
which becomes more obvious with the increase ofstrength. The brittleness of plain concrete in bolting
and shotcreting support system mainly reflects in thismode, that is, the micro cracks on the plain shotcrete
lining surface rapidly develops wider, deeper andlonger until cutting through the shotcrete lining
surface and fully fracturing the shotcrete lining. Bytaking the C20 plain shotcrete lining as an examples,the fracture morphologies under the coupled action of462

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

plates and shotcrete linings after bolt axial pull-out
tests are shown in Fig. 7.

Flat plate（a）Front side

Flat plate（b）Back side`
Butterfly plate（a）Front side

New-type plate（a）Front side

Butterfly plate（b）Back side

New-type plate（b）Back side

Figure 7. Fracture morphologies of C20 plain
shotcrete linings

As demonstrated in Fig.7, the fracture modes ofthe flat plate and butterfly plate are similar. The
cracks extend from the vicinity of drill hole in theinitial lining to the border as well as the secondarylining, until the shotcrete lining gets fractured. The
crack pattern is outward radial with the drill hole as
the center point. Under the coupled action of newplates and plain shotcrete linings, the fracture
morphology is cracks radiating outward in the initiallining with the drill hole as the center point. The
cracks in the secondary lining run through along thesame direction, which is attributed to that the platedeforms with the increasing drawing force andintroduces pressure on the shotcrete linings to hinder
the generation of cracks. Thus, it is indicated that the
new plate has the function to prevent shotcrete lining
fracturing.

6. CONCLUSIONS
Based on axial pull-out of bolt tests conductedon the self-developed multi-function bolt mechanicaltest system with three types of plates combining with
C15, C20 and C25 plain shotcrete linings, a couple ofconclusions can be drawn:(1) The relation curves between bolt drawing
force and elongation under different combination
conditions of plates and shotcrete linings can bedivided into three stages with obvious features, which
are elastic, yield and strengthening. The influence of
shotcrete strength on the bolt yield strength is very
limited, but has a significant effect on the bolt
stiffness at the elastic stage, during which the bolt
stiffness increases with the increase of shotcrete
strength.
(2) Under the condition that flat plates areused, the bolt yield strength is not obviously affectedby the shotcrete lining strength, but bolt elongation
expands slightly with the shotcrete strength
increasing after yielding. When butterfly plates areused, the bolt yield platform width increases with the
reduction of shotcrete strength. As for the new-typeplate condition, the bolt yield platform width and theelongation to yield are similar. The butterfly plateand new-type plate are revealed to have the functionof pressure relief(3) The shotcrete lining strain increases with theincreasing drawing force, and the shotcrete linings
present obviously yielding features at the late loading
stage. The shotcrete lining often starts to breakaround the drill hole. The stress at the contact
interface between the initial lining and surroundingrock is greater than those at the contact interface
between the initial and secondary linings, and at theexternal surface of the secondary lining.
(4) When flat plates or butterfly plates are used,the cracks are radically distributed outward with drill
holes at the center points. As for the new-type plate,the fracture morphology is cracks radiating outward
in the initial lining with the drill hole at the center
point, while cracks cut through along the same
direction in the secondary lining. Thus, a certain
degree of layer-fracture resistance of the new-typeplate is revealed.

7. ACKNOWLEDGEMENTS
This work is financially supported by National
Natural Science Foundation of China(Grant No.
51474097) and Provincial Key Technologies andDevelopment Program of Henan(Grant No.
152102210318) .

8. REFERENCES
Anders Ansell. (2005). Laboratory testing ofa new type of energy absorbing rock bolt[J].
Tunneling and Underground Space Technology,
20 (4):291-330.

463

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

FANG Shu-lin et al. (2012). Mechanicalmonitoring and analysis on shorcrete layer ofsoft rock main roadway supported by boltshotcrete[J]. Journal of Mining & Safety
Engineering, 29(6): 776-782.(in Chinese)
HE Manchao et al. (2014). Development of a
Novel energy-absorbing bolt with extraordinarily
large elongation and constant resistance[J].
International Journal of Rock Mechanics &Mining Sciences, 67: 29-42.
JIANG Tieming. (2008). Mechanism of
support unit of anchor bolt in coal roadway andapplication research in Jincheng mining
area[D].Beijing: China university of mining andtechnology (Beijing).
M.Cai, D.Champaigne. (2012). Inluence ofbolt-grout Bonding on MCB cone bolt
performance[J].Inte-rnational Journal of RockMechanics & Mining Sciences, 649: 165-175.
SHI Ling. (2011). Development of study on
support mechanism of sprayed concrete liners intunneling and Caving engineering[J]. Chinese
journal of underground space and engineering,
7(4): 759-763.(in Chinese)
WANG Jianzhi, He Tangyong, Yang
Gengshe. (1989). The influences of bearing plateon the internal force of overall reinforced
bolts[J]. Journal of Xi an Mining Institute, (3): 712,18.(in Chinese)
WANG Jin-hua. (2007). New development ofrock bolting technology for coal roadway in
China[J]. Journal of China coal society, 32(2):113–118.(in Chinese)
WEN Jingzhou, ZHANG Yongxing, WANG
chen. (2011). Analysis on interfacial stressbetween surrounding rock and shotcrete
lining[J]. Journal of railway engineering society,01: 39-46.(in Chinese)
XIANG Wei et al. (2011). Model test studyof rock-shotcrete layer structure under freezingthawing cycles[J]. Chinese Journal of RockMechanics and Engineering, 30(1): 18191825.(in Chinese)
ZHAO Tong-bin et al. (2011). Mechanical t
est of Bolt Interface and Microscopic Simulationof transfer Law for Shear Stress[J]. Journal of
Mining & Safety Engineering, 8(2): 220-224.(inChinese)464

Part 3

Coal

ISMS 2016

Paper No. 130

Mathematical model for gas diffusion from non-homogeneous coal particles
Yanwei Liua,b,c,*, Mingju Liua,b , Hani S. Mitric,daSchool of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo 454000, China
The Collaborative Innovation Center of coal safety production of Henan Province, Jiaozuo 454000, Chinac
Department of Mining and Materials Engineering, McGill University, Montreal, H3A0E8 CanadadSchool of Civil Engineering, Henan Polytechnic University, Jiaozuo, China, 454000b

ABSTRACT
By establishing model and experimental verification, this paper aims to improve the accuracy and applicability ofgas diffusion mathematical models from coal particles in engineering applications. Firstly, based on Fick's second
law and the continuity theory of gas diffusion in porous media, a new constitutive model for gas diffusion from nonhomogeneous coal particles with three-layer pore structure is constructed by considering the difference ofcharacteristics in pore structure between soft coal and hard coal. Then, the analytical solution is derived from thenew model, that is, the quantitative relationship between gas diffusion rate (Qt/Q∞) and diffusion time (t). The pore
structure parameters of soft coal and hard coal from Juji coal mine are determined by using the mercury injection
method. Gas desorption and diffusion rules of coal samples are numerically calculated and investigated by using
physical simulation methods. Lastly, the applicability of the constitutive model is verified. The results show that thehomogeneous model that is currently widely used only applies to the description of the gas diffusion process of thehard coal within the initial 10 minutes, while the new model can describe the gas diffusion law of different pore
structure characteristics. The calculated results from the new model and the physical experimental results are nearly
identical within the initial 30 minutes. The difference in the gas diffusion process between soft coal and hard coalcan be effectively reflected by the parameters of pore structure in the new model.
KEYWORDS: soft coal and hard coal; gas desorption and diffusion rules; pore structure; mathematical models

1.

INTRODUCTION

Gas diffusion laws and models from coal particles
are the key theoretical bases for the determination ofgas content in coal seams. At present, there are acouple of theoretical models to describe the law of gas
diffusion from coal particles based on different
perspectives. These models can be classified into two
types, including homogeneous diffusion models(Qiluan and Youan, 1986; Nie, et al, 2001) andBidispere diffusion models (Clarkson and Bustin,
1999; Ruckenstein, et al, 1971). However, when thesemodels are applied to describe the gas diffusion laws ofoutburst prone soft coal, there are usually noticeable
deviations that lead to not meeting the requirements ofengineering (Liu, et al, 2015).
The conventional model commonly used is atransient mathematical model of gas diffusion based on
uniform porous coal particles and the solution to Fick’s
second law for spherically symmetric flow (J. Crank,
1975). Its analytical solution is an infinite series*Corresponding author-email: yanweiliu@hpu.edu.cnfunction of diffusion rate vs. time, as shown inequation (1). Based on the numerical model
calculations, Yang (Qiluan and Youan, 1986) foundthat the relationship between ln [1-(Qt/Q∞)2] and t islinear.
Qt
6 ∞ 1= 1 − 2 ∑ 2 e − n BtQ∞
π n =1 n(1)
2

Where, Qt is the total volume of the diffusing gas attime t, cm3/g; and Q∞ is the total diffusion volume
cm3/g; t is the time of gas diffusion, s. B=π2D/a2, Thevalue of B ranges from 6.5797×10-6 to 6.5797×10-3. D
is the diffusion coefficient of gas in coal particle, m2/s,
To verify the homogeneous model, theexperiment concerning gas diffusion from soft coal andhard coal of Juji coal mine was performed. The
experimental results showed that the relationshipbetween ln [1-(Qt/Q∞)2 ] and t is not linear, as
illustrated in Figure 1.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016ln(1-(Qt/Q∞)2 )

0

10

20

30

40

50

60

t(min)
70
80

0.00
-0.05
-0.10
y5 = -0.0094x

-0.15

2

-0.20

R = 0.9828

y30 = -0.0048x

y10 = -0.0076x

R = 0.8374

2

2

R = 0.9622

y60 = -0.0031x
2
R = 0.5284-0.25(a): Soft coalln(1-(Qt/Q∞)2 )

0

10

20

30

40

50

60

70

t(min)
80

0.000
y10 = -0.0003x-0.004y5 = -0.0003x-0.008-0.012R2 = 0.9961

2

R = 0.9892
y30 = -0.0003x

y60 = -0.0002x

R2 = 0.9925

2
R = 0.9841-0.016-0.020(b): Hard coal
Figure 1: Fitting curves of Juji coal samples according to theunipore model.

described. Clarkson and Bustin (1999) developed an
isothermal adsorption rate model based on
Ruckenstein’s model, considering variable pressure
adsorption rate experiments as described by Mavor etal. (1990) and the adsorption isotherm that can be
described by the Langmuir equation. They indicate thatdull or banded coals have a more complicated pore
structure, and are adequately modeled with diffusion
models that incorporate a bidisperse pore volume
distribution. However, it is inadequate to describe thegas diffusion process from soft coal.

2.

THE DEVELOPMENT OF MODEL AND
DISCUSSION

The current desorption model assumes atridisperse pore structure for coal, as schematicallyshown in Figure 2, considering a macroporous particle
which consists of uniform size mesoporous particles
containing uniform microporous particles. The radiusof the larger sphere is much more than that of thesmaller sphere. Unlike the previous models, the current
model takes into account the tridisperse pore structure
based on the difference between soft coal and hardcoal. It also assumes that there is no pressure gradientsduring intra-particle diffusion. The only driving force isthe concentration of gas. In addition, the adsorption is
occurring in both micropores and mesopores. The
assumptions for the current model may be summarized
as follows.
(1) Isothermal system.
(2) Applicable transport equation is Fick’s secondlaw.

Considering the mass transfer resistance of thesurface of coal particles, Nie et al. (2001) adapted theunipore diffusion model based on the third kindboundary condition. Its analytical solution was
obtained using the mathematical and physical methods.
The simplification of the solution to the equation issimilar to the empirical formula developed by Bolt and ∂ 2C 2 ∂C 
∂C D ∂ 2 ∂C
=
⋅ (r
)=
D 2 +

2
Innes (1959).
∂t r ∂r∂r
r ∂r 
 ∂rBi-disperse diffusion models are based on theassumption that pore structure of coal merely consistsr
C (r ,t)of macro-porous and micro-porous.
R
C (r ,t)
Ruckenstein et al. (1971) developed the continuousrDbi-disperse diffusion model by considering theRradsorbent to be a spherical particle (macrosphere)rDD r
containing an assemblage of microspheres of uniformr R
C (r ,t)size. The Henry linear adsorption model and a stepchange in concentration of the adsorptive external to
Figure 2: Conceptual model for tridisperse pore structure.
the particle are assumed in Ruckenstein’s model. Smithand Williams (1984) adapted Ruckenstein’s model and(3) Transport is the diffusion in both macro, meso
found that the bidisperse diffusion model betterand micropores.
described the entire desorption rate curve than the(4) Significant adsorption occurs in both micro-,
unipore model for some coals. Crosdale et al. (1998)
meso- and macroporosity and the adsorption isothermhas verified successfully the bidisperse model by
can be described by Langmuir equation as follows.
investigating Australian coal gravimetric transientadsorption data. In particular, it is believed that dull =Cs a 'b 'C / (1 + b 'C )coal adsorption rate data are better a fit with the
Where, Cs is adsorption of gas concentration on
bidisperse model than with the unipore model when thethe surface, mol/m3, C Free gas concentration in porewhole process of diffusion from coal particles is
w

w

w

w

z

z

w

w

d

d

d

d

d

d

z

z

z

Z

466

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

after desorption, mol/m3, stands for a gas concentration
which is complete monolayer coverage of micropore ofgas-solid surface, mol/m3, b langmuir constant,b′=bRT
MPa-1，R gas constant, R=8.314(cm3.MPa)/(K.mol),
T stands for the temperature, K;(5) Pores are incompressible.
(6) Void volume is constant with time. No
correction is made for void volume shrinkage during
adsorption of gas.
(7) Coal particle is spherical in shape and uniform
in size.
(8) The gas transport through pores complies withmass conservation and fluid continuity theorem.
The concentration field inside macropore satisfies
the following equation (2).
3 (1 − φd ) ∂Cz ∂ 2C 2 ∂Cd  ' ' ∂  Cd 
Ddφd  2d += a b Sd 
 + Dz
r =R
'
1
r
r
r
t
b
C
Rzφd rz z z
∂
∂
∂
+
d
d 
d 
 d

(2)

Where the first term is due to variation ofdiffusional flux in the macropore, the second toaccumulation in the macropore, and the third to the
diffusional flux at the surface of mesospheres.
The mesopore (3) and micropore (4) transport
equation used in the current study are thus.
3 (1 − φz. p ) ∂Cw ∂ 2C 2 ∂Cz  ' ' ∂  Cz 
Dzφz  2z += a b Sz  + Dw
r =R
'
1
r
r
r
t
b
C
Rwφz. p rw w w
∂
∂
∂
+
z
z 
z 
 z

(3)

 ∂ 2 Cw 2 ∂ Cw ∂  Cw +
Dwφw 
a 'b ' S w =
2rw ∂rw ∂t  1 + b 'Cw 
 ∂rw

(4)

With initial conditions:C=rd ) C=rz ) Cw=( 0 rw ) C0
d ( 0，，，z (0(5)

And boundary conditions:
∂Cd
∂C
=0，，；
t ≥ 0 ，，；
rd =0 ，， z =0 t ≥ 0 rz =0
∂rd
∂rz

∂Cw
=0 t ≥ 0 rw =0∂rw(6)

Cd ( t，；
Rd ) = C1=
Cz ( t，，，，，Rz ) C=rd ) Cw ( t Rw ) Cz ( t rz )
d (t

∞

∞

−16π 2 φd Rd3 Dd ( C1 − C0 ) ε ∑∑
Q∞ =
=
k 1=
q 1

(7)

∂C
Qt =
t ≥ 0 rd =Rd
∫0 −4π R Ddφd ∂rdd rd = Rd dt，，(8)tt=0, moles/m3; C1 sorbate concentration at r=Rd,moles/m3; rw the radius of small coal particle inspherical coordinate, m; rz the radius of medium coalparticle in spherical coordinate, m; rd the radius of coalparticle in spherical coordinate, m; Rw the radius ofsmall coal particle, m; Rz the radius of medium coalparticle, m; Rd the radius of coal particle, m. t is thetime of diffusion, s; φw the average porosity of
micropores; φzp the average porosity of mesopores andtransition pores in a single coal particle, φz.p=φz/nm3/m3; n the number of the lower grade coal particle
in unit volume, n=(1-φ)/(4πR3/3); φd the porosity ofmacropores, m3/m3(%); Sw the specific surface area of
micropores, m2/m3; Sz the specific surface area ofmesopores and transition pores, m2/m3; Sd the specificsurface area of macropores, m2/m3; Qt total diffusion
volume at time t, cm3/g.
At t=0, gas concentration is assumed to be equal in
the macro, meso and micro-spheres (Eq. (5)). A no gas
diffusion flow internal boundary condition is used forthe macro, meso and micro-spheres (Eq. (6)). Eq.(7)states that the gas concentrations at micro and mesospheres boundary are equal to the gas concentration in
the meso and macro-porosity at rz and rd respectively,
and the gas concentration at macro-spheres boundary is
eternally equal to the constant C1. Eq. (8) is a balancestatement which express that the change in mass of gas
stored interparticle void space is equal to the mass fluxof gas across all particle boundaries for t>0.
The initial and boundary conditions are substituted
into Equations (2) - (4). After a series of derivations,the relationship between Qt and t is obtained. As shownin equation (9), the function is an exponential relation,
and also a solution of infinite series. The infinite
diffusion amount (Q∞) is shown in Eq. (10). The
relationship between Gas diffusion rate (Qt/Q∞) andtime t is shown in Eq. (11).
( −αεξqk2 t )  δ22∞ ∞ k π Rz  1 − eQt =−16π 2 φd Rd3 Dd ( C1 − C0 ) ε ∑∑
ω
=
k 1=
q 1
(9)

2
d

Where, Dw is micropore diffusion coefficient,m2/s; Dz mesopore diffusion coefficient, m2/s; Ddmacropore diffusion coefficient, m2/s; Cw micropore
sorbate concentration, moles/m3; Cz mesopore sorbate
concentration, moles/m3; Cd macropores sorbate
concentration, moles/m3; C0 sorbate concentration at

∞

∞

∑∑

Qt =k 1 =q 1=Q∞

k 2 1 − e

∞

(10)

2
qk




k 2δ

∑∑ ω

=
k 1=
q 1

ω

( −αεξ t )  δω∞k 2π Rz2δ

(11)

Where

467

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

α=Dw Rz2

D R Sφ=，w
abS w Dz R S φ
D R2
z

ε=

model, and were determined by mercury porosimetry
method, as shown in Table 2.

abS z

w

φz

φw

2
z z w
2
w w z

abS z
φ z Dd Rz2 S zφd=， 2
Dz Rd S d φ z
2 abS dThe above data and the intermediate parameters
shown in Table 3 were substituted into equation (12).
The theoretical curves of (Qt/Q∞) vs. t are plotted, as
shown in Figure 4. Meanwhile, the effective diffusivity(D/R2) was determined by fitting experimental dataaccording to unipore analytical solution (equation (2)).
Dynamic process tests of gas diffusion from coalparticles were carried out on specially prepared coalsamples 1-3mm in diameter by the experimental
system shown in Figure 3. The experimental process
can be classified as having 4 stages: firstly, vacuums
pumping of the air-proof system bearing samples isperformed until the gas pressure becomes stable at
10±0.1 Pa. Then, methane is gradually charged into thesamples until the adsorption achieves equilibrium at
0.74 ±0.01 MPa. The third step is to release the free gas
in void space until the pressure becomes 0. This step
takes about 10 seconds. Lastly, the data of desorption
volume and corresponding time are measured. The
experimental temperature is kept at 298 K by constanttemperature bath across the process.
As shown in Figure 4, the dots are experimental
data, and the curves are the theoretical values from theanalytical solution. A comparison of experimental rate
curves for hard and soft coal samples with theoreticalcurves gives some indications of the process of gas
diffusion from coal particles. Experimental results
show that the numerical calculation results by the newmodel are almost identical to the experimental data
within the first 30 minutes, although there are
increasing deviations between the two types of results
after 30 minutes. The main reasons for this finding may
be the truncation error of infinite series solution andthat the values of k and q in the series general solution
are taken as 100, as well as the determination error of
porous parameters.

Dd Rz2Dz Rd

3D R 2 (1 − φd − φz )Dz Rw2φzβ =， w z

φd

3D R 2 (1 − φ )η =， d z 2 d δ =−αξ qk2 ξ qk cot ξ qk β + β
Dz Rd φd

( )

ξ qk

is the root of transcendental Eq. (12)

(12)

3.

EXPERIMENTAL VERIFICATIONThe soft coal and hard coal samples werecollected from Juji coal mine in China, and the physicalparameters that reflect their characteristics were
determined. As shown in Table 1, these parameters
show the differences between soft coal and hard coal in
hardness, industry analysis, adsorption constants, andporosity. Then, these samples were dried, sieved, andclassified. The porous structure parameters needed to
be provided when calculating according to the newTable 1: Physical properties of soft coal and hard coal from Juji coal mine.

Samples
Hard
coal
Soft coalFirmnesscoefficient f

Industry analysis/%

Adsorption constants
a/m3·t-1
b/MPa-1

Porosity/%

Apparent
density/(t-1·m3)

Mad

Aad

Vdaf

0.85

0.89

10.08

10.00

36.117

0.668

4.0793

1.41

0.15

0.92

9.92

8.64

32.6540.930

6.1406

1.43

Table 2: porous structure parameters by mercury intrusion porosimetry method.

Samples

Vdaf
/%

Hard
10.00
coal
Soft coal 8.64

Pore specific surface area/(m2·g -1)
Sw
Sz
Sd
St

Ratio of pore volume /% Connectivity
/%
φw
φz
φd

10.00

3.922

1.428

0.002

22.32 26.91

50.76

26

8.64

4.167

1.807

0.014

15.31 37.78

46.92

39

468

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Charging Pressure gauge
vavle

Gas
tank

Gas
bomb

Big
samle
bomb

1
Vacuum
gauge

Big
samle
bomb

Big
samle
bomb

Constant
temperature
bath

Small
bomb

1

Vacuum pumpGas volumetric cylinder

Figure 3: Experimental set up.
Table 3: Results of gas diffusion parameters according to the new model

Samples

α

ε

β

η

β/α

η/ε

Hard coal

0.256

315.0

220.0

302.6

860.0

0.96

Soft coal

9.62E-03

4.23E+04

3.5270710526.85

9.62E-03

0.25

Dd/R2d
1.57E-04

Dz/R2z8.00E-05

Dw/R2w
5.50E-05(a) Verification of soft coal(b) Verification of hard coal
Figure 4: Experimental verification of the new model.

CONCLUSIONS(1) Due to the different porous structure between
soft coal and hard coal, there is a noticeable distinctionof transient gas desorption rules. The previous models
are inadequate to describe the transient process fromsoft coal.

(2) A model for transient desorption from coalparticles, which shows the influence of competing
effects of macropore, mesopore and micropore
diffusion has been developed. Compared to previous
models, the new model considers the effect of themesopore based on the difference between soft coal

4.

469

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016and hard coal, and the gas adsorption equation of coalas Langmuir equation.
(3) The general solution of infinite series of the
new model is theoretically derived. The relationship of
the rate of diffusion with time is an exponentialfunction. The results of experimental verification showthat the new model precisely describes the gas
diffusion process from coal particles within the first 30
minutes.
(4) The new model should be optimized andsimplified in the future to be satisfactory for field
application.

pore structures. Chemical Engineering Science,
volume26, No.9, pp. 1305-1318.
Smith, D.M. and Williams, F.L. (1984). Diffusion
models for gas production from coals: Application tomethane content determination. Fuel, volume 63, No.2,
pp.251-255.

5.

ACKNOWLEDGEMENTS
This article is supported by the National Natural
Science Foundation of China (51374095) and Doctoral
Fund of Henan polytechnic University (B2013-005)
and the China Scholarship Council.
6.

REFERENCES
Bolt, B.A. and Innes, J.A. (1959). Diffusion ofcarbon dioxide from coal. Fuel, volume 38, No.3,
pp.333-337.
Clarkson, C.R. and Bustin, R.M. (1999). The
effect of pore structure and gas pressure upon thetransport properties of coal: a laboratory and modelingstudy.2.
Adsorption rate modeling. Fuel, volume 78,
No.11, pp.1345-1362.
Crank, J., 1975. The Mathematics of Diffusion:
2d Ed. Clarendon Press.
Crosdale, P.J., Beamish, B.B. and Valix, M. (1998).
Coalbed methane sorption related to coal composition.
Int Jour of Coal Geology, volume 35, No.1, pp.147158.
Liu Y., Liu M. (2015). Effect of particle size on
difference of gas desorption and diffusion between soft
coal and hard coal. Journal of China Coal Society, 40(3):579-587.
Mavor, M.J., Owen, L.B. and Pratt, T.J., (1990).
Measurement and evaluation of coal sorption isotherm
data. January. In SPE Annual Technical Conference
and Exhibition. Society of Petroleum Engineers.
Nie B, Guo Y, Wu S. (2001). Theoretical modelof gas diffusion through coal particles and its analyticalsolution. Journal of China University of Mining &Technology, volume 30, No.1, pp.19-22.
Qiluan, Y. and Youan, W. (1986). Theory of
methane diffusion from coal cuttings and its
application. Journl of China Coal Society, No. 3, pp.
88-94.
Ruckenstein, E., A. S. Vaidyanathan, and G. R.
Youngquist (1971). Sorption by solids with bidisperse

470

ISMS 2016

Paper No. 139

Permeability prediction for coal reservoirs and reconstruction of a different
scales pore-fractures network
Ni Xiaominga,b, Chen Wenxuec,d,*, Li Zheyuana and Gao XiangaaSchool of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo, CHINA, 454000bCollaborative Innovation Center of Coalbed Methane and Shale Gas for Central Plains Economic Region，Henan Province,
Jiaozuo CHINA, 454000
cOpening Project of Key Laboratory of Deep Mine Construction, Henan Polytechnic University, Jiaozuo, China, 454000
dSchool of Civil Engineering, Henan Polytechnic University, Jiaozuo, CHINA, 454000

ABSTRACT
Describing the connectivity of different scaled pore-fractures and quantitatively expressing permeability can provide
an important basis for the output degree of the gas. A network for different scales pore-fracture was reconstructed byobserving a large number of coal samples, and using software simulation of the Monte Carlo method. A seepage
model about the different scales pore-fractures network was established by assigning zero method and using MatLab
software. The effect permeability about different scales pore-fractures network was obtained using a twodimensional seepage equation. Predicted permeability results are compared with the measured permeability results,
and the results show that: the dominant order of different scales pore-fractures connected from highest to lowest is
millimeters fractures, seepage pores and micron-sized fractures. The contribution of coal reservoir permeability frombiggest to smallest is millimeters fractures, micron-sized fractures and seepage pores. Different parameters in
different scales pore-fractures have differing influence on permeability. The reconstruction of a different scales
pore-fractures network can clearly display the connectivity of pore-fractures, which can provide a basis for selecting
migration paths and studying flowing patterns for gases.

1.

INTRODUCTION

Coal reservoir permeability is one of thequantitative parameters that characterizes thefractures development degree in coal. Researchers
have previously conducted fruitful research
examining the relationship between the coal reservoir
fractures and permeability, at home and abroad.
Through experimental tests about pore size,
permeability and porosity, it has been found that therelationship between fracture width and permeability
is a factor of 3 (He and Liu, 2011; Feng Zengchao etal., 2007). The relationship between fracture porosityand permeability is proportional (Zhang et al., 2008;
Cui et al., 2005). According to the fractal theory, thecoal reservoir permeability increases exponentiallywith an increase of the fractal dimension of thefracture (Barton C C., 1988; Babagagli Tayfun,
2001). The differences between coal reservoir
fracture width, length, density, and connectivity
result in differences of gas migration speed andmode. Establishing the relationship between fracture
porosity and permeability could lead to certain
deviations in the process of studying gases.
Reconstructing the different scales of the porefractures network can more help to more clearly
understand and master the flow state of gas in coal

*Corresponding author – email: wen1xue2@126.com(Sisavath et al., 2004; Chen and Feng, 2006).
Microscopic fracture information can be extracted byusing the image processing method (Chen et al.,2016), and different scales of pore-fractures networks
can be reconstructed by using the Monte Carlo
method. In order to obtain the different scales ofpore-fractures networks and the impact of coalreservoir permeability, the microscopic observation
and
Monte
Carlo
pore
fissurenetworkreconfiguration method are used. Connectivity andcontribution of permeability to different scales ofpore-fractures are studied. This can provide the basis
for studying gas migration in coal.

2.

THE BASIC IDEAS AND METHODSFOR THE RECONSTRUCTION OF
DIFFERENTSCALES
POREFRACTURES NETWORK

Coal reservoir permeability is one of thequantitative parameters that characterizes thefractures development degree in coal.
2.1 Different fracture scales diversion
In order to describe fine distribution
characteristics of the pore-fracture, it is necessary toclassify the coal reservoir fracture. Based on

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

divisions of different scales of pore-fractures in thepast, the millimeter scale is called a millimeter scalein millimeter, and the scale between the micron andthe millimeter is called micron. Based on B.B
decimal division, combined with studying results
about Fu Xue-hai etal, seepage pores are greater than
75nm pores.
1.2 The basic ideas concerning the reconstruction ofdifferent scales pore-fractures network
In order to reconstruct the different scales porefractures network, it is necessary to find thegeometrical parameters of different scales porefractures in coal samples. Different scales porefractures in coal samples were observed and counted
using scanning electron microscopy, optical
microscopy, and a series of testing instruments.
According to the statistical results, the probability
distribution model of pore-fractures network was
established. Finally, a random pore-fractures network
graph was produced based on the principle of theMonte Carlo simulation and using Matlab software.
1.3 Realization method of the reconstruction of thedifferent scales pore-fractures network- Sample Preparation
Coal samples in Sihe Mine in Shanxi Province
were collected and crushed into small pieces. These
small pieces were polished and made into briquettes.
The sizes of these briquettes are approximately 3cm

× 3cm × 2cm. these briquettes were observing. Partsof the briquettes were shown in figure 1.

(a)

(b)

(c)

Figure 1: Parts of the briquettes.

- The statistics about geometrical parameters ofdifferent scales pore-fractures
The geometrical parameters of pore-fractures
simulation mainly include density, direction, trace
length, and opening degree. First, the uniformly
distributed random numbers of the geometricalparameters were generated using statistical data.
Second, the other distributed random numbers weregenerated using a direct sampling method (LU B. etal., 2005; ODA M A. 1988).

=
bn ( abn −1 + c )( mod M )

bn

=
,n∈ N
rn
M

initial value is b0(1)
Where: M is the modulus; mod M is the residual
value of the modulus; a is a multiplier; c isincrements; b0 is the initial value; and rn is uniformly
distributed random numbers in the range from 0 to 1.

Table 1: Geometric parameters of pore-fractures.

Millimeter
fracture

Micronfracture

Seepagepore

packetdensity2(strip/mm )Trend (°)
means

Fracture length (mm)Standard deviation

1
2

0.1
0.1

77.8
156.7

4.2
7.8
angle (°)

packetdensity2(strip/um )

means

1
2

0.00040.000440.8
127.4

packetdensity2(strip/nm )meansStandard deviation

1
2

0.000005
0.000005

60.3
136.4

2.8
6.2

Standard deviation
1.6
5.8
angle (°)

When uniformly distributed random numbers
were generated, then other distributed random
numbers could also be generated. Such as:
x = µ x + σ x × − 2 ln(rand ) × cos(2 × π × rand ) ,Where: x is the normally distributed random
numbers; rand is the uniformly distributed randomStandard
deviation
2.89
0.16
3.74
0.19
fissure length (um)Standardmeans
deviation
46.1
4.9
92.3
8.6
fissure length (nm)Standardmeans
deviation
531.4
9.3
453.7
12.4
means

Fracture width(mm)Standardmeans
deviation
0.000650.00020.000650.0002
fissure width (um)Standardmeans
deviation
0.75
0.02
0.75
0.02
fissure width (nm)Standardmeans
deviation
12.32
2.35
12.32
2.35

numbers in the range from 0 to 1, and so on. Other
distributed random numbers were obtained.
The briquettes were observing by the best
magnification of the microscope. The direction,
length and width of different scales pore-fractures472

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

were counted. Statistical geometrical parameters areshown in Table 1.
The center of pore-fractures were uniformly
distributed, the tracing length of pore-fractures werenormally distributed, the trend of pore-fractures were
lognormal distributed, and the opening degree ofpore-fractures were normally distributed.
- The reconstruction about different scales of porefractures network
1) Generating domain and characterization of
pore-fractures
The pore-fractures network was generated via
the Monte Carlo method. In order to generate thepore-fractures network, the generating domain andcharacterization of pore-fractures were needed. The
following steps were performed:(1) The generating domain of pore-fracture
network was determined by the pore-fracture length.
For example, the average length of fractures was l ,so the size of the generating domain about thefracture was 6l × 6l .
(2) If pore-fractures were always straight, thecenter coordinate of pore-fractures was (x, y), thelength of pore-fractures was s, trend angle of thepore-fractures was α (defined as the angle from xaxis rotated counter clockwise to the pore-fractures),and the endpoint coordinates of pore-fractures wereas follows:
starting point coordinates： x0 = x − (s 2 ) cos α y 0 = y − (s 2 )sin α

end coordinates： x0 = x + (s 2 ) cos α y 0 = y + (s 2 )sin α(2)(3) The number of fractures in each group was
calculated using the following formula:S

N = S ⋅ ρ or N = S ⋅ d(3)

Where: N is the number of fractures; ρ is surface

density of fractures; S is the generating domain area;s is the length of fractures; and d is average value offractures spacing.
2) The realization of reconstruction of thedifferent scales of pore-fissure network
According to Table 1, the average length valueof millimeter fractures is 3.315mm. Thus the size ofgenerating domain about the millimeter fractures
network can be determined to be 20 mm × 20 mm,
with the size of analysis domain being 10 mm × 10
mm. The sizes of the generating domain about
micron fractures and seepage pores were obtained by
the same method, with the sizes being 400 um × 400
um, 3000 nm × 3000 nm, respectively. Sizes of theanalysis domain about micron fractures and seepage
pores were 200 um × 200 um, 1500 nm × 1500 nm,
respectively. According to equation (3), the numbersof each group about millimeter fractures, micron
fractures and seepage pores were 40, 64 and 45,
respectively.
The Millimeter fracture network models wereshown in Figure 2.
10
8
6
4
2
0
-2
-4
-6
-8
-10
-10

-8

-6

-4

-2

0

2

4

6

8

10

Figure 2: Millimeter fracture network.

3.

PERMEABILITY PREDICTION AND
VERIFICATION ABOUT DIFFERENTSCALES OF PORE-FISSURE NETWORK

3.1 The establishment of penetration model diagram
The fluid could not flow in generating
disconnected pore-fractures, therefore, disconnected
pore-fractures should be eliminated. The method of
elimination was assigned zero (Min et al., 2004; Xu
ZhongJi., 1985; Liu et al., 2007). The intersection ofeach pore-fissure was calculated using Matlab
software, which exists in a lower triangular matrix.
While the matrix corresponding position was
assigned zero among not intersect fractures, asymmetric matrix was given by the sum of theoriginal matrix. The point of intersection was thenfound between the boundary and the pore-fractures,and the same place was assigned in anotherintersection matrix. When an intersection was
disjointed or located in boundary extension cord, thecorresponding position at the intersection matrix was
assigned zero. The boundary node matrix was placed
under the inner point of intersection, which was
combined into the new total intersection matrix.
Those not meeting the requirements of pore-fractures
were eliminated by judging the number ofintersection points of the pore-fractures. The porefractures network model diagram can be obtained byusing the pore-fractures intersection connection. The
network models are shown in Figure 3.

473

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

It can be found from the above equation that:(5)T
Where: [D] = (A1TA1 ) , [D] is inverse matrix of [D] ;5{H } = −[D ]−1 {Q}

4

−1

3

{Q} = {Q1 + A1TA H 3 }T
3

2

When H1 was calculated, equation (6) could beobtained combined with equation (4), namely:1
0

Q2 = − A2TA1T H 1 − A2TA2T H 2 − A2TA3T H 3
Q3 = − A3TA1T H 1 − A3TA2T H 2 − A3TA3T H 3

-1
-2

(6)
The size of the analysis domain was a square of
10mm × 10mm. According to Darcy's Law,permeability coefficient can be obtained as follows:

-3
-4
-5

-4

-3

-2

-1

0

1

2

3

5

4

K=

Figure 3: Millimeter seepage model.

Q L
V
Q
=
=
∇H L ∇H L ∇H

(7)
According to the relationships between
permeability coefficient and permeability, equation(8) can be obtained:

3.2 The calculation method for permeability
If the direction of water flowing in fractures was
one-way, fracture width in the coal reservoir was notchanged. Coupling effects between seepage field andstress field were ignored. According to the second
type of boundary conditions combined with the waterbalance principle, water seepage in fractures wasanalyzed by establishing a computing matrix. A twodimensional computing equation of steady flowing
was used: (Baghbanan et al., 2008; Chen et al., 2012;
He et al., 2013)

k=

Kη
ρg

(8)
Where: η is the dynamic viscosity coefficient ofwater; ρ is the density of water; g is gravitational
acceleration, and k is permeability.
3.3 The prediction and verification of permeability
The matrix equation could be calculated using
Matlab software. The permeability coefficient about
different scales of pore-fractures can be calculatedusing the matrix equation. Combined with equation(8), the permeability about different scales of porefractures can be calculated. At the same time, in orderto verify the accuracy of the predicted results,
permeability tests were carried out by collecting coalsamples in Sihe mine. The testing results and matrix
calculations result were shown in Table 2.
The average permeability was 0.56 mD. The
matrix weighted permeability was from 0.172 to
0.531
mD.

A1TA1T H 1 + A1TA2T H 2 + A1TA3T H 3 + Q1 = 0
A2TA1T H 1 + A2TA2T H 2 + A2TA3T H 3 + Q2 = 0
A3TA1T H 1 + A3TA2T H 2 + A3TA3T H 3 + Q3 = 0(4)Where: A1, A2, A3 are the convergence matrix; T theis diagonal matrix; H1 is head vector within a node(m); H2 and H3 are respectively intersection headvector in upper / lower and around bounds of themodel (m); Q1 is water sink sources within node(m3); Q2 is flow value about intersection of the upperand lower boundary of the model (m3); and Q3 isflow value around the intersection of the boundary of
the model, inflow is positive and outflow is negative(m3).

Table 2: Comparisons with experimental results and calculated results about permeability in Sihe coal samples.

SampleRocksamples
description

SH-1
SH-2
SH-3
SH-4
SH-5
SH-6

coal
coal
coal
coal
coal
coal

density3
g/cm

Effective
porosity%

millimeter
fractures

1.45
1.46
1.45
1.45
1.44
1.45

3.2
3.4
3.5
2.0
2.4
3.9

0.19
0.31
0.46
0.59
0.23
0.55

Average permeability was 0.352 mD, thecalculated results were on the same order ofPermeability(mD)
micronWeightseepagefracturecalculatio
pore
s
n
-6
0.00982.85×100.17198-50.00047 3.69×10
0.279047-6
3.3×100.414082
0.00082-5
3.6×100.531218
0.00218-6
6.1×100.20833
0.0133-5
4.5×100.495632
0.00632

Actual
test
0.28
0.39
0.42
0.75
0.47
0.83

magnitude with the experimental results. Millimeter
fractures were major contributors to the permeability,474

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.

INFLUENCE ON THE VALUES OF THE
PERMEABILITYIN
DIFFERENTSCALES FRACTURE PARAMETERS

3.1 The influence on the permeability by the densityof the fractures
The relationship between the permeability andthe density of millimeter fractures is as shown in
Figure 4.
1.8

Model
1.6

1.4

NewFunction30 (User)

Equation

a*exp(b*x)

ReducedChi-Sqr0.00135

Adj. R-Squar

0.99357

0.9
Model

0.8

a

0.11530.0111b

13.2670.53507

a*exp(b*x)

ReducedChi-Sqr4.34951E4

Adj. R-Squ

0.98617permeabilit aybStandard E

0.058

0.00799

3.014

0.16421

0.6

0.65

0.70

0.75

0.80

0.85

0.90

fissure width (mm)Figure 5: Relationships between the width of millimeter
fractures and permeability.

0.6

0.4
0.10

Value

0.4

1.0

0.8

0.7

NewFunction30 (User)

EquationStandard E（
mD）

permeability

permeability

3.3 The influence on the permeability by the width offractures
The relationship between the permeability andthe width of fractures was found by fitting. It is asshown in Figure 5.

0.5

Value
1.2

The number of nodes and connectivity increased
with increases of the length. When the length of thefractures achieves a certain value, the value of thepermeability was almost increased.

permeability (mD)followed by micron fractures, and finally seepage
pores were minimal contributors. The simulation
results were corroborated with testing results. This
paper discusses the influencing law of permeability
by different scales fractures parameters.

0.12

0.14

0.16

0.18

0.20

density（mm 2）

Figure 4: Relationships between the density of millimeter
fractures and permeability.

The diversion ability of the fractures increased
exponentially with increases of the fracture density.
Therefore, increasing density can raise connectivity
and permeability.
3.2 The influence on the permeability by the length of
the fractures
The relationship between the permeability andthe length of fractures is as shown in Table 3.
Table 3: Calculated results for permeability in different
lengths about millimeter fractures.
Fissure length Permeability coefficient Permeability(mm)(mm/s)(md)-6
2.87/3.74
4.3157×10
0.399-63.09/ 3.94
4.3749×10
0.400-63.29/4.14
4.5473×10
0.420-63.49/4.34
4.7433×10
0.441-63.69/4.54
4.7616×10
0.443-63.89/4.74
4.7649×10
0.443

The diversion ability of the fractures wasincreased with increases in the fracture width andincreases in the permeability of the coal reservoir.
The relationship between the permeability and thewidth of the fractures was exponential.
The influence laws of the main parameters of
the fractures were such that: density and width in the
millimeter fractures and seepage pores have a larger
influence on permeability, and the length has little
influence on permeability. The density and length of
micro fractures have a larger influence on
permeability, and the width has little influence on
permeability.

5.

CONCLUSIONS

According to the simulation about different
scales pore-fractures and predicting permeability, thefollowing conclusions can be made:(1) The networks for different scales porefractures were reconstructed using observation and
the Monte Carlo method. The networks can clearlyshow the connectivity between pore-fractures.
(2) The contribution order of different scales
pore-fractures on the coal reservoir permeability fromlargest to smallest are the millimeter fractures, micro
fractures, and seepage pores. The advantages ofconnected paths for different scales pore-fracturesfrom highest to lowest are millimeter fractures,
seepage pores, and micro fractures.

475

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

6.

ACKNOWLEDGEMENT

The authors thank for financial assistance inmajor projects of Henan province university scienceand technology innovation talent support program(15HASTIT050), Henan Province the high school
youth backbone teacher assistance program(2013GGJS-049),
ScienceandTechnology
Department of Henan province (142102210050),
Henan
Polytechnic
University
Funds
for
Distinguished Young Scientists (No.J2013-01) andInternational Cooperation Project of Henan Province(144300510041).

7.

REFERENCES

Barton C C. (1988). Fractal geometry of twodimensional fracture networks at Yucca Mountain,
Sputhweastern
Nevada.
In:proc.Int.Symp.on
Fundamentals
ofRock
Joints.
Rotterdam:A.A.Balkema, pp. 77-84.
BABADAGLI TAYFUN. (2001). Fractal
analysis of 2D fracture networks of geothermal
reservoirs in south-western Turkey. Journal ofVolcanology and Geothermal Research, Volume 11,
No. 2, pp. 83-103.
Baghbanan A and Jing L. (2008). Stree Effects
on Permeability in a Fractured Rock Mass with
Correlated
Fracture
LengthandAperture.
International Journal of Rock Mechanics and Mining
Sciences, Volume 45, No. 3, pp. 1320-1334.
CHEN S H and FENG X M.(2006). Composite
element model for rock mass seepage flow. Journalof Hydrodynamics: Series B, Volume 18, No. 2, pp.
219-224.
CHEN S H, HE J and SHAHROUR I. (2012).
Estimation of elastic compliance matrix for fractured
rock masses by composite element method.
International Journal of Rock Mechanics and Mining
Sciences, Volume 49, No. 1, pp. 156-164.
CUI X and BUSTIN R M. (2005). Volumetricstrain associated with methane desorption and its
impact on coalbed gas production from deep coalseams.AAPG Bulletin, Volume 89, No. 9, pp. 11811202.
Feng Zengchao,Zhao Yangsheng and Lu
Zhaoxing. (2007). Study on percolation law of 2D
porous and fractured double-medium. Acta Physica
Sinica (in Chinese), Volume 56, No. 5, pp. 27962801.
HE J, CHEN S H and SHAHROUR I. (2013).
Numerical estimation andprediction of stressdependent permeability tensor for fractured rockmasses. International Journal of Rock Mechanics andMining Sciences, Volume 59, No. 1, pp. 70-79.

He Yaoyao and Liu Jianjun. (2011). Numericalexperimental research of equivalent seepage
characteristic for fractured porous media. Advancesin Porous Flow (in Chinese), Volume 1, No. 2, pp.
17-20.
LIU Y R, ZHOU W Y and YANG Q.(2007). A
distributed memory parallel element-by-element
scheme based on Jacobi-conditioned conjugate
gradient for 3D finite element analysis. Finite
Elements in Analysis and Design, Volume 43, No.
6/7, pp. 494-503.
LU Bo, CHEN Jian-ping and GE Xiu-run.
(2005). Fractal study on the representative element
volume of jointed rock masses. Chinese Journal ofRock Mechanics and Engineering, Volume 24, No. 8,
pp. 1355-1361.
Min K B, Rutqvist J and Tsang C F.(2004) Stressdependent Permeability of Fractured Rock Masses: A
Numerical Study. International Journal of RockMechanics and Mining Sciences, Volume 41, No. 5,
pp. 1191-1210.
ODA M A. (1988). Method for evaluating therepresentative elementary volume based on joint
survey of rockmass. Canadian Geotechnical Journal,
Volume 25, No. 3, pp. 281-287.
SISAVATH S, MOURZENKO V andGENTHON P. (2004). Percolation and transport
properties of fracture networks derived from line
data. Geophysical Journal International, Volume 157,
No. 2, pp. 917-934.
Wenxue Chen, Xueqiu He, Mingju Liu, Hani
Mitri & Qian Wang (2016). Meso- and macrobehaviour of coal rock: observations and constitutive
model development, International Journal of Mining,
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10.1080/17480930.2013.878561
Xu ZhongJi.(1985). Monte carlo method.
Shanghai: Shanghai Science and Technology
Publishing House (in chinese), 324p.
ZHANG H B, LIU J S and ELSWORTH D.
(2008). How sorption-induced matrix deformation
affects gas flow in coal seams: A New FE Model.
International Journal of Rock Mechanics and Mining
Sciences, Volume 45, No. 8, pp. 1226-1236.

476

ISMS 2016

Paper No. 142

Quantitative risk assessment on large-scale oil depots of opencast coal mine
Ru Jun Wang, Shu Jiao Tong*
Key Laboratory of Major Hazard control and Accident Emergency Technology, State Administration of Work Safety,
China Academy of Safety Science and Technology, Beijing, China, 100012

ABSTRACTIn recent years, many large-scale oil depots have been built in the opencast coal mine in China. In order to preventand control major accidents of the opencast mine, it is important to assess the risk of large-scale oil depots. This
paper aims to bring about a quantitative risk assessment (QRA) method to assess the fire risk of opencast coal mines.
Firstly, risk analysis of large-scale oil depots for coal mine are made, the hazardous characters of gasoline and diesel
are described, and the risk consequences are discussed. It is found that pool fire is the most typical and serious
consequence, therefore, a mathematical model of pool fire is introduced. Furthermore, the quantitative risk
assessment (QRA) method is developed to assess the fire risk of the large-scale oil depots. The QRA method isapplied to assess the risk of a selected large-scale oil depot in a large opencast coal mine in China based on the QRA
software CASSTQRA. For the gasoline tank of 1 × 104 m3, the death, serious injury, and light injury affected radiusof a pool fire are 64.75 m, 75.66 m, and 106.86 m and the individual risk was acceptable. Finally, some suggestions
are proposed to improve the safety of the large-scale oil depots. The study is useful for the safety management andprevention of major accidents in opencast coal mines.
KEYWORDS: opencast mine; oil depot; risk assessment; QRA

1.

INTRODUCTION

With the development of the economy andsociety, China's coal industry has made remarkableachievements in recent years. The production safetyof coal mines has greatly improved. However, many
major accidents have happened in the last decades.
Many large-scale oil depot have been built in the
opencast mine in China in order to meet the demandsof the production of opencast coal mines. The
emergence of those large-scale oil depots havebrought new challenges to the safety of the opencast
coal mine. In order to prevent or control major
accidents of the opencast mine, it is important toassess the risk of the large-scale oil depots.
Risk is the sum of accident consequence and its
probability caused by the risk. It has been shown thatthe main accidents associated with large-scale oil
depots are fires and explosion of the oil tanks.
Further, as a flammable liquid, pool fire is the mostfrequent and has more serious consequences than
explosion once the gasoline and diesel oil leak in thefire dike. Based on the quantitative risk assessment,
the mathematic model of pool fire consequences is
introduced in this paper. A large-scale oil depot in an
opencast coal mine in China is assessed based on the
QRA method. Pool fire consequences such as deathradius, serious injury, and light injury radius of thelarge-scale oil depot are also calculated by the QRA
software CASSTQRA developed by the China
academy of safety science and technology. The*Corresponding author – email : tongshujiao@mail.neu.edu.cn

acceptable individual risk of the large-scale oil depot
can be drawn. Finally, some conclusions andsuggestions are proposed to improve the safety of thelarge-scale oil depots for opencast coal mines. The
results can provide a theoretical basis andmanagement guidance for government departments tomanage opencast coal mines.

2.

PROCEDURE OF QUANTITATIVE RISKASSESSMENT

Quantitative risk assessment (QRA) is a complex
and technical risk assessment method, which not only
analyzing the causes of accidents qualitatively, butalso calculates the frequency and consequence ofaccidents quantitatively. The risk result is comparedwith the existing acceptable risk standard to put
forward measures to reduce or mitigate risk. The
general procedure of QRA is shown in Figure 1.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

In viewing of the risk to the surrounding people,
facilities and environment, the acceptable individual
risk criterion of the newly-built and existing facilities
with hazardous chemical materials are defined in2014 in China (as shown in Table 1).

Data collection

Risk

Table 1: Acceptable individual risk criteria of China.

Probability

Consequenc
Protection target

Riskcal calculation（R=P×C）

Risk assessment

Assessment results

Figure 1: Procedure of quantitative risk assessment.

Individual risk is the key quantitative index of thequantitative risk assessment. The so-called individual
risk refers to the risk of a variety of potential fire,
explosion, and toxic gas leakage accidents caused bya fixed position in the region of a fixed position of
the individual probability of death, which is theindividual mortality. It is usually shown as a risk
contour line (as shown in Figure 2), which canmeasure the size of an individual risk via acomparison with an acceptable risk criteria.

Low density areas（person
number <30）: Single or asmall amount of exposure
persons.
High density residential
places (30 ≤ person number <100): residential areas, hotels,
resorts etc.
Public gathering places withhigh density (30 ≤ person
number < 100): office,shopping malls, restaurants,
entertainment etc.
High sensitive places: schools,
hospitals, kindergartens,
nursing homes, prisons, etc.
Important goals: militaryforbidden zone, military
management area, cultural
relics protection unit, etc.
Special high density sites( person number ≥ 100): large
stadiums, transportation hub,open-air market, living district,hotels, resorts, offices, shopping
malls, hotels, entertainment
venues.

Individual acceptablerisk criteria(probability)
NewlyIn-service
built
facilities
facilities
（per
（per
year）≤
year）≤
1×10-5

3×10-5

3×10-6

1×10-5

3×10-7

3×10-6

Seen from the Table 1, for the existing facilities,
the acceptable individual risk cannot exceed 3 × 105/year in the low density areas, 1 × 10-5/year in highdensity residential places and public gathering places
with high density, and 3 × 10-6/year in high sensitive
places, important goals and special high density sites.
For the newly-built facilities, the acceptable
individual risk cannot exceed 1 × 10-5/year in the low
density areas, 3 × 10-6/year in high density residential
places and public gathering places with high density,and 3 × 10-7/year in high sensitive places, importantgoals and special high density sites.
Figure 2: Sketch map of individual risk contour line.

478

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3. MATHEMATICAL MODEL OF POOL FIRE
FOR OIL DEPOTS
3.1 Mathematical Model of pool fire
When the boiling point of the combustible liquidin the liquid pool is higher than the temperature of
the surrounding environment, the velocity of
combustion of the unit area on the surface of theliquid pool can be expressed by equation (1).

t

r =(

9πρ
32 gQ0

3（1）
When the boiling point of the flammable liquidin the liquid pool is lower than that of the ambient
temperature, the velocity of combustion of the unit
area on the surface of the liquid pool can be expressedby equation (2).
（2）

Where,

H c ——Combustion heat of combustible liquid,
j/kg；

Cp

1

 πρ  2 8 gQ （4）
For continuous leakage, the liquid pool radius
can be expressed by equation (5).

0.001H cdm=
dt C p (Tb − T0 ) + H

dm 0.001H c
=
dt
H

t

r=

——Constant pressure specific heat of liquid,j/kg·°K;

3)4

r ——radius of liquid pool, m;
S ——Area of fire dike, m2;
ρ ——Density, kg/m3;
g ——Acceleration of gravity, 9.8m/s2;
Q ——leakage amount, kg;

Q0 ——leakage velocity, kg/s.
And then, the total heat flux from the liquid poolcan be expressed as Eq(6).
dmdm
E = (πr 2 + 2πrh) ηH c [( ) 0.61 + 1]
dt
dt
（6）
Where,

Tb ——Boiling point of liquid, °K;η ——efficiency factor, 0.13～0.35；

T ——Ambient temperature, °K;
H ——Liquid steam heating, j/kg.

h ——flame height, m;

For analysis, it is assumed that the liquid pool isround. If the liquid has reached the artificial boundary,
the liquid pool area is the area of the artificial
boundary, and the radius of the liquid pool can be
expressed by equation (3).

r=

（5）

Where,

Assuming that all the radiation heat is emitted
from a small spherical surface of the center of theliquid pool, the heat radiation intensity at a distancefrom the center of the liquid pool can be expressed byequation (7).

I=

S

π

（3）
Because of the dangerous goods transportation
accidents occurring in the road and the leakage ofliquid usually without an artificial boundary, it isassumed that liquid to leaks as a cylindrical flatsmooth surface toward the outer edge of the diffusion.
At this time, the area of the liquid pool is changed
with time, and the radius of the liquid pool can becalculated according to the following method.
For instant leaks, the pool radius can be
expressed by equation (4).

Et c
4πx 2

（7）

Where,

E ——total heat radiation flux, w;
t c ——air coefficient of thermal conductivity;
x ——object point to the center distance of theliquid pool, m.
Therefore, for the pool fire situation, personnel
and equipment under the influence of different
damage effects can be expressed by equation (8).

x=

Et c
4πI

（8）

Where,

x ——Pool fire damage distance, m;479

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

I ——the criteria for judging the damage, w/m2.

Figure 4.1: Influence area of pool fire of diesel oil tank(each 2 × 104 m3).

3.2 Influence Area Analysis
Generally, the affected area can be divided into thedeath radius, serious injury, and light injury radius.
The influence radius is the threshold distance of theoil fire accident, which experiences the consequencesof death, environmental pollution, property loss, etc.
Therefore, the influence area of large-scale oil depots
is a certain threshold distance from the surrounding.
The closer to the oil tank or depot, the higher the riskof the impact of an accident.
4.

CASE STUDY
In this paper, a large-scale oil depot of a large
opencast coal mine is taken as a case to study the risk
assessment. There are 9 oil tanks in the large-scale oil
depot, two gasoline tanks (each 1 × 104 m3) and sevendiesel oil tanks (each 2 × 104 m3). Aiding with the
QRA software CASSTQRA, the affected area andindividual risk are shown as the following figures.

Figure 4.2: Influence area of pool fire of diesel oil tank(each 2 × 104 m3).

The individual risk contour line of the largescale oil depot can be drawn as Figure 5.

Figure 5: Individual risk contour line of the large-scale oil
depot.

Figure 3: Influence area of pool fire of gasoline tank (each1 × 104 m3).

For the influence area (Figures 3-5), the red lineis the death area, the blue line is the serious injury
area and the green line is the light injury area. For theindividual risk (Figure 5), the red line is 3 × 10-5, theyellow line is 1 × 10-5, and the blue line is 3 × 10-6.
5. CONCLUSIONS
Quantitative risk assessment (QRA) is a complex
and technical risk assessment method to assess therisk of large-scale oil depots for opencast coal mines.
The pool fire is the most frequent and serious
consequence, followed by explosion once the oil has
leaked in the fire dike.
For the gasoline tank of 1 × 104 m3, the death,serious injury and light injury affected radius of apool fire were 64.75 m, 75.66 m, and 106.86 m,
respectively. For the diesel oil tank of 2 × 104 m3

480

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

gasoline, the death, serious injury, and light injury
affected radius of a pool fire were 78.61 m, 88.72 m,
and 120.13 m, respectively. For the diesel oil tank of
1 × 104 m3, the death, serious injury, and light injury
affected radius of a pool fire were 53.43 m, 63.75 m,
and 85.59 m, respectively.
All the individual risks were acceptable.
However, some of the facilities may be affected by
the pool fire of the large-scale oil depots, therefore,
the opencast coal mine should take effective measures
to avoid the risk of pool fire.

6. ACKNOWLEDGEMENT
The research work was supported by National
Science and Technology Foundation of China underGrant No. 2015BAK16B03 and Basic Science andTechnology Foundation of CASST under Grant No.
2016JBKY12.

7. REFERENCES

Pre-warning System, Journal of China Safety Science20, p.171.
Majid, ZA., Mohsin, R. (2012). Failure
Investigation of Natural Gas Pipeline, Arabianjournal for Science and Engineering 37, p.1083.
Paeka H.J., Hilyard K. (2010). Theory-BasedApproach and Understanding Public Emergency
Preparedness: Implications for Effective Healthand Risk communication, Journal of HealthCommunication: International Perspectives, Volume
15, No. 4, pp. 428-444.
Palacios, A., Munoz, M., Casal, J. (2009). Jet
Fires: An Experimental Study of the Main
Geometrical Features of the Flame in Subsonic andSonic Regimes, AIChE Journal 55, p.256.
Wu Z.Z, Liu M. (2000). Risk assessment method,
Chemical Industry Press, pp. 38~69.
Young, Do Jo, Bum, Jong Ahn. (2005). A
method of quantitative risk assessment fortransmission pipeline carrying natural gas, Journal ofHazardous Materials 123, p. 1.

Baozhi Chen. (2011). System safety assessmentand forecast (the second edition), MetallurgicalIndustry Press, Beijing.
Boling Zhu, Xiaochun Yu. (2009).. Research for
PHAST in the process of liquefied natural gas
discharge and dispersion, Computers and Applied
Chemistry 26, p.1418.
Cumber, PS. (2009). Efficient calculation of theradiation heat flux surrounding a jet fire, Fire Safety
Journal 44, p. 580
Deming Yu. (2000). Quantitative risk assessment
to the storage and transportation process of theinflammable, explosive and toxic dangerous goods,
China Railway Press, Beijing.
Gomez-Mares, M., Munoz, M., Casal, J. (2009).
Axial temperature distribution in vertical jet fires,
Journal of Hazardous Materials 172, p. 54.
Han, Z.Y, Weng, W. G. (2011). Comparison
study on qualitative and quantitative risk assessment
methods for urban natural gas pipeline network,
Journal of Hazardous Materials 18, p. 509.
Hapue C.E., Burton I. (2005). Adaptation
Options Strategies for Hazards and vulnerability
Mitigation: An International Perspective, Journal of
Mitigation and Adaptation Strategies for Global
Change , Volume 10, No. 3, pp. 335～353.
Hong L, Wang H.P. (2009). Evaluation of
emergency management level mutation theory of coalmine emergency, Journal of Coal Mine Safety,
Volume 6, No. 1, pp. 111-113.
Jianguo Ren, Shunqing Lu. (2006).. Applicationof Gas Diffusion Mathematical Model to Safety
Assessment, China Safety Science Journal 16, p. 12.
Ma, Lei, Li, Yongshu. (2010). Research andRealization of Urban Natural Gas Pipeline Network

481

Paper No. 175

ISMS 2016

Development and realization of a coal and gas outburst simulation device
NIE Baishenga,b, HU Shoutaoa,b,*, LI Xiangchuna,b, MENG Junqinga,b, FAN Penghonga,babState Key Lab of Coal Resources and Safe Mining, China University of Mining and Technology(Beijing), Beijing, China 100083
School of Resource & Safety Engineering, China University of Mining and Technology(Beijing), Beijing, China, 100083

ABSTRACT
Similar coal and gas outburst simulation devices both at home and abroad are analyzed and their advantages anddisadvantages are examined. A large size experimental device of coal and gas outburst simulation is developed basedon the congeneric testing device. This device consists of coal and a gas outburst model system, gas injection system,
loading system, stress measurement system, gas pressure measurement system, temperature measurement system,
electromagnetic radiation testing system, and high-speed photography system. The functions of the device are as
follows: (1) to study the laws of roof break development and stress evolution during outburst process by simulating
coal seam, roof and floor with similar material, (2) to simulate stress distribution of a roof at high strength springs ofdifferent sizes, (3) to realize the uniform adsorption in coal by 3 gas injection pipes that are pre-buried, (4) to induce
coal and gas outburst at predetermined gas pressure by blasting bursting disc instantly that set on the outburst hole, (5)to observe and record fracture and migration process of coal in the cavity during outburst that is achieved by a visualglass window on the side of cavity.
KEYWORDS：coal and gas outburst; testing device; similar simulation; gas pressure; ground pressure

1.

INTRODUCTION

Coal and gas outburst is a kind of complicateddynamic instability tbat occurs in underground coalmines (Hu Qianting et al., 2007). Most researchers study
the mechanism of coal and gas outburst throughlaboratory simulation because of the danger involved intracking studies of real coal and gas outburst occurringin coal mines. The one dimensional outburst simulation
tests were conducted firstly in Soviet Union in the 1950s(Аируни, 1955). The results showed that the coal can be
broken and thrown only under conditions of great gas
pressure gradient. In the beginning of the 1960s,
Japanese scholars conducted a simulation test of theejection of coal through a shock tube (SHI Ping, 1985).
In the test, ice crystals of carbon dioxide, rosin, cement,
and coal particles were used to make a model. Driving
was also simulated. Adsorption performance of themodel varied wildly from the coal. Researchers believethat the degree of metamorphism, the diffusion
coefficient, permeability, and porosity are closed relatedwith coal and gas outburst, as shown throughexperiments and theoretical analysis (Beamish BB,
Crosdale PJ., 1998, Sobczyk J., 2011). Norbert
Skoczylas conducted an externally induced outburst test
and the results showed that the intensity of outburst isaffected by unloading time (Norbert Skoczylas, 2012).
In China, many universities and research institutes
such as Shenyang Branch of China Coal ResearchInstitute, Institute of mechanics of China Academy of
Sciences, China University of Mining and Technology,*Corresponding author – email: hst510@163.com

Henan Polytechnic University, and Chongqing
University furthered the research of coal and gas
outburst by developing different simulation test devices.
Deng Quanfeng et al. (1989) simulated the coal and gas
outburst of Ⅳ, Ⅴ coal induced by rock cross-cut coal
uncovering, and the coal model was conducted without
any additive agent. Jiang Chenglin (1994; 2003)
simulated the coal and gas outburst of Ⅳ , Ⅴ coalinduced by rock cross-cut coal uncovering with a one
dimensional outburst simulation test. Meng Xiangyue etal. (1996) conducted many tests using a
two-dimensional simulation test device, and the results
showed that the destruction of coal exists with“dehiscence” and “outburst”. Cai Chenggong (2004)
designed a three dimensional simulation test device
based on the similarity theory and mechanical model. A
mathematical model of the relationship between theintensity of outburst and gas pressure, coal forming
strength, three dimensional stress, and gas pressure wasestablished. The simulation condition between briquette
outburst and real coal seam outburst was put forwardand dimensionless parameter criterion of outburst wasestablished based on the comprehensive function
hypothesis of outburst and similarity theory by Zhang
Jianguo (Zhang Jianguo and Wei Fengqing, 2002). Thechange trend of temperature in the process of outburst
was analyzed by Guo Liwen (Guo Liwen et al., 2000).
The research team of Yin Guangzhi and Xu Jiang
developed a comprehensive simulation device. In thisdevice, different forming stress, different loading stress,
different loading form and different diameter of outburst

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

can be simulated for coal and gas outburst simulation
tests. The cusp catastrophe instability model of creep
fracture of coal containing gas based on testing machineand specimen system was established (Xu Jiang et al.,2008; Wang Dengke, 2009; Tao Yunqi, 2009; Ying
Guangzhi et al., 2009). Wei Chunfu et al. (2014) studied
the gas pressure effect in coal and gas outburst through aself-designed coal-rock gas dynamic disaster simulation
test system. Wang Zhirong et al. (2014) discussed themechanism of delayed outburst in “three soft” mining
area through establishing nonlinear viscoelas to plastic
rheological model of soft coal containing gas. Wang
Gang et al. (2015) established a model of energy
conditions for outburst and a prediction model for
outburst intensity.

installed at the outburst hole. Coal and gas outburst canbe induced through fast blasting of blasting sheet at aprescribed gas pressure.
The design idea of a coal and gas outburst
simulation device is shown in Figure1.

loading stress
gas
inj
ect
ion

coal seamgas injection pipelinefloor

2. THE DEVELOPMENT IDEA AND PURPOSE
2.1 The development idea
In the light of deficiency of current coal and gas
outburst devices, the development ideas of thesimulation test device are as follows:(1) The simulation test device is a large size device.
The roof and floor of coal seam can be simulated bysand, quartz sand, gypsum and other aggregate, fromwhich development of cracks in the roof and evolutionof stress after and during the process of coal and gas
outburst can be analyzed.
(2) The change of various physical parameters isvery important for the research of outburst. Physicalparameters such as coal temperature, gas pressure, stress,
strain, and acoustic signal need to be collected in the test.
This function will be realized by a variety of sensors andenameled wire.
(3) The simulation of real roof stress distribution ofcoal in front of mining face is always a difficult point insimulation tests. In this device, a series of springs are
installed between the loading piston and the top of theroof. And the size and specifications of springs need tobe calculated by real roof stress distribution of coal infront of mining face.
(4) This device should simulate coal and gas
outburst under different condition such as different
stress, different gas pressure, different loading form, anddifferent diameter of outburst. In addition, the process ofoutburst can be record by high-speed camera. So theobservation windows need to be installed at the device
for the recording of the high-speed camera.
(5) The gas can be aerated and adsorbed evenly inthe coal sample. To insure the gas can be aerated andadsorbed evenly in the coal sample, three inflatable
tubes will be curried evenly in the coal sample in theprocess of coal forming. Some small holes will be
drilled at the inflatable tubes for the inflow of gas into
the coal sample.
(6) Blasting sheet and clamping device need to be

roof

1000mm

10
00
mout
mbur
st
hol
60 e
0

Figure 1: The design idea of a simulation device.

2.2 The development purpose
This test device is designed to simulate coal andgas outburst. Outburst process under conditions such as
different forming stress, loading stress, gas pressure,loading form, thickness of coal seam, roof and floor
conditions, and diameter of outburst is researched using
this device. The stress, temperature, roof strain, gaspressure, acoustic parameters in the process andmigration law, size classification, and distribution
characteristics of the coal sample after outburst arestudied in order to study the mutual coupling effect ofstress, gas pressure, and the physical and mechanicalproperties of coal and its comprehensive mechanism foroutburst. The coal and gas outburst mechanism can berevealed based on a comprehensive mechanism (Wang
Jiren et al., 2008, Zhang Yugui et al., 2007).

3.

THE DESIGN OF THE SIMULATION
DEVICEThe outburst simulation device consists of theoutburst model system, vacuum pumping and gas
injection system, stress loading system, stress testing
system, gas pressure testing system, temperature testing
system, the electromagnetic and radiation measurement
system, high speed photography system ,and the dataacquisition, control and processing system. A system
diagram of the coal and gas outburst simulation deviceis shown in Figure 2.

483

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

12

11
3.2

stress testing
system100

70

hydraulicpower packgas pressure
testing system

vacuum pumping andgas injection system

22

outburst
hole

AE and EME
testing system

Vacuumvalve

vacuum
meter

21
3.2

Hydraulic cylinder

tempareture
testing system

2ZX-4Z Vacuum
pump

3.2

loading systemcomputer8¡ã-0.2

data acquisition andprocessing system coal and gas outburst model systemhigh speed
photography system323

gas-filled tube
1620

vacuumcontainer

intake pressure
valve regulating valve

3

2

1

20

Figure 2: System diagram of simulation device.

3.2

5

4

6

7

8

11

(b) Side view of simulation test device

826

13

120

30

20

1620
1870

24

23

25

22

26

(c)Top view of simulation test device
1-vacuum interface 2-charging port 3-patch board 4-big press
plate 5-hydraulic piston 6-piston base 7-upper cover plate
8-sealing ring of upper cover plate 9-spring group 10-guiding
mechanism of spring 11-small press plate 12-sealing ring offront cover plate 13-fixing mechanism of observing window
14-glass observing window 15-inner flange of outburst hole
16-outer flange of outburst hole 17-clamping device of
blasting sheet 18-blasting sheet 19-differential pressure sensor
20-floor 21-front supporting plate 22-inner front cover plate23-outer front cover plate 24-the left side plate 25-the rear sideplate 26-the right side plate

360

3-¦ µ
200

3.2

The cavity size of outburst model system is 1500
mm x 600 mm x 1000 mm. The various physicalparameters are tested through sensors such astemperature, gas pressure, stress cell, electromagnetic
radiation, and acoustic emission and so on. The roof andfloor of the coal seam can be simulated using similarity
material. A series of springs are installed between theloading piston and the top of the roof to simulate the realroof stress distribution of coal in front of mining face.
The front cover plates consist of two layer cover plates.
The outboard plate is used for sealing. The inboard
plates consist of five small plates, which are used forcompression molding of coal, roof, and floor. The heightof the small plate is 20 cm. Blasting sheet and clamping
devices need to be installed at the outburst hole. Coaland gas outburst can be induced through fast blasting of
the blasting sheet at a prescribed gas pressure. Threeobservation windows are installed on the device for therecording of the high-speed camera. Three inflatable
tubes are be curried evenly in the coal sample in theprocess of coal forming. A structure diagram andphysical diagram of the coal and gas outburst simulation
device are shown in Figure 3 and 4.

120

20

8¡ã-0.2

1490

Figure 3: Structure diagram of coal and gas outburst
simulation device.

80

9
10
11

28*M42*3
深90

3

1980

R30

R20

4.

12

O型圈槽1780*Φ10

15
16

80 120

¦ µ
200
¦ µ
300

17

50 1201390
1，21290(215*6)

13
14
34-M24

18

19

R31

225

1320(6*220)
1660
1870

225

Front view of simulation test device(a)

THE TEST CASE

Two successful tests were conducted through coaland gas outburst simulation test device. The coalsamples were from 2# coal seam in Zhenxing Er coalmine and 2# coal seam Dashucun coal mine. The coalsamples were crushed into a 1mm particle size, in thelaboratory. The floor was laid by similarity material.
The molding stress was 20 MPa, and the loading stress
was sustained for 30 min. The crushed coal sample wasplaced into the cavity layer by layer. The molding stressis 20 MPa, and the loading stress was sustained for 30

484

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

min. The roof was laid by similarity material. The
molding stress was 20 MPa, and the loading stress was
sustained for 30 min. In the two tests, the weights of thecoal sample and similarity material are 1109 Kg and
1186 Kg, respectively. After the model was completed,
it was dried for fifteen days. After leakage detection was
successful, the cavity was vacuumed. Carbon dioxidewith 99.99% concentration was aerated into the cavity,
and adsorption equilibrium was ensured. Adsorption
equilibrium pressure was 0.4 MPa and 0.6 MPa,
respectively. The time for adsorption equilibrium was 7days and 13 days. The blasting pressure of the blasting
sheet was 0.5 MPa and 0.74 MPa. After adsorption
equilibrium, gas was aerated to the blasting pressure
continuously and blasting sheet bursts and the outburst
occurred. The state diagram during the coal and gas
outburst experiment and the distribution of the coalsample after coal and gas outburst are as shown in
Figures 5 and 6.

of the outburst hole was the symmetry axis. The farthest
ejection distance of sample from the outburst hole was
41.4 m and 49.5 m, respectively.

5.

6.

Figure 5: The state diagram during coal and gas outburst
experiment.

Figure 6: the distribution map of coal sample after
outburst.
The results were as follows:(1) The weight of coal sample and rock sample thatwas ejected outside the cavity was 369.9 Kg and 373.6
Kg respectively in the two tests.
(2) The shape of the outburst hole was pear-shapedwith a small opening and big cavity.
(3) The coal sample and rock sample that wereejected outside the cavity present obvious sorting
features. The sample with big particles was near theoutburst hole and the sample with small particle was far
from the outburst hole.
(4) The sample which was ejected outside showedaxisymmetric fan-shaped distribution and the center line

CONCLUSIONS

Development, purpose, ideas, and scheme designof a coal and gas outburst similar simulation device
were introduced in detail based on similar devices athome and abroad. The functions are as follows:(1) To study the laws of roof break development
and stress evolution during outburst process by
simulating coal seam, roof and floor with similarmaterial. (2) To simulate stress distribution of a roof athigh strength springs of different sizes. (3) To realize theuniform adsorption in coal by three gas injection pipesthat were pre-buried. (4) To induce coal and gas outburst
at a predetermined gas pressure. (5) To observe andrecord the fracture and migration process of coal in thecavity during outburst, achieved using a visual glass
window on the side of the cavity.

REFERENCES

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аэолгии лабораия внзапных выбросов утляигаза.
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Beamish BB, Crosdale PJ. (1998). Instantaneous
outbursts in underground coal mines:an overview andassociation with coal type. International Journal Coal
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CAI Chenggong. (2004). Study on three
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DENG Quanfeng, LUAN Yongan, WANG Youan.
(1989). Experimental study of simulation of coal andgas outburst.Safety in Coal Mines, volume 11, pp. 5–10.
GUO Liwen, YU Qixiang, JIANG Cheng-lin, at el.
(2000).Experimental study of temperature change in theprocess of coal and gas outburst. Journal of RockMechanics and Engineering, 19(3), pp. 366–368.
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JIANG Chenglin. (1994). The research of shell
instability mechanism of dynamic phenomenon in theprocess of rock cross-cut coal containing gas
uncovering. Xuzhou: China University of Mining andTechnology, pp. 62-63.
JIANG Chenglin. (2003). Study of forming
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MENG Xiangyue, DING Yansheng, CHEN Li, at el.
(1996). Study on two dimensional simulation
experiment of coal and gas outburst. Journal of China
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Norbert Skoczylas. (2012). Laboratory study of thephenomenon of methane and coal outburst. International
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55, pp. 102-107.
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SHI Ping. (1985). Study on model and theory ofcoal and gas outburst mechanism. The 21st international
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Sobczyk J. (2011). The inﬂuence of sorption
processes on gas stresses leading to the coal and gas
outburst in the laboratory conditions. Fuel, volume 90,
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TAO Yunqi. (2009). Study on the gassy coal thm
coupling model and coal and gas outburst simulation.
Chongqing: Chongqing University, pp.73-72.
WANG Dengke. (2009). Research on constitutive
models and instability rules of gas-saturated coal.
Chongqing: Chongqing University, pp.56-57.
WANG Gang, WU Mengmeng, WANG Haiyang, atel. (2015). Sensitivity analysis of factors affecting
coaland gas outburst based on a energy equilibrium
model. Journal of Rock Mechanics and Engineering,34(2), pp. 238-247.
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WANG Jiren, DENG Cunbao, DENG Hanzhong.
(2008). Study on microscopic mechanism of coal andgas outburst. Journal of China Coal Society, 33(2), pp.
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WANG Zhirong, SUN Lingxia, SUN Long. (2014).
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face in “three soft” mining area. Journal of China
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WEI Chunfu, LI Huamin, YUAN Ruifu. (2014).
Gas pressure effect in the process of coal and gas
outburst. Coal Geology & Exploration, 42(6), pp.24-28.
XU Jiang, TAO Yunqi, YIN Guangzhi. (2008).
Development and application of coal and gas outburst
simulation test device. Journal of Rock Mechanics andEngineering, 27(11), pp. 2354-2362.
YING Guangzhi, ZHAO Hongbao, XU Jiang, at el.
(2009). Experimental study of simulation of coal andgas outburst. Journal of Rock Mechanics andEngineering, 28(8), pp. 1674-1680.
ZHANG Jianguo, WEI Fengqing. ( 2002). The
experiment of coal and gas outburst of coal seamcontaining gas. Mining Safety & Environmental
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ZHANG Yugui, ZHANG Zimin, CAO Yunxing.

(2007). Deformed coa structure and control to coal-gas
outburst. Journal of China Coal Society, 32(3), pp.
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486

ISMS 2016

Paper No. 191

The distribution and origin of hydrogen sulfide abnormal enrichment coalmines in China
Deng Qigena,b*, Liu Mingju a,b, Zhang Saia, Cui Xuefeng a, Wen Jiejie aaSchool of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo, China, 454003
State Key Laboratory Cultivation Base for Gas Geology and Gas Control (Henan Polytechnic University), Jiaozuo, China,
454003b

ABSTRACT
Coal mines that contain hydrogen sulfide (H2S) are widely distributed in China. At present they are mainly locatedin Zaozhuang in east China, Xin'an, Anyang, and Shuangfeng in central China, Qinshui basin, Taiyuan - Liulin andWuhai in north China, and Tongchuan-Xianyang area in northwestern China, as well as places such as Shizuishan,
Houdon, Changji, Liuhuanggou, and Sikeshu which belong to Xinjiang, mainly in northwest China. These coalmines are showing a rapid increase. The contents of H2S in coal mines has changed greatly, from 10 ppm to 5000
ppm. The abnormal coal seams are mainly distributed in the Permian Longtan Formation of southwest China,
Permian Shanxi Formation and Carboniferous Taiyuan Formation of east, north and central China, and Jurassic
Xishanyao and Yan'an Formation of northwest China. The abnormal areas have a favourable overlying strata, andthe hydraulic connections between the underground water and other aquifers are weak, therefore, they are good thickreservoir-seal combinations, which are beneficial to the origin of Bacterial Sulfate Reduction (BSR) or
Thermochemical Sulfate Reduction (TSR). The main origin of H2S in coal mines are BSR or TSR, and the origin
model can be identified synthetically via the tectonic evolution, coal thermal evolution history, isotopic
characteristics of carbon and sulfur, methane gas component testing, sulfate sources, and sulfate-reducing bacteria
activity features.
KEYWORDS: coal mine; hydrogen sulfide; distribution; origin; BSR; TSR

1.

INTRODUCTION

Disasters and the potential hazards caused by theabnormal enrichment of hydrogen sulfide (H2S)
frequently occur in coal mines in China as well as
abroad. In recent years, more than 30 sudden releasesof H2S has been recorded in 10 provinces in China,
such as in Guizhou, Sichuan, Shandong, Henan,
Shanxi, Shaanxi, Inner Mongolia and Xinjiang, etc.
These incidents have caused more than 20 casualties.
In addition, a considerable number of coal mines
experiencing the abnormal enrichment of the lowcontent of H2S do not cause serious casualties, andthus do not call up widespread concern. H2S acts as akind of potent nerve poison upon contact. The main
target organs, on which its toxicity has an effect, arethe central nervous system and the respiratory
system. The tissues that are the most sensitive to thetoxicity are the brain and the contact sites of mucous
membranes, thus, H2S can cause systemic poisoning,or even respiratory arrest (Ma et al., 2008; Liu et al.,2011). In the long term, it poses a serious threat to theminers' occupational health and safety. Therefore,
conducting research like geological surveys,
distribution characteristics, and causes of coal mines*Corresponding author – email : dengqigen@hpu.edu.cn

that are rich in H2S is an urgent issue and has
important significance.
2.

DISTRIBUTION OF COAL MINES OF
HYDROGEN SULFIDE ABNORMALGATHERING IN CHINAIn China, coal mines that are rich in H2S are
widely distributed. The statistics concerning partial
coal mines containing H2S are as shown in Table 1.
Table 1: Distribution characteristics of hydrogen sulfide
abnormally accumulated in China’s coal mines.
Coal
Reserv H2SS
R0 Abnorm
formingoir (ppm(%)
environme(%) al zone
layer
)
nt
Xintian ofLongta3.50~ Drilling
Sealand
20 0.98~7.91
Guizhun3.80 process
WorkinLongtanMarine Longta
1.44~1300 2.14~4.52
gof Sichuan faciesn
1.88
surface
Guang’an Marine Longta
1.21~ Aquifer
2500 2.01~5.26
of Sichuan faciesn1.79 of roof
WorkinAnyang of Littoral
1.94~
Shanxi -- 0.51~0.98
g
zone
3.22
Henan
surface
Xin’an of Littoral Shanxi -- 1.80~2.30 1.02~ Drilling
Coal
mines

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Henan
Cuizhuan
g of
Shandong
Shandong
Bayi
Xiqu of
Shanxizone
SealandSealandSealand

2.32

processⅢ
0.65~
Shanxi 5000 0.65~0.83
mining1.25
area
0.59~ Well
Shanxi 1500
2.68
1.24
area
WorkinTaiyuaLow0.98~350gn
medium 1.60
surface

Wuda of0.81~ Mining
TaiyuaInner
Sealand
400 1.56~6.69
1.22
area
n
Mongolia
Xishan of Continent- Xishan
Low0.64~ Mining
1500
Urumqi al facies
yao
medium 0.79
areaWorkinTingnan
0.51~
Sealand Yan’an 56 0.13~2.90
gof Shaanxi
0.72
surface

Currently, the known coal seams that containhigh levels of H2S mainly are Permian Longtan
Formation in southwest China, Permian Taiyuan andCarboniferous Shanxi Formations which are in east,
north, and central-south China, and Jurassic
Xishanyao and Yan'an Formations in northwest
China. Xinjiang is not only the region with the mostcoal mines that contain H2S in China, but also theregion which has the largest number of mines with anabnormal gathering of H2S in China. In China, mostcoal mines are hydrogen sulfide-bearing gas
reservoirs or micro hydrogen sulfide-bearing gas
reservoirs (Dai, 1985).
3.

CHARACTERISTICSOFTYPICAL
HYDROGEN SULFIDE ABNORMALGATHERING COAL MINES IN CHINA

The three necessary conditions for the
production of BSR are plenty of organic matter,abundant sulfates, and conditions that suit sulfate
reducing bacteria to grow and reproduce (Machel,
2001; Cai et al. 2003; Oayer, 1999). The δ34S valueof H2S in the coal mines mainly depends on thecharacteristics of sulfur isotopic composition of thesulfur source itself, the abundance of sulfur in thesulfur source, and the genesis model of H2S in the gas
generation medium. The δ34S value of H2S and pyrite
is generated by BSR, as the alienation effect ofsulfate-reducing bacteria can result in the large-scalesulfur isotope fractionation, so the isotopic
composition of this sulfur is usually negative. The
fractionation of the H2S δ34S value usually can reachthe range of -30‰ - -15‰, which is generally around20‰ lower than the sulfur isotope of sulfate.
Accompanying H2S, the CO2 gas component isgenerally lower, usually less than 5%. The carbon
isotope of CO2 has a lighter characteristic and theδ13CO2 value is generally less than -5‰. The shape ofthe byproduct (pyrite) generated by BSR is generally
spherical berry. The main hydrocarbon component inmethane gas is CH4. The CH4 usually has biogenic
features and its accompanying hydrocarbon may have
many heavy hydrocarbon components (C2+). The
generation and preservation reservoirs of H2S may
have traces of biological effects.
The three basic conditions for the origin of TSR
are the higher temperature that coal and rock strata
experience, plenty of hydrocarbon organic matter,and the abundant supply of sulfates (Liu et al. 2011;
Machel, 2001; Cai et al., 2003; Oayer, 1999; Zui etal. 2006). The δ34S value of H2S generated by TSR is
usually larger. The sulfur isotopic compositions of
H2S are slightly less than or equal to the δ34S value ofthe homologous sulfate, and the δ34S value of H2S isgenerally between 10‰ and 20‰. The coal and rockstrata generally experience environments of hightemperatures above 120°. Accompanying H2S, thecarbon isotope composition of CO2 is heavier andusually around 0‰. It is often similar to the carbon
isotopic composition of carbonates in strata. The
shape of pyrite generated by TSR is usually cubic orcolumnar. Since TSR is a process which gives priority
to the consumption of heavy hydrocarbons, the drycoefficient of the methane gas is usually higher. The
content of heavy hydrocarbons in the gas is less, but
the content of non-hydrocarbon generally increases.
3.1 Characteristics of H2S in Xiqu coal mine of
Shanxi Province
The location map of Xiqu coal mine of Shanxi
Province is shown in Figure 6. The No. 9 coal seam
is located at middle and lower part of the Taiyuan
formation and is high grey, medium-low sulfur. The
average sulfur content in raw coal is 1.37%. The
main type of coal is coking coal, and the averagevalue of the maximum vitrinite reflectance of coal(Ro,max) is 1.60% (Liu et al. 2012). The roof and floor
is mostly sandy shale or mud sandstone. The
abnormal area of H2S in the No. 9 coal seam islocated in a wide and gentle folding wing of the19101 and 19102 working face in the south panel. It
presents the zonal distribution and its width is about
400 m. In the leeward side of the mining machine,
the maximum concentration of H2S measured is up to
350 ppm[10]. In the gas produced by spontaneous
combustion of the ground coal gangue piles, thecontent of H2S reaches 89 ppm (Zeng et al. 2012).
Within the area of the above two working faces, thegeological structure is simple and it has no faults
collapse column, but in the northwest side of thefaces, it develops a large number of faults andcollapsed pillars. The biggest slip of fault is 5.0 m
and the slip of the small secondary fault is in therange of l.0 m - 2.0 m. The inside of the collapsed
pillars which formed in Yanshan movement period
are often found to be filled by the later generated488

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

epigenetic calcite and pyrite crystals. The subsided
columns are finely cemented, and less permeable towater in the deep.
The overlying seam of the abnormal area of H2S
in the No. 9 coal seam is the gob area of No. 8 coalseam whose thickness is 8 m – 12 m. The averagesulfur content in No. 8 coal seam is 2.57% (pyrite
accounts for 1.58%, organic sulfur accounts for
0.98%) (Song et al., 2000). The distribution of Pyrite
is in an irregular grain shape (tetrahedral) andmouldiness. The roof of No. 8 coal seam is composedof limestone, mudstone, carbonaceous mudstone or
sandy mudstone. Its floor is composed of sandy
mudstone or shale, and some is carbonaceous
mudstone or sandstone.
The groundwater of coal mine is acidic, where
sulfate ions are abundant and the content is up to1928.9 mg/L, much higher than that in other water
bodies, such as the deep groundwater and the Fen
River Reservoir (Yang et al., 2013). The content of
Na+ increases significantly, and the content of HCO3declines dramatically. The total hardness of water ishigh and the type of water is Na-Ca-SO4.
Sulfate-reducing bacteria reduction is a process
which consumes sulfate ions constantly. The processthat generates H2S is as shown by formulas (1) and(2) (Cai et al., 2003; Oayer et al., 1999; Pan et al.
1992; Rye, 2005; Dai et al., 2000).
(1)
→ H 2 S ↑ +CO2 + CO32−∑ CH + SO42− + H 2O SRB
CH 4 + SO42− → HS − ↑ + H 2O + HCO3−(2)

Formulas (1) and (2) shows that if the H2S iscaused by BSR, during the reduction process, thesulfate ions in the water body will usually reduce andthe content of CO32- and HCO3- will increase. This is
in contradiction to the fact that in this area, sulfate
ions obviously increase, and the content of HCO3decreases. Therefore, the BSR cause can be initiallyruled out. In the groundwater of the original Gujiao
No. 2 and No. 3 mines, the values of δ34S are in therange of 8.2‰ - 11.6‰ (Pan, 1989), with all of thevalues being positive. They do not have thecharacteristics of BSR. In the process of coal and rockformation, this area does not exhibit magma
intrusion, so the magmatic origin can be excluded.
The metamorphic degree of regional coal is highmetamorphic focal smoke, and the average value ofthe maximum vitrinite reflectance of coal (Ro,max) isover 1.5%. According to the corresponding relation
between vitrinite reflectance and temperature, thecoal and rock should has experienced a thermal
evolution environment with temperatures of over120°, in order to have the temperature conditions of
TSR. Regional water and coal petrography are rich insulfate ions. The roof of No. 8 coal seam is limestone(good reservoir stratum), and it has plenty ofhydrocarbon compounds. Every condition that isnecessary for the occurrence of TSR is met. The δ34S
value in groundwater is about 10‰, has thecharacteristics of TSR genesis. Therefore, according
to the changes of temperature, sulfur isotope
characteristics, and sulfate ions in water bodies, it ispossible that the generation of H2S in this area iscaused by TSR. However, it should not be ruled out
that, due to the effect of microbe assimilation
reduction in the gob area of No. 8 coal seam which is
the overlying adjacent layer, the H2S generated under
the role of corrupt migrated to the abnormal
enrichment zone of No. 9 coal seam by the mining
fissure.
3.2 Characteristics of H2S in Xishan coal mine of
Xinjiang Uygur Autonomous Region
Xishan coal mine of Xinjiang is located in thebinding sites which combine the middle of theSouthern Junggar Basin with the northern Tianshan.
Its location map is shown in Figure 6. The main coalbearing strata of mines are the lower segments of
Xishanyao formation of Jurassic system middle
Triassic, and belong to coal formations in terrestrial
facies. Most of the coals belong to the range of
middle - ultra low sulfur. The reflectance of coalvitrinite (Ro) is in the range of 0.64% - 0.79%, socoals belong to the low rank bituminous coal. Eachcoal seam in this region exhibits the abnormal
enrichment of H2S. The concentration of H2S is not
distributed evenly, having distinct subdivision andzoning phenomenon. The underground water ofmines is rich in H2S. The methane gas in coal seams
is mainly composed of N2 and CH4, accompaniedwith CO2 and heavy hydrocarbon components, like
C2H6, C3H8, and H2S. In the gas component, CH4
accounts for 2.42% - 86.5%, N2 accounts for 15.91%- 73.68%, CO2 accounts for 0.81% - 12.31%, H2S
accounts 0 ppm - 1500 ppm. One hour after blasting,the concentration of H2S in the air flow reached100ppm. At 0:00 on November 5, 2011, after blastingin the working face of the track uphill, due to theimpact of the vibration, a lot of water and harmful
gases suddenly rushed out from the roof of No. B19
coal seam. The H2S concentration in the air flow was
up to 400ppm, and the gas concentration was up to
19.5%. Since in the process of H2S generation, heavyhydrocarbons are preferentially generated, TSR
thereby leads to the increase of the gas dry
coefficient. Methane gas of Xishan coal mine isprimarily wet gas, indicating that the genetic featuresof H2S by TSR in the coal seams are not distinct.
The changes of H2S concentration which aremonitored daily in each point of mine are shown in
Figure 1.

489

H2S（ppm）

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 201680

Table 2: Distribution of SRB in the each mine of region.
SRB
Depth T
Stage positions(m) (℃) (A/g sample)

Driftingroadway of B14

60
40
20
0

2-4 2-19 4-4 4-19 5-4 5-19 6-3

7-5

Date
H2S（ppm）

300
One team
200
100
0
4-1

4-11

4-21
5-1
Date

5-11

6-29

Figure 1: The monitored concentration of H2S in the eachpoint.

The testing of gas composition in No. B7 coalseam by exploration holes was conducted in 2011 for
Xishan coal mine. The results are shown in Figure 2.
H2S

150

CH4（%）

CH4

100
50
0
4

100
80
60
40
20
0

7

CH4

10 13 16 19 22
Hole depth (m)
CO

H2S

600
H2S、CO（ppm）

1

H2S（ppm）

200

100
80
60
40
20
0

CH4 (%)

400
200
0
1

5

9

13 17 21 25 29 33
Hole depth (m)Figure 2: Gas composition of 1# and 3# exploration holes.

Figure 2 shows that, the maximum volume
component of CH4 measured by exploration holes is98.0%. The maximum concentration of H2S is
500ppm, and the maximum concentration of CO is
450ppm. The number of sulfate-reducing bacteria in
the inspected samples of mines and adjacent mines isshown in Table 2 (Cheng et al., 2009). It is known
that the SRB breed acts fiercely, so a large amount of
H2S will be generated by BSR.

Beishan coal mine-1
Xiaolongkou coal mine-1
Beishan coal mine-2
Qitai coal mine-1
Xishan coal mine
Xishan coal mine

272.8
312.0
209.5
463.5
563.0
750.0

30
55
55
30
25
28

100
3500
650
234
235
528

The values of carbon isotope δ13CCO2 of regional
CO2 change within the range of -18‰ - -11‰ (Dai,1985), indicating that CO2 in the region is a productof the carbonate decomposition leaching effect aswell as the organic decomposition oxidizing effect.
The CO2 represents characteristics of organic origin,and also represents the genesis features of BSR. The
δ34S of pyrite in the each coal seam of region has a
distribution range of -15.3‰ - +3.7‰, further
confirming that the H2S in the each coal seam of thestudy area is generated by BSR.

4. GENESISCHARACTERISTICSOF
HYDROGEN SULFIDE IN CHINA'S
COAL MINE
Due to the geological movement and various
chemical reductions in China, H2S that is generated
by biodegradation under the early accumulation ofpeat in the oxygen-rich conditions of the early coalforming period is impossible to preserve in the coalrock strata.
The content of H2S in the coal rock strata isconcerned with the sulfur content in coal, and has apositive correlation with the content of sulfur inpyrite. Coals of the Permian Longtan group in theProvince of Guizhou, Sichuan and Chongqing aremostly high-sulfur coal, and pyrite is widely
developed. The sulfur content in Guiding coal of
Guizhou Province is up to a range of 9.49% 10.46%, and more than 70% of coals in Sichuan
Province are high-sulfur coal. According to the
Ministry of Environmental Protection of the People's
Republic of China (http://www.zhb.gov.cn), acid rain
mainly focuses on the south of the Yangtze River,
Sichuan, and eastern Yunnan, including the Zhejiang,
Fujian, Jiangxi, Hunan, etc., and cities of the Yangtze
River, the Pearl River Delta region. Figures 3 and 4
show that high-sulfur coal producing areas havecharacteristics consistent with the distribution of acidrain in China (Deng et al., 2013).

490

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Urumqi
Beijing

Xian
Shanghai
Lhasa
Not included in statistics
St,d≤1%
1%<St,d ≤2%2%<St,dSt,d>3%≤3%

ChengduWuhangTaipeiHong Kong

Figure 3: The distribution of sulfur in coal in China.

Xishan coal mine

Xiqu coal mine
Bayi coal mineseams, sulfur isotopes have the characteristics ofpositive end, whose value is closer to the δ34S ofsulfate. It may be that under the action of thermal
properties of the magmatic rock intrusion, the coal,sulfur-bearing organic matter, and sulphate rocks inthe surrounding rock conduct the thermal chemical
decomposition and the thermal chemical reduction to
generate H2S. For carboniferous coal seams in north
China, the high sulfur coal is widespread. Types ofcoal are mostly coking coal and above. The average
maximum vitrinite reflectance Ro,max of coal from partof coal seams is over 1.2%, having the genesis
conditions of TSR. For example, the coal rock strata
of Qinshui basin in Shanxi Province may haveexperienced high temperatures of more than 268°,
with the temperature generally being above 150°
(Cheng et al., 2009). Through measurement of gas
samples from the exhaust gas of the block surface
well head in Fanzhuang and Panzhuang, the content
of H2S in the coal seam gas component is 0.0001% 0.001%. The H2S content in the desorbed gas of twocoal samples from Sihe coal mine is 0.0001% and0.0002%, respectively (Ma et al., 2008). Since H2S
can easily react with metal, the actual content of H2S
is much larger than the above data. The distributionof coal mines in which H2S is caused by BSR is
broader, such as Wuda of Inner Mongolia, Tingnanof Shaanxi Province and the vast region of Xinjiang
Autonomous Region.
5.

Figure 4: The contours of the annual average pH value in
China in 2014.

In the high sulfur coal of the late PermianLongtan Formation in Guizhou Province, the δ34S
values of pyritic sulfur and organic sulfurare in therange of -30.30‰ - 62.69‰ and -13.43‰ ~ \10.87‰ respectively. The peak values of δ34S inpyrite are in the range of -30.30‰ - -9.18‰ and9.45‰ - 38.40‰ (Ni et al., 1999; Luo et al., 2005).
These data suggest that the formation of the regional
H2S may experience the double genesis of BSR and
TSR.
The sulfur content in coal has an increasing trend
from the east to the west in China. In the threenortheast provinces, coals have the lowest sulfur
content and currently, coal mines in the region have
not reported that H2S is abnormal. The sulfur content
in coal of the Carboniferous Taiyuan formation in thesouthwest of Shandong Province is mostly over 1%,
and some are up to 5%. The maximum sulfur content
in coal of the Permian Shanxi formation in thesouthwest of Shandong Province and in the Yongxia
coal field which belongs to Henan Province is up to
3%. In the methane gas of the above regional coal

DISCUSSION AND PROSPECTS

The H2S content in the coal rock strata isconcerned with the sulfur content in coal, and has apositive correlation with the content of sulfur inpyrite. In the coal-forming environment of marine
facies, the sulfur content in the coal rock strata is
generally higher and H2S is easy to generate andpreserve. Due to the insufficient sulfur ion
abundances and sufficient heavy metals, H2S of coalformation in terrestrial facies is relatively difficult togenerate, reserve and accumulate. The coal seams of
Xishanyao Formation in Xinjiang Autonomous
Region belong to terrestrial facies of coal. The H2S inthis region is abnormally accumulated and widelydistributed. Therefore, conducting research on thecauses and distribution of H2S in coal, which belongs
to terrestrial facies of coal, is particularly important.
The polarity characteristics of H2S determinethat the distribution (enrichment) of H2S is controlled
by many factors. The control action of factors in theabnormal gathering of H2S in coal mines, such as, theregional structure, the nature of the reservoir cap,
groundwater activity, temperature, and the burial
depth of the coal seam should be considered
synthetically.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

At present, research on the mechanisms causing
H2S is still low. The genesis category of H2S in thecoal mine can be judged comprehensively bygeologic and tectonic evolution, thermal evolution
history of coal and rock series, characteristics ofcarbon and sulfur isotope, groundwater chemistry,methane component characteristics, source of sulfate,enrichment state of pyrite in coal and activity
characteristics of sulfate-reducing bacteria.
Coal mines that contain H2S are widelydistributed in China. With the increasing depth ofcoal mining, the threat that H2S poses to miners’
occupational health as well as the safe and efficient
exploitation of the mine is increasingly serious.
Therefore, it is important to identify the genesis anddistribution characteristics of hydrogen sulfide incoal mines as soon as possible, to ensure effective
prediction and safety and efficient mining.
6.

ACKNOWLEDGEMENTS

This work was supported by “National Natural
Science Foundation (U1504403)”, “the research ofbasic and cutting-edge technology of Henan Province(142300413210)” and “the Fundamental ResearchFunds for the Universities of Henan Province”. In the
study process, Deng, Q. is grateful to Professor Liu,
M. of Henan Polytechnic University for his ardent
guidance and help.
7.

REFERENCES

Cai, C., Worden, R.H. and Bottrell, S.H,. (2003).
Thermochemical sulphate reduction and thegeneration of hydrogen sulphide and thiols(mercaptans) in Triassic carbonate reservoirs fromthe Sichuan Basin. China. Chemical Geology,
Volume 202, pp. 39-57.
Cheng, J,. Wang, X,. Wang, X,. (2009). The
thermal history of the Qinshui basin in Shanxi
province.Geo Science, 23 (6): pp. 1093-1099.
Dai, J. (1985). Distribution, classification andorigin of natural gas with hydrogen sulphide in
China. Acta Sedimentologica Sinica, Volume 3, No.
4, pp. 109-120
Dai, S., Ai, T. and Jiao, F. (2000). Componentsof sulfur isotopes and characteristics of sulfur
evolution in Wuda coalfield Inner Mongolia. Acta
Petrologica Sinica, Volume 16, No. 2, pp. 270-274.
Deng, Q., Liu, M. and Wang, Q. (2013).
Geochemistry Characteristics of Sulfur in Coals.
Disaster Advances, Volume 6, pp. 234-240.
Fu, X., Wang, W. andYue, J. (2006). Genesis
analyses of H2S gas abnormity in gas of Bayi coalmine in Zaozhuang. Journal of China Coal Society,
Volume 31, No. 2, pp. 206-210.
Liu, H., Liu, C., Wang, H., et al. (2006).
Simulation experiment of biogenic gas in northwest

China. Xinjiang Geology, Volume 24, No. 2, pp.
149-152.
Liu, M., Li, G. and Hani M. (2011). Genesis
modes discussion of H2S gas in coal mines. Journal
Of China Coal Society, Volume 36, No. 6, pp. 978983.
Liu, G., Zhang, Z. andSong, Z. (2012).
Adsorption experiments on CH4 under the conditionsof high temperature and pressure and equilibrium
water. Journal of China Coal Society, Volume 37,
No. 5, pp. 794-797.
Luo, Y., Li, W., Jiang, Y. (2005). Distribution of
sulfur in coals of China.Coal Conversion, 28(3): pp.
14-18.
Ma, Yu., Tao, M. and Zhang, X. (2008). Hazardof H2S and SO2 contents in coalbed gas and naturalgas. Acta Geologica Sinica, Volume 82, No. 10, pp.
1408-1411.
Machel H G. (2001). Bacterial andthermochemical sulfate reduction in diagenetic
settings-old and new insights. Sedimentary Geology,
Volume 140, pp. 143-175.
Ni, J., Hong, Y. (1999). Sulfur isotopic
composition of late permian coal from Guizhou
province[J]. Geology Geochemistry, 27 (2): pp. 6369.
Oayer R A, Rose M, and Dehmer J. (1999).
Impact of sulfur and trace element geochemistry on
the utilization of a marine influenced coal: Casestudy from the South Wales Variscan foreland basin．Inter.J Coal Geol, pp. 151-157.
Pan, S. (1989). Application of stable isotope tothe research on karst water in Taiyuan area,
Carsologica Sinica, Volume 8, No. 2, pp. 151-155.
Pan, G., Dai, J. and Qi, H. (1992). Research onsour gas in China. Natural Gas Geoscience, Volume
3, No. 3, pp.1-10.
Rye R. O. (2005). A review of the stable-isotope
geochemistry of sulfate minerals in selected igneousenvironments and related hydrothermal systems
isotope properties of sulfur compounds inhydrothermal processes. Chemical Geology, Volume
215, No. 1-4, pp. 5-36.
Song, S., He, J. and Lu, M. (2000). The study of
the Characteristic of sulfur in Xiqu coal and theprobability of desulfur by preparation. Coal
Conversion, Volume 23, No. 1, pp. 76-78.
Yang, Y., Meng, Z., Qin, Z., et al. (2013). Water
resource destruction processes of mining in Shanxi
province combining isotopic and hydrochemical
tracer. China Environmental Science, Volume 33,
No. 8, pp. 1447-1453.
Zeng, F., Tian Y., Lu, G., et al. (2012).
Detection and control technology of spontaneous
combustion area in coal rejects dump of Xiqu mine.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Coal Science and Technology, Volume 40, No. 6, pp.
41-43, 85.
Zhao, Y. and Zhang, C. (2011). H2S gas controlof Xiqu mine N0.9 coal seam. Coal Science andTechnology, Volume 39, No. S, pp. 26-29.
Zhu, G., Zhang, Y.and Lian Y., (2006). Genesis
and evidence of hydrogen sulfide in Weiyuan gas
field of Sichuan basin. Chinese Science Bulletin,
Volume 51, No. 23, pp. 2780-278.

493

ISMS 2016

Paper No. 192

Accumulation pattern of groundwater containing Hydrogen Sulfide in thesouthern Junggar basin in China
Deng Qigena,b*, Liu Mingju a,b, Cui Xuefeng a, Wen Jiejie aaSchool of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo, China, 454003
State Key Laboratory Cultivation Base for Gas Geology and Gas Control (Henan Polytechnic University), Jiaozuo, China,
454003b

ABSTRACTThe surface water and groundwater flows from south to north to the interior basin in the midst of southern Junggar
basin in China. The thick and loose gravel sand layer accumulates in the region, Tectonic depressions of echelon arearranged. Tectonic depression or basement uplift, under the control of hydrodynamic block gas, provides a large
space for the occurrence and migration of groundwater (Hydrogen Sulfide). The water is rich in sulfate and chloride.
Runoff, dissolution, and leaching may occur in the infiltration and runoff process, and under intense evaporation.
The water with high salinity may form HCO3-Ca-Na, HCO3-SO4-Na-Ca, Cl•SO4-Na, and HCO3-SO4-Cl-Na-K. The
water rich in SO42-, Cl-, Ca2+, Mg2+ and Na+ through the hydrocarcon-rich zone (ΣCH, C), plays a role in geothermal
warming. Under suitable geological conditions BSR or TSR may ocurr, and H2S can be generated, resulting in asignificantly lower concentration of calcium and higher concentration of hydrogen sulfide in the water.
KEYWORDS：Southern margin of Junggar basin; Groundwater, Hydrogen Sulfide; Accumulation pattern
1.

INTRODUCTION

The midst of southern Junggar basin lies in the
combining site of southern Junggar and north
Tianshan. The surface water and groundwater flows
from south to north to the interior basin. Salinity andhardness is both in increase, while the concentrationof Ca2+ reduces greatly. Hydrogen sulfide (H2S) is
rich in underground water. Although regional watercontaining hydrogen sulfide are widely distributed,
the current understanding of the patterns of watercontaining hydrogen sulfide is still limited.
Developing the accumulation pattern of hydrogensulfide-bearing
groundwaterhas
theoreticalsignificance and practical value.

①-Structural belt of Qingshuihe, ②-Structural belt of Qigu,③-Structural belt of Changji, ④-Structural belt of Kalazha
Figure 1: Regional structure in the midst of southern
Junggar basin of China.

THE CHEMICAL CHARACTERISTICS
OF WATER

2. REGIONAL STRUCTURE

3.

Two or three belts of arching and syncline
depression formed in the regional piedmont zone.,
These alternate with each other in the piedmont
depression, and are divided into four secondary units,
including, Shihezi sag, West of Urumqi piedmont
fold belt, and Sikeshu sag (Jia et al., 2003; Fang et al.,2005; Wang et al., 2013). The lineament distribution
and Tianshan fold belt direction structure consists ofa series of syncline and anticline and thrust faults
which lie east west-north east, as shown in Figure 1.

The chemical composition, ion concentration,and salinity of groundwater have an important
influence on the genesis and enrichment of H2S.
Sulfate ion is a sufficient condition in order forbacterial sulfate reduction (BSR) and thermochemicalsulfate reduction (TSR) to occur. The chemical
characteristics of groundwater in each coal mine of
the study area from south to north are as shown in
Table 1.

*Corresponding author – email: dengqigen@hpu.edu.cn

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Coal mine groundwater chemical properties fromsouth to north basin areas.
H2S
Hydrochemistry SalinitypHtype（g/L） （mg/L）
Daxigou SO4-Cl-HCO3-Ca 1.1
7.89-25.32 8.3
Qianshuihe
SO4-Cl-Na
2.6
9.26-51.29 8.5
Liuhuanggou SO4-Cl-K+Na
3.5 23.89-69.45 8.5
XishanCl-SO4-K+Na
6.2 41.89-259.63 9.0
Coal mines(1) The depth of groundwater in Toutun river
becomes gradually more shallow from south to north.
There is a large amount of water surface overflow
and flow into big and small Quangou in the first beltof the structure, leading to the development of hot
river in the first row structure. The H2S is rich in thewater. Along the flow direction, the chemical typesof groundwater by HCO3-Ca-Na, HCO3-SO4-Na-Ca
water evolve into HCO3-SO4-Cl-Na-K.
(2) The water salinity and hardness of surface
water and shallow groundwater goes from low tohigh from the mountains of Yilinheibiergen to theresearch area. The salinity starts at less than 1.0 g/L,
and increases to more than 6.0 g/L. The pH value
also gradually becomes larger, from 7.1 to 9.6. The
water is weak alkaline saline water.
(3) The ion constants (except HCO3-) massconcentration components increase along thedirection of deep confined water runoff. The cationic
content of Na + and K+ show a strong increasing
trend, from 27.4% to 72.9%. The dominant evolutionof Ca2+ dominant is given priority over Na+. Ca2+ isreduced to 21.2%, from 57.8%. Anionicconcentrations (mainly HCO3 -) are reduced, except
for SO42- and Cl-.. HCO3- is reduced from 73.5% to48.1%. SO42- increases from 19.3% to 30.2% and Clincreases from 6.7% to 13.3%. The evolution of theregional deep confined water chemical compositionreflects the leached and the roles of cationicalternating adsorption effect on the evolution of deep
confined water (Duan et al., 2007; Hou, 2001).

Maliaodi SO4-Cl-Na-7.2
Jianquangou SO4-HCO3-Na+K-8.6
Shuimogou Cl-HCO3-SO4-Na
135~204 9.6
Shuimogou CO3-HCO3-Cl-Na
160~210 9.3
Hongyanchi SO4-HCO3-Na
2.1~3.3 8.0
Hongyanchi HCO3-SO4-Cl-Na
2.8~3.5 8.6
Gongyuan SO4-HCO3-Cl-Ca+Na-7.6
Yongfengqu Cl-Na+K-Daquangou Cl-SO4-HCO3-Na
56.0~89.0 8.2
Baiyanghe Cl-Na
6.4 7.3

5. ACCUMULATION MODEL OF WATERCONTAINING HYDROGEN SULFIDE
5.1 Hydrological control function in the region
The mountain of Yilinheibiergen is rich in ice
and snow, which is the main source of groundwater.
Surface water and groundwater flow from south to
the north basin. Constituting a centripetal water
system, the water system follows developed track
extensional faults, where the end point is the northernedge of the desert, as shown in Figure 1.
The thickness of the regional quaternary
sediments is about 400-1300 m. In the first andsecond structural belt between tectonic uplift, and thethird and fourth structural belt format the echelon
arrangement structure depressions there is a piled up
thick and loose sand gravel layer. Sag tectonic orbasement uplift provides a huge space forgroundwater (H2S) occurrence and migration. The
groundwater circulation characteristics are as shownin Figure 2.
TianshanMountainSnowmeltrunoffBedrock

New tectonic movement leads to the exposure of
hot springs (well), most of which are fault springs.
The water chemical characteristics of hot springs(well) in the study area are as shown in Table 2(Wang, 1998; Gao et al., 2000; Xu 1994)..
Table 2: Water chemical characteristics of hot springs(well) in the study area.
Salinity T
Water chemical
H2S
pH
Areas
(g/L) (℃)(mg/L)
characteristics
Ergong SO4-HCO3-Cl-Na
North gate SO4-HCO3-Cl-Na+K---

7.7 0.88
7.1 2.86

10.8
11.5

10.4
11.3
19.5
21.0
11.6
12.0
10.4
11.4
8.0
35.8

As shown in Table 2, regional hot springs (well)
are more exposed in the complex faults, anticline
structure belt. Water is weakly alkaline and rich in
H2S, with the water chemical characteristics being
HCO3-, SO42-, Cl -, and Na+.

↓ Rainfall ↓↓ Rainfall ↓4. REGIONAL HOT SPRING (WELL)
WATER FEATURES

2.86
0.78
1.66
7.98
0.85
1.04
0.86
14.4
1.78
0.44

↓

↓

The first structural belt
Tectonic belt ofAlluvial fan flood
piedmont overthrust↑ Evaporation ↑Infiltration

↓ ↓

↓ ↓

Displacement
direction of fault

ltration of
surface water

Infiltration &precipitation

Exposed of spring

Direction of runoff
and recharge

Fine soil plain Desert↑ Evaporation ↑Evaporation
consumption

Figure 2: Characteristics of the water cycle in the region

Regional water types can be divided into loose
rock pore water, clastic pore water, and fissure water.
Local areas have the loess layer cross water, therefore

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

local groundwater is under pressure, Hydrogensulfide has significantly higher solubility under stressconditions, resulting in the abnormal enrichment ofwater containing H2S. On 0 o’clock November 5,2011 in Xishan coal mine, after drilling and shooting
on the mountain track working face a large amount ofwater and harmful gas suddenly poured out from theB19 coal seam roof, due to the effect of the impact
and vibration. Instantaneous H2S concentration was
as high as 400 parts per million, and the gas
concentration was as high as 19.5%.
Regional hydrogeology controlling gas is themain factor in the effect of hydrodynamic seal
controlling gas (Qiao et al., 2005), as shown in
Figure 3.
Mountain
Tectonic belt of piedmont overthrust
Runoff of overlying aquifer

Coal reservoir

Gas pool of coalbed

Figure 3: Regional hydrogeology controlling gas & archivemode of coalbed methane.

The groundwater accepts melting (surface
water) supplies in sealing black bill root at thenorthern foot of the mountain strata outcrop, withbedding going from shallow to deep down the steep
slope. Mudstone water-resisting layers develop at the
top and bottom of the coal. The movement of theinternal waters and gases are stopped due to thelithostatic pressure, which makes the coal seam
permeability vary in the deep. In addition to theworsening continuity of sand body of surrounding
rock, the coal bearing period of the groundwater
movement was slow. Upward dissipation of H2S incoal strata (gas) was blocked, and the groundwater
carrying H2S (gas) makes it move deeper, resulting in
the abnormal concentration of H2S in water and coalrock.
5.2 Regional lithologic control function
Most mountains towering in the southern regionof the black bill mountain have snow and ice meltthat is rich in SO42 - and Cl-. Because the hydraulicgradient is large along the radial direction, the waterexchange effect is strong. The make-up water withsulfuric acid salt rocks, silicate rock, carbonate rock,glauber's salt, and salt may be dissolved and leachedin the process of rainfall infiltration and runoff. The
potential chemical reactions are expressed byreactions 1 to 6:
CaCO3 ⋅ 2 Al 2 O3 ⋅ 4SiO2 (Anorthite) + 2CO2 + 5H 2 O →2 HCO3− + Ca 2+ + 2 H 4 Al 2 Si2 O9

Na2 Al2 Si6 O16 (Albite) + 2CO2 + 3H 2O →(2)

2 HCO3− + 2 Na 2+ + 2 H 4 Al2 Si2O9 + 4 SiO2
MgCO3 + CO2 + H 2 O → 2 HCO3− + Mg 2−

CaMg(CO3 ) 2 → Ca2+

CaSO4 → Ca

2+

2+

+ Mg

2+

(1)

2−
3

+ 2CO

2−
4
−

+ SO

(3)
(4)
(5)

(6)
NaCl → Na + Cl
High salinity of HCO3-Ca-Na, HCO3-SO4-NaCa, Cl•SO4-Na and HCO3-SO4-Cl-Na-K type water
can be formed under the action of the above
dissolution, leached and strong drought evaporation.
Deep confined water in a closed environment isrelatively good, under the effect of revivification andmicroorganisms and thermodynamic factors. Whensufficient hydrocarbon organic matter is in coal strata(∑CH, C), under appropriate conditions like asuitable temperature range, BSR or TSR can occur(Liu et al., 2011; Deng et al., 2013), The hydrocarbon
organic matter can react with sulphate, producing H2S
and other compounds. The possible reactions are as
follows:
BSR
→ H 2 S ↑ (7)∑ CH (or C ) + SO42− + H 2O + CO2 ↑ +CO32− ( BSR)

2C + CaSO4 + H 2 O → CaCO3 ↓ + HS 2 ↑+ CO2 ↑ (TSR )(8)

CH 4 + SO42− + 2 H + → H 2 S ↑ +CO2 ↑ + H 2 O (TSR ) (9)∑ CH + CaSO → CaCO ↓ + H S ↑ +CO ↑ (TSR)
4

3

2

2

(10)
2−
4

Cn H 2 n+2 (Heavier hydrocarbons) + nSO →Cn−1 H 2 n (Lighter hydrocarbons) + CO2 ↑ +(11)(n − 1) H 2 S ↑ + S + H 2O + CO32− (n ≥ 2) (TSR )The result is lower Ca2+ concentration in
groundwater, and the water becoming rich in H2S and
CO2.
The groundwater of the mines (district) area isweakly alkaline, but H2S is acidic, so there may be abalanced relationship as shown in reaction (12).
H 2 S + OH − ↔ HS − + H 2O
(12)HS − + OH − ↔ S 2− + H 2O
Groundwater is blocked near the fault, and waterthat is rich in H2S (spring) is exposed on the surface.
The accumulation mode of water containing H2S in
the region is as shown in Figure 4.

496

4500

Ice

an
sh
an

4000



¡ý
R ainfall¡ ý

Ti

Altitude /m

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

ou
nt
ain

¡ý
R ainfall¡ ý¡ýInfiltration¡ ýSupply
Mg 2+ 、o
Gr 、C - f SO 24、
rec oun l
Ca 2+¡ýInfiltration¡ ý
ha dw
rge ateSGe(Σ upp
are r
l
oth
y
a
CH
er
、 of
at B mal wC)he
SR armpee、d
TS ing
of
zo
R
ne
ply
p
Su
Direction of runoff &Infiltration&
Fault
recharge
precipitation

3000

2500

2000
1500

Fa
ul
to

fm

3500

Exp
of s rosed
prin
g

Water
contains H2S

Anticline of mountain Yilinheibiergen
0

2

4

8
10
6
The horizontal distance/km

1214Figure 4: Accumulation mode of water containinghydrogen sulfide in regional

6.

CONCLUSIONS(1) The surface water and groundwater flows
from south to north to the interior basin of southern
Junggar basin. The thick and loose gravel sand layer
accumulates in the region. Tectonic depressions ofechelon are arranged. There is tectonic depression orbasement uplift, under the control of hydrodynamic
block gas, which provides a large space for theoccurrence and migration of groundwater (Hydrogensulfide).
(2) The water rich in SO42- and Cl- along theradial direction can form high salinity type water of
HCO3-Ca-Na, HCO3-SO4-Na-Ca, Cl•SO4-Na, andHCO3-SO4-Cl-Na-K under the action of the
dissolution, leached, and strong drought orevaporation reactions.
(3) When water rich in SO42-, Cl-, Ca2+, Mg2+,
and Na+ flows through the area rich in hydrocarbons(∑CH, C), BSR or TSR may occur. H2S may then be
produced in proper geological conditions, which leadto a large loss of Ca2+ in water, but a large increase ofhydrogen sulphide in the water. Therefore, it ispossible to draw the accumulation pattern of watercontaining H2S.

7. ACKNOWLEDGEMENTS
This work was supported by “National Natural
Science Foundation (U1504403)”, “the research ofbasic and cutting-edge technology of Henan Province(142300413210)” and “the Fundamental ResearchFunds for the Universities of Henan Province”. In the
study process, Deng, Q. is grateful to Professor Liu,
M. of Henan Polytechnic University for his ardent
guidance and help.
8.

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Hydrochemical Characteristics and Formation
Mechanics of Groundwater in the Middle of Northern
Slope of Tianshan Mountains. Jouranl of Arid Land
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southern margin of Junggar basin thrust belt structure
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Hou, S. (2001). Chemical Characteristics ofPrecipitation at the Headwaters of the Urumqi Riverin the Tianshan Mountains. Jouranl of Glaciology
and Geocryology. Volume 23, No. 1, pp. 80-84.
Jia, C., Wei, G. and Li, B. (2003). Tectonic
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control for natural gas accumulation in China
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No. 2, pp. 13-17.
Liu, M., Deng, Q. and Zhao, F. (2011). Origin ofhydrogen sulfide in coal seams in China. Safety
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Qiao, X., Wang, W. and Chen, Y. (2005).
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Wang, D. (1998). Tianshan region ground waterlevel dynamic anomalies of sensitive preliminary
analysis (new 04 well for example). Inland
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ISMS 2016

Paper No. 225

Application research on gas drainage technology at low permeability coal seam
Shengchu Huang, Li Zhang*
China Coal Strategies Research Center & China Center for Occupational Safety and Health, Beijing, China, 100713

ABSTRACTGas drainage at low gas permeability coal seams is a main barrier affecting safety and efficient production in coalmines. The research and application of drainage technology in low gas permeability coal seams is key for coal minegas control. In order to improve the drainage effect, this paper establishes a three-dimensional solid-gas-liquid
coupling numerical model and studies the gas drainage amount of different schemes inside the overburdened rockaround the goaf. Yangquan mine area is chosen as the research target, and the gas movement regularity and emission
characteristics are comprehensively analyzed, as well as the stress and fissure variation regularity, the scope of
released gas movement, enrichment range, and movement regularity during coal extraction. Then the gas drainage
technology and parameters for the current coal seam are studied. After measuring the gas drainage amount in-situ, it
was found that the technology can achieve notable drainage results, where gas drainage rate increase by 30%~40% for
low permeability coal seams.
KEYWORDS: gas drainage; low permeability; ground drilling holes; coupling model; abutment stress

1. INTRODUCTION
Mine gas incidents are the main disaster associatedwith coal mines. Mine gas extraction in China isdifficult due to characteristics such as micro-porosity,
low-permeability, and high adsorption of coal seams.
However, coal seams in most coal mining areas belong
to difficult-to-drain coal seams with low permeability,
making it difficult to conduct pre-drainage as thedrainage efficiency is quite low. Gas drainage in low
permeability coal seams is a main barrier affecting safeand efficient production in coal mines. Therefore, theresearch and application of drainage technology in low
gas permeability coal seams is a key technical problem
in coal mine gas control.
Wang et al. (2014) studied the Klinkenberg effect ofcoal seams and raised an improved model. Alam et al.
(2014) studied the change of permeability induced by
the change of confining pressure. Wang et al. (2014)
studied and utilized the drainage technology for high gas
and low permeability. Guo et al. (2013) also studied
methods of predicting the permeability of coal seams.
Through experiments Chen et al. (2013) discussed thedevelopment of damage and permeability in coal. Other
scholars have also studied coal seam permeability (Guand Chalaturnyk, 2010; Liu and Chen et al., 2010; Liuand Rutqvist, 2010; Wang and Wei et al., 2010; Cappa
and Rutqvist, 2011; Liu and Chen et al., 2011; Wangand Elsworth et al., 2011; Mitra and Harpalani et al.,2012; Pan and Connell, 2012; Aziz, 2013; Wang andElsworth et al., 2013)
In this paper, the solid-gas-liquid coupling model will
be employed to study the permeability of the coal seam*Corresponding author-email: zhangli@ccsr.cn

in Yangquan Coal mine, and the gad drainage
procedures will be addressed. At the same time, themeasurements in-situ will help to test the coupling
model and the drainage technology utilized in the coal
mine.

2.

THE SOLID-GAS-LIQUIDMODELCOUPLING

2.1. The measuring method for properties of low
permeability coal seam
The initial speed of methane emission（△p）is one ofthe predictions of risk indicators in coal and gas outburst.
It can reflect the speed of coal body containing gas
radiation gas and uses WT-1 gas diffusion velocity test
system to measure. In addition, the competentcoefficient of coal shown soundness of coal. The
methane adsorption constants on coal were measured by
the isothermal adsorption instrument so as to obtain
adsorption constants a and b.
2.2. The analysis of gas distribution patterns by using
the coupling model
Surface borehole well drawing gas is chiefly used inmining face goaf gas extraction. However, gas
reservoirs and flow patterns depend on the
motion features and the movement rule of overlying
strata. As is well known, the moving crack ofoverburden can be divided into three vertical zones andcross three areas caused by mining. The three verticalzones were distributed from the bottom to the top of thecaving zone, fault zone, and bending zone along the roof

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016240m

Φ=152mmHole #1
3000m

Figure 1: The plan view of the working face.
-20m
Thickness of coals------------------------Coal seam b = 0.6m
Coal seam a = 0.6m
Coal 11.1 = 1.2m
Unit 12
Coal 11.2 = 2.8m
(siltstone/mudstone)
Unit 11 (sandy mudstone) Coal 13.1 = 2.7m
Coal 16.1 = 2.0m
Unit 10 (shale, sandstone) Coal 17.1 = 2.0m
Coal 17.1
Unit 9 (fine sandstone, sandy mudstone)
Coal 16.1
Unit 8 (siltstone, sandy mudstone, fine sandstone)
Coal 13.1
Unit 7 (fine sandstone, siltstone)
Top soil andweathered rocks

-400m
-449m
-494m
-510m
-589m
-646m

Unit 6 (sandy mudstone, fine sandstone)
Coal 11.2 (mining coal seam)
Unit 5 (sand mudstone)
Coal 11.1
Unit 4 (sandy mudstone, siltstone)
Coal seam a
Unit 3 (sandy mudstone, siltstone)
Coal seam b
Unit 2 (sandy mudstone, mudstone)

-670m
-680m
-689m
-714m
-738m

12
10

8
6

Scheme 1
Scheme 2
Scheme 3
Scheme 4

4
2
0
0

100

200
300
Mining distance (m)

400

500

Figure 3: Comparison between the simulated and measured
results.

For the specific circumstances of the measured face,
the basic distribution pattern of goaf was establishedfrom a CFD model. The data which was used in themodel was collected from the coal mine field, the resultof COSFLOW, and the experience of the previous CFD
modelling of methane flow. The basic model to theworking face which was advanced 500 m from theopen-off cut was used to research its goaf methane flow.
The width of the basic model is 240 m, the height of thegoaf fracture development zone is 100 m, the height ofseam and roadways is 3.0 m, the width of all roadways is
4.0 m, the elevation of return roadways is 60 m higher
than the machine roadways, and face elevation is thesame with the open-off cut. Those geometriccharacteristics of the basic model are shown in Figure 4,
which correspond with the actual situation.

50m

-360m

The simulation results of panel methane emission
are shown in Figure 3, in which the value of facemethane emission is between 9.2-10.5 m3/min, whichapproximately corresponds to the average value ofmethane emission of 9.6 m3/min that is measured in theworking face.
Gas flux amount (m3/min)of the goaf in the vertical direction, while the cross threeareas were divided into the area effected by the solid,
separation area, and recompaction zone along thedirection of the advancing working face. With the
failure of the floor caused by mining, there were “thenext three-zone”, the goaf floor from top to bottom
respectively including direct damage, effect, and thesmall changes zone. The cracks of rock strata on theworking face goaf provided space and channels for thegas reservoir and transport, and made it possible for thesurface borehole well gas extraction. The changes ofgoaf gas flow field were analyzed by 3D model using
COSFLOW simulation of the working face to thevertical stress distribution. The simulation working face
was 240 m wide and 3000 m long. The mining 11.2#coal
seam had an average thickness of 2.8 m and an
inclination of about 13~16° on the working face. Figure
1 shows the plan of the panel. Figure 2 shows thegeologic log of the model. Table 1 shows the different
schemes of the model.

The goaf

Unit 1 (sandstone)-850m

Figure 2: The geologic log of the model.
Figure 4: The numerical model.

Table 1: Gas content of coal of different schemes.
Scheme1 – 1 borehole in the goaf, low gas content
in coal 11.1 and 11.2
2 – 1 borehole in the goaf, high gas
content in coal 11.1 and 11.2
3 – 1 borehole in the goaf, low gas content
in coal 13.1 and 16.1
4 – without borehole, high gas content incoal 11.1 and 11.2

Coal
11.1

Coal
11.2

Coal
13.1

Coal
16.1

Coal
17.1

3.84

3.84

10.4

9.6

8.0

4.6

4.6

10.4

9.6

8.0

4.6

4.6

9.3

9.3

8.0

4.6

4.6

10.4

9.6

8.0

There are two groups of ground well drilling to thegoaf in the model, that is, one of the groups is along thecenterline of the working face, and the other is 75 mfrom the return roadways. Those drillings can be opened
and closed individually. The first hole is 50 m awayfrom the working face open-off cut; the interval for the
rest of the boreholes is 150 m. Table 2 provides detailed
information on the modelling parameters.

499

Model parameter

Value

Working face size

length 500m/1000m, wide 240m，high 3.0m
2Roadway size

wide 4m，high 3.0m (12m )CFD model size－roof
and bottom

High 100m –include segment 90m above
and10m below

Seam inclination

14°

Vertical face (advance)
Return roadways in the upper (haulage roadways
direction & Along theabove 60 m) & the left panel with the open-off
face (promote)cut of working face at the same level.
direction
The ventilation system,
air volume“U” type ventilation, 35m /s

Goaf gas emission
quantity

The goaf 300 l/s – 400 l/s

Gas component

100% CH4

Goaf gas drainage

along the center line of the working face and near
return road (75m), the first hole is 50m awayfrom the working face open-off cut; the intervalin the rest of boreholes is 150m.

3

Figure 5 shows the methane distribution in theworking face. It indicates that the gas concentration in
the upper corner ranges between 2% to 6%, which fits
the site measurements well. The figure also indicatesthat due to the low density of the methane, there is asmall concentration at the upper part of the inlet
roadway. According to the simulation, it is better toarrange the drilling holes around the inlet roadway fromthe surface.
0.10
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00

Inlet roadway

The working face

The upper
cornerFigure 5: The methane distribution near working face.

2.3. Gas migration and emission regularity in low
permeability coal seamDuring the extraction, abutment pressure ahead of
the working face will give the coal different degree of
deformation, and coal permeability changes with thisdeformation, then affects the coal gas deposit andtransport conditions in the coal, thus influencing thedrainage effect of the coal seam gas drainage hole.
The relationship between the abutment pressure of
the working face and the gas drainage amount ofworking face 9404 is shown in Figure 6.

0.2
0.15
0.1
0.05
0

0

10

20 30 40 50 60 70
Distance to working face (m)8090Figure 6: The relationship between the confining pressure andthe gas drainage amount.

According to Figure 6, the area in front of theworking face could be defined and divided into 5 zones,
which are: a) zero abutment pressure and freed gas zone,
where there is no abutment pressure and the gas could
go through the fractures and cracks freely; b) distressedsurrounding rock zone, mainly 0-10 m in front of theworking face, the pressure of the surrounding rock lows,
and the pressure of the coal seam lows as well, and thecoal expanded due to the lower pressure, and gas has
more paths to release; c) decreased abutment stress zone,
which is usually 10-30 m in front of the working face, inthis zone, the closer to the working face, the higher thegas emission speed; d) increased abutment stress zone,
which is usually 30-60 m ahead of the working face, andwith the increment of the stress, the fractures and cracks
in the coal shrink and close, the permeability is lower
than the original coal and as a result, the gas flux getssmaller; e) the original coal and gas area, which is morethan 60 m ahead of the working face, and is barely
influenced by the extraction, and the parameters of thecoal and gas remain the same.

3.
Return roadway

CH4

Abutment pressure
Gas flux

14
12
10
8
6
4
2
0

Gas flux (m3/min)

Table 2: Parameters of the models.

Abutment pressure (MPa)

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

GAS DRAINAGE IN LOWPERMEABILITY A COAL SEAM

3.1.

Gas drainage plan
Based on the numerical modelling results and thein-situ measurements, the gas drainage plan in thecurrent coal seam is determined as follows.
The drilling holes of the current coal seam, which isperpendicular with the middle line of the transportation
roadway, are drilled from the wall of the working faceside. The drilling holes are separated into two verticalrows with a distance of 1.5 m, and the angles of thedrilling holes are determined by the dip angle of the coalseam. Meanwhile, there are drilling holes with a 3 m
distance between each other on the opposite side of theworking face side. The starting drilling hole is located
18 m away from the working face in the transportation
roadway and 21 m from the return roadway. All thedrilling holes are 50 m long. The plan view of thedrilling holes’ arrangement is shown in Figure 7.

500

154 #

153 #

152 #

151 #

50 m

150 #

3m

149 #

3m

50 m

4#

5#

3#

2#

1#

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The inlet
进风顺槽
roadway

50 m

97 #
198 #
98 #
199 #
99 #
200 #
100 #
201 #
101 #
202 #
102 #
203 #

1#
109 #
2#
110 #
3#
111 #
4#
112 #

50m

1.5m

317 #
471 #
316 #
470 #

1.5m

315 #

469 #
314 #
468 #
313 #
467 #

165 #
324 #
164 #
323 #
163 #
322 #
162 #
321 #
161 #

1.5m

drillingfield 1#1#钻场

21m
drilling
11#钻场
field 11#drilling
10#钻场
field 10#

2m 4m

The
opencut 切
of
the眼
worki
ng

204 #
103 #

50 m

18m

3m

The
opencut切
of
the
眼
worki
ng

30m

Figure 7: The layout of the drilling holes.

The drainage effect
The 15# coal seam is difficult to drain, and theincrement of the abutment pressure during the coal
extraction has a significant influence on increasing thedrainage effect of the coal seam drilling holes. As shownin Figure 8, the drainage amount results throughmeasurements could roughly be divided into four stages:I) the original drainage stage which is 40 m away fromthe working face; II) the weakening drainage stage,
which is located between 40 m and 21.3 m away fromthe working face; III) the increasing drainage stage,
which is located between 21.3 m and 10.3 m away fromthe working face; IV) the attenuate drainage stage,
which is located within 10.3 m away from the working
face.
Abutment pressure
Gas flux

20

0.021
0.018
0.015
0.012
0.009
0.006
0.003
0

Gas flux (m3/min)

Abutment pressure (MPa)

3.2.

15
10
5
0
0

10

20 30 40 50 60 70
Distance to working face (m)8090Figure 8: Relationship between confining pressure and gas
drainage amount.

We can see from Figure 8 that the four drainage
stages correspond to the abutment stress in front of theworking face.
In stage I, the drainage amount is at a normal value,
and it represents the in-situ stress before extraction. As aresult, the coal is not influenced by the working face, thestress, porosity, and the storage situation of the gas are
not changed, and the drainage results remain the same.
In stage II, due to the effect of the working face,
there is increased abutment stress in this stage, and thepores in the coal are compressed to shrink and shut,
which leads to the decrease of the coal permeability, gas
flux, and gas drainage amount.
In stage III, the coal seam is located in thedecreased stress zone, and the pores distribution field
and the stress field are also changed, which lead to themining-induced fractures in the coal seam. Meanwhile,
the gas pressure is lowering, which causes someadsorbed gas to turn into free gas, and the gas drainage
amount from the drilling holes also grows. In this stage,
the gas drainage amount keeps growing and reaches amaximum value. The measurement in-situ indicates thatthe drainage amount of a single drilling hole is 1.88 to
5.84 times more than in stage I, with an average of 4.7,
while for the drilling hole group, the drainage amount ofa group is around 3.5 to 6.4 times more than a single
drilling hole, with an average of 4.3.
In stage IV, though the coal seam is still located in
the decreased stress area, there are too many fracturesand cracks that connect to the free space of the working
face and as a result, there is a lot of air pumped from thefree space mixed in the drainage gas, which reduces thegas amount of the drilling holes.

4.

CONCLUSIONSThis paper studies the gas drainage technology inlow permeability coal seams and the main factors that
affect the gas drainage with the help of theoreticalanalysis, numerical modelling, laboratory experiments,

501

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

and in-situ measurements.
Through the measurements, the abutment pressure
field, the displacement field, and the gas movement near
the working face are studied, and a solid-gas-liquid
coupling model is built to simulate the gas emission andthe gas drainage from the ground surface.
The Yangquan coal mine gas movement andemission characteristics are studied, and the gas
drainage method and key parameters of the drainage
technology for the current coal seam are determined.
According to the numerical model, thearrangement of the drilling holes from the groundsurface is optimized and refined. After the in-situ
application, the drainage effect and the stability of thedrilling holes are tested, and it indicates that thetechnology of gas drainage used in this paper could
indeed enhance the drainage effect by 30%-40% andimprove the efficiency of drainage in low permeability
coal seams.

5. REFERENCES
Alam, A. K. M. B. and M. Niioka, et al. (2014).
"Effects of confining pressure on the permeability of
three rock types under compression." International
Journal of Rock Mechanics and Mining Sciences 65:
49-61.
Aziz, N. (2013). "Permeability and volumetricchanges in coal under different test environment." Acta
Geodynamica et Geomaterialia: 163-171.
Cappa, F. and J. Rutqvist (2011). "Modeling of
coupled deformation and permeability evolution during
fault reactivation induced by deep undergroundinjection of CO2." International Journal of Greenhouse
Gas Control 5 (2): 336-346.
Chen, H. and C. Yuan-Ping, et al. (2013). "Damage
and Permeability Development in Coal During
Unloading." Rock Mechanics and Rock Engineering 46(6): 1377-1390.
Gu, F. and R. Chalaturnyk (2010). "Permeability
and porosity models considering anisotropy anddiscontinuity of coalbeds and application in coupledsimulation." Journal of Petroleum Science andEngineering 74 (3-4): 113-131.
Guo, P. and Y. Cheng (2013). "Permeability
Prediction in Deep Coal Seam: A Case Study on the No.
3 Coal Seam of the Southern Qinshui Basin in China."
The Scientific World Journal 2013: 1-10.
Liu, H. and J. Rutqvist (2010). "A New
Coal-Permeability Model: Internal Swelling Stress andLiu, J. and Z. Chen, et al. (2011). "Evolution of
coal
permeability
fromstress-controlledtodisplacement-controlled swelling conditions." Fuel 90(10): 2987-2997.
Mitra, A. and S. Harpalani, et al. (2012).
"Laboratory measurement and modeling of coal
permeability with continued methane production: Part 1– Laboratory results." Fuel 94: 110-116.
Pan, Z. and L. D. Connell (2012). "Modelling
permeability for coal reservoirs: A review of analyticalmodels and testing data." International Journal of Coal
Geology 92: 1-44.
Wang, G. X. and X. R. Wei, et al. (2010).
"Sorption-induced swelling/shrinkage and permeabilityof coal under stressed adsorption/desorption
conditions." International Journal of Coal Geology 83(1): 46-54.
Wang, G. and T. Ren, et al. (2014). "Improved
apparent permeability models of gas flow in coal with
Klinkenberg effect." Fuel 128: 53-61.
Wang, S. and D. Elsworth, et al. (2011).
"Permeability evolution in fractured coal: The roles offracture geometry and water-content." International
Journal of Coal Geology 87 (1): 13-25.
Wang, S. and D. Elsworth, et al. (2013).
"Permeability evolution during progressive deformationof intact coal and implications for instability inunderground coal seams." International Journal of RockMechanics and Mining Sciences 58: 34-45.
Xufeng, W. and Z. Dongsheng, et al. (2014).
"Methane Drainage and Utilization Technologies forHigh Gassy and Low Permeability Coal Seams in Tiefa
Mining Area.".

Fracture – Matrix Interaction." Transport in PorousMedia 82 (1): 157-171.
Liu, J. and Z. Chen, et al. (2010). "Linking
gas-sorption induced changes in coal permeability todirectional strains through a modulus reduction ratio."International Journal of Coal Geology 83 (1): 21-30.

502

Paper No. 2

ISMS 2016

Influence of temperature on gas desorption-diffusion laws of coal particles
Linchao Dai a,b,*abState Key Laboratory of the Gas Disaster Detecting, Preventing and Emergency Controlling, Chongqing, China, 400037
Chongqing Research Institute Co.,Ltd. of China Coal Technology and Engineering Group, Chongqing, China, 400037

ABSTRACTWith the continuous increase in coal mining depth in China, temperature has a more and more apparent effect on thecoal seam gas adsorption, desorption-diffusion, and seepage. To investigate the effect of temperature on the gas
desorption and flow law of coal, the coal gas desorption test system by independent research and development isused. The gas desorption diffusion process of coal particles was studied under the conditions of adsorption
equilibrium pressure 1.1 MPa and desorption temperature (20℃, 30℃and 40℃). The variation law of the coalparticle gas desorption-diffusion amount and the gas desorption-diffusion rate change with temperature are defined.
Subsequently, the mathematical physics equations of coal particle gas desorption diffusion is established based on
the third boundary condition, and the desorption-diffusion coefficient is solved by using the piecewise fitting
method combined with the dynamic process characteristic of gas desorption-diffusion and the experimental data.
The variation law of the gas diffusion coefficient change with temperature is found. The results show that: (1) the
cumulative amount of coal particle gas diffusion desorption is a capped monotonically increasing function, and thehigher the temperature, the faster the initial rate of gas desorption-diffusion. (2) in the short time (t<10min), the gas
desorption-diffusion coefficient decreases as the temperature increases, and when t>10min, temperature change has
little effect on the desorption-diffusion coefficient. This effect is mainly due to the fact that the rise in temperatureaccelerates the velocity of the gas molecules, therefore increasing the probability of collisions between the gas
molecules. The diffusion length of gas molecules is reduced, followed by a decrease in the effective diffusion crosssectional area. Finally, the gas desorption-diffusion coefficient is reduced. This provides theoretical guidance for theprevention of coal and gas outburst and the prediction of gas emission quantity and extraction.
KEYWORDS: coal particles; gas; desorption-diffusion; temperature
1.

INTRODUCTION

More than 95% of China's coal resources are
obtained from underground coal mines. Gas, water,
fire, dust, ground pressure, heat damage and otherdisasters often influence the process of mining due tothe complex condition of coal resources, the poor
geological conditions, and the large depth of burial(Yu, 2011). Mining depth increases at an annual rateof 10 to 30 m deep (the deepest to 1501 m). Many
shallow low gas mines gradually change into highgas mines, resulting in increases in stress,
temperature, and pressure (Xie et al., 2015).
According to data obtained from the observation of acoal field in China, temperature increased from 1.5 to
4.5 K/100m (Zeng et al., 2011). In China's stateowned mines, the average temperature of the originalrock is 35.9℃ to 36.8℃ in 650 m production levels,and in mines more than 1000 m, the original rocktemperatures reaches as high as 40 to 45 degrees. At
present, there exist more than 80 mines showing thepatterns of differing levels of heat. At the same time,the effect of downhole temperature on coal gas
adsorption, desorption, diffusion, and percolation is*Corresponding author – email : dailinchao@126.com

becoming increasingly outstanding (Sun et al., 2003;
Zeng et al., 2009; Li et al., 2003).
The process of gas desorption-diffusion in thecoal seam is extremely complex, and much researchhas been conducted by domestic and international
scientists. Winter et al. (1969) discovered that after
adsorption equilibrium is reached, the amount of gas
adsorption is determined by the gas content of thecoal, time, temperature, adsorption equilibriumpressure, and the particle size of coal samples.
Jaroniec et al.’s (1990) study on the process of gas
desorption in coal showed that some deformation will
occur when the coal body adsorbes gas. Yee et al.
(1993) put forward the theory of diffusion, findingthat the square root of desorption quantity and time
does not show a simple linear relationship. Marecka(1995) found that the pores in coal and coalmetamorphic degree play an important role in theprocess of gas desorption. Pokryszka et al. (2010)
study the competitive adsorption of CH4 and CO2
diffusion behaviour, considering the influence oftemperature on the effective diffusion coefficient.
Sun (1983) studied coal seam gas solution

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

desorption, desorption rate, and grain size of coalsamples as factors influencing the desorption rate.
Nie et al. (2000) studied the micro mechanism of coal
bed methane diffusion in coal pores. Cao et al. (2007)
studied gas desorption attenuation coefficients anddesorption intensities as a function of coal granularity
in different samples, and analyzed the influence ofparticle size on desorption intensity. Fu et al. (2008)
analyzed the difference between tectonic coal andnon-coal structures on the microstructure carried onby the structure of coal gas radiation, using
mathematical models of micro and macro theory
research. Liu et al. (2013) studied the quantitative
relationship between diffusion flux and thetemperature of coal particles with different coal rank,
and the influence of temperature on the gas diffusion
dynamic process of coal particles.
At present, these theoretical and experimental
studies of coal particles gas desorption-diffusion aremostly carried out under isothermal conditions.
However, the changes in and mechanism of the coalparticle gas desorption-diffusion flux, the gas
desorption-diffusion rate and the diffusion coefficient
still lack in-depth study. Therefore, based on previous
research, and in order to further investigate the effectof temperature on the gas desorption and flow law ofcoal, the coal gas desorption test system byindependent research and development is used to
study the variation law of the coal particles gas
desorption-diffusion under different temperatures.
The present study has practical significance on theprediction of coal and gas outburst, as well as coalseam gas content prediction.
2.

EXPERIMENTAL
METHODSSYSTEM

11

8

7

12
5
4

4
4

5
5

4

4

6

4

3

3

9
10

13

1

2

2

1

1-reference tank 2-coal samples tank 3-pressure transmitter 4-needle valve 5-ball valve
6-exhaust pipe 7-vacuum gauge 8-gas gathering system 9-vacuum pump
10-industrial computer 11-incubator 12-pressure gauge 13-high pressure vessel

Figure 1: The schematic diagram of the experimental
system.

2.2 Experimental coal sample
Samples of Shanxi Jincheng Phoenix Mountaincoal seam face 9# were collected. The coal sample
industry analysis data is shown in Table 1.A balance
was used to weigh the coal sample of 50 g (weighing
accuracy 0.001 g), with the bottle containing the coalsample being pre-numbered and weighed. In order to
exclude the impact of moisture, the weighed coalsample was placed in a vacuum oven, and heated to100~105℃ for 4~6 hours. The vacuum degree of theoven was at least 700 mmHg. The coal sample wasthen dried and placed in a desiccator to cool and save.
Table 1: Experimental coal industry analysis.
Moisture
Volatile
Ashcontent
content
content
Sample%%%Jincheng
Phoenix
3.17
7.09
8.32
Mountain9#

Fixedcarbon
%
81.42

AND

2.1 Experimental system
To achieve the law of coal particles gas
desorption-diffusion under different temperature, theexperimental system was independently designed andassembled. The system mainly consisted of thetemperature control system, the adsorptiondesorption system, the data acquisition andprocessing system, the desorption-diffusion gas
gathering system, the gas supply and control system,and other auxiliary devices. A schematic diagram ofthe experimental system is as shown in Figure 1.

2.3 Experimental procedure
The purpose of this experiment is to study the
dynamic rule of coal particles gas desorptiondiffusion under different temperatures (20, 30 and 40℃) with pressure held constant (1.1 MPa).
Using coal particles of 40~60 mesh at atemperature of 20℃ as an example, the specificexperimental procedure is as follows:(1) Weigh the prepared coal sample of 50 g, andload it into the sample tank. Connect with theexperimental system.
(2) Open the temperature control system andkeep the temperature at 20℃.
(3) Access the methane gas cylinders to theexperimental system, open the vacuum pump, andperform vacuuming tanks and piping systems forabout 1 hour.
(4) Fill the reference tank with the methane gas
to keep it at a stable pressure, and adjust the valve to504

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

connect the reference tank with the sample tank.
Collect the pressure values of the reference tank withthe sample tank.
(5) After the adsorption equilibrium is reached,adjust the valve to connect the sample tank with theatmosphere.
(6) Once the sample tank pressure drops below
atmospheric pressure (0.1 MPa), access it using thedesorption gas gathering system quickly. Meanwhile,
open the gas desorption acquisition software torecord the gas desorption change varying with time,
until the end of the desorption experiments. Lastly
save the experimental data.

diffusion desorption decreases when the temperature
increases. (3) The higher the temperature, the fasterthe initial rate of gas desorption diffusion.
Meanwhile, the rate of gas desorption diffusion
gradually decreases and finally stabilizes with time.
This is because of two main reasons: (1) The
kinetic energy of gas molecules will increase due tothe increase in temperature, giving a greater chanceof surpassing the higher adsorption barrier energy,
shortening the residence time on the coal poresurfaces. This reduction in the adsorption capacity
leads to a reduction in the amount of gas adsorption.
Finally, the amount of desorption will decrease, so
the limit cumulative amount of coal particles gas
diffusion desorption also decreases. (2) Under thesame size and adsorption equilibrium pressure in thesame coal sample, the thermal motion of gas
molecules will be increased because of the increasein temperature. Thus the desorption diffusion
capacity is enhanced, and the desorption-diffusion
rate also accelerates.

3. RESULTS
The variation law of the coal particles gas
desorption-diffusion amount and the gas desorptiondiffusion rates of change with temperature were
measured, as shown in Figures 2 and 3.

The cumulative amount of gas diffusion
desorption/ ml.g-1

18

4.

15
12

20℃

9
30℃
6
40℃
3
0
0

100 200 300 400 500 600 700 800 900 1000
T /minFigure 2: The gas desorption diffusion amount curve.

The gas desorption diffusion rate/ml.(min. g)-1

2.5
2
20℃
1.5
30℃
1

40℃

0.5
0
1

2

3

4

5

6
7
T/min

8

9

10

11

Figure 3: The gas desorption diffusion rate curve.

Figures 2 and 3 show that: (1) the cumulative
amount of coal particles gas diffusion desorption is acapped monotonically increasing function. (2) The
limit cumulative amount of coal particles gas

12

EFFECT OF TEMPERATURE ON THE
GAS DIFFUSION COEFFICIENT

Most scholars (Charriere et al., 2010; Yang etal., 1986; Zhou, 1990; Gives, 1992; Li, 2005) findthat the process of coal particle gas irradiation is thedesorption-diffusion process, and the methane
adsorption (desorption) on the coal surface is
physical adsorption (desorption). In principle, it canbe completed in an instant (10-10~10-5 s) and be
negligible, therefore, the process can be describedusing Fick's second law and the driving force is theconcentration gradient. In the complex system ofcoal, gas adsorption in the pore system follows Fick’s
diffusion law and free gas in the fractures follows theDarcy law. Most studies research the kinetics of coalparticles gas desorption-diffusion.
According to the literature (Dai, 2012; Nie et al.,2001), the mathematical physics equations of coalparticle gas desorption-diffusion were establishedbased on the third boundary condition. The meaningof symbols is as shown in the literature.

 ∂C ∂ 2 C 2 ∂C 
= D  2 +r ∂r 
 ∂r
 ∂t 0 < r < r ,C =
C0
0
t =0

∂C

t > 0,=
0
∂r r = 0∂C=α (C r = r − C f )− D0∂r r = r0


(1)

505

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The approximate solution is obtained by using
the variable separation method.
Qln(1 − t ) = ln A − λ t
(2)
Q∞

=
Where: A

6(sin β1 − β1 cos β1 ) 2
β12 D
=
,
λ
,
β12 ( β12 − β1 sin β1 cos β1 )r0 2

Qt is the cumulative amount of gas diffusion at any
time. Q∞ is the limit cumulative amount of gas
diffusion desorption. D is the desorption-diffusion
coefficient in m2/s.
According to the obtained approximate analyticalsolution, the desorption-diffusion coefficient was
solved by using the piecewise fitting method
combined with the dynamic process characteristic ofgas desorption-diffusion and the experimental data.
The results are shown in Table 2 and Figure 4.
Table 2: The solution results of desorption-diffusion
coefficients under different temperature.
Tempe
rature
20℃

30℃

40℃

D ×10-

Time(min)

Fitting formula

R2

t<10
10<t<100t>100t<10
10<t<100t>100t<10
10<t<100t>100y=-0.028x-0.0672
y=-0.0094x-0.453
y=-0.0051x-1.3544
y=-0.0308x-0.1067
y=-0.0104x-0.4978
y=-0.0064x-1.4028
y=-0.0301x-0.1369
y=-0.0115x-0.561
y=-0.0061x-1.6426

0.98020.98750.99870.97940.98820.99710.98890.98880.9986(m2/s)

11

0.27650.04600.01760.25340.04930.02180.2251
0.05240.0198

Desorption diffusion coefficient
D×10-11/m2.s-1

0.4

gas desorption-diffusion coefficient decreases astemperature increases, and when t>10 min,temperature changes have little effect on thedesorption-diffusion coefficient. This is mainly
because the rise in temperature accelerates thevelocity of the gas molecules, and increases theprobability of collisions between the gas molecules,
decreasing the diffusion length of gas molecules. The
effective diffusion cross-sectional area decreases, andfinally the gas desorption-diffusion coefficient are
reduced.

5.

CONCLUSION

The coal gas desorption test system byindependent research and development was used andthe gas desorption-diffusion process of coal particles
was studied under conditions of adsorption
equilibrium pressure of 1.1 MPa at desorption
temperatures of 20℃, 30℃and 40℃. The variation
law of the coal particles gas desorption-diffusion
amount and the gas desorption-diffusion rate ofchange with temperature were defined.
The mathematical physics equations of coalparticle gas desorption-diffusion were establishedbased on the third boundary condition, and thedesorption-diffusion coefficients were found by using
the piecewise fitting method combined with the
dynamic process characteristic of gas desorptiondiffusion and the experimental data. The variation
law of the gas diffusion coefficient change withtemperature was found.
Studying the influence of temperature on gas
desorption-diffusion laws of coal particles ispractically significant for use in coal and gas outburst
prediction, as well as coal seam gas content
prediction.

t<10min
0.3

10<t<100min

6.

t>100minThis work was financially supported by the
National Basic Research Program of China(2012CB724206), the National Natural Science
Foundation of China (51574280). The author would
like to thank the reviewers of this paper for theirconstructive comments and suggestions to improve
the publication.

0.2

0.1

0
20

30

40

Temperature/ ℃

Figure 4: The segment fitting results under different
temperature.

Figure 4 shows that temperature has a greater
impact on the gas desorption-diffusion coefficientwhen t<10 min, but is less affected when 10<t<100
min and t>100 min. For short times (t<10 min), the7.

ACKNOWLEDGEMENTS

REFERENCES

Cao, Y.L. and Qiu, H.S. (2007). Gas desorption
laws of clastic coal core study. China Mining
Magazine, Volume 16, No. 12, pp.119-123
Charriere, D., Pokryszka, Z. and Behra, P.
(2010).Effect of pressure and temperature on
diffusion of CO2 and CH4 into coal from the Lorraine
basin (France). International Journal of Coal
Geology, Volume 81, No. 4, pp.373-380

506

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Dai, L.C. (2012). Experimental and theoretic
research on gas desorption-diffusion in coal. China
University of Mining & Technology (Beijing)
Fu, X., Wang, K.J. and Yang, T.H. (2008). Gas
irradiation feature of tectonic coal. Journal of China
Coal Society, Volume 33, No. 7, pp.775-779
Gives, H.F. (1992). The process of coal gas
desorption .Coal Engineer, Volume 2, pp.52-56
Jaroniec, M., Lu, X. and Madey, R. (1990). Useof argon adsorption isotherms for characterizing
microporous activated carbons. Fuel, Volume 69, No.
4, pp.516-518
Li, G.X. (2005) Adsorption science. Chemical
Industry Press
Li, Q.G., Kang, Y.L. and Luo, P.Y. (2003).
Analysis of the factors affecting processes of CBM
desorption, diffusion and percolation. Coal Geology&Exploration, Volume 31, No. 4, pp.26-29
Liu, Y.W., Wei, J.P. and He Z.G. (2013).
Influence rules and mechanisms of temperature on
dynamic process of gas diffusion from coal particles.
Journal of China Coal Society, Volume 38, pp.100105
Nie, B.S., Guo, Y.Y. and Wu, S.Y. (2001).
Theoretical model of gas diffusion through coalparticles and its analytical solution. Journal of China
University of Mining & Technology, Volume 30, No.
1, pp. 19-22.
Nie, B. S., Zhang L. and Ma, W.F.
(2000).Diffusion micro-mechanism of coal bed
methane in coal pores. Coal Geology &Exploration,
Volume 28, No. 6, pp.20-22
Marecka, A. (1995) .Effect of grain size on
diffusion of gases in coal. Coal Science
Sun, C.X. (1983).Study on coal samples gas
desorption and the characteristics of prominent coalseam gas desorption. Chongqing Institute of Coal
Science Research InstituteSun, Y.L. and Gui, X.Y. (2003). Research onmine heat-harm and its treatment. Journal of
Liaoning Technical University, Volume 22, pp.35-37
Winter, K. and Janas, H. (1969). Gas emission
characteristics of coal and methods of determining
the desorbable gas content by means ofdesorbometers. XIV International Conference of Coal
Mine Safety Research
Xie, H.P., Gao F. and Ju Y. (2015). Quantitative
definition and investigation of deep mining. Journalof China Coal Society, Volume 40, pp.1-10
Yang, Q.L. and Wang Y.A. (1986). Cinder gas
diffusion theory and its applications. Journal of China
Coal Society, Volume 3, pp.87-93
Yee, D., Seidle, J. P. and Hanson, W.B. (1993).
Gas sorption on coal and measurement of gas
content. In: Law B E, Rice D D (Eds.),

Hydroncarbons from Coal. AAPG Studies inGeology, Volume 38, pp.203-218
Yu, B.F. (2000). Prevention of coal-mine gas
hazards and utilization manual. Coal Industry Press,
China
Zeng S.J., Ma, D.M. and Wang, P.G.
(2009).Effect of temperature changing on desorptionof coalbed methane. Jouranl of Xi’an University of
Science And Technology, Volume 29, pp.449-453
Zheng, G.S., Luan, Y.B. and Bai, L.Y. (2011).
Discussion on the zonations of shallow geothermalenergy resources in China. City geology, Volume 6,
pp.12-16
Zhou S.N. (1990). Mechanism of gas flow incoal seams. Journal of China Coal Society, Volume
15, No. 1, pp. 61-67.

507

Paper No. 4

ISMS 2016

Numerical simulation of gas migration tule in mining-induced fractures field
Cao Jie a,b,*, Li Minghui c, Li Wenpu caState Key Laboratory of Gas Disaster Detection, Prevention and Emergency Control, Chongqing, China, 400037
Chongqing Research Institute Co.,Ltd. of China Coal Technology and Engineering Group, Chongqing, China, 400037
cState Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing, China, 400044b

ABSTRACTGas extraction practice has proven that the vast majority of mining areas in China use unfavourable gas drainage
technology, such as ground drilling hole, and should instead use mining-induced fractures for gas extraction.
Therefore, research concerning the gas migration rule in mining-induced fractures field above the goaf can provide
technical support for optimizing system arrangement of pressure-relieved gas extraction, and increasing the rate ofgas extraction.
At present, scholars are utilizing numerical simulation to study the gas migration rule in working face and goaf
without considering the influence of the mining-induced fractures. There is currently no simulation software that cansimulate not only the space-time evolution of the mining-induced fractures field, but also the rule of gas migration.
This study takes the mining face of the 10th mine in Pingdingshan Coalmine Group in Henan China as an example
case. First, a numerical calculation model is established, and then UDEC software is used to calculate the evolution
formation of the mining-induced fracture field. Afterwards, a spatial diagram is obtained by the image processing
method, and then imported into COMSOL MULTIPHYSICS software in order to simulate the process of gas
migration.
By combining the UDCE and COMSOL software, the gas migration rule in mining-induced fractures above goaf isnumerically simulated. The results are as follows: When the working face advances to a certain distance, goaf
overburden gradually forms a mining-induced fractures trapezoid table, and with the working face advancing, theheight of the mining-induced fractures trapezoid table increases; Compared to the gas migration in the overburden
matrix, the gas flow in abscission layer crack and vertical fracture of mining-induced fractures is directional, and thegas enrichment area is located in the biggest abscission layer crack area in upper end of mining-induced fractures
trapezoid table; When drilling for gas extraction in mining-induced fracture field, the gas concentration declines in
the whole region during the process of gas drainage, and the rate of gas concentration declines faster in fractured
zones. With the gas drainage, the velocity of the gas flow in the mining-induced fracture is faster.

1.

INTRODUCTION

The geological conditions of coal seams in China
are complex and permeability is generally low. Gas
extraction practices has proven that the vast majorityof the mining areas in China use unfavourable gas
drainage technology, such as ground drilling hole.
Mining-induced fractures should instead be used forgas extraction. In the process of coal mining, thesurrounding rock stress is redistributed and generates
the mining-induced fractures caused by mining stope.
The gas desorption of coal mass is promoted, and thepermeability of coal is also increased in order toprovide a gas flow channel in coal and rock mass
near the working face. Therefore, researchconcerning the gas migration rule in mining-induced
fractures field above the goaf can provide technicalsupport for optimizing system arrangement ofpressure-relieved gas extraction, and increasing therate of gas extraction.

*Corresponding author – emai: cqcaoj@126.com

At present, scholars have carried plenty of
research on the gas migration law in mining-induced
fracture field above goaf. Qian and Xu (1998)
studied the distribution characteristics of mininginduced fractures in the overlaying strata by means ofmodel experiments, image analysis, and discreteelement simulation method. Their findings revealed a
two stage development law of fracture caused bymining and distribution characteristics of “O-shape”
circle in long wall faces, and a guide for hole patternsof relieving gas drainage. Li (1998) classified themining induced fracture field through research on theformation and characteristics of fracture fields above
the goaf and in front of the working face. Tu and Liu(2002) researched the influence of formation,
development, closure, and variation of the cracks in
the roof of a coal seam on coal mining, and described
the range of fracture development. Liu et al. (2012)
found that according to the breakage and fracturedeveloping of overlying strata, the layer with a3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
fracture diameter of more than 10-1 mm is the mining
gas channels development area. Other scholars havestudied the gas migration law of coal seams using thenumerical simulation method. However, nosimulation software has been developed that cansimulate not only the space-time evolution of themining-induced fractures field, but also the rule ofgas migration.
This study takes the mining face of the 10thmine in Pingdingshan Coalmine Group in Henan
China as an example case. Establishing numericalcalculation model according to the different laws ofgas flow in different zones of the working face, andcombining the UDCE and COMSOL software toresearch the gas migration rule in mining-induced
fractures above goaf, which can provide technicalsupport for optimizing the system arrangement ofpressure-relieved gas extraction.

2.

MATHEMATICAL MODEL OF GASMIGRATION UNDER THE MINING
INFLUENCE

Mining fissure fields belongs to a porous
medium and the gas therein can be regarded as theideal gas mixture consisting of gas and air. The gas
flow follows the continuity equation, momentum
equation, and mass conservation equation.

Where 𝜏𝑖𝑗 is stress tensor, 𝜏𝑖𝑗 = 𝜇𝑒𝑓𝑓 ��
2 𝜕𝑢𝑖
3 𝜕𝑥𝑖

𝜕𝑢𝑖

𝜕𝑥𝑗

+

𝜕𝑢𝑗
𝜕𝑥𝑖

�−

𝛿𝑖𝑗 � , 𝛿𝑖𝑗 is Kroneker symbol, 𝑔𝑖 is the gravity

force and the external volume force on the i direction,
and 𝐹𝑖 is a custom porous media source term.

2.3 Motion equation
Because of the complex gas flow channel in coaland viscous effect, the motion equation of the gas
flow in the porous media of coal and rock needs to be
described according to different area conditions.
According to previous research (Yang et al., 2010),
the Navier-Stokes equation is appropriate fordescribe the fluid flow in the roadway, and theBrinkman equation focuses on the fracture zone
while simultaneously considering the characteristicsof the fluid pressure and movement, which isappropriate for describing the fluid flow in the cavingzone. Using the two equations can build a working
face airflow model, as shown in Figure 1. The
velocity and pressure on the interface is consistent in
the region where the gas flow is in accordance with
the Navier-Stokes and Brinkman models. The
velocity and pressure distribution of the coal face andgoaf can be predicted by solving the model.

2.1 Continuity equation
The gas flow in coal and rock follows the law ofmass conservation. If the mass sources (sink) are notconsidered, the gas continuity equation is:∂ ( ρ gφ )∂t

+ ∇ ⋅ ( ρ gφ v g ) = 0 (1)The gas transportation in mining fissures should
satisfy the law of conservation of the gas quality. Itshould consider the mass sources of gas, so the gas
continuity equation is:∂ ( ρ g cg ) ∂∂+( ρ g cg ui ) =−( J g ui ) + S g (2)
∂t
∂xi
∂xi
Where 𝑢𝑖 is average flow velocity for porous medium
in the i direction, 𝑆𝑔 is the additional production rateof gas source term, and 𝐽𝑔 is gas diffusion flux.

2.2 Momentum conservation equation
In a given fluid system, the time variation of its
momentum is equal to the sum of the external forces
acting on it. For porous media, the momentum
conservation equation of the i direction in the inertial(non accelerating) coordinate system is:∂ ( ρ g ui )∂t+∂τ ij ∂p∂
( ρ g ui u j ) =− + ρ g gi + Fi (3)∂x j∂x j ∂xi

Figure 1: The schematic diagram of description of the fluid
motion equation in different areas front and after theworking face.

(1) Fluid motion equation in front of working face
To determine the fluid flow with Reynolds
number of gas flow in the coal seam, the expression
for the Reynolds number, Re is:q ⋅ k (4)Re =v ⋅ dmWhere q is the gas flow velocity, m/s, k is thepermeability, m2, v is coefficient of kinematic
viscosity, m2/s, dm is the average particle size, m.
When the Re ≤2320, the fluid flow state is laminar
flow, it is transition flow for 2320< Re<4000, it isturbulent flow for Re ≥4000 (Xu xianliang et al.,2011).
When the fluid flow state is laminar flow, theflow in coal bed is in accordance with Darcy's Law:509

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016u=−Where the subscript br means described by the
Brinkman equation.

K dp (5)⋅µ dx

Where u is the gas flow velocity in coal bed, m/s, K
is the permeability of coal, m2, µ is dynamic viscosityof the fluid, Pa/s, and dp/dx is the fluid pressure
gradient.
When the fluid flow state is turbulent flow, thegas flow in the coal bed is Non-Darcy flow, and thefluid pressure gradient can be expressed as follows:−dp µ
u + βρ u n (6)=dx K

Where n is related to the characteristics of the porous
media of coal, and 𝛽 is the 𝛽-factor of Non-Darcyflow.
The coal permeability in front of the working
face is related to its effective stress. Considering theeffect of gas pressure, mechanical effect andabsorption effect, the expression of the relationshipbetween permeability and effective stress of coal in
the condition of mining dynamic loading andunloading is:  3K (1 − 2ν s )  ρ RTa ln (1 + bp )   =
k ck0 exp  d Θ − 3 p 1 −
1 −
   Esp (1 − ϕ )   


 


(7)
(2) Fluid motion equation in working face
Navier-Stokes equation can describe the fluid
flow in the pipeline. The fluid flow is faster in theworking face, and it can be solved by Navier-Stokes
equation:−∇ ⋅η ∇uns + (∇uns )T  − ρ g ( uns ⋅∇ ) uns + ∇pns = 0 (8)∇ ⋅ uns = 0
Where η is coefficient of viscosity, kg/(m·s), 𝑢 isvelocity vector, m/s, ρ𝑔 is the fluid density, kg/m3,
and p is pressure, MPa. The subscript ns means
described by the Navier-Stokes equation.

3.

NUMERICALSIMULATIONOFOVERLYING STRATA MOVEMENTLAWIN
MINING-INDUCEDFRACTURES FIELD

The fracture field is formed within a certain
distance in overlying strata above the gob area after
coal mining. There are two main types: bed separated
fissures and vertical rupture fissures. Overlying strata
will have different degree of deformation, resulting indifferent gas migration and accumulation rules indifferent positions of the mining-induced fracture
field. Therefore, the moving law of overlying strata
in mining-induced fractures field simulated by UDEC
software is firstly carried out.
3.1 The establishment of numerical model
The 15# coal seam 24080 coal mining working
face in No.10 mine of Pingdingshan Tianan Coal
Mining Co., Ltd is used as the example case. The
calculation model is established according to theintegrated histogram and physical and mechanicalparameter of coal seam, as shown in Figure 2. The
model is 200 m × 100 m, the working face advancedistance is 120 m, left and right sides of the recovery
boundary reserve 40 m distance from the model
boundary to eliminate the boundary effect, and thecoal seam is divided into 12 times for excavation,
where each time excavates 10 m. The simulated coalseam mining depth is 890 m, the thickness of the coalseam is 2.4 m, the upper boundary is loaded with 20
MPa, and the left or right side and the bottom of themodel are normal to the displacement constraint. The
bottom boundary limits the vertical displacement.
The physical and mechanical parameters of the coalor rock and the mechanical parameters of the joints ofmodel are shown in Tables 1 and 2, respectively.

(3) Fluid motion equation in gob area
The Brinkman equation describes a flow
between Darcy and Navier-Stokes. The fluid flow inporous media can be described by Darcy's law whenthe velocity is small, not considering the energy
transfer caused by shear stress. When the flow
velocity is relatively large, the energy transfer causedby shear stress is considered, and the Brinkman
equation is used:η−∇ ⋅η ∇ubr + (∇ubr )T  − ( ubr + ∇pbr − F ) = 0 (9)kFigure 2: Numerical simulation model.

∇ ⋅ ubr = 0

510

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Physical and mechanics parameters of coal orrock.
Elasticity
Compressive
Densitymodulusstrength
Lithology
3(kg/cm )
(MPa)
(GPa)
Mudstone

2.4

17

39

Coal

1.4

13

21

Sandstone

2.8

41

68.5

Sandy mudstone

2.5

20

42.4

Medium-coarse
sandstone

3.1

43

70.6

Fine sandstone

2.6

37

58.2

(b) The excavation distance is 60 m

Table 2: Mechanics parameters of joints of the model.
NormalShear
Frictional
stiffness
stiffness
Lithology
angle (°)
(GPa)
(GPa)
Mudstone

7

1

30

Coal

3

0.3

28

Sandstone

21

15

39

Sandy
mudstone

14

7

34

Medium-coarse
sandstone

25

17

41

Fine sandstone

19

13

37

3.2 The simulated results
The evolution raw of the fracture field when the
excavation distance is 30 m, 60 m, 90 m, and 12 0m
is shown in Figure 3. It can be seen from Figure 3
that the overlying strata movement follows a dynamic
spatiotemporal evolution process. When the working
face is advanced different distances, the overlying
strata above the gob area form the mining-induced
fracture trapezoidal platform. With increases of the
excavation distance, the height of the platform is also
increased.

(c) The excavation distance is 90 m(d) The excavation distance is 120 m
Figure 3: The distribution form of mining fracture fieldunder different excavation distance.

4.

NUMERICAL SIMULATION OF GASMIGRATION IN MINING-INDUCEDFRACTURE FIELD

The shape of the mining induced fracture field isobtained using UDEC numerical simulation, and thencolour is given to the fracture field, and finally
extracted using CORE DRAW software. The fracture
distribution of the extracted fracture field is as shownin Figure 4.

(a) The excavation distance is 30 m

511

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 4: The distribution situation of fracture in themining fracture field.

The extracted fracture field is imported into the
COMSOL MULTIPHYSICS software for numericalsimulation, and the gas migration law at different
times in the mining-induced fracture field can beobtained, as shown as Figure 5. The size of the arrowin the figure represents the size of the gas flux. It isclear that the gas flux in mining-induced fracture is
far greater than that in the matrix of overlying strata.
The bed separated fissures and vertical rupture
fissures are the channels of gas flow, compared withthe matrix of overlying strata, the gas flow in there
has more guiding. With the gas migrate in themining-induced fracture field, the gas fluxes arelarger in the overlying area where the bed separation
degree is large. The gas enrichment area is basicallylocated in the largest mining fracture region at theupper end of the trapezoidal table.

(c) t= 800 000 s(d) t= 2 400 000 s
Figure 5: The schematic diagram of gas migration at
different time in the mining fracture field.

The schematic diagram of gas concentration
nephogram and streamline diagram of gas flux are
shown in Figure 6. Assuming that the gas flow to acertain time, the gas concentration in the whole
region reaches equilibrium, and the gas drainage iscarried out in the fractured zone. From the
distribution of gas concentration in Figure 6, it can beseen that the gas concentration in the whole region is
falling, and the decreasing rate is relatively large inthe fracture development area.

(a) t= 200 s

Figure 6: The schematic diagram of gas concentration
nephogram and streamline diagram of gas flux.

(b) t= 200 000 s

Figure 7 shows a schematic diagram of gas
concentration by height expression. As can be seenfrom the chart, the height in the surrounding coalmatrix descends gently, and it decreases rapidly inthe fractured zone of the mining-induced field. Th
gas concentration rate decrease in overlying strata
matrix is smaller, and in the fractured zone of themining-induced fracture field the decrease rate is512

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

faster, indicating that with the drainage, gas floworientation in the mining-induced fracture field isstronger.

No.51574280), Chongqing Research Program of
Basic Research and Frontier Technology (No.
cstc2015jcyjBX0076), The Science and Technology
Innovation Fund of China Coal Technology &EngineeringGroup(No.2014QN007,
No.2015ZDXM14).

7. REFERENCES

Figure 7: The schematic diagram of gas concentration byheight expression.

5.

CONCLUSIONS

The mathematical model of gas migration in thecoal seam is established according to the flow type in
different positions. Using the combination of UDEC
software and COMSOL software, the numericalsimulation of gas migration in mining-induced
fracture above the goaf is carried out. The following
conclusions are made:(1) The movement of overlying strata above
goaf is a dynamic spatiotemporal evolution process.
With increases of the excavation distance, the areas
form the mining-induced fracture trapezoidal
platform, and the height of the platform is also
gradually increased with excavation.
(2) Compared with the matrix of overlying
strata, the gas flows in fractures are more guiding.
With the gas migrate in the mining-induced fracture
field, the gas enrichment area is located in the largest
mining fracture regional at the upper end of the
trapezoidal table.
(3) If gas drainage is carried out in the fractured
zone, the gas concentration rate decrease in overlying
strata matrix is smaller than that in the fractured
zone. This means that with the drainage, gas floworientation in the mining-induced fracture field isstronger.
This paper has carried out a preliminary analysis
of gas migration in mining-induced fracture above
the goaf using numerical simulation. In the future, thegas content test will be carried out on the scene tovalidate the simulation results, and to ensure thevalidity of the model.

6. ACKNOWLEDGEMENT
This study was financially supported by Special
Foundation of Par-Eu Scholars Program, National
Natural Science Foundation of China (No.51374236,

Guo, Z.L. (2002). Lattice Boltzmann model forincompressible flows through porous media. The
American Physical Society, Volume 66, No.3, pp.1-9.
Gao, J.L. (2010). Simulation study on theinfluence of permeability on gas migration in gob.
China Safety Science Journal, Volume 20, No.9,
pp.9-14.
Li, S. G. (1998). Gas delivery feature and it’scontrol influenced by movement of the surroundingrock in fully-mechanized top coal caving. Xi’an
University of Science and Technology, Xi’an, China.
Liang, D. and Zhou, X.H. (1999). Numeric
simulation on gas movement law in working face.
Journal of Liaoning Technical University (Natural
Science), Volume 18, No.4, pp.337-340.
Liu, H.Y., Cheng, Y.P., Chen, H.D., Kong, S.L.
and Xu, C., (2012). Characteristics of mining gas
channel and gas flow properties of overlying stratum
in high intensity mining. Journal of China Coal
Society, Volume 37, No.9, pp.1437-1443.
Qian, M.G. and Xu, J.L. (1998). Study on the‘O-shape’ circle distribution characteristics ofmining-induced fractures in the overlaying strata.
Journal of China Coal Society, Volume 23, No.5,
pp.466-469.
Tu, M. and Liu, Z.G. (2002). Research andapplication of crack development in mining seamroof. Coal Science and Technology, Volume 30, No.7,
pp.54-56.
Teng, G., Tan Y.L. and Gao, M. (2007).
Simulation of gas seepage in fissured coal based on
lattice Boltzmann method. Chinese Journal of RockMechanics and Engineering, Volume 26, No.supp1,
pp.3503-3508.
Yang, T.H., Chen, S.K., Zhu, W.C., Liu, H.L.,
Huo, Z.G., Jiang, W.Z. (2010). Coupled model ofgas-solid in coal seams based on dynamic process ofpressure relief and gas drainage. Rock and Soil
Mechanics, Volume 31, No.7, pp.2247-2252.
Xu, X.L., Wang, K.S., Meng, L.M. (2011). Fluid
Mechanics. National Defence Industry Press, Beijing,
242p.
Yang, M.D., Li, Y.M. and Zhang, H. (2013).
Numerical simulation of gas concentration field in
the partial W-type ventilation system. Journal of
Safety and Environment, Volume 13, No.6, pp.186190.

513

ISMS 2016

Paper No. 11

Methods of measuring the effective drainage radius of 3# coal seam in
Huoerxinhe coal mine
Linchao Dai a,b,*, Kai Wang a,b, Jie Cao a,b, Bo Wang a,babState Key Laboratory of the Gas Disaster Detecting, Preventing and Emergency Controlling, Chongqing, China, 400037
Chongqing Research Institute Co.,Ltd. of China Coal Technology and Engineering Group, Chongqing, China, 400037

ABSTRACTAt present, the radius of coal seam gas drainage can be determined using the theoretical calculation method, the insitu test method, and the numerical simulation method. Determining a reasonable gas drainage radius parameter has
important practical significance for improving drainage and for eliminating the danger of quick outburst. In order todetermine the gas drainage parameters of Huoerxinhe 3# coal seam and to efficiently eliminate the prominent risksof mining, the current methods of determining the gas drainage radius are analyzed. Based on the gas and geologicalconditions of Huoerxinhe 3# coal seam, the theoretical calculations, laboratory parameters, and site measurement
were used to investigate the effective drainage radius of Huoerxinhe 3# coal seam. The results show that the methodof site measurement of gas drainage radius is more difficult to test and has worse precision, as well as other issues.
However, the exact value of effective drainage radius can be obtained by combining the theoretical calculation
method with the in-situ test method. By using this combined method, the effective drainage radius of Huoerxinhe 3#
coal seam is found to be 1.6 m. This combined method provides a basis for gas drainage borehole design, increasinggas drainage efficiency, and ensures safe mining. Simultaneously, the method put forth in the present study can beused as a general method to determine effective drainage radius.
KEYWORDS: Huoerxinhe coal mine; gas drilling; effective drainage radius; theoretical calculation method
1.

INTRODUCTION

Coal seam gas is the main measure to control
coal and gas outburst, and the distance between holes
is an important consideration in the design of mineboreholes. Whether it is reasonable or not is directly
related to the effect and cost of controlling outburst.
If the distance between holes is too small, theperforation phenomenon will occur, and it will
increase the cost of controlling the outburst, reduce
the effect of extraction, and exacerbate the mining
shortage situation. If the distance between holes is
too large, it will form the drainage blind, therefore
the drainage effect will not reach the target, and will
fail to eliminate the prominent risk on the mining
face. However, the distance between holes isdetermined by the size of drainage radius. Therefore,
it has important practical significance to determine
reasonable gas drainage radius parameters for
improving drainage effect and eliminating the dangerof outburst. In order to determine the gas drainage
parameters of Huoerxinhe 3# coal seam, and toeliminate the prominent risk of on the mining face,the effective drainage radius of Huoerxinhe 3# coalseam was determined based on the gas and geologicalconditions of the coal seam.

*Corresponding author – email : dailinchao@126.com

2.

THE CALCULATIONDRAINAGE RADIUS

METHODOF

In the pre-seam gas extraction, with the joint
action of seam gas pressure and hole negative
pressure, gas around the borehole is continuously
pumped into the borehole. It then forms a similar
circular hole centerline axis as the drainage effect.
The influence circle radius is called the pumping
influence radius. With the extension of the pumping
time, the influence radius will gradually increase
until the difference between the gas pressure in thecoal seam and the negative pressure in the holebottom is not enough to overcome the resistance ofthe deep coal seam gas migration to the borehole. In
the borehole pumping influence circle, the coal bodygas pressure will be reduced, and the gas emission
quantity will be increased.
At present, theoretical calculation, field tests, andnumerical simulations are generally used todetermine the pumping radius. However, due to thecomplexity of coal seam occurrence and therheological properties of coal containing gas, thenumerical simulation method has a large error in
determining the effective drainage radius. The
present study focuses on the theoretical calculation
method and the field test method.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2.1 The theoretical calculation method of drainage
radiusResearch has found that whatever the numericalsimulation calculation, the measured data analysis, orapproximate analytical solution, the relationshipbetween the gas emission quantity of borehole
surrounding rock and time is approximately
consistent with the exponential function law with e as
the bottom.
(1)
Q =Q0 e − At
In the formula, Q is the drilling gas flow at any
time in m3/min. Q0 is the drilling initial gas flow in
m3/min. A is the drilling gas flow attenuation
coefficient, d-1. t is the borehole gas drainage time, d.
The relationship between the amount of gas
drilling cumulative emission and the time is obtainedby the formula (1) integral.
t∫ 24 × 60 × Q e

Qt=

− At

0

0

dt

1440Q0(1 − e − At ) = Qmax (1 − e − At ) (2)A
In the formula, Qt is the drilling cumulative gas
drainage in m3. Qmax is the drilling limit pumping gas
quantity in m3.
The effective drainage radius of gas drainage
borehole is defined so that in the specified time, thegas pressure or gas content in the radius is reduced tothe safe allowable value.
When the impact between the two holes is notconsidered, according to formula (2) and massbalance principle, then the formula (3) and (4) can beobtained.
=r= Q∫ 2π rL × M ×η dr

max

r1

(1 − e − At )Q (1 − e − At )r (t ) 2 − r12 =max
π LM η

(3)(4)

Due to r >> r1 , so

=
r

Qmax
× 1 − e − At
π LM η

(5)

Mc× 100%M(6)=ηln(1 −
t= −π r 2 LM η
)
Qmax
A

(7)

In the formula, η is the coal seam gas extraction
rate when coal seam gas content is at the safe
concentration in %. Mc is the coal seam residual gas
content after drainage in m3/t. M is the coal seam
original gas content in m3/t. The remaining symbols
are as previously listed.

In order to meet the requirements of coal and gas
outburst prevention, "coal and gas outburst
prevention rules" and "coal mine safety regulations"stipulate the coal seam gas extraction rate ( η =25% or30%).
2.2 Field test method for pumping radius
The method of site measurement of gas drainage
radius leads to greater difficulties in testing, worse
precision, and other issues. It cannot determine thegas drainage radius with consideration to the change
in gas geological conditions. The pressure reducing
method and flow method are most commonly used in
the coal mine. The pressure reducing method
involves the set up of more pressure measuringboreholes, and the gas pressure measurement is
influenced by many factors. It can be difficult tomeasure the gas pressure, as the pressure issometimes too large, and the hole leakage pressureoften decreases rapidly.
Coal and gas outburst prevention rules determine
the method of measurement for the effective
discharge radius. Firstly, gas flow measuring parallel
drillings (diameter of 42 mm) are placed in the work
face layer with variable spacing. Then a parallel
discharge hole is placed to one side of the measuringhole, and the variation in gas emission quantity in theholes by time is observed. If within two hours theamount of gas emission in the hole is increased by
10%, the distance between the hole and the dischargehole is called the effective radius.

3.

THEORETICAL CALCULATIONHUOERXINHE PUMPING RADIUS

OF

Shanxi Huoerxinhe Coal Industry Co. Ltd. islocated in Zhangzi County, Changzhi City. The minearea is 71.3947 km2, and the 3# coal seam is locatedin the lower part of the Shanxi formation. The coalseam dip angle is about 5 degrees, and the coal
thickness is 4.49-7.17 m with an average of 5.65 m.
The 3# coal seam gas content is 8-10 m³/t。.
According to "the 3# coal seam coal and gas
outburst hazard identification", the maximum gas
pressure of 3# coal seam is 0.52 MPa, the maximum
initial velocity of gas emission is 23.1, the minimum
coal firmness coefficient is 1.27, and the damage typeof coal is II. The 3# coal seam in the identification
range above +430 m level is without outburst danger.
In the Huoerxinhe 3301 return air trough,measurements of the attenuation coefficient of gas
flow and borehole flow in one hundred meters wereconducted by field test. Four measuring points werearranged, with a pore diameter of 94 mm, a holedepth 100 m, a drilling angle of 0 degrees horizontal,

515

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016a vertical angle degree of 1, and a hole distance 10 m.
The following four holes are as shown in Figure 1.

26

2

2.4

2.6

1.8

27

2

2.4

2.4

1.8

28

2

2.4

2.4

1.6

29

2

2.4

2.6

1.6

30

2

2.2

2.4

1.6

Table 2: Instantaneous flow on the second day.
Time/min1#
2#
3#

Figure 1: Drilling layout.

After the end of sealing, the gas meter wasconnected and observed every day for 30 min.
Through the data acquisition, it is found that the fourholes had zero flow in the three days.
The data were recorded for the first two day’s 30
min (as shown in Tables 1 and 2). In order to get thehole attenuation law, the data were fitted and theresults were as shown in Figures 2 and 3.
Table 1: Instantaneous flow on the first day.

4#

1

1

1.2

1.2

1

2

1

1.2

1

1

3

0.8

1.2

1

0.8

4

0.8

1

1

0.8

5

0.8

0.8

1

0.8

6

0.8

0.8

1

0.8

7

0.8

1

1.2

0.8

8

0.8

1.2

1.2

0.8

9

0.6

0.8

1

0.8

10

0.6

0.8

1

0.8

11

0.6

1

0.8

0.8

12

0.6

1

1

0.8

2.2

13

0.6

1

0.8

0.8

2.8

1.8

14

0.6

1

0.8

0.6

3.4

2.6

1.8

15

0.6

1

1

0.6

3.4

2.6

1.8

16

0.6

1

1

0.6

3.4

2.8

2

17

0.6

1

1

0.6

0.6

1

1

0.6

Time/min
1

1#
2.6

2#
3.2

3#
2.8

4#
2

2

2.4

3.4

3

2

3

2.4

3.4

2.8

4

2.6

3.6

5

2.4

6

2.6

7

2.4

8

2.6

3.2

2.6

2

18

9

2.4

3.2

2.4

2

19

0.4

0.8

1

0.6

20

0.6

0.8

1

0.6

21

0.6

0.8

1

0.6

22

0.6

0.8

0.8

0.6

23

0.6

0.8

0.8

0.6

24

0.6

0.8

0.6

0.6

10

2.6

3.2

2.8

2

11

2.4

3.4

2.8

2

12

2.6

3.2

2.6

1.8

13

2.4

3.2

2.8

1.8

14

2.6

3

3

1.8

25

0.6

0.8

0.6

0.6

15

2.4

3

2.6

1.8

26

0.6

0.8

0.6

0.6

16

2.6

3.2

2.8

1.8

27

0.6

0.6

0.6

0.6

17

2.4

3

2.6

1.8

28

0.6

0.6

0.6

0.6

18

2.4

3

2.4

1.6

29

0.6

0.6

0.4

0.4

30

0.6

0.6

0.4

0.4

19

2.2

2.8

2.4

1.6

20

2.2

2.8

2.6

1.6

21

2.2

2.8

2.8

1.6

22

2.4

2.6

2.6

1.6

23

2.2

2.6

2.6

1.8

24

2.2

2.8

2.8

1.6

25

2

2.6

2.6

1.6

516

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3.8

Time

Instantaneous flow /L/min

3.4

y=3.6792e-0.014x

3

1#

2#

3#

4#

first
day

y=2.8081e-0.004x

2.6
2.2

y=2.6734e-0.009x

secondday

1.8
y=2.0276e-0.008x

1.4
1
0

3

6

9

12 15 18 21 24 27 30
Time /minFigure 2: 1, 2, 3, 4 hole flow chart within the first day 30
min.

Instantaneous flow/L/min

1#

2#

3#

4#

1

y=0.9439e-0.022x
y=1.1588e-0.018x

0.8

Q0(m3/min)

r(m)

1

0.009

2.67342.006479

2

0.014

3.67922.2721023

0.004

2.80812.132388

4

0.008

2.0276

1.76

1

0.015

0.8144

1.061569

2

0.018

1.15881.240409

3

0.026

1.27571.233736

4

0.022

0.94391.089657

FIELD
TEST
OF
PUMPING RADIUS

HUOERXINHE

4.1 Measurement point arrangement and method
The field test of gas drainage radius was tested in
Huoerxinhe 3203 singh transport trough. Fivemeasuring points were arranged, as shown in Figure

y=1.2757e-0.026x

1.2

A(min-1)

From the Table 3, the effective pumping radiusof Huoerxinhe is 2.043 m on the first day, and theaverage is 1.156 m on the second day. Therefore, thetotal average is 1.6 m.

4.
1.4

Hole

4. Among them, drilling holes 1-4 are the test holes,
and drilling hole 5 is the pre drainage hole.

y=0.8144e-0.015x

0.6
0.4
0.2
0

3

6

9

12

15 18 21
Time /min

24

27

30

33

Figure 3: 1, 2, 3, 4 hole flow chart within the second day 30
min.

According to the formula of the hole flow
attenuation fitting of four holes, gas flow attenuation
coefficient A and the initial speed of 100 m drillingQ0 can be obtained by the corresponding formula (1).
The theoretical pumping radius r of four holes
can be calculated by coal seam gas extraction rate
30% and A, Q0 into the formula (5),. The specificparameters are shown in Table 3.

Figure 4: Drilling layout.

The steps of the determination method are as
follows:(1) Four parallel test holes were arranged along
the soft stratification seam with a pore diameter of 94
mm, hole depth 100 m, a drilling angle of 0 degrees
horizontal angle and a vertical angle of degree 1, withhole distances as shown in Figure 4.
(2) Polyurethane was used to seal holes 1-4. The
gas flow of the boreholes was determined
immediately after the end of sealing. Meanwhile,each hole was tested every 1 min with each test holemeasurement time being at least 30 min.
(3) The pre-pumping hole was arranged inparallel between holes 2 and 3. After the constructionof the pre pumping hole, polyurethane was used toseal the hole immediately. Sealing length was at least
8m.

Table 3: Theoretical pumping radius calculation results.

517

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 20163
Instantaneous flow before pumping
2.6

Instantaneous flow after pumping

Gas flow/L/min(4) After the end of the sealing, networking
drainage was implemented immediately. Holes 1-4
were then tested every 1 min with each test holemeasurement time being at least 30 min.
(5) After completing the pre drilling within 2 h,
the gas flow rate of each test hole was determinedand plotted. If the test hole gas flow rate is increasedby 10% compared with that of the pre drilling holefor 3 continuous measurement times, it then follows
that the test hole is in the effective radius of the hole
drilling. The most distant in accordance with theabove test hole distance is the effective radius of the
pre-drilling hole.

2.2
1.8
1.4
1
0

4.2 Determination of gas drainage radiusWith time as the horizontal coordinates and gas
flow as the longitudinal coordinates, the gas flow
observation data was used to draw the hole gas flow
curve, as shown in Figure 5 and Table 4.

5

10

15
20
Time/min2530(c) No. 3 test hole3
Instantaneous flow before pumping

Gas flow/L/min

2.5

Instantaneous flow before pumping

2.5

Instantaneous flow after pumping

Gas flow/L/min

3

2

Instantaneous flow after pumping

2

1.5

1.5
1

1

0.5

0.5
0

5

0
0

5

10

15
20
Time/min2530(a) No. 1 test hole

15
20
Time/min2530(d) No. 4 test hole
Figure 5: The test hole gas flow before and after the prepumping.
Table 4: Average flow before and after the pre pumping.
Average flow (L/min)
Hole
Before pumping
After pumping

5
Instantaneous flow before pumping
Instantaneous flow after pumping

Gas flow/L/min

4

10

3

1

1.96

0.75

2

1.86

2.29

3

1.87

1.94

4

1.94

0.98

2
1
0
0

5

10

15
20
Time/min(b) No. 2 test hole

25

30

From Figure 5 and Table 4, it can be seen thatthe gas flow rate of test hole 2 is increased by morethan 10% after the pre pumping. The gas flow rate forhole 2 is increased by 23%, 3% for hole 3, and thegas flow for holes 1 and 4 are decreased.
According to the principle of the gas drainage
radius, the Huoerxinhe 3# coal mine gas drainage
radius is 1-2 m. It can be seen that the sitemeasurement of gas drainage radius leads to greater518

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

difficulty in testing, worse precision, as well as otherissues.

5.

CONCLUSION

Yu T., Lu P., Sun J.H. (2012). Measurement ofeffective drainage radius based on gas flow andpressure of boreholes. Journal of Mining & Safety
Engineering, Volume 29, No. 4, pp.596-600(1) When taking the pumping rate of 30% above
the standard as the condition, the effective pumping
radius of Huoerxinhe 3# coal mine is 1.6 m as foundthrough the theoretical analysis and calculation.
(2) Using the field test method to measure theeffective extraction radius is feasible, and theeffective drainage radius of Huoerxinhe 3# coal mineas measured by the field test method is 1-2 m.
(3) Through a combination of the fieldmeasurement and the theoretical calculation, theeffective extraction radius of Huoerxinhe 3# coalmine is 1.6 m.

6.

ACKNOWLEDGEMENT

This study was financially supported by Special
Foundation of Par-Eu Scholars Program, National
Natural Science Foundation of China (51374236,
51574280), The Science and Technology Innovation
Fund of China Coal Technology & EngineeringGroup (2014QN007, 2015ZDXM14).
7.

REFERENCES

Cai C.G., Zhou G.Z. (2004). Gas drainage inseam with large auto variable diameter bore holes.
Coal Science and Technology, Volume 32, No. 12,
pp.39-41
Cao X.Q., Xin H.H., Xu L.H. (2009).
Determination of effective drainage radius of gas
drainage borehole, Coal Engineering, No. 9, pp.88-90
Hao F.C., Liu M.J., Sun L.J. (2012).Study oncomparison of methods to determine gas drainage
radius and existed problems. Coal Science andTechnology, Volume 40, No. 12, pp.55-58
Li Z.W., Lin B.Q., Guo M.G.(2014).
Determination on effective influence radius of gas
drainage through borehole based on one-dimensionalradial flow. Coal Science and Technology, Volume
42, No. 12, pp.62-64
Liu S.J., Ma G., Lu J. (2011).Relative pressure
determination technology for effective radius foundon gas content. Journal of China Coal Society,
Volume 36, No. 10, pp.1715-1719
Wang Z.F., Zhou S.H., Li Z.Q. (2011).
Numerical calculation method of effective drainage
radius for gas drainage borehole. Coal Engineering,No. 6, pp.82-84
Xu S.M.(1996).Discussion on the method todetermine the effective gas drainage radius. CoalEngineer, No. 3, pp.43-45
Yu, B.F. (2000).Prevention of coal-mine gas
hazards and utilization manual. Coal Industry Press,
China

519

ISMS 2016

Paper No. 33

Temperature Variation of Coal during the Gas Adsorption Process
Tao Yang a,*, Baisheng Nie b, Xuexi Chen a, Peng Chen bab

Department of Safety Engineering, North China Institute of Science and Technology, East Yanjiao, Beijing, China,101601
Faculty of Resources & Safety Engineering, China University of Mining and Technology (Beijing), Beijing, China,100083

ABSTRACT
Using a self-made coal gas adsorption-desorption instrument, laboratory research on temperature variations of theadsorption process under different conditions was completed to study the adsorption law of coal gas and to reveal
coal gas adsorption mechanisms. Under the same conditions, the order of unit mass of coal’s gas adsorption and thetemperature variation is: Zhenxing 2# Coal > Runhong 3# coal > Malan 8# coal. The results show that gas
adsorption gets lower as the temperature increases. For the same coal sample under the same conditions, the smaller
the particle size, the greater the pressure variations of the methane adsorption process and the larger the gas
adsorption in the same period. The results of this paper reveal the mechanism of coal and gas outburst.
KEYWORDS: coal particles; gas adsorption; thermal effect; temperature variation; experimental study

1. INTRODUCTION
China is the largest coal producer in the world
and it also has the most serious coal mine disasters.
According to the statistics, there are nearly athousand coal mines in China, including more than
110 key state-owned mines that at a risk for coal andgas outburst. Hundreds of coal and gas outburst
events occur each year, often causing serious
casualties and economic losses (State Administrationof Work Safety, 2007). With the continuing
exploitation of coal resources, the depth of Chinese
coal mines increases about 100 meters every year,
causing serious (Xie et al., 2006). Face coaltemperature is closely related to ground stress, gas
content, and coal’s physical and mechanicalproperties. The three factors above are related to coaland gas outburst (Zhang, Z Z et al., 2010. Liu, Z etal., 2012. Chen, G et al., 2014). Gas in the coal bodyis mainly in the adsorption state hosted in coal matrix
when undisturbed.
At present, the real mechanism of gas adsorption,
desorption, and the diffusion process in coal and theinfluence factors are not clear. Because of the limitsof current prediction methods and technologicallevel, gas accident prevention theory and technology
are not valid.
Energy conversion is associated with the processof gas adsorption and desorption (Nie et al., 2013a;
Chaback et al., 1996; Nodzeński, 1998; An, ZX.,
1983; Rike & Yuan, 1989; Zhao, 1994; Niu, GQ.,
2003). Temperature variation exists along with theprocess of coal and gas outburst (Nie et al., 2013b;
Guo et al., 2000a; Guo & Jiang, 2000; Zhang et al.,2011; Wang et al., 1999). Some scholars try to
predict gas accidents according to temperature*Corresponding author – email :yangtao585@163.com

variation (Wang, 2001; Guo et al., 2000b; и.а.Renke& и.я.Lieming, 1985; Lun and Tang, 1992). The
predictive indexes that have been developed aremainly empirical values. There is a gap between thepractical application and theory, because there iscurrently no systematic study of temperature change
in the process of gas desorption and diffusion,
especially the relationship between the equilibriumpressure, adsorption volume, adsorption rate, andtemperature variation.
This paper aims to systematically study the lawsof temperature variation in the process of gas
adsorption under laboratory conditions to reveal theenergy conversion and transmission process.

2. TESTS OF THE BASIC PARAMETERS
OF COAL BODY
2.1 Basic information of coal samples
Three kinds of coal samples were taken fromhigh gas coal mines in different areas of China,
including coal 8# from Malan coal mine, coal 2#
from Zhenxing second coal mine, and coal 3# from
Runhong coal mine. The industrial analysis anddensity test results of three kinds of coal samples areshown in Tables 1 and 2.
Table 1: True density and apparent density of coal.
True
Apparent
Coal sample
Name of coaldensity,density,IDsample
g/cm3
g/cm3
1
Malan coal 8#
1.28
1.12
2
Zhenxing coal 2#
1.42
1.24
3
Runhong coal 3#
1.303
1.18

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 2: Industry analysis of coal.
CoalsampleID
123

Name ofcoal
sampleMalan coal8#
Zhenxing
coal 2#
Runhongcoal 3#

Vdaf

Fc

（%）

（%）

（%）

0.44

2.66

51.18

45.72

2.22

11.96

9.45

76.37

2.02

16.05

12.25

69.68

Ad

M ad

（%）

Among them, M is the moisture content ofcoal, Vdaf is the volatile content of coal, A is the ash
content of coal, and F is the fixed carbon content ofcoal.

0.25 mm in diameter, were collected with a sorting
sieve.
3.1Experimental system
To study the temperature response characteristics
during gas adsorption process, temperature change
tests were carried out. The structure diagram of theadsorption-desorption instrument is shown in Figure
2.

ad

d

2

3

4

III
IV

II

c

I

a) Malan 8#,35000 timesb) Runhong 3#，35000 timesc) Zhenxing 2#，35000 times
Figure 1: SEM images of Coal Samples.

Experimental results showed the presence of alarge fissure structure and an obvious loose layered
structure in the coal sample from Zhenxing coalmine. Degree of pore developments were roughly:
Malan 8 # coal < Runhong coal < Zhenxing second
mine coal.

3. TEMPERATURE TEST DURING GASADSORPTION PROCESS
According to certain experimental standards, thecoal samples were crushed and those particles
measuring 60-80 mesh, namely between 0.178 mm-

8

VI

18
4

5
2

6

2.2 Test of pore structure in coal samples
After being collected and processed, coalsamples were scanned with electron microscopy indifferent magnification. Scanning results reflect thecoal samples’ pore structure conditions. The micropore’s development situation is one of the mostimportant factors affecting the adsorption of methane.
Using a Hitachi S-4800 scanning electron
microscope, morphology of the coal samples wasscanned. The scanning magnification was 35,000
times, as shown in Figure 1.

V

5
9

4
1
7

①high pressure gas cylinder ②pressure gauge ③vacuum pump ④ball valve ⑤ pressure sensor ⑥ reference tank ⑦ industrial
computer ⑧needle valve ⑨temperature sensor ⑩sample tank ⑪
temperature signal acquisition card ⑫sample tank ⑬desorption
test system ⑭ measuring cylinder ⑮ leading bottle ⑯ lifting
platform ⑰rubber hose

Figure 2: The system schematic diagram of gas adsorption
and desorption experiment.

3.2Experimental procedure of adsorption process
The system should first be debugged. The main
steps are as follows:
1) Connect the high-pressure gas tank to theexperimental system.
2) Turn on the vacuum pump, open valves II, IV
and V and make sure other valves stay closed. After
vacating the sample tank for 4 hours, close valves II,
IV and V.
3) Open the temperature acquisition system andpressure collection system. Adjust the high-pressure
gas tank outlet valve to the desired pressure value.
Open valve I and then slowly open valve IV until thereference tank pressure reaches the predeterminedvalue. Close valve I, open valve V slowly, andcontinuously inflate for 12 hours. Record and savethe temperature and pressure values.

4. TEMPERATURE VARIATION RESULTS
OF THE COAL GAS ADSORPTIONEXPERIMENTS
The three coal samples were sealed fromdifferent coal mines and were transported to thelaboratory. They were processed into four different
mesh sizes such as 10 to 20 meshes, 20 to 40 meshes,
40 to 60 meshes and 60 to 80 meshes. The
information about coal samples are presented inTable 3.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Malan8#Runhong60-80 mesh
10-20 mesh
20-40 mesh
40-60 mesh
60-80 mesh
60-80 mesh551.8266

769

603.1798
621.5689
556.6884
489.9777541.13530.4417
431.8605
493.9033

701.4
657.6
695.82
784.9
600
618.3
467.4
562

4.1 Temperature variations during gas adsorption fordifferent coal samples
Figure 3 shows the adsorption process results forthe three coal samples in 60 to 80 meshes under a gas
pressure of 3.1 MPa.

gas adsorption amount (ml/g)

18
15
12
9

MaLan 8#
RunHong 3#
ZhenXing 2#

6
3
0

0

10000

20000
t (s)

30000

40000

△T (℃)a) Relationship of adsorption volume and time of the 3 coalsamples18
16
MaLan 8#14
RunHong 3#
ZhenXing 2#
12
10
8
6
4
2
0
0
1000 2000 3000 4000 5000 6000 7000
t（s）b) Temperature variation of the 3 coal samples during theadsorption process

The variations were 14.056℃, 5.0℃ and 2.304℃,
respectively. The methane adsorption was an
exothermic physical process, where the higher theadsorption the more heat was released.
4.2 Temperature variations of gas adsorption under
different adsorption equilibrium pressures
The current study examined the gas adsorption
law of coal under different adsorption equilibriumpressures. The adsorption experiment results of 40 to
60 mesh coal samples from Malan 8# mine andZhenxing 2# mine were analyzed. Figure 4 shows theadsorption experiment result for the Malan 8# coalsample while Figure 5 shows the adsorption
experiment result for Zhenxing 2# coal sample.

gas adsorption volume (ml/g)

10-20 mesh
Zhenxing
20-40 meshsecond mining 40-60 mesh

The results showed that under the same
conditions, the order of gas adsorption reachingequilibrium was: Zhenxing second mining 2# coal >Runhong 3# coal > Malan 8# coal. Equilibrium
adsorption capacity values were 15.06 ml/g, 15.2
ml/g and 16.1 ml/g, respectively. Similarly,
temperature variations during the adsorption process
were different, and the order of temperature variation
for a unit mass of coal sample was: Zhenxing second
mining 2# coal> Runhong 3# coal > Malan 8# coal.

15

equilibrium pressure 0.434 MPa
equilibrium pressure 0.79 MPa
equilibrium pressure 1.728 MPa
equilibrium pressure 2.16 MPa

12
9
6
3
0

0

10000 20000 30000 40000 50000

t (s)a) Adsorption volume change

coal temperature (℃)

Table 3: The parameters of coal sample in coal gas
adsorption experiment.
Free volume of Coal sample
Coal sample Coal sample
sample canister
quality
name
size
ml
g

32.0
31.5
31.0
30.5
30.0
29.5
29.0
28.5
28.0
0

c) Temperature change rate of the 3 coal samples during
the adsorption processequilibrium pressure 0.434 MPa
equilibrium pressure 0.79 MPa
equilibrium pressure 1.728 MPa
equilibrium pressure 2.16 MPa
500 1000 1500 2000 2500 3000 3500

t (s)b) Temperature variation during adsorption process

Figure 3: the adsorption experimental results of three coalsamples in 60 to 80 meshes under gas pressure of 3.1 MPa.

522

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

0.10

0.06

equilibrium pressure 0.434 MPa
equilibrium pressure 0.79 MPa
equilibrium pressure 1.728 MPa
equilibrium pressure 2.16 MPa

0.04
0.02
0.00

-50 0 50 100150200250300350400450500

t (s)c) Temperature change rate during adsorption
Figure 4: adsorption experimental results of Manlan 8#
coal sample(40-60 mesh) under different equilibriumpressure.

The initial aeration pressures were 1.0 MPa, 2.7MPa, 3.4 MPa, and 4.1 MPa, respectively in thereference tank. After equilibrium, the pressures were0.434 MPa, 0.79 MPa, 1.782 MPa, and 2.16 MPa,
respectively. The pressure variations △P were 0.206
MPa, 0.24 MPa, 0.2712 MPa, and 0.411 MPa,
respectively while the adsorptions were 4.756 ml/g,
5.536 ml/g, 6.345 ml/g, and 9.254 ml/g, respectively.
The maximum amounts of temperature variations

14
12
10
8
6
4
2
0

equilibrium pressure 0.34MPa
equilibrium pressure 1.10MPa
equilibrium pressure 1.43 MPa
equilibrium pressure 1.70 MPa

010000 20000 30000 40000 50000

t (s)a) The adsorption volume change

42.5
40.0
37.5
35.0
32.5
30.0
27.5
25.0
22.5
20.0
17.5

（

temperatures ℃）

equilibrium pressure 0.34MPa
equilibrium pressure 1.10MPa
equilibrium pressure 1.43 MPa
equilibrium pressure 1.70 MPa

0 50 100150200250300350400450500

t (s)c) The change rate of adsorption temperature
Figure 5: the adsorption experiment result of Zhenxing
mine coal samples in 60 to 80 mesh.

As shown in Figure 5, the initial aerationpressures were 1.0 MPa, 2.7 MPa, 3.4 MPa, and 4.1
MPa, respectively in the reference tank when thesample can was filled with coal samples in 40 to 60
mesh. The coal sample was selected from Zhenxing
coal mine. After equilibrium, the pressure values
were 0.34 MPa, 1.1 MPa, 1.43 MPa, and 1.7 MPa,
respectively. The pressure variations △P were 0.218
MPa, 0.44 MPa, 0.557 MPa, and 0.589 MPa,
respectively. The adsorptions were 5.118 ml/g,
10.488 ml/g, 12.96 ml/g and 13.702 ml/g,
respectively. The maximum amounts of temperature
variations were 6.307 ℃ , 11.81 ℃ , 13.23 ℃ , and（ml/g）

gas adsorption volume

were 1.66 ℃ , 1.856 ℃ , 2.845 ℃ , and 3.108 ℃
respectively.

dT/dt(℃/s)

dT/dt(℃/s)

0.08

0.16
0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00

0

500

equilibrium pressure 0.34MPa
equilibrium pressure 1.10MPa
equilibrium pressure 1.43 MPa
equilibrium pressure 1.70 MPa
1000
1500
2000

t (s)
b) The temperature variation during adsorption

14.28℃, respectively.
The experiment results showed that the coal’s
adsorption for gas increased with the rising of gas
pressure for a specific temperature. In the initialadsorption stage, the smaller the particle size, thelarger the gas adsorption volume and the greater thetemperature rise gradient. Adsorption is an
exothermic process. Theoretically, coal temperature
will always rise. However, the experimental system is
not an adiabatic system. There is heat exchange withthe external environment in the adsorption process,thus the adsorption temperature will reach amaximum at about 700 s in the adsorption
temperature change chart. After that, as theadsorption gets weaker, heat exchange will occur
between the coal and the external environment
because of the temperature gradient. Thereby, thecoal temperature decreases until it reaches the same
temperature as the external environment.
4.3 The temperature variation of gas adsorption at
different temperatures
Figure 6 shows the results of the adsorption
process for the Zhenxing 2# coal sample in 60 to 80
meshes at 20℃, 30℃, 40℃, and 50℃ when the
charging pressures were all 3.1 MPa.

523

0.179 MPa, respectively. The unit mass coal’s
adsorptions were 17.787 ml/g, 16.79 ml/g, 16.255
ml/g, and 15.19 ml/g, respectively after equilibrium,
which showed that the gas adsorption dropped as thetemperature was getting higher.
The coal adsorption of methane was an
exothermic physical process. The larger theadsorption, the more heat released. This law can also
be reflected by the temperature variation in

20℃
30℃
40℃
50℃

adsorption experiments. The △Tmax at 20℃, 30℃,

010000 20000 30000 40000 50000
t (s)

55
50
45
40
35
30
25
20

20℃
40℃

30℃
50℃

（

coal temperatures ℃）a) The adsorptions at different temperatures

02000 4000 6000 8000 10000
t（s）b) The adsorption temperature

18.0

20℃

17.0

30℃

16.5

40℃

16.0
15.5

13.43℃, respectively. △Tmax represents the absolutedifference between the initial temperature and the
maximum temperature of the adsorption process.
Because the adsorption-desorption experiment
system was not an adiabatic system, with thedecrease of the adsorption rate, the external
environment had more and more impact on thetemperature inside the sample tank. Whentemperature reached the peak, the environmental
temperature played a dominant role. Therefore, thetemperature variations from beginning to thetemperature peak were studied in this experiment.
4.4 Temperature variations during gas adsorption indifferent particle size
Figure 7 shows the adsorption equilibrium
curves of coal samples in 10 to 20 mesh, 20 to 40
mesh, and 40 to 60 mesh from Malan 8# coal minewhen the charging pressure were 1 MPa, 2 MPa, 3
MPa, and 4MPa, respectively. Under the samecharging pressure, the smaller particle size was, thelarger gas adsorption was after adsorption
equilibrium.

50℃

15.0
20

（
ml/g）

gas adsorption volume

17.5

40℃, and 50℃ were 15.93℃, 14.06℃, 13.57℃, and25 30 35 40 45
temperatures （℃）50c) The equilibrium adsorption volume
Figure 6: The experiment results of adsorption processes ofZhenxing second mining coal samples in 60 to 80 mesh atdifferent temperatures

The gas adsorption capacity for coal was easily
influenced by the temperature change. For the coalsamples in 60 to 80 meshes from Zhenxing coalmine, the final equilibrium pressure was very
different under the same charging pressure. The coalsample’s adsorption equilibrium pressures at 20℃,
30℃, 40℃, and 50℃ were 1.269 MPa, 1.2455 MPa,
1.303 MPa, and 1.33 MPa, respectively. The pressure
drops were 0.214 MPa, 0.188 MPa, 0.1816 MPa, and

14
12
10

10 to 20 meshes
20 to 40 meshes
40 to 60 meshes

8
6
4
2

（
ml/g）

20
18
16
14
12
10
8
6
4
2
0

gas adsorption volume

adsorption amount (ml/g)

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

1.0 1.5 2.0 2.5 3.0 3.5 4.0
gas pressure （Mpa)

Figure 7: The Malan 8# coal samples adsorption indifferent particle sizes and pressures.

The charging pressure of the 10-20 mesh, 20-40
mesh, and 40-60 mesh coal samples tank were 1.06
MPa, 1.07 MPa, and 1.0 MPa, respectively. The
initial pressures were 0.6835 MPa, 0.65875 MPa, and524

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

0.643 MPa, respectively after opening the valve
between the reference and sample tanks. The final
equilibrium pressures were 0.60 MPa, 0.539 MPa,
and 0.434MPa, respectively. The pressure variations△P were 0.0835 MPa, 0.145 MPa, and 0.206 MPa,
respectively from the beginning of the adsorption to
the end.
The adsorption of Malan 8# coal samples in 1020 mesh, 20-40 mesh and 40-60 mesh after
adsorption equilibrium were 1.971 ml/g, 3.388 ml/g,
and 4.756 ml/g, respectively when the charging
pressure of the reference tanks were 1 MPa.
The results showed that for the same coal sample
under the same condition, the smaller particle size is,the greater the pressure variations for the methane
adsorption process and the larger the gas adsorption
volume. In addition, the influence of particle size on
adsorption was also reflected on the temperature
variations of the coal adsorption process. Namely, thesmaller the particle size, the greater the temperature
variation of the adsorption process was when otherconditions remain unchanged. The reasons were thatthe smaller the coal particle size is, the greater the
specific surface area. The greater the adsorbed area ofmethane molecules, the larger the methane adsorption
volume under the same gas pressure and temperature
conditions.
According to adsorption potential theory(Dubinin M M, 1960; Clarkson C R et al., 1997;
Mosher K et al., 2013), methane molecule adsorption
would release a part of the potential energy in an
exothermic physical process. Thus, the higher the gas
adsorption volume, the more heat was generated, andthe greater the temperature variation.

5. CONCLUSIONS
Adsorption laws of coal gas were tested withdifferent coal samples at different temperatures, indifferent sizes and under different adsorption
equilibrium pressures. Specific conclusions are as
follows:(1) The difference of temperature variations inadsorption process was large. The order of unit massof coal samples’ temperature variation was: Zhenxing
2# coal > Runhong 3# coal > Malan 8# coal. Theirvariable quantities were 14.056℃, 5.0℃, and 2.304℃, respectively. The rate of temperature variations
followed the same order: Zhenxing 2# coal >Runhong 3# coal > Malan 8# coal, indicating that
Zhenxing 2# coal has a stronger adsorption capacity.
(2) At a specific temperature, with the increasinggas pressure, coal’s gas adsorption capacity
increased. At the initial adsorption stage, the smaller

the particle size, the higher the gas adsorption
volume, as well as the temperature rise gradient.
(3) For Zhenxing 2# coal samples in 60 to 80
mesh at 20℃, 30℃, 40℃, and 50℃, the adsorption
and desorption process were studied when the
charging pressure was 3.1 MPa. The results showedthat gas adsorption decreased as the temperature
increased.
(4) For the same coal sample under the same
conditions, the smaller the particle size, the greater
the pressure variations of the methane adsorption
process and the larger the gas adsorption volume inthe same period.

6. ACKNOWLEDGEMENT
This research was supported by the Fundamental
Research Funds for the Central Universities （3142015002, 3142015020 ） and by the Research
project of science and technology in Hebei Province(Z2015104).

7. REFERENCES
Bi D, Wu Z. (2010) Research on the regularpattern of temperature distribution when gas gushes
out from the bemi-infintely great coal body. Science
Technology and Engineering. Volume 10, No. 7,
pp.1607-1610
Chen G, Li T, Zhang G, et al. (2014)
Temperature effect of rock burst for hard rock indeep-buried tunnel. Natural Hazards. Volume 72, No.
2, pp. 915-926
Clarkson C R, Bustin R M, Levy J H.
(1997)Application of the monomultilayer andadsorption potential theories to coal methane
adsorption isotherms at elevated temperature andpressure. Carbon. Volume 35, No. 12, pp. 1689-1705
Feng J, Li W, Xie K. (2002) Research on coal
structure using FT-IR. Journal of China University of
Mining and Technology. Volume 31, No. 5, pp. 362366
Guo L, Jiang C. (2000) The theoretical analysisof the influencing factors on temperature change inthe process of coal and gas outburst. Journal of China
Coal Society. Volume 25, No. 4, pp. 401-403
Ferraro J R, Louis J. (2012) Fourier Transform
Infrared Spectra: Applications to Chemical Systems.
Academic Press.
Mosher K, He J, Liu Y. (2013) Molecularsimulation of methane adsorption in micro-andmesoporous carbons with applications to coal and gas
shale systems. Journal of Coal Geology. Volume 109,
pp. 36-44
Liu Z, Feng Z. (2012) Theoretical study on
adsorption heat of methane in coal. Journal of Coal

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Science ＆Engineering. Volume 37, No. 4, pp. 647653
Dubinin M M. (1960) The potential theory ofadsorption of gases and vapors for adsorbents withenergetically no uniform surfaces. Chemical
Reviews. Volume 60, No. 2, pp. 235-241
Solomon P R, Carangelo R M. (1988) FT-ir
analysis of coal: 2. Aliphatic and aromatic hydrogenconcentration. Fuel. Volume 68, No. 7, pp. 949-959
Zhang Z Z, Gao F, Liu Z. (2010) Research onrock burst proneness and its microcosmic mechanismof granite considering temperature effect. Chin J
Rock Mech Eng. Volume 29, No. 8, pp. 1591-1602
Zhang Y. (2012) Study on the Microcosmic
Characteristics and Macro Parameters in the Processof Coal Oxidation and Spontaneous Combustion.
Xi’an: Xi’an University of Science and Technology.
Zhang H, Zhou M, Song C, et al. (2010)
Research on coal mine gas sensor systems based onnear infrared spectrum. In: Hefei, China.
Zhang L, Lu H, Yan H, et al. (2013)
Quantitative Analysis and Research on Coal Quality
Based on Near Infrared Spectrum. Infrared
Technology. Volume 35, No. 8, pp. 522-525

526

ISMS 2016

Paper No. 43

Statistical analysis of coal mine accidents in China from 2005-2013
Xinsheng Hua, Zongzhi Wub,*, Rujun Wangc,d, Yingquan Duoc,daFaculty of Resource and Safety Engineering, China University of Mining and Technology (Beijing), Beijing, China,
100083b
The Occupational Safety and Health Administration, State Administration of Work Safety, Beijing, China, 100713
c
Institute of safety technology for hazardous chemicals, China Academy of Safety Science and Technology, Beijing,
China, 100012
d
Key Laboratory of Major Hazard control and Accident Emergency Technology, State Administration of Work Safety,
Beijing, China, 100012

ABSTRACTThe present study files and categorizes coal mine accidents in within China from 2005-2013 using
mathematical statistics Aspects such as accident types, occurrence time, geographical distribution, and death
rate per million tons are focused on. The characteristics of the coal mine accidents are analyzed, and the coalmine accident potential regularity is summarized. From this analysis, technical prevention means and safety
management measures to prevent and reduce coal mine accidents scientifically and effectively are proposed.
According to the accident categories, it is found that the number deaths caused by roof accidents are thehighest, while the average mortality of fire related accidents are the highest. The curve of accidents is in linewith the curve of death toll and both show fluctuation according to month. February has the lowest accident
rate and death toll. This effect is closely related to the low temperatures. According to the 27 provincial units,
the death toll of Guizhou, Sichuan, Hunan, Shanxi, and Chongqing coal mine accidents is relatively high. To
combat this, China should strengthen the supervision of these places.
KEYWORDS: Statistical analysis; Coal mine accidents; Prevention countermeasure; Safety management

1. INTRODUCTION
Safety production level is an important symbolof the progress of a social civilization. Safety
production is closely related to economic and social
development level, industrial structure, regulatory
system, the rule of law, education, science andtechnology, culture and other factors (Wu, 2007;
China Academy of Safety Science and Technology,
2005; Wang, 2008). China’s safety production levelhas increased stably with the rapid development ofa national economy, the striking improvement ofsafety management, and technical measures.
However, the coal mining field remains an industry
where supervision needs to be strengthened, as
there is a high accident rate (State Administration ofWork Safety, 2008; Shi et al., 2014; Wei et al.,2014).
On July 22, 2001, a gas explosion tore througha coal mine in Xuzhou city, Jiangsu province,
killing 92 people. On February 14, 2005, a gas
explosion ripped through a coal mine in Fuxin
mining group co., LTD, Liaoning province, leaving
214 people dead. On March 29, 2013, a gas
explosion tore through a coal mine in Tonghua

mining group, Jilin province, killing 36 people.
These coal mine accidents, which have caused hugeproperty losses and casualties, have drawn wide
attention.
This paper completes data analysis based on
China’s Coal Mine Accident statistics during
2005-2013 provided by State Administration ofWork Safety (State Administration of Work Safety,2015). The characteristics of the accident are
analyzed on the basis of objective data. Thesestatistics provide related industry practitioners andregulators with countermeasures and suggestions
based on facts, in order to prevent and control coalmine accidents, avoid loss of life, and reduce
accident loss.

2. ACCIDENT ANALYSES
2.1 Accident overall condition
Coal mine accidents and the death toll from2005-2013 were submitted to statistical analysis.
The corresponding curve is shown in Figure 1.
According to analysis, a total of 16,229 coal mine
accidents occurred in China from 2005-2013,*Corresponding author – emai: huxinsheng1989@126.com

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
causing a total of 27,173 casualties. The equivalentof an average of 1,803 coal mine accidents occurredannually with an average death toll of 1-2 people
per accident. Figure 2 shows the raw coalproduction (one hundred million tons) and death
rate per million ton. It can be seen from the figurethat China's raw coal production is increasing eachyear, Conversely, the death rate per million tons is
dropping year by year.

safety management level and technical level play avital role in reducing coal mine accidents andmortality (Yang and Li, 2014).
2.2 The accident category analysis
Coal mine accidents from 2005-2013 were
input to statistical analyses according to 8 kinds ofaccident categories, including roof, gas,
electromechanical, transportation, blasting, flood,fire, and other accidents, as shown in Figure 3.

Figure 1: The number of coal mine accidents and deaths
from 2005-2013.
Figure 3: The number of coal mine accidents and deaths
according to the accident categories from 2005-2013.

Figure 2: Raw coal production and death rate per million
ton from 2005-2013.

It also can be seen from Figure 1 that the trendsof the accident curve and the death toll curve areconsistent. These two curves trend down, which
illustrates that the number of accident and thenumber of deaths is proportional to the decrease. It
also can be seen from Figure 2 that the trends of theraw coal production curve and the death rate per
million tons curve are contrary to each other,showing that high production does not mean highaccident rate.
Overall, China’s raw coal production has
increased steadily from 2.35 to 3.68 billion tons
from 2005-2013 (National Bureau of Statistics of
the People's Republic of China, 2015). The annual
average growth rate was 5.45%. On the contrary,
the total number of coal mine accidents, total deaths,
and death rate per million tons all decreased withthe average annual decline rate of 19.14%, 19.31%,
and 24.78%. This shows that improvements in

The number of accidents and the death toll in
the roof category is the largest. A total of 8,483
roof-related accidents occurred, killing 9,917
people, accounting for 52% of the total number ofaccidents and 36.5% of all deaths. Fire-related
accidents were the least common, with a total of 67
cases. Blasting deaths were the least common,killing 513 people. The average death toll offire-related accidents was 8 deaths per accident,
which is the highest average death toll of eachaccident type. The second most fatal are flood andgas-related accidents, with 4-5 deaths per accident.
Therefore, we should focus on strengthening themanagement of fire, flood, and gas accidents.
2.3 Accident analysis according to the month
Coal mine accidents during 2005-2013 are
input to statistical analyses according to the month,as shown in Figure 4. It can be seen from Figure 4that in the month with the highest accident rate,
April, there were 1,679 accidents; there were 2,770
casualties which is the highest of any month. In
February, the number of accidents and the death toll
were 664 and 664, respectively, which is the least of
any month. In addition, accident rate and the death
toll in January were relatively low.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
and an increase in the death toll.

Figure 4: The number of coal mine accidents and deaths
according to the months from 2005-2013.

The accident rate is lower in January andFebruary because all the working strength is low atthe beginning of the year. Moreover, lowtemperatures result in a decrease of fire-related
accident risk (Wang and He, 2013). Therefore, there
are fewer accidents in this period of the year.
Conversely, there are more accidents in March andApril due to the increasing workload on theemployees who have not yet fully adapted to theworking environment. As a result, weak safety
consciousness and fluky mentality lead to more
accidents. Therefore, the government should
strengthen supervision in this accident-prone
period.
2.4 The accident area analysis
In the 27 provincial coal-producing statisticalunits (with the exception of Tianjin, Shanghai, andHainan), 5 regions including Chongqing, Shanxi,
Hunan, Sichuan, and Guizhou suffered the largest
number of deaths from 2005-2013, as shown in
Figure 5. The corresponding death tolls were 2,185,
2,340, 2,681, 2,862, and 3,865 people, respectively,
accounting for 51% of the total death toll.
On November 5 and 12, 2006, 7 days apart, 2coal mine accidents occurred in Shanxi Province,
47 and 34 people were killed, respectively. These
two accidents were the "11•5" gas explosion
accident in Jiaojia ore coal group and the "11•12"
Explosive burning accident in Nanshan coal mine,
Jinzhong city. On October 20 and November 11,
2004, 22 days apart, 2 coal mine accidents occurredin Henan Province. 148 and 34 people were killed,respectively. These two accidents were gas
explosion accidents in Zhengzhou coal group andLushan County, Pingdingshan city. It can be seenfrom Figure 5 that coal mine accidents are relatively
concentrated in the northeast, central and southwest
regions, mainly in coal production areas. The coalmine production in these areas is relatively dense,
leading to a high probability of coal mine accidents

Figure 5: Region distribution of death toll in coal mine
accidents from 2005-2013.

3. ACCIDENT CAUSE ANALYSES
According to the curve trend of overall
accident situation, China’s coal mine accidents
were decreasing yearly from 2005-2013. The
improvements in safety production situation areclosely related to the supervision work of all
localities and departments. In 2010, the StateCouncil issued a "notice on carrying out the safe
production activities further" and a "notice on
strengthening safety production work in enterprises
further". These two files not only clarified general
requirements and major target tasks of safety
production work in enterprises, but also createdcomprehensive requirements for the enterprise's
safety production work. At the same time，the StateCouncil issued a "notice on strengthening backward
production capacity further " and a "notice on
several opinions of accelerating the coal mine
enterprise merger and reorganization", to put
forward the requirements of eliminating backward
production capacity, optimizing the industrial
structure, promoting the healthy development of thecoal mine industry, and ensuring national energy
security. Focusing on coal mines, metal andnonmetal mines, State Administration of Work
Safety issued " the decision of modifying part of theterms about coal safety regulations", "take theleadership class to go down and mine safety
supervision and inspection requirements", "take theleadership class to go down and metal and nonmetal
mines safety supervision and inspection
requirements". These rules are emphasized tostrengthen the site safety management and discoverand eliminate hidden dangers.

529

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
In 2010, China is focusing on prevention,
strengthening
supervision,andincreasing
responsibility through promulgating a series ofregulatory documents, rules and regulations toadvance "three actions" stably, intensify "threeconstructions", and concentrate on illegal special
operation, rectification, comprehensive supervisionand inspection of key industries (sectors) in safety
production. As a result, coal mine gas accidents
have dropped, coal mine gas extraction andutilization has increased, villages and towns coalmine accidents have declined dramatically, and coalmine gas control and closed work has had great
achievements. At the same time, cracking down on
illegal production and business operation
construction behaviour has made new progress andsignificant results were obtained in safety
production management action.
From 2011-2013, the State Council issued "theopinions of adhering to the scientific development
and safe development to promote safety production
situation steadily", and the "notice on deepen the"safe production" activities continually" in order toeffectively prevent and curb serious accidents. The
main focus was on strengthening and carrying out
the safety production "three responsibilities" ofenterprise main body, department supervision andterritorial administration. At the same time, they
continue to crack down on illegal production andbusiness operation construction behaviour. China’s
series of major policy decisions over safety
production work show their strict, which directly
led to a decline in coal mine accidents. Thus,
perfecting
legalsystemandenhancingsuperintendence strength are important measures tocurb production safety accidents and are strong
protections to reduce safety production accidents(Cao, Q. and Li, K., 2012).

4. CONCLUSIONS
China’s coal mine accidents curve trend andthe death toll curve trend from 2005-2013 areconsistent, and both show an overall downward
trend. This shows that the development momentumof China's coal mine accidents tends to improve.
Perfecting the safety law system and improving
safety supervision system are key actions to control
accidents.
Roof accidents are the most common, making
up about half number of the total accidents. From asafety level, we should strengthen the safety
management of coal mine industry, and especially
focus on reducing roof accidents.
Few accidents happen at the beginning of theyear. The accident-prone period falls around themonth of April.. The government should increasesafety investment in order to reduce the accident
rate during the accident-prone period.
Coal mine accidents in the northeast, central
and southwest regions are relatively concentrated,
mainly in coal production areas. Regional safety
production technical support ability should bebalanced and safe investment for high-risk areas
and accident-prone areas should be increased inorder to reduce the accident rate.

5. REFERENCES
Cao, Q., Li, K. (2012) Risk management andworkers’ safety behavior control in coal mine.
Safety Science Volume 50, pp. 909-913
China Academy of Safety Science andTechnology. (2005) Dangerous chemical accident
cases. Chemical Industry Press, Beijing, 225p.
National Bureau of Statistics of the People's
Republicof
China.
http://www.stats.gov.cn/tjsj/ndsj/
Shi, L., Wang R., and Duo Y. (2014) Problems
and suggestions of safety supervision of dangerous
chemicals major hazard in China. Journal of Safety
Science and Technology. Volume 10, pp. 162-166
State Administration of Work Safety. (2008)
Accident Analysis Report of Hazardous Chemicals
in 2007. Economic Analysis of China Petroleum
and Chemical Industry. Volume 4, pp.54-59
State Administration of Work Safety.
http://media.chinasafety.gov.cn:8090/iSystem/shigumain.jsp
Wang, K. (2008) Chemical production accident
analysis and prevention. China petrochemical Press,
Beijing, 209p.
Wang, C., He, M. (2013) Temperature
influence on macro-mechanics parameter of intact
coal sample containing original gas from Baijiao
Coal Mine in China. International Journal of
Mining Science and Technology. Volume 23, pp.
597-602
Wei G., Yang Z., and Li Y. (2014)
Non-explosive Dangerous Chemical Accidents in
Major Chinese Cities. Environmental Pollution ＆Control. Volume 28, pp. 711-714
Wu, Z. (2007). Study on some strategy
problems of China's work safety by 2020. Journalof Safety Science and Technology. Volume 3, pp.
3-7Yang, C., Li, X. (2014) Statistical Analysis andCountermeasures of Gas Explosion Accident in
Coal Mines. Procedia Engineering. Volume 84, pp.
166-171530

ISMS 2016

Paper No. 55

Analysis of coal crack and permeability characteristics slotted by water jet
and the effect on gas outburst
Chunming Shen a,b,c,*, Baiquan Lin c , Lang Zhang a,b, Dong Wang a,baMine Safety Technology Branch of China Coal Research Institute, Beijing, China, 100013
State Key Laboratory of Coal Mining and Clean Utilization, Beijing, China, 100013
c
Faculty of Safety Engineering, China University of Mining & Technology, Xuzhou, China, 221116b

ABSTRACT
Water jet slotting technology is an effective method of increasing coal permeability, improving gas extraction
quantity, and preventing mine gas dynamic disasters. The designs of the slot parameter and layout are the key
factors. The present study investigated the mechanical properties of slot samples and acoustic emission
characteristics in different slotting numbers and angles by uniaxial loading tests. Tests indicated that the coalstrength was weakened by slotting and reduced significantly with increasing slotting numbers, and the coal wasdamaged more easily when the slot plane was perpendicular to the axial stress. Using Guhanshan coal mine 1603
working face as an example, the paper analyzed the evolution of the coal fracture, stress and porosity when the slots
were at the same level and at the different levels by numerical simulation of Particle Flow PFC2D. The results
showed that, to the sample of slots at the same level, the area around the slot was damaged significantly and thestress concentration was distributed between the adjacent slots, which easily induced coal and gas dynamic risk.
However, the stress and crack fields were distributed uniformly when the slots were at the different levels, the stress
was decreased significantly, and the porosity of coal was 1.5 times higher than the original value.
KEYWORDS: Mine safety; gas extraction; permeability improve; hydraulic cutting; slot layout

1. INTRODUCTION
Underground coal seam hydraulic technology,
such as water jet slotting technology and hydraulicfracturing technology, can effectively increase thecoal permeability, (Huang et al., 2011). The influenceof hydraulic fracturing technology is large, but thefractures improving permeability are easily closed
again when the coal is soft and the geostress is high.
However, water jet cutting forms large-sized slots
and fractures, which can reduce the geostress leveland expand the coal cracks (Shen et al., 2012). It isan effective method to prevent outburst occurrence
and improve gas extraction. Research on the
improvement of of coal permeability by water jet
cutting has been done. Based on the rock dynamic
damage model, Li and Lu analyzed and numericallysimulated coal dynamic damage and fracture
impacted by the high-pressure pulse water jet, andconsidered that the pulse function significantly
affected the state of coal fracture field (Li et al.,
2000; Lu et al., 2010). Lu (Lu et al., 2009; Lu et al.,2011) considered that water jet cutting technology
can release the internal energy and reduce the coalseam stress level, which improves the gas drainage
volume and eliminates the outburst risk. However,the permeability influence on the coal damage
induced by the slots isn’t negligible, especially multilevel slotting. Therefore, the authors have carried out*Corresponding author – email : scmcumt@163.com

research on the coal permeability improvement
mechanism of the slot crack network by water jet
multi-level slotting, in order to improve CMG
extraction. The study took Guhanshan Coalmine as
the background, and using acoustic emission (AE)technology analyzed the multi-level slotting coalmechanical properties and crack propagation
characteristics under the condition of uniaxial
loading. Then, using PFC2D the fracture wasnumerically simulated as well as stress and porosity
evolutions of the slotting coal. The study results areof great significance for the improvement of Chinese
CMG extraction underground.
2.

CRACK PROPAGATION EXPERIMENT

2.1 Experiment system
The experiment system mainly includes the MTS
servo machine, AE instrument, and video camera.
When slotting the coal under the uniaxial loading, AE
was monitoring the crack extension and at the sametime the camera was monitoring the deformation andthe failure of the sample surface (Figure 1). The typeof MTS was C64.106, of which the rated load was1000 kN and the displacement resolution was 0.2 μm.
The AE system with 8 channels was produced by
PAC company, of which the center resonancefrequency was 120 kHz, the pre-amplifier and main

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

amplifier gain were 40 dB, and the adjusting
threshold voltage was 1.0 V.

camera. When the loading up to the sample isdamaged, stop the test and collect the features of thebroken sample.

Uniaxial compression

3. RESULTS ANS ANALYSIS

Pump
AmplifierMainframe

VidiconControlandacquisition

Acquisition PC

Figure 1: Experiment system schematic of uniaxial
compression.

2.2 Sample preparation
Using similar materials the side length of 100
mm cubic coal samples with no slot and with threeslots were prepared. The slot width was 20 mm, thethickness was 2.5 mm, and the angle of the slot
surface and horizontal plane was 0°. The raw
materials of the samples were pulverized coal (grain
diameter of 0.2-1.0 mm), cement, gypsum powder
and water and mixed into the mold. The samples
were maintained 45 days to form and the slots wereformed through pre-embed metal bars. In order tocompare the sample mechanics performance with theoriginal coal, firstly, large pieces of original coalfrom Guhanshan Coalmine 1063 working face werecollected, then processed into the standard specimens
in the laboratory. Lastly, the mechanics parameter ofthe similar material and the original coal samples
were tested. As Table 1 shows, the mechanics
parameters were similar.

3.1 Slot coal mechanical strength
The different slot angle and slot number of peakstress block statistics are shown in Figure 2. The peakstress of the single slot sample was the largest, and as
slot angle increases, the peak stress increases. Whenthe slot angle was 0° to 45°, peak stress increased
obviously. The slot number increased and peak stress
was decreased. Compared to the single slot sample,
the peak stress of the double slot and three slot
samples were decreased by 30-50%. Based on the test
results, slotting could change rock mechanics
properties, where when slot number increases thecoal compressive strength is decreased. When the slot
number reaches a certain amount, there is less of aneffect on the coal rock mass mechanics performance.
For single slot samples, when the slot plane and the
maximum principal stress were vertical, the sample
failed easily.
10
Angle 0°
Angle 45°
Angle 90°

9

Peak stress/MPa

Sample8765Table 1: Mechanics parameters of coal and similar material
samples.
Compressiv
Elasticity
TensileSheare strength
modulusstrength
strength
Sampleσc/MPaE/GPaσt/MPaτ/MPa
raw coal

5.60

0.78705

0.72

3.03

similarmaterial

6.24

0.954

0.87

4.28

2.3 Text operation
Each type of sample test was repeated threetimes, and the test parameters and conditions were as
follows: ① select MTS loading mode and set thestress loading rate as 1.0 kN/s, when the sample
damaged, stop loading, ② eight sensors of AE areevenly placed on the four free surfaces, and eachsurface has two pieces. Before testing, set up anddebug the instrument, and paste the sensor on thesample surface. Then, contact the MTS pressure platewith the sample by a small load, and then start the
MTS loading system, the AE instrument, and the4

One slot

Two slots

Three slots

Figure 2: Peak stress distributions of different slottedsamples.

3.2 Crack propagation of AE features
The peak stress of three slots sample with twolevels distributed was far less than that of the no slot
sample (Figure 3). AE parameters were very small in
the initial compaction stage and elastic deformation
stage, increased in the plastic deformation stage, andincreased significantly when approaching the peakstress. In the yield strain stage, the value of AEenergy and accumulated events increased markedly,
the number of AE hits maintained a high rate andslowly decreased, which shows that the crack
propagated easily. The locations of AE events wereas shown in Figure 4. The cracks between the slots
surfaces grew early on. At 60% of peak stress, thecracks distributed between the slots above and below
were concentrated and at the same time, the cracks
around the slot expanded to the boundary. At the532

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

peak stress, a lot of cracks around the slots grewquickly.

90
60

5

0

25
C

4

20

3

15

2
30

30

StressEnergyEvent

Accumulated AE energy（ ×103）

120

6Stressσ/MPa

Accumulated AE events

150

10

B

1
0

5
0

10

20

30

40

0
60

50

shown in Table 3. In order to simulate the confining
stress limiting conditions, the limit wall was set all
around the model, and four walls would load in thecalculation. To simulate and analyze the effect ofdifferent slot fracture size and distribution, two slot
models were established by deleting particles fromthe incompetent bed. The parameters anddistributions of the slot fractures were as shown in
Figure 6. The slot distribution was heterogeneous.
The particle parameters between the surfaces and on
both ends of the slots were recorded in the processingof the simulation, shown as the circles in Figure 6.

Time/sLimit boundary wall

Figure 3: AE parameter variation of three slots sample with
two level distributed.

80

80

Z /mm

100

60

Coal particle

60

Floor particle

40

40
0
20
40
60
80

0

20

40

X /mm

60

80

0

0

20

40

X /mm

100

（a）20% peak stress

0
20
40
60
80

20

Y /mm

20
0

Limit
boundary
wall

60

80

100

（b）60% peak stress

100

Z /mm

Figure 5: Particle model including boundary and particles
stratum.
Table 2: Basic parameters of the model.
Parameter nameMinimum grain diameter（mm）
Particle diameter ratio

8060Particle density（kg/m3）

40
0
20
40
60
80

0

20

40

X /mm

60

Y /mm

20
0

Limit boundary wall

Y /mm

Z /mm

100

Roof particle

80

100

（c）Peak stress
Figure 4: AE events locating process of three slots
sample with two level distributed.

4. CRACK EVOLUTION PFC SIMULATION

1.66
1450.0The ball - the ball contact modulus（GPa）
Particle stiffness ratio

0.8

Friction coefficient between particles

0.5

1.0

Table 3: Parallel bond parameters.
Parameter namevalue

Parallel bond radius multiplier

1.0

Parallel bond modulus（GPa）

0.8

Normal stress average value of parallel

4.1 Numerical model
Using particle flow PFC2D to build a rectangularmodel with the incompetent bed (Cundall, 2004), themodel length as 1400 mm and the width was 900
mm. The model was divided into three stratums,
including the roof rock stratum (200 mm),incompetent bed (500 mm), and bottom rock stratum(200 mm), the original particle model was as shownin Figure 5. The parameters of the roof and floor
rocks were the same, the bond strength of which wasfive times more than the incompetent bed, as shownin Table 2. The parallel bond parameters were as

value
0.3

bonding（MPa）
Normal stress standard deviation of parallelbonding（MPa）
Tangential stress average value of parallelbonding（MPa）
Tangential stress standard deviation of parallelbonding（MPa）

4
0.01
4
0.01

533

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The instantaneous stress, porosity andcoordination number and particle migration aroundthe small slots in the unit circle A and B were asshown in Figure 8. The stress of A position showed
continuous increase, lower porosity, and coordination
number increase. The stress of location fluctuatedand increased to about 12 MPa. The porosity
increased after the first reduction, but remained lower
than the original. The instantaneous stress, porosityand coordination number and particle migration
around the medium slot in the unit circle C and D
were as shown in Figure 9. The stress of C position
increased slowly and the porosity declined. The stressof D location increased to about 10 MPa first, andthen reduced to 2 MPa. The porosity significantly
increased to far more than the original porosity at thefirst peak stress. The instantaneous stress, porosityand coordination number and particle migration
around the large slot in the unit circle E and F wereas shown in Figure 10. The stress of E position
slowly increased, the maximum of which was lower
than the small and medium slots. The porosity was
similar to the original, however, the coordination
number and particle instantaneous displacement were
not obviously changed. The stress of F position was
irregular. In the first peak stress, the porosity
increased rapidly and then increased slowly. The
porosity increased to about 1.5 times higher thanoriginal value.

Roof
顶板

E

C

A
B

F

D

底板
BottomFigure 6: Slot fractures model parameters and distributions.

4.2 Simulation results and discussion
The single-level slots rock model structure,stress and crack distribution are shown in Figure 7.
With the load step increasing, the deformation
displacement around big slot happened first, and theslots were filled with particles. Stress appeared
around the small and medium-sized slots, and thestress concentration appeared between the adjacentslots. As the calculating steps increased, the stressaround large slot and medium slot area were reduced.
With the stress increasing, crack propagation aroundthe big slot was not significant, and mainly took theform of tension fractures. However, the cracks
around the secondary slot increased mainly due toshear failure, and the crack around the small slot
grew and expanded to the roof and floor.

12×104step

Rock stratum of roof and floor

Stress

15×104step

incompetent bed

Porosity

Coordination

Migration

Slot(a) Particle structure change

12×104step

Compressive stress

15×104step

Tensile stress

Slot

Figure 8 : Parameter variation around the small slots (Blocation).

(b) Model stress distribution

12×104step
Shear failure

Tensile failure

15×104step
Roof and floor

incompetent bed

Slo(c) Crack evolution and distribution
Figure 7: Crack evolution of single -level slots model inloading.
Figure 9 : Parameter variation around the medium slots (Dlocation) .

534

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 10: Parameter variation around the large slots (Flocation).

The analysis above found that the greater the slot
width, the lower the rock peak stress around the slot,
and the rock mass was more easily broken. Due to thelow stress, the porosity was increased significantly.
The cracks were mainly distributed around the areaof the adjacent slots. Compared with the multi-levelslots model, the cracks and stress were unevenly
distributed, inducing the instability phenomenon.

5. CONCLUSIONS(1) The experiment found that multi-level slots
can significantly weaken the coal strength, cause theoccurrence of micro-cracks around the slot, cause
crack propagation to form a rock-bridge, and lead tothe appearance and extension of numerous microcracks around slot surface.
(2) Under the conditions of the same slot
arrangement, the peak stress of the big slots model
was smaller and the fracture distribution was uneven.
As the slot size increased, the rock model became
more unstable and the porosity increased
significantly after the peak stress. The fractures of theuneven slot distribution model grew and extended
more significantly than the even distribution model,
and induced the coal and gas to more easily losestability.
6.

Journal of Rock Mechanics and Mining Science.
Volume 48, No.6, pp. 976-983.
Li X.H., Wang J.S., Lu Y.Y., Yang L., Kang
H.M., Sun J.J. (2000). Experimental investigation of
hard rock cutting with collimated abrasive water jets.
International Journal of Rock Mechanics and Mining
Science. Volume 37, No.7, pp. 1143-1148,.
Lu T.K., Yu H., Zhou T.Y., Mao J.S., Guo B.H.
(2009). Improvement of methane drainage in highgassy coal seam using waterjet technique.
International Journal of Coal Geology. Volume 79,
No. 1-2, pp. 40-48.
Lu Y.Y., Liu Y., Li X.H., Kang Y. (2010). A
new method of drilling long boreholes in low
permeability coal by improving its permeability.
International Journal of Coal Geology. Volume 84,
No. 2, pp. 94-102.
Lu T.K., Zhao Z.J., Hu H.F. (2011). Improving
the gate road development rate and reducing outburst
occurrences using the waterjet technique in high gas
content outburst-prone soft coal seam. International
Journal of Rock Mechanics and Mining Science.
Volume 48, No.8, pp. 1271-1282.
Shen C.M., Lin B.Q., Meng F.W., Zhang Q.Z.,
Yang W., Zhang L.J. (2012). Induced drill-spray
during hydraulic slotting of a coal seam and its
influence on gas extraction. International Journal of
Mining Science & Technology. Volume 22, pp. 785791.

ACKNOWLEDGEMENTS

Gratefully acknowledged the financial supportsof National Key Basic Research Development
Program (973 Program) (2011CB201205) andNational Major Projects of Oil and Gas(2011ZX05040-001).
7.

REFERENCES

Cundall P.A.,PFC2D user's manual (Version 3.1)
(2004). Minnesota: Itasca Consulting Group Inc.: 15p.
Huang B.X., Liu C.Y., Fu J.H., Guan H. (2011).
Hydraulic fracturing after water pressure control
blasting for increased fracturing. International

535

ISMS 2016

Paper No. 61
Numerical simulation on Gob gas migration law
He Ning a,*, Xiang Cong bab

Department of Safety Engineering College, North China Institute of Science and Technology, Beijing, China, 101601
Department of Safety Engineering College, Beijing Institute of Technology, Beijing, China, 100083

ABSTRACTIn the mining process, gas accumulation and overrun often occur in the upper corner of mining face, making it
important to create a numerical simulation to study goaf gas migration. In this paper, the numerical simulation ofgoaf gas was solved based on the ShenDong 1201 working face. The goaf gas concentration distribution was
performed, the heaviest accumulation area was given, and the goaf gas migration was developed.

1. INTRODUCTION（2）Momentum Equation:

High gas mines and coal and gas outburst mines
make up about 49.5% of state-run coal mines in
China. Gas emissions in one year are more than 15
billion squared. It is more common for gas
accumulation and overrun to occur in the upper
corner of mining face in the high gas mines and thecoal and gas outburst mines. Controlling methane
overrun in the working face has definite theoreticalvalue and practical significance. This is accomplishedby studying the gab gas concentration distribution,
mastering the rules of gas migration, and determining
the heaviest accumulation area. This paper usednumerical simulation to research the gas migration
law, based on SD1201 in fully mechanized caving
faces of the Shendong coalmine, which provides astrong basis for optimizing the layout of theunderground ventilation system and mine gas control.

∂( ρ j ui )2.

GOAF GAS MIGRATION LAWS OF
MATHEMATICAL MODELLING

Establish the control in differential equation witha porous medium and control theory of differential
equations.
（1）Equation of Continuity:∂u i ∂u j ∂u k
+
+
=0
∂x
∂y
∂z

（1）

u ,u ,uWhere, i j k is the mean velocity or thesurface velocity of the unit, in other words, it is theaverage velocity of the unit; its relationship with themean velocity of the pore is:u i = vi × n（1-2）

where, n is the porosity. In the following
mathematical model, the velocity is referred to as themean velocity of the unit, unless otherwise stated.

*Corresponding author – email: 283293363@qq.com

∂t

+

∂
∂p ∂τ ij++ Fi
( ρ j ui µ j ) = −∂x j∂xi ∂x j

Where, p −（2）static pressure, τ ij − stress tensor.

（3）Gas Component in differential equation:∂ ( ρYi )+ ∇ ⋅ ( ρv Yi ) = −∇J + Ri + Si∂t

（3）

Where, Ri is the net production rate of thechemical reactions, Si is the extra production ratecausing by the source terms that consist of discrete
phase and user defined.
（4）Energy equation:∂
(nρ f c f T + (1 − n) ρ s c s T ) + ∇ ⋅ (v ( ρ f c f uT )) = ∇k e ff ∇T + S h∂t（4）
Sh is the calorific value of residual coal ( w / m 3 ):Sh = η

2(b1 + βb2 )⋅r
1 + 2β（5）Where, η is the coefficient of flow geometry
factor, selected as 0.8 for this paper; b1, b2 is thethermal oxidation of coal oxidation that generates CO
and CO2 under a balanceable state, J/mol ; β is theratio oxidized to form CO and CO2, taken as β =10 inthis paper; r is the oxygen consumption velocity tocrushed coal in unit volume, kg/(s.m3).

3. NUMERICAL SIMULATION OF GOAFGAS MIGRATION

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3.1 SD1201 working face Overview
SD mine is a high-gas coal mine. SD1201 working
face main aquifer 3# coal has large gas content in thiscoal seam, with gas content at 15.87 m3/t and gas
emission at 40-50 m3/min. The working face uses the"U+L" ventilation system, and has a face length of
240.3 m and a strike length 1011.9 m. The specificarrangement to be used for drilling through layers ofgoaf gas drainage has a drilling hole entrance
arranged in the gas emissions lane layout, the drillinghole exit in the rock above the mined-out area within
the fracture zone, four drill holes uniformly arranged
between the two contact lanes (approximately 50 m)
drilled directly at 94 mm with a hole length of 120 m,
and a vertical coal wall with an elevation of 14°.
3.2 Computational grid and calculation conditions
Roadways are laid out and the computationalmodel is built According to the actual production of
the SD mine. The structured non-uniform grid of
discrete computational domain is used. The grid
number is 429,596. Roadway entrance and exit
turbulence parameters are shown in Table 1. Assume
goaf gas emission at the backplane and an emission
rate of 0.0076 m3/s (according to the actual case ofgas emission).

z=1.0mTable 1: The boundary conditions.
boundary conditions
Into the air inlet air flow troughvin=60.8m3/s

Auxiliary inlet air flow Cut

vin=24.8m3/s

Entrance into the wind trough the
turbulent kinetic energy
Entrance into the wind troughturbulent kinetic energy dissipation
Gushing outlets gas velocity, gasconcentration
return airway export boundary
Technical roadway export boundary
Boundary wall2

kin=(0.5~5%) × 1 2 v in
3/ 2

ε i n =cDk

/D

0.0076m3/s，100％
Pressure conditions of export
boundary
Pressure conditions of export
boundary
Wall function

4. RESULTS AND ANALYSIS
4.1 Results
Figures 1 and 2 showed the different sections
along the z-direction of air flow and the gas
concentration distribution. The cross-sections along
the z-coordinates of the location (the distance fromthe bottom) are: 1.0，2.5, and 5.0 m. It can be seenfrom the figure that gas concentration basicallyfollows the same trend at the different sections along
the z distribution. Figures 3 and 4 show the velocity
contours and the gas concentration distribution at thedifferent sections along the x direction. The locationof the profile along the x direction cut-hole from 0,
10.0, 20.0, and 30.0 m

z=2.5m537

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

z=5m

Figure 1: The gas concentration contours perpendicular toZ direction.

z=2.5mz=5m

Figure 2: The velocity contours along x direction.

Figure 3: The velocity contour along x direction.

z=1.0m

4.2 Results Analysis1) Due to fresh air in-leakage, air intakes near
the working face of the goaf area diluted and carried
off the gas along the airway, so the gas concentration
was quite small in this region. The gas tunnel and thedrainage hole which induced the air flow with gas
flowing out through the gas tunnel, drainage flowbelt, and the gas tunnel which induced the flow-belt of
the air with gas formed an effective "barrier"preventing gas in deep goaf flow into the upper corner.
The gas concentration within the goaf area and theupper corner was largely reduced.

538

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

6. ACKNOWLEDGMENT
This work was supported by Special Fund for
Basic Scientific Research of Central Colleges( AQ1202A).
7.

Figure 4: The gas concentration contours along the x direction.

2) With the advance of the working face, thescope of the mined area has increased. In the goaf area
beside the interconnection, the compaction degree ofcoal rock was weak, porosity was large, the air flow
velocity faster, and the gas concentration lower. The
gas concentration showed a rising tendency as the
distance from the interconnection increased. It wasmore effective for diluting the gas while the air
quantity and drainage quantity was large. This willlead to a fresh air flow into the goaf area which willcause spontaneous combustion in the goaf.

5. CONCLUSION
Based on the production conditions in SD coalmine, the numerical simulation of goaf gas was
solved. It can be seen that the gas tunnel and thedrainage hole, which induced the air flow with gas
flowing out through the gas tunnel, drainage flowbelt, and the gas tunnel which induced the flow-belt of
the air with gas formed an effective "barrier"preventing gas in deep goaf flow into the upper corner.
The numerical simulation of goaf gas found thegas concentration distribution in SD1201 working
face, thus concluding the gas delivery law. The gas
roadway and the drainage hole largely reduced the gas
concentration within the goaf area and upper corner ofthe working face by inducing the air flow with gas
flowing out through the gas roadway; a larger volume
of face air quantity and drainage value will help
somewhat ease the problems of gas accumulation in
the upper corner.
In the mining process, gas accumulation andoverrun often occur in the upper corner of the mining
face, making it important to build a numericalsimulation to study goaf gas migration. In this paper,
the numerical simulation of goaf gas was solved basedon the ShenDong 1201 working face. The goaf gas
concentration distribution was performed, the heaviest
accumulation area was given, and the goaf gas
migration was developed.

REFERENCES

Fan Weitang,"The status quo and development
orientation of long-wall mining technic in thick coalseam in China", Journal of China Coal
Society,1993,18(1):pp.5-6
Hu Qianting, Liang Yunpei, and Liu Jianzhong,“CFD simulation of goaf gas flow patterns”, Journalof China Coal Society, vol.32,pp.719-723, July.2007
Li Shugang,”Gas delivery feature and its control
irrfluenced by movement of the surrounding rock infully-mechanized top coal caving”, Chinese Journalof Rock Mechanies and Engineering, 2009,19(6):pp.809–810.
Meng Xianrui,Chen Haibo,”Top-coal movement
theory of top-coal mining and establishment of its
mathematical model”, Coal Engineering,2003,4(10):pp. 32–33.
Meng
Xianrui,
Zhang
Wenchao,andHeyongqiang, “Study of Gas Emission Characteristic
in Long-Wall Top Coal Caving Face with a High Gas
Content”, Journal of Ming& Safety Engineering, vol.
23, pp. 419–422, Dec. 2006.
Qin Yaoping, Liu Peng, “Research on
calculation error of simplified mathematical model ofgas emission in coalseam”, Journal of Ming& Safety
Engineering, vol.45, pp.19-24, Jan. 2016
Yuan Liang,“Strategic thinking of simultaneous
exploitation of coal and gas in deep mining”, Journalof China Coal Society, vol.41,pp.1-6, Jan.2016
Zhang Xuebo, Zhangfan,” Determination onreasonable length of wind curtain for‘U + L’type
ventilation in fully mechanized face”, Journal of
Safety Science and Technology,vol.12,pp.163-168,
Jan, 2016539

Paper No. 72

ISMS 2016

Research on the negative pressure distribution law and its application forboreholes in coal seam bedding gas extraction
Linchao Dai a,b,*, Kai Wang a,babState Key Laboratory of the Gas Disaster Detecting, Preventing and Emergency Controlling, Chongqing, China, 400037
Chongqing Research Institute Co., Ltd. of China Coal Technology and Engineering Group, Chongqing, China, 400037

ABSTRACT
Making boreholes along seams is a part of the distribution process of gas extraction in coal mines, and afundamental measure for preventing and controlling gas disasters as well as an important means to explore coal-bed
methane resources. Recently, the borehole technology along the seam has been widely applied to gas extraction withthe development of borehole rigs and kilometer-borehole rig. Presently, research by domestic scholars on theextraction theory mostly focuses on pre-extraction by boreholes through beds and shallow boreholes along the seam,with few considering the influence of viscous mechanics of gas flow in boreholes. Therefore, the research on thevariation of negative pressure inside the borehole along the seam is greatly important to guide the design ofboreholes along the seam for gas extraction, the determination of key parameters, and the theoretical application of
the technology.
This paper focuses on the distribution of negative pressure inside the boreholes along the seam and its application,with two sections: (1) The distribution of negative pressure inside the borehole along the seam in the borehole
direction. Based on gas occurrence, flow theory, fluid dynamics theory, and the definite mechanism of negative
pressure inside the borehole along the seam on gas extraction, both gas flow models around boreholes and inside
boreholes are established. Distribution of the negative pressure inside the borehole along the seam in the borehole
direction was found by classifying the pressure loss inside boreholes and coupling the flow conservation equationsof two models. The distribution of negative pressure inside the borehole was technically determined via field tests toverify the feasibility of the proposed models. (2) The application of the distribution of negative pressure inside theborehole along the seam in the borehole direction. Considering the shortages of traditional extraction processes, two
new ones were put forward applying the distribution of negative pressure inside the borehole along the seam in theborehole direction, and the extraction pipe reaching a certain distance or covering the whole length. Technicalprocesses such as theory analysis, field test, and numerical simulation verified the superiority of the new extraction
processes.
This study found the variation of negative pressure inside the borehole along the seam in the borehole direction andthe distribution of negative pressure inside the plume borehole along the seam, derived the calculating formula ofreasonable borehole length, put forward new extraction processes, and verified the superiority of the new extraction
processes in some conditions.
KEYWORDS: coal mine; bedding gas extraction; bedding borehole; inside-borehole negative pressure distribution
law

1.

INTRODUCTION

Gas extraction is fundamental for the prevention
and control of gas disasters in coal mines, and also an
important means to develop coalbed methane
resources. Particularly, bedding boreholes is one of
the important ways to distribute boreholes in gas
extraction of the coal mines (Wang, et al., 2005;
Wang, et al., 2006). In recent years, with thedevelopment of the drill and borehole rig as well as
the emergence of 1,000m borehole machine, thebedding long boreholes gas extraction technology has
been widely used. Hu (2011) carries out a theoreticalanalysis, field expedition, and numerical simulation*Corresponding author – email : dailinchao@126.com

process concerning seam long boreholes used forpreventing coal and gas outburst using Pan-yi mineand Pan-san mine as the experimental cases. The
purpose is to reduce construction volume, improvepumping rate, shorten the cycle of outburst, andachieve safe and fast driving. Xie, et al. (2013)selected Xin'an mine as a trial zone of the gas preextraction technology and studied the boreholes
drilled along the mining seam and the rationalparameter values of the gas pre-extraction technology
for coal seam.
However, with the in creasing length of theborehole, the extraction effect is not necessarily

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

necessarily improved (Lin, et al., 1990; Xu, et al.,2010). With the increase of borehole length, thepressure drop generated from the gas flow along theborehole length direction should not be ignored.
Extraction negative pressure will decay in the transfer
process. The extraction negative pressure hassignificant influence on the extraction effect to theextent that the extraction effect is possibly notsignificant when reaching a certain length. At
present, the domestic research on extraction theories
applies to cross-layer borehole pre-extraction andbedding borehole shallow borehole extraction,
without considering the mechanical impact ofviscosity on the gas flow in the borehole (Xin, 1998;
Li, 2012; Li, 2013). The changing law of negative
pressure along the length of long coal seam boreholes
is of great significance for the theoretical guidanceof the bedding borehole gas extraction design, thedetermination of key parameters, and technology
applications. Therefore, research on the distributionof negative pressure inside the borehole along theseam in the borehole direction and its applications
were studied.

2.

THEORETICAL ANALYSIS

Bedding boreholegas extraction can be divided
into two processes: the first process is the gas flow inporous media like coal; the second process is gas
flow inside the borehole.
The surrounding-borehole coal gas flow modeland the inside-borehole gas flow model can be set up
to characterize these two flow processes.
2.1 Surrounding-borehole gas flow model
A

A− A

A

Figure 1: Radial flow in coal around the borehole.

From the Figure 1, the unit length of coal at theborehole length direction is analyzed with theconclusion that field of gas flow in the coalcorresponds to a radial unsteady flow field. Gas flow
speed, direction, and pressure at any point in the flow
field change over time. The following equations canbe derived based on porous media theory, coal seamgas adsorption theory, and thermodynamics (Zhou, etal., 1965; 1990; Yu, et al., 1989).

∂X
div( ρ v) = − ∂t

K
v =
− ⋅ gradp

µ


abcp
X
=
⋅ ρ + np
(1 + bp )

ρn
=
ρ
⋅p

pn


(1)

(For concrete parameters refer to Sun, 1991;
1993; Wang, 2014). The solution to the solutiondetermination problem leads to the approximate
analytical solution of the gas seepage model of unit
length of coal, as is shown in formula (2).
abcp0 (2 + bp0 ) (2)λπq (t ) = ( R − r ) ⋅ ( p 2 − p 2 ) ⋅
[n +
]
0

0

1

(1 + bp0 ) 2

2 pn p0 t

2.2 Inside-borehole gas flow mode
In the process of gas flowing to the orifice, theinside-borehole gas flow corresponds to variable
mass flow due to the constant gas emission off fromthe borehole wall with the changing quality,. The
inside-borehole gas flow will result in pressure loss,
the four major factors being: on-way frictional
resistance loss, acceleration pressure drop, mixing
loss, and local resistance loss resulting from gas inflow of the borehole wall (Ozkan, 1992; Yuan, et al.,
1996; Zhou, et al., 1997; Schulkes, et al., 1997), as isshown in the Figure 2.
1

2

V1>V2
∆E

1

②

③

④

2

①

①On-way frictional resistance loss ②Mixing loss
③Acceleration pressure drop ④Local pressure loss
Figure 2: Classification of gas flow losses in the borehole.

In reality, due to the uncertainty of the borehole
deformation, and to facilitate the theoretical analysis,
it is presumed that the borehole wall is not deformedin the process of extraction; therefore, the local
pressure loss is zero.
q( x)
Q( x)
p( x)

qm − 2 qm −1 qm qm +1

q1 q2⋅⋅⋅ ⋅⋅⋅xx=0

Qm − 2 Qm −1 Qm Qm +1
pm − 2 pm −1 pm pm +1
vm − 2 vm −1 vm vm +1

qn −1 qn⋅⋅⋅ ⋅⋅⋅dx
x=L

Figure 3: The differential schematic of coal seam boreholealong the length direction.

It can be seen from Figure 3 that when the coal
body that is around the borehole is dispersed into
infinitesimal sections along the borehole length
direction, each gas flow in an infinitesimal section541

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

can be represented by the previously built gas flow
model around the borehole. Wall inflow mixing loss
is not calculated separately. Instead, the on-way
frictional resistance coefficient is modified, and themixing loss is included in the on-way frictional loss.
The on-way friction formula, continuity equation,and momentum equation can respectively infer onway frictional resistance loss ∆p fri and theobtained from the definite-solution problem (5).
However, the analytical solution to second ordernonlinear partial differential equations is very
complex; generally, the parameter substitution
process can greatly simplify the solving process.
The Chongqing Songzao Yuyang coal mine wasselected for the field test in this study. When using
the industrial parameters of Yuyang No. 7 coal seam
into the formula (5), it can be found that: when theorifice negative pressure is 7 KPa, the boreholepressure loss in the 100 meters process is 466.7 Pa.

acceleration pressure drop ∆pacc . When x is thevariable, the total pressure drop of dx infinitesimal
section can be drawn (Ihara et al., 1994; Wu, 1999;
Liu, et al., 2000).
dp ( x)= ∆p fri + ∆pacc
dx
2 f i ρ[2Q( x) + q ( x)]2 16 ρ[q 2 ( x) + 2Q( x)q ( x)]=+
π 2 D5π 2 D43.

(3)

In formula (3), f i is the frictional resistancecoefficient of wall fluid when it flows into theborehole, and its size can be calculated through theborehole flow state in the infinitesimal section, thatis, by calculating the Reynolds number (Re) of each
infinitesimal section, determine the flow state of thefluids, and use the calculation formula of thefrictional resistance coefficient f 0 when there is nowall fluids inflow to obtain the frictional coefficient.
Concrete parameters can be found in Fan, et al.
(2000) and Zhang (2009).


abcp0 (2 + bp0 )
λπ
2
2
[n +
]
q ( x, t ) = ( R − r0 ) ⋅ ( p0 − p1 ) ⋅2 pn p0 t(1 + bp0 ) 2

22
 dp ( x) 2 f i ρ [2Q( x, t ) + q ( x, t )] 16 ρ[q ( x, t ) + 2Q( x, t )q ( x, t )]
=
+

2 5
π D
π 2 D4
 dx
[
(
,
)]
d
Q
x
t

= − q ( x, t )dxThrough boundary condition:=, p (0) p1
 x 0==x0=, Q(0, t ) QTheinside-borehole
negativepressure
distribution formula of bedding borehole can be

Concentration
Bus tube and negative
pressuremeasurement

Extraction Borehole sealing
pipe
sectionCopper pipe

Coal seam

Air hole

Gas metering
Borehole sealing length is 10m; there are five measuring points in the borehole,which are 10m, 30m, 60m, 80m and 90m deep respectively.

Figure 4: Field test process for measuring the negative
pressure within the borehole.

In the 90 day extraction inspection period, threesets of representative data at three time points are
selected for analysis. The negative pressure values atdifferent depths inside the borehole with extraction
times of 10 days, 40 days, and 80 days are measured
and recorded, as is shown in Figure 5.
9.177 9.024

9.5

Negative pressure /KPa

2.3 Modal coupling
According to the theory of fluid dynamics, thegas flow of the infinitesimal section x from the orifice
is in line with the flow conservation equation (Ben,1990; Liu, et al., 2006), as is shown in formula (4).
d [Q ( x)](4)= −q( x)dx
The gas flow model of surrounding-boreholecoal and inside-borehole gas flow model can becoupled through the following inside-borehole flow
conservation equation (5).

FIELD MEASUREMENT

The borehole that is 100m deep in the N3702
transportation lane of Yuyang Coal Mine uses copper
pipe as its connecting pipe. Combined with the fullhole-section downing sieve pipe process, hollow
copper pipes with different lengths are sent into theborehole to determine different negative pressure
values at varying depths. The negative pressure fieldtest process diagram is shown in Figure 4.

8.761

87.315 7.182

6.55.985

6.883

8.477

8.379 8.329

6.617

6.501 6.451

5.087

4.951 4.921

5.719
5.353

5
10 days

40 days

80 days

3.5
0

20

40
60
80
100
Borehole depth/m
Figure 5: Negative pressure distribution in borehole indifferent extraction time.

From Figure 5, the curve of negative pressure
distribution of different depths inside the borehole atdifferent time shows that the inside-hole negative542

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016pressure of bedding gas extraction decays along theborehole length direction. The 100 m attenuation in
the extracted borehole is about 800 Pa in the fieldmeasurement. However, the theoretical calculation
does not consider factors such as the occupied area ofcopper pipe, borehole leakage, and borehole
deformation, which will increase pressure loss. The
built theoretical model is feasible and in accord withthe requirements of engineering practice.

4.

reducing negative pressure loss and increasing thenegative pressure of the whole borehole section. At
the same time, because of the frictional resistanceloss, the differential pressure on both ends of theborehole sealing section will be reduced and the leaksituation will be improved compared to the traditional
extraction process.
The maximum negative
pressure value

APPLIED RESEARCH

The traditional extraction process has many
shortcomings, as shown in the negative pressure
distribution law in the bedding borehole of Figure 6.
(1) With longer boreholes, borehole pressure loss ismore serious and the extraction effect is more andmore poor along the borehole length direction. (2)The maximum negative pressure at the orifice and theformation of the differential pressure on both ends ofthe borehole sealing section are very big, therefore, itis easy to cause leakage that leads to low extraction
concentration and a poor extraction effect. (3) Coalquality in many of China's coal mines is soft and easy
to deform after forming the borehole. This increases
the frictional resistance coefficient of the coal walland causes negative pressure attenuation if theborehole collapse blocks the negative pressure in the
direction of the borehole’s bottom due to borehole
scraps.
The maximum negative
pressure value∆p∆p

Negative pressure/P∆p

Borehole sealing section
Extraction
pipe

Borehole length/L∆p

Figure 7: Extending extraction pipe process.

(2) Soft coal - using sieve pipe
As shown in Figure 8, the friction factor of thesieve pipe is much smaller than the coal wall(commonly used industrial piping equivalentroughness). New polyethylene pipe K s (the stability
against sliding coefficient) is 0 - 0.002, concrete pipe
K s is 0.3 - 3.0), reducing the negative pressure
losses from orifice to bottom. At the same time, it cankeep the gas flow channel clear when boreholecollapse occurs, improving the extraction effect andraising the utilization rate of the borehole.
The maximum negative
pressure value

Negative pressure/P
Borehole collapse

Borehole sealing section
Extraction
pipe

Borehole length/L

Negative pressure/P∆p∆p

Figure 6: The traditional extraction process.

Two new extraction processes in view of thehard and soft coal quality were put forward to address
the deficiency of traditional extraction processes,
combined with borehole forming conditions andnegative pressure distribution in the borehole.
(1) Hard coal - extending extraction pipe
As shown in Figure 7, compared with thetraditional extraction process and under the same
borehole length, extending the extraction pipe places
the maximum negative pressure in the middle of theborehole. The distance of the maximum negative
pressure on both sides in the borehole is shorter,

Borehole sealing section
Extraction
pipe

∆p

Borehole collapse

Borehole length/L

Sieve pore

Figure 8: Using sieve pipe to replace extraction pipe.

In order to verify the superiority of the new
extraction process, a field test was carried out inN3702 working face. Traditional extraction process
were used for the No. 1 borehole, extending
extraction pipe process was used for the No. 2
borehole, and the sieve pipe process was used for the
No. 3 borehole, as shown in Figure 9.

543

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Concentration
Bus tube and negative
pressuremeasurement

Extraction
pipe

Sealing segment Copper pipe Air hole(b) Extraction for 40 days

Coal seam

9400

9100

Negative pressure /Pa

Borehole sealing length is 10m; there are five measuring points in the borehole, whichare 10m, 30m, 60m, 80m and 90m deep respectively.

9024
8877

8800

Borehole sealing length is 10m; there are three measuring points in the borehole, which are
10m, 50m and 90m deep respectively.

8778

8500

Borehole sealing length is 10m; there are no measuring points in the borehole.

7500
Negative pressure value/Pa

7200

No.1
No.2

7182

6900

6883

6780

6750
6617

6600

6501
6451

6300
0

20

40
60
Borehole depth/m(a) Extraction for 10 days

80

100

6300
6000

5985

Negative pressure /Pa

No.1
No.2

5985

5700

5719

5400

5423

5453
5353

5100

5087
4951
4921

4800
0

20

40
60
Borehole depth/m

80

8477

0

,The negative pressure distribution in theborehole of the traditional extraction process and theextending extraction pipe process were compared andstudied under conditions of the same borehole sealing
quality. The inspection period of extraction time was
90 days. The negative pressure values of different
depths in the borehole were determined and analyzed
by field measurement under the three representative
stages in extraction time for 10 days, 40 days, and 80
days, as shown in Figure 10(a), (b), and (c).

7315

8761

8379
8329

8200

Figure 9: The compared field test of extraction effect under
different extraction processes.

7315

No.1
No.2

9177

9177

Gas table

100

20

40
60
80
100
Borehole depth/m(c) Extraction for 80 days
Figure 10: Negative pressure distribution of No. 1 and 2
borehole.

From Figure 10 (a), (b), and (c), negative
pressure in the borehole presents an attenuating trend
distribution along the borehole under conditions of
the traditional extraction process, and negative
pressure in the borehole presents a "mountain" trend
distribution along the borehole under conditions of
the extending extraction pipe process. The area
covered by the curve in the figure shows that the
average negative pressure value and full negative
pressure energy of the extending extraction pipe
process are bigger than for the traditional extraction
process. Using the sieve pipe process in the fullborehole section can not set pressure measuring
points, therefore the experiment of negative pressure
determination in the borehole was not carried out.
The two extraction effects (extraction
concentration and flow) were taken for indexes, andcompared under the different extraction processes inorder to verify the superiority of the new extraction
process.
The extraction concentration investigation forborehole No. 1, 2, and 3 are shown in Table 1.
Table1: Extraction concentration of borehole No.1, 2, 3.
Extraction
Extraction concentration (%)
time(d)
No.1
No.2
No.3
0
93%
89%
90%
3
66%
95%
95%
11
89%
95%
95%
27
89%
85%
95%
37
30%
50%
90%
50
30%
50%
90%
58
30%
50%
30%
64
30%
93%
30%
78
70%
90%
80%
86
66%
80%
83%
93
65%
85%
85%

544

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Within 90 days of extraction time, extraction
effect: No.2 borehole > No.3 borehole> No.1
borehole. Under the same borehole sealing quality,
the extending extraction pipe process is superior to
the sieve pipe process, and the extraction effect of the
traditional extraction process is the worst.
The cumulative mixed flow and theaccumulative gas flow trend figures of boreholes No.
1, 2, and 3 found by field measurement are shown in
Figures 11 and 12.
Accumulative mixed volum/m³

4000
No.1
3000

No.2
No.3

2000

the two indexes are the lowest and the borehole islikely to leak. Negative pressure loss is the mostserious, therefore it should be improved. The
concentration and flow rate for the No. 2 borehole
using the extending extraction pipe process are better
than that of No. 1 and 3 borehole. Implementation is
simple in the field, and is worth promoting. The
extension concentration and flow rate for No. 3 using
the sieve pipe process are better than No. 1 boreholeand smaller than No. 2 borehole. The reason is thatthe small sieve pore on the pipe restrains the gas flow
into the pipe. When the borehole undeforms, theadvantage of using the sieve pipe process is not
obvious. However, using the sieve pipe process insoft coal seams has a better effect.

5.

1000

0
0

20

40
60
80
100
Extraction time/dFigure 11: No. 1, 2, 3 borehole accumulative mixed flow
trends.
4000
Accumulative gas volum/m³

No.1

3000

No.2
No.3

2000

1000

0
0

20

40
60
80
100
Extraction time/dFigure 12: No. 1, 2, 3 borehole accumulative gas flow
trends.

From Figures 11 and 12, the accumulative mixed
flow and accumulative mixed gas flow of threeboreholes show a rising trend with the increase of
extraction time. The borehole extraction effect issuch that No. 2 > No. 3 > No. 1. Under the same
borehole sealing quality, the extending extraction
pipe process is superior to the sieve pipe process, andthe extraction effect of the traditional extraction
process is the worst.
According to the above, it can be obtained thatthe extraction effect of No. 1 borehole using the
traditional extraction process is the worst. Meanwhile

CONCLUSION(1) The gas flow model in the coal body aroundthe borehole and the calculation model of gas flow inthe borehole were established. The pressure
distribution calculation model in the bedding gas
extraction borehole was found, and a field test
calculation was carried out to verify the feasibility ofthe built model.
(2) The field test process was applied todetermine the different depth points of negative
pressure values in bedding gas extraction boreholes.
The negative pressure distribution law along the long
boreholes was summarized, Results showed that thenegative pressure presents an attenuation trend
distribution along the long borehole direction in thebedding gas extraction boreholes.
(3) In order to address the shortcomings of the
traditional extraction process, two new extraction
processes were put forward, namely the extending
extraction pipe process and the sieve pipe process.
(4) Through the extraction effect contrast test
under different extraction processes, the extraction
effect of the new extraction process was found to bebetter than the traditional extraction process. In coalseams with good borehole forming conditions, it is
optimal to use the extending extraction pipe process.
In coal seams with bad borehole forming conditions,using the sieve pipe process is optimal.

6. ACKNOWLEDGEMENT
This study was financially supported by National
Natural Science Foundation of China (51574280,
51374236), Chongqing Frontiers and Applicationbased Research Program (cstc2015jcyjBX0076), The
Science and Technology Innovation Fund of China
Coal
Technology
andEngineeringGroup(2015ZDXM14, 2015ZYJ002).

7. REFERENCES

545

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Ben, J.D. (1990). Pressure drop in horizontal
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Hu, S.T. (2011).Optimization of processparameters and application of along seam long
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Ihara, M. (1994). Flow in horizontal wellborewith influx through porous wells. SPE 28, pp.485
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546

ISMS 2016

Paper No. 86
Mathematical simulation and experiment of CBM detection
LIANG Qing-hua*
China Coal Technology Engineering Group Chongqing Research Institute, Chongqing, China, 400039

ABSTRACT
In order to accurately detect the underground Coal Bed Methane (CBM) accumulation in coal mining faces by mineradio wave perspective method, this study simulated the characteristic curve of received values through coal seams
and discussed the feasibility of CBM. The experiments were conducted in Chinese mines. The study concluded
that the existence of CBM could cause abnormal areas. Compared to the normal reception curve, the abnormal curveof CBM showed a much smaller value, and the attenuation was larger in the middle area and smaller on both sides.
The pattern formation was a "saddle" shape. The radio wave penetration method could be a more reliable method forthe detection of CBM in underground coal mines.

Coal Bed Methane (CBM) has a great influenceon the normal production of coal mines. When coalmines are enriched there is a chance of explosion.
Mining methods have changed in order to avoid this.
Coal and CBM total mining technology is a main
research direction for coal mines in China. The
distribution of CBM is irregular and the physicalparameters of CBM are not obvious, therefore,
research into CBM detection technology andequipment is difficult. At present, there exists noeffective method to detect CBM in the working face ofcoal mines in China. Previous studies have not been
concerned with radio wave instrument detection
through CBM. There has been no research on thecharacteristic curve perspective of radio waves for
CBM detection. For the present study, the authors
conducted curve theory perspective detection on radio
waves through CBM using mathematical simulation
tools, combined with coal mine experiments to verify
the reliability of the theoretical analysis in order tomake reference for similar mines.

1. THE BASIC PRINCIPLES
Mine radio wave perspective is used to detectvarious geological formations through two tunnels.
The transmitter and receiver are located in different
tunnels. The transmitter is in a relatively fixed position
within a predetermined time and the receiver received
field strength values are within a certain range (Liu etal., 2014; Wan et al., 2011) point by point, as shownin Figure 1.
Assume that the radiation source midpoint O is
the origin, in the approximately uniform and the same
nature seam, the distance from the observation point P
to the point O is r , electromagnetic field strength at*Corresponding author – email: linqing1110@163.com

point P H P is represented by (Liang et al., 2009; Liu etal., 2012; Li et al., 2011; Wu, 2002):
O

Transmission tunnel

Transmission pointr
Coal seam

Reception tunnel

Reception pointP

Figure 1: Schematic diagram of radio wave tunnel
perspective instrument.
H P = H0e−β rf (θ )
r(1)

In formula (1), H 0 is the initial field intensity
around the antenna seam at a certain transmission
power, A/M. β is the coal absorption coefficient ofelectromagnetic waves. r is the straight-line distanceof P point to O point, m. f (θ ) is the directivity factor.
θ is the angle between the dipole axis and the
direction of the observation point, which is generally
used to calculate f (θ ) = sin(θ ) .
According to the literature (Liang et al., 2010),
take ln( H p ) = H P′ , ln( H 0 ) = H 0′ :H P′ = H 0′ − β r − ln(r )(2)islittlechangeintheformula
(2),
it
can
be
ln(r )
approximated that formula (3) is the slope of thestraight line − β . H P′ and r are considered to have anapproximately linear relationship.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016y2. MATHEMATICAL MODELLINGSTUDIES OF CBM

According to formula (3), the change in H P
can be simulated.

′ with200m

Coal seam F

G
H

E

Fault

Transmission tunnel

O(0,0)

500m

Transmission pointy
Reception point
Reception tunnel

500m

Coal seamPr

Collapse column

Transmission tunnel

O(0,0)

x

Transmission point

4-b Model of a collapse column

Reception point
Reception tunnelyReception point
Reception tunnel
D

500m

C

Coal seam

200m

200m

x

4-a Model of a fault

200m

According to most of the coal mining facefeatures in China, the length of the tunnel model was
500 m, and width was 200 m. The transmission point
was below the midpoint in the tunnel, with the tunnel
below the midpoint as origin O (0,0), as shown in
Figure 2. According to the experience of underground
exploration, H 0′ was generally in the 110-155 dB
range, and the β varied between 0.2 and 0.55. Most
simulation parameters were selected as coal mine
normal physical parameters.
Here H 0′ = 130dB and normal seam β = 0.3.

Reception point
Reception tunnel

Transmission tunnel

O(0,0)

500m

Transmission point

Coal seam gas

Coal seamx

Figure 2: Normal coal seam simulation model.

Transmission tunnel

A

B

O(0,0)

Transmission pointx

4-c Model of CBM

H P′

Figure 4: The simulation model of various abnormal cases.

(dB)

x(m)

Figure 3: The reception value changes of abnormal cases.

In the normal case, coal seam function was
F(x,y) = {−250 ≤ x ≤ 250,0 ≤ y ≤ 200} . According toformula (2), when the reception points moved in astraight line, we had：130 − 0.3 x 2 + y 2 − ln x 2 + y 2 ,H P′ = ( y = 200,−250 ≤ x ≤ 250)
(3)

According to formula (3), using the MATLAB
simulation, the field-strength curves of the normal coalseam reception values were found, as shown in Figure
3.

Impact of fault simulation: To simplify thecalculations, the intermediate simulation model was afault with a fault length of 100 m and distance of 5 m(Figure 4-a). The attenuation coefficient of the fault
was β = 0.5 and changes on the fault model abscissa
were x : −50 ~ 50 , ordinate y : 100 ~ 105 . Fault
function was F1(x,y) = {−50 ≤ x ≤ 50,100 ≤ y ≤ 105} .
When electromagnetic waves went through the fault:
2
2
2
2


′ = 130 − 0.3 x + y − ln x + y − 1, .
H Pf
 ( y = 200, − 100 ≤ x ≤ 100)
Impact simulation of collapse column: A circularcollapse column was in the middle of the model(Figure 4-b). The attenuation coefficient was β = 0.5
and the radius was 50 m. The circular collapse column
equation was: x 2 + ( y − 100) 2 = 2500 .
The
functionofcollapsecolumn:22.
Whenelectromagnetic
F2(x,y) = {x + ( y − 100) ≤ 2500}
waves went through the collapse column:
130 − 0.3 x 2 + y 2 − ln x 2 + y 2 −


 .
′ =
H Pcc
x 2
200
200 
2
≤x≤
)
0.4 50 − [100 sin(arctg )] , ( y = 200,−
y

3
3 

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Impact simulation of CBM: CBM was located in
the middle of the model (Figure 4-c). The attenuation
coefficient was β = 0.5 . The influence scope of CBM
was: −50 ≤ x ≤ 50 , 0 ≤ y ≤ 200 . CBM function:
.
When
the
F3(x,y) = {−50 ≤ x ≤ 50,0 ≤ y ≤ 200}
electromagnetic wave through the CBM:

been verified many times in actual detection
experiments.
In the actual detection process, due to the
influence of other factors, changes in the data might
not be in strict accordance with this rule, but the basic
trend is substantially the same.

130 − 0.3 x 2 + y 2 − ln x 2 + y 2 + 10 x 2 + y 2 / x,
 y = 200, − 250 ≤ x < −50

2
2
2
2
.

′ = 130 − 0.5 x + y − ln x + y ,H Pwz
 y = 200,−50 ≤ x ≤ 50
130 − 0.3 x 2 + y 2 − ln x 2 + y 2 − 10 x 2 + y 2 / x,
 y = 200,50 < x ≤ 250

3. EXPERIMENTAL STUDY ON CBM
Yanmazhuang mine had a CBM enrichment
phenomenon in Henan Province of China, whichbrought some difficulties to the production and safetyof coal. In order to discover the enrichment of CBM
the coal seam was detected.
The coal seam thickness of 27131 working face
was 5.9-6.5 m in Yanmazhuang mine, the length was
370 m, the inclination was 110 m, and the average dip
angle of the coal seam was 5°. To ensure thepenetration distance and detection accuracy, afrequency of 0.5 MHz was chosen and the fixed point
scanning method was selected. The reception points
space was 5 m and the transmission point space was
50 m. The results of the survey are shown in Figure 6,
from left to right of the upper roadway: 800 to 895,
from left to right of lower roadway: 200 to 274.
Through the computer data processing, two moreconcentrated anomaly areas were drawn andnumbered the no.1 and no.2 areas. The detected
anomaly areas colour was mainly gray and black.
No.1 abnormal area: The abnormal area was
located in the right of Figure 6 and was the largest areaof electromagnetic wave attenuation. Combined withcoal mine geological data, there was no large
geological structure. Coal gas content was 16-18 m3/t,
therefore, the anomaly analysis was mainly caused by
the change of gas concentration, and this area was acoal and gas outburst danger area.
No.2 abnormal area: The abnormal area was
located in the left of Figure 6. The coal gas content inthis area was relatively low, at 3-4 m3/t, but there wasa large F147 fault. Therefore, the regional anomaly
was mainly caused by large faults, which was not indanger of outburst.

H P′
(dB)

x(m)

Figure 5: The reception value changes of various abnormalcases.

Based on the above abnormalities, the comparison
diagram of various abnormal conditions could be
simulated, as shown in Figure 5. With respect to thereception value for normal seam, the fault curve wasrelatively gentle; however, the received values weresignificantly decreased at the fault. The values of thecollapse column curve were gradually smaller, andthen gradually became larger. In contrast, the values of
the CBM curve were small, further intermediate
region attenuation was larger, and the sides relative
attenuation were relatively smaller, forming a "saddle"
shape. Therefore, under the conditions of CBM thereception value of radio wave perspective wassignificantly decreased, and curves showed the overallattenuation characteristics, a typical characteristic of
CBM. The conclusion of this curve has been verified
in the thesis of Dr. Wu Yanqing (2002), and has also
Y:Width(m)100
No.1 Area50
No.2 Area

0
-100

-50

0

-25

-20

50

100

-15

150

-10

200

250

-5

0

300

350

X：Length(m)Figure 6: Radio wave penetration result map of 27131 working face in Yanmazhuang mine.

549

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 20167-a fault curve

7-b CBM curve

Figure 7: Typical curves of CBM and fault in mine.

The typical curves of Figure 7 were analyzed.
Figure 7-a was a variation of the fault curve. The
coordinate of transmission point number 200 was (x:0,y:0) in Figure 6, and the coordinate of reception point
number 807-827 was (x: -100-0, y: 110) in the vicinityof the No.2 abnormal area. The measurement curve
was below the theoretical curve in Figure 7-a, and thebasic form was similar to the theoretical curve. It wasin line with the change of the abnormal fault curve in
Figure 5.
Figure 7-b was a variation of the CBM curve. The
coordinate of transmission point number 880 was(x:265, y:110) in Figure 6, and the coordinate ofreception point number 245-265 was (x：225-325，y：0) in the vicinity of the No.1 abnormal area. From
the CBM curve, the measurement curve was below thetheoretical curve. The curve changed from relatively
flat at the beginning to a more rapid decay, and thenquickly climbed to the initial value. The characteristicof the measurement curve was in agreement with thetheoretical curve of Figure 5. The existence of a gas
enrichment zone in the area was described, and it wasalso proven that the curve of the simulation wascorrect.

4.

CONCLUSIONS

Because of the differences between CBM andnormal coal seam, the exist of CBM made theelectromagnetic wave refraction, reflection andabsorption vary. The CBM could be seen as a loss ofelectromagnetic energy, therefore CBM could cause
abnormal erosion areas on radio wave perspective.
After the scene of the experiment in coal mine, radio
waves perspective method could be more reliable todetect CBM. In the actual detection process, changes
in the data were affected by other factors, which would
not change in strict accordance with this law, but thebasic trend was roughly the same. This required acomprehensive analysis based on the analysis of thedata.
From the simulation analysis of the radio wave
perspective curve, with respect to the reception value
for a normal seam receiver, the values of CBM curve
were smaller. The values for attenuation were bigger
in the middle region and smaller in the side edge,
forming a ‘saddle’ shape. Therefore, in the conditionsof CBM, the reception value of radio wave perspective
was significantly decreased and the curves showed alarge area of overall attenuation characteristics typicalof CBM.
Detection and qualitative analysis of CBM
enrichment area by radio wave perspective method
broke through the blind zone of the CBM
accumulation area, filling a gap in the research. The
technology of underground CBM detection has strong
practical significance for safe production in coal mines.
5.

REFERENCES

CHENG Jiu-Long, LI Li, YU Shi-Jian. (1999).
Research on direct current electric field characteristics
of overburden failure and its applications. Journal of
Coal Science & Engineering, Volume 5, No. 1, pp. 2429
Li J H, Zhu Z Q, Feng D S, et al. (2011).
Calculation of All-time Apparent Resistivity of Large
Loop Transient Electromagnetic Method with very
Fast Simulated Annealing. Journal of Central South
University of Technology, Volume 18, No. 4, pp. 287291
LIANG Qing-hua, SONG Jin. (2009). Advanced
detection theory and experimental research of multiwave and multi-component seismic exploration inmine. Journal of Central South University（Scienceand Technology), Volume 40, No. 5, pp. 1392-1398
LIANG Qing-hua, WU Yan-qing, SONG Jin.
(2010). Study on the qualitative analysis andapplication of radio wave tunnel perspective. Journalof Chongqing University(Natural Science Edition),
Volume 33, No. 11, pp. 113-118
LIU Jian-xin, DENG Xiao-kang, GUO Rongwen, et al. (2012). Numerical simulation of advanced
detection with DC focus resistivity in tunnel by finite
element method. The Chinese Journal of Nonferrous
Metals, Volume 22, No. 3, pp. 970-975
LIU Sheng-dong, LIU Jing, YUE Jian-hua.
(2014). Development status and key problems ofChinese mining geophysical technology, Journal of
China Coal Society, Volume 39, No. 1, pp. 19-25
MEI K K, FANG J Y. Superabsorption—amethod to improve absorbing boundary conditions[J].
IEEE Trans, Volume 40, No. 9, pp. 1001-1010
WAN Guoxiang, LI Xibing, WANG Qisheng.
(2011). Effect of linear joint on propagation of rockelectromagnetic emission. Journal of Central South

550

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

University（ Science and Technology), Volume 42,
No. 4, pp. 1133-1139
WU Yan-qing. (2002). Study on the undergroundelectromagnetic wave detection and application.
Changsha: Central South University, 75p.

551

ISMS 2016

Paper No. 89

Numerical modelling and rescaled range analysis on spontaneous combustion
under surface methane drainage in a Chinese coal mine
Xincheng Hu a,b,c, Shengqiang Yang a,b,*, Wei Victor Liu c, Jiawen Cai a,b, Xiuhong Zhou a,baSchool of Safety Engineering, China University of Mining and Technology, Xuzhou, China, 221008
Key Laboratory of Gas and Fire Control for Coal Mines, Xuzhou, China, 221008c
Department of Civil & Environmental Engineering, University of Alberta, Edmonton, Canada, T6G 2W2b

ABSTRACTIn China, surface boreholes have frequently been used to drain methane/gas emitting from overlying layers andlongwall mining gobs in underground gassy coal mines. In this work, a numerical model was established using
COMSOL TM to study the influence of surface drainage boreholes on coal spontaneous combustion and Rescaled
Range Analysis (R/S analysis) was employed to investigate the chaos characteristic of Nitrogen (N2)/Oxygen (O2)drained from the gob. The simulation results show that there is a circular “dissipation zone” around the drainage
borehole all the time and an elliptic “spontaneous combustion zone” when the borehole is located in deep gob. It isalso found that the advancement of drainage boreholes has little influence on spontaneous combustion zones on theintake side of the gob but it can tremendously enlarge the width of a “spontaneous combustion zone” in the middle
gob and reduce the depth of self-heating zones near the return side. The R/S analysis indicates that the influence of
surface boreholes on spontaneous combustion can be divided into two stages: the safety drainage stage (Hurst index> 0.85) and the spontaneous combustion initiating stage (Hurst index≤ 0.85). It can be concluded that the gas
drainage from gob through surface boreholes can tremendously intervene spontaneous combustion "three zones" ingob. In addition, the length-fixed R/S analysis on N2/O2 series from surface boreholes can effectively reflect coalspontaneous combustion conditions in gob.
KEYWORDS: Coal spontaneous combustion; surface drainage borehole; Hurst index; R/S analysis

1. INTRODUCTION
Coal spontaneous combustion has long been oneof the most serious disasters in underground longwall
coal mines, especially in the working face gobs
(Ham, 2005). In China, about 32% of undergroundcoal mines are spontaneous combustion prone andhighly gassy (high methane content), which may
cause severe disasters, especially when mining goesincreasingly deeper (Zhou et al., 2013).
In highly gassy coal mines, methane drainage
must be carried out before or along with mining.
However, improper gas drainage may induce coalspontaneous combustion, leading to disastrous
methane combustion and even explosions. In spite oflong-time research on coal spontaneous combustion
and methane prevention (Song and Kuenzer, 2014),
few recent studies have addressed the severe threat of
the combined effects of methane and coalspontaneous combustion (Madeja-Struminska andWidzyk-Capehart, 2006).
Although much research has focused on fracturedevelopment and gas migration after mining, little
attention has been paid to coal spontaneous
combustion caused by methane drainage. The 10416
working face in Yangliu Co.ltd., Huaibei, Anhui
Province, China, was chosen to investigate theinfluence of surface methane drainage on coalspontaneous combustion in gob. COMSOLTM wasadopted to simulate the influence of surface drainage
boreholes on coal spontaneous combustion in gob.
The chaos characteristic of N2/O2 indicator series
collected from one surface borehole was analyzed
using Rescaled Range Analysis (R/S analysis). The
risk of coal spontaneous combustion in 10416
working face gob was divided and the corresponding
critical values were confirmed in the end.

2. WORKING FACE DESCRIPTION
Coal 10, with an average distance of 74 m, 81 m,
and 106 m from overlying coal 82, 81, and 72, ismined in 10416 working face. As the middle coalseams (72, 81 and 82) are coal and gas outburst prone,
it serves as the remote protective layer for these three
middle coal seams. In order to control the methane in
the middle coal seams and the gob, surface drainage
boreholes were drained before the advancement of
10416 working face to extract methane relieved fromoverlying methane-bearing strata and the longwall
face gob.
As seen in Figure 1, the surface boreholes werelocated at the middle of working face, 70 m from thereturn tunnel in the dip direction. The surface
drainage holes were drilled to the gob of the face,with an opening diameter of 311 mm and a final*Corresponding author – email: ShengqiangYang@hotmail.com

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

diameter of 91 mm. To guarantee long-term
extraction effect, the interval was set as 120 m.
Intake tunnel

Barrier pillar

Gobpermeability in the middle and deep gob. There is arelationship between porosity and permeability in thegob, according to the Carmon equation:𝑘=

Coal 1010416 working face

Surface drainage borehole

Return tunnel
Barrier pillar

2
𝐷𝑝

𝑛3

(1)

150 (1−𝑛)22

Where k is the permeability in the gob, m ; n is
the porosity in the gob, m; Dp is the average particle
diameter in the gob, m. In order to simulate flow fieldin the gob, the boundary conditions were confirmed
as per the practical parameters of 10416 working face
as shown in Table 1.
Table 1: The boundary conditions of 10416 working face
Site
Size
Flow
Boundary
Intaketunnel4 m×10 m

Free
flow

Pressure(0 Pa)

4 m×10 m

3. THE INFLUENCE OF SURFACEMETHANE DRAINAGE ON COALSPONTANEOUS COMBUSTION IN GOB

ReturntunnelFree
flow

Velocity(2.1 m/s)

Workingface

180 m×2 m

Free
flow

/

3.1 Modelling of 10416 working face gob

Supporterarea

180 m×4 m

Free
flow

/

Gob

180 m×150 m

Porousflow/

Surfaceborehole

91 mm(diameter)

Free
flow

Velocity(0.5 m/s)

Figure 1: Tunnel arrangement of 10416 working face,
Yangliu coal mine (units are in meters)

Porosity

ReturnReturnGob

Working face
IntakeFigure 2: Porosity distribution in 10416 gob area

The height of the fractured zone can be
confirmed as 35 m according to the empiricalformula used by other researchers (Yang et al., 2011).
The 10416 working face gob is slightly affected by
the gas that might emit from the middle coal seams
because of the long distance to coal 10 (Szlazak,
Obracaj et al., 2014). Due to the remoteness of gasbearing coals, the simulation model of 10416
working face gob can be simplified as a twodimensional model, as previous researchers havedone (Yuan and Smith, 2007).
As the porosity is dustpan– shaped in gobs (Li,Wu et al., 2008), the porosity distribution in 10416
working face gob can be estimated (Figure 2), and ishighly permeable along the boundary with low–

Although there are three main criteria (O2concentration criteria, flow velocity criteria, andtemperature
ratecriteria)
indetermining“spontaneous combustion zone”, flow velocity
criteria was chosen to indicate the self–heating
danger in gobs because of the arduousness insimulating O2 concentration distribution and heatfield in gobs. It is recognized that if the flow rate in a
gob is between 0.1 m/min and 0.24 m/min, the site isin a spontaneous combustion area. As the gob has
been seen as porous media (Karacan et al., 2007), theFree and Porous Media Flow Model was chosen in
COMSOLTM to simulate the influence of surface
methane drainage on “three-zone” distribution in thegob.
3.2 The influence of surface drainage borehole on“three zones”
Methane can be drained by surface drainage
boreholes, thus tremendously disturbing the airflow
distribution. Figure 3 describes the distribution of
three zones in the gob with different strike depths ofsurface drainage boreholes. Overall, the influence ismore obvious on the return side of the gob than theintake side. There is a circular dissipation zone
around the borehole during the whole extraction
process and an elliptic ring-sized spontaneous553

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016combustion zone when the borehole reaches the deep
gob. With the movement of boreholes to deeper gobs,
the spontaneous combustion zone near the return sideadvances toward the face while the dissipation zone
narrows. By contrast, the impact on the intake side issmaller compared with the return side. However, thespontaneous combustion zone near the borehole isreduced at the beginning and then broadened with theincreasing depth.
The spontaneous combustion zone is encroachedby both the dissipation zone and the suffocation zone,
owing to the drainage effect of the surface borehole
in shallow gobs (around 30 m). When the location of
the borehole approaches the middle gob (around 60m), there is a round dissipation zone around thedrainage hole. The width of the self –heating zone
near the intake side of the drill is increased whilst the(a) Strike depth=30m(c) Strike depth=90m

depth along the return roadway is reduced. With thefurther advancement of the face (about 90 m), theinfluence of the surface borehole enlarges. The
spontaneous combustion zone near the drill is drained
to deeper gob with greater width, but the width along
the return roadway is shortened. When the boreholegoes deeper (120 m), an elliptic ring–shaped
spontaneous combustion zone emerges. As a result,the gob along the moving route of the drill is moredangerous than other area in gob because of theenlarged spontaneous combustion zone and the long–
lasting elliptic self –heating zone around the drill.
Due to the complexity of methane drainage throughsurface boreholes, the prediction of the coalspontaneous combustion condition in gobs is of great
importance.

(b) Strike depth=60m(d) Strike depth=120m

Figure 3: The influence of strike location of surface drainage borehole on spontaneous combustion in gob

4. COAL FIRE PREDICTION DURINGMETHANE DRAINAGE

4.1 Chaos characterisation554

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Rescaled range analysis (R/S analysis) is widely
employed to scale the chaos characteristic of timeseries. As chaos is pervasive in engineering, gas
indexes from surface boreholes are no exception. The
relationship between R and S accords with theformula below (Zhu and Ji, 2011):(2)
R/S=(ατ)HWhere R is the extreme range of the time series,
S is the standard deviation of the time series, R/S is
the rescaled range, τ is the observational frequency, α
is a constant value, H is Hurst index. It has been
proven that if 0.5<H≤1.0 the time series is a growing
series, implying the future can be reflected by thepresent (Falconer, 2013).

weigh the spontaneous combustion condition in gob
as shown in Figure 6.
Hurst Index Variation of N2/O2
1.0

Hurst index value

0.8

0.6

0.4

0.2

0.0
20

4.2 Chaos characteristic of the indicator for coalspontaneous combustion
Considering the influence of methane emission
and CO2 injection, most gas indexes including single
gas indexes and Graham ratios are not inapplicable inpredicting coal spontaneous combustion in gobs,
while the N2/O2 ratio is an exception (Hu, Yang et al.
2015). Gas samples were gathered from a surface
drainage borehole every four hours i.e. two samples
every shift. As showed in Figure 4, a total of 218
N2/O2 ratios were collected on the ground during
methane draining.

80

100 120 140 160

180 200 220

Figure 5: Hurst index variation of N2/O2 with data number

It is apparent that whether or not CO was
detected, the Hurst value fluctuates between 0.5 and1. At first, when CO was not detected or in low
concentration, the ratio fluctuates regularly. Although
CO2 was injected when CO was detected, the value isstill larger than 0.8, showing a stable chaos
characteristic. However, a dramatic decline isobserved and relatively higher CO concentration
follows owing to the deeper oxidation of coal in
gobs. Depending on a certain length of statistical
data, the influence of seldom abnormal value can be
avoided. Therefore, the Hurst value is more stable
and misinformation can be eliminated.

N2/O2
CO

60
14
50

Length -fixed Hurst index
CO

12

1.0

40

20
6
10
4
0
2
0

20

40

60

80

100 120 140 160 180 200 220
Data number

Figure 4: The variation of N2/O2 ratio during methane
draining from surface boreholes

During the whole draining process, the N2/O2
ratio fluctuated up and down. If the N2/O2 soared up,
CO ensued. Owning to the cooling and stifling effectof CO2 on self –heated coal, the N2/O2 ratio
descended and CO faded away.
4.3 Chaos characteristic of N2/O2 time series
Figure 5 shows that the Hurst value graduallylevels out around 0.9, showing a stable chaos
characteristic. Setting the observation frequency as
80, the length-fixed time series can be employed to

0.9

50
40

0.8

30
Effect of CO2 injection

0.7

20
10

0.6

0
0.5
80

100

120

140

160

180

200

220

Data number

Figure 6: Variation of length–fixed Hurst index and CO

4.4 Critical values
Fixing the length of the N2/O2 time series to 80,
the risk of surface methane drainage in the working
face gob can be divided into two stages based on the
aforementioned analysis:(1) Safety drainage stage (Hurst index>0.85)555

CO (ppm)

8

Length -fixed Hurst index

30

CO (%)

60

10
N2/O2

60

Data number

16

Effect of CO2 injection

40

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Pursuant to the analysis above, 0.85 is the lowest
value under normal condition when there was no CO,
indicating that the oxidation condition of coal in
10416 working face gob was in low-temperatureoxidation stage.
(2) Spontaneous combustion initiating stage(Hurst index≤0.85)
Similarly, if the Hurst value of N2/O2 in surface
borehole is lower than 0.85, the oxidation of coal in
gob is accelerated. The smaller the Hurst index thedeeper the oxidation of coal.

5. CONCLUSIONSThis paper highlights the influence of surface
drainage boreholes on coal spontaneous combustion
by COMSLTM simulating and coal spontaneous
combustion predicting possibility employing R/Sanalysis. Several conclusions can be made as follows:(1) In the vicinity of the working face, themethane drainage can narrow the width of
spontaneous combustion zone around the borehole,whilst deeper strike depth leads to a wider
spontaneous combustion zone in the middle gob withthe advancement of the borehole.
(2) The advancement of the surface drainage
borehole has little effect on the spontaneous
combustion zone on the intake side but it reduces thedepth of the self -heating area dramatically on the
return side.
(3) N2/O2 time series has a chaos characteristic.
The risk of coal spontaneous combustion in 10416
can be divided into two stages: the safety drainage
stage (Hurst index>0.85) and the spontaneous
combustion initiating state (Hurst index≤0.85).

6. ACKNOWLEDGEMENTS
This work was conducted in the context of coalspontaneous combustion control in Yang Liu Co.ltd
and financially sponsored by the National Natural
Science Foundation of China (51174198), the StateKey Laboratory of Coal Resource and Safety Mining,
China University of Mining and Technology(SKLCRSM11X01) and CSC (China ScholarshipCouncil). The authors wish to express their gratitude
to the sponsors and especially to the staff of the
YangLiu Mining Co. Ltd.

gob using chaos analysis on gas indicators fromupper tunnel." Journal of Natural Gas Science andEngineering 26: 461-469.
Karacan, C. "A new method to calculate
permeability of gob for air leakage calculations andfor improvements in methane control."Li, Z.-x., Q. Wu and Y.-n. Xiao (2008).
"Numerical simulation of coupling mechanism ofcoal spontaneous combustion and gas effusion in
goaf." JOURNAL-CHINA UNIVERSITY OF
MININGANDTECHNOLOGY-CHINESE
EDITION- 37(1): 38.
Madeja-Struminska, B. and E. Widzyk-Capehart(2006). Correlation between methane and fire hazards
in abandoned workings of longwall mining. 11th
U.S./ North American Mine Ventilation Symposium
2006: 325-330.
Song, Z. Y. and C. Kuenzer (2014). "Coal fires
in China over the last decade: A comprehensive
review." International Journal of Coal Geology 133:
72-99.
Szlazak, N., D. Obracaj and J. Swolkien (2014).
"Methane drainage from roof strata using an
overlying drainage gallery." International Journal of
Coal Geology 136: 99-115.
Yang, W., B. Q. Lin, Y. A. Qu, S. A. Zhao, C.
Zhai, L. L. Jia and W. Q. Zhao (2011). "Mechanismof strata deformation under protective seam and its
application for relieved methane control."International Journal of Coal Geology 85(3-4): 300306.
Yuan, L. and A. Smith (2007). "Computational
fluid dynamics modeling of spontaneous heating in
longwall gob areas." transactions-society for mining
metallurgy and exploration incorporated 322: 37.
Zhou, F.-B., T.-Q. Xia and B.-B. Shi (2013).
"Coexistence of gas and coal spontaneous
combustion (II): New prevention and control
technologies." Meitan Xuebao/Journal of the China
Coal Society 38(3): 353-360.
Zhu, H. and C. Ji (2011). Fractal Theory and Its
Applications. Beijing, Science Press.

7. REFERENCES
Falconer, K. (2013). Fractal geometry:mathematical foundations and applications, John
Wiley & Sons.
Ham, B. (2005). A review of spontaneous
combustion incidents. COAL 2005: 6th Australasian
Coal Operators' Conference. 2005: 237-242.
Hu, X., S. Yang, X. Zhou, Z. Yu and C. Hu(2015). "Coal spontaneous combustion prediction in

556

ISMS 2016

Paper No. 216

The strength properties of fibre glass dowels used for ground control in coalmines
Naj Aziza*, Wenxue Chenb, Ali Mirzaghorbanli a, Jiao YuzhaobaRock Bolting Research Group, School of Civil, Mining and Environmental Engineering
Faculty of Engineering and Information Sciences,
University of Wollongong, Wollongong, Australia 2500
b Shandong Safety Industries Co Ltd- Tai’an, CHINA

ABSTRACT
Glass-Reinforced Polymer (GRP) bolts, commonly known as Fibre Glass (FG) dowels or plastic dowels are
increasingly applied for strata reinforcement in mines as well as in concrete reinforcement in civil engineering. The
most popular dowels used in Australian coal mines are the 22 mm diameter fully threaded type. FG bolts are
cuttable, easy to handle, lightweight and corrosion resistant. The tested dowels were all black in colour, which is afavoured colour in coal mines. A series of tests were undertaken to evaluate various strength properties of FG
dowels. These tests include the tensile failure test by the double-embedment method, single guillotine shear test,
double shear test both in steel frame and in concrete blocks, and finally the punch shear test. The study found thatthe tensile strength by pull testing of the 22 mm diameter fibre glass dowels was in the order of 27 t. The shear
strength testing of dowels in both single guillotine and double shear steel frames were in agreement with each other.
In general the shear strength values of dowels tested, using single shear guillotine testing, were around 20% of theaxial strength in comparison with 70% in the same diameter steel rebar tests. The peak shear load values obtained
from double shear tests in concrete blocks was influenced by the encapsulation grout type and the level of fibre glass
axial pre-tension. The punch shear tests revealed that there was a more than threefold increase in the punch shear
strength value of fibre glass dowels tested perpendicular as against parallel to the dowel axis.
KEYWORDS: Fibre glass dowels; rib support; tensile strength; single and double shear test; punch shear test

1. INTRODUCTION
Glass-Reinforced
Polymer(GRP)
bolts,
commonly known as Fibre Glass (FG) dowels, areincreasingly used in Australian coal mines as a meansof rib support in heading development and for coalfaceequipment
recovery.
The
increasedmechanisation of coal winning particularly by
longwall mining necessitated the use of non-metallic
rib dowels for rib support, where extraction includes
cutting of bolts. FG dowels are made by pultrusion, aprocess that combines extrusion and pulling ofmolten or curable resin and continuous fibres usuallyarranged in unidirectional layers, through a die of adesired structural shape (“pull” and “extrusion”). FG
dowels are made of glass strands pulled through asaturated thermoset resin and heated (Lowenstein,1973). Presently FG dowels used in coal mines rib
support have continuous rope thread profiles
providing deformations for high bond strength withresin and rock. Other factors contributing to theincreased application of polymeric dowels, as
elements of support instead of steel, include: Improvement in the strength properties of thenon-steel based dowels. The ultimate tensile

Corresponding author-email: naj@uow.edu.austrength of presently made 22 mm diameter
dowels can range between 57 - 85 % of steel rebarof the same diameter Easy and safe handleability of the non-steel
dowels particularly FG
 Lightweight, fire resistant and easy to handle,
 FG dowels are relatively cheap, Cuttable, longer lasting and can be supplied at agreater length
Presently, there are two types of GRP bolts in themarket, they are plastic and FG dowels, however, FG
dowel is characterised as having lower yield
deformation against shearing, and can twist on
torqueing. Properties and characteristics of polymericbolts are variable depending on the chemistry of the
product, dowel diameter, solid or hollow core,surface profile shape and composition. FG dowels areused as rib support dowels. Dowels of the same core
diameter can vary in length, identified by dowel
colour and colour coding. Typical dowel lengths withcolour coding include dowel length 1.2 m (blue),
1.5m (orange), 1.8m (red), and 2.1 m (green).

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2. TENSILE STRENGTH PROPERTIES
Six 1.2 m long 22 mm diameter black dowels
were tested for tensile strength. Each sample wasdouble embedded in 400 mm length steel tubes andpull-tested to failure. Oil based chemical bolt resin
was used to install the dowel in steel tubes. Figure 1
shows a dowel with both embedded ends being
encapsulated in the steel tubes. Figure 2 shows the
sample being tested in 50 t Instron Universal Testingmachine. Figure 3 shows the load displacement offour failed samples out of six tested samples. Figure 4
shows post-test dowels. Two samples did not failFigure 2: Tensile testing of a dowel in 50 t Instron
Universal Testing Machine and monitoring system.

because of poor encapsulation. The average peak
failure load of four failed dowels is 273.36 kN, as
shown in Table 1.

300

Tensile Test Results Black
Fibreglass Dowel

250
200
150

Sample 1
Sample 2
Sample 3
Sample 46

100
50

Load (kN)

Procedures used for evaluating strength integrityof dowels are based on Australian and various
international standards. These include American
Standards of Testing Materials (ASTM. C-759, 1991),
The British Standard (BS 7861- Parts 1 and 2, 1996),
International Standard ISO 10406-1 (2008), South
African Standard, SANS1534 (2004), and others. In
general, many well-known standards are invariablyinterrelated; however, the suitability of any particular
standard, for testing the given property of the dowel,
will depend on the purpose of the dowel used andhost medium properties. The current reporting of theshear strength of dowels is normally based on
guillotine testing of the FG rod in steel apparatus.
Guillotining of the GRP dowels in steel shear
apparatus yields lower shear values and is anundesirable test, unless the dowels are contained invery thick grout encapsulation sleeve. It is importantthat the shear strength of dowels must be determinedbased on simulated ground conditions, and therefore
it is logical to test dowels in rock or cementitious
medium of concrete. Accordingly there is a need forestablishing a credible testing methodology andprocedures for effective marketing strategy. The
double shear testing of dowels in concrete blocks
represents a novel approach to simulating the shear
behaviour of dowel in rock formation in situ. This
paper discusses tensile and shear strengthcharacteristic of 22 mm core diameter FG dowels,
which are used in Australia coal mines.

00

10 (mm)Extension

20

Figure 3: Load displacement profiles of four tested black
dowel samples.

Figure1: Black dowel with ends encapsulated in 450 mm
long tubes used for tensile strength testing.

Figure 4: Tensile failure of four out of six tested samples.

558

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: Average peak load for tested samples.
SamplePeak Load (kN)1
264.832
273.793
275.34
6
279.48Average273.36

3.

SHEAR TESTING OF DOWELS

3.1 Single shear guillotine test
Figure 5 shows the single shear apparatus used forshear testing of FG dowels. Commonly known as the“guillotine test”, the instrument allows direct
shearing of dowels and steel rock bolts to failure.
Figure 6 shows typical tested samples. Figure 7
shows typical graphs of single shearing tests of nine,
300 mm long black dowel sections. Details of the test
results are also shown in Table 2. The average valueof the shear strength was 150.45 MPa. The cut facesurface of all ten tested dowels was identically
stepped at mid-face as is obvious in Figure 6. Thismay be attributed to the fact that dowel sections were
not grouted in the frame and the guillotining effectmay have caused a slight bending and incremental
elongation of the uncut half FG elements. Also it
should be noted that the slight displacement at theearly stage of testing, as indicated in the circled
section of the graphs in Figure 7, may be attributed tothe early crushing of the dowel rifle profiles.

Figure 5: Single shear testing of black dowel.

Figure 6: Sheared dowel face with stepped cut.

Figure 7: Single shear test results of 22 mm diameter
dowels tested for single shear.
Table 2: Single shear test data for nine dowels.
Sample
1
2
3
4
5
6
7
8
9
AveragePeak Load (kN)
56.33
52.78
53.98
60.63
62.35
56.75
58.04
58.43
55.42
57.19

Shear Strength(MPa)148.19138.86141.99159.49164.01149.29152.68153.71145.80150.45

3.2 Double shear test method - in steel frame
The purpose of this section was to compare thesingle shear strength capacity of FG dowels using adouble shear guillotine testing apparatus. Like thesingle shear test, this test does not represent theshearing action encountered in undergroundconditions. The test produces steel on dowelinteraction whereas in underground it would be thestrata on grout on dowel interaction. However, thistest was carried out to compare with the single shear
strength result observed using the single shear
method. Each dowel was machine cut into 300 mm
specimen lengths. Four samples were tested.
Figure 8 shows the double shear test apparatus
that was used for the study. It consists of two steel
pieces. The bottom piece or ‘U’ shaped piecemeasured 143 mm x 83 mm x 70 mm. The top pieceor ‘T’ shaped piece is inserted into the ‘U’ shaped
piece. It measures 131 mm x 92 mm x 70 mm. The
dowel was inserted through the middle of the
combined apparatus and sheared up to a maximum
depth of 30 mm. Figure 9 shows the loaddisplacement and failure of tested dowel sections.
Figure 10 shows sheared samples.
Table 3 shows peak failure load and shear
strength of the dowel. The average value of the shear
strength is 157.62 MPa. This value is in reasonableagreement with the results of the single tests shown559

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

in Table 2. By taking a biased average of four tests asshown in the right column Table (blue writing), it isclear the results of single shear concur favourablywith the results of double shear tests. Also the failure
pattern in double shear test is similar to that of single
shear test, with step cuts as shown in Figure 10.

Figure 8: Double shear guillotine apparatus set up.

The shear strength of the dowel was determined using:

Where:
𝜏 = shear strength in mega-Pascals
𝐹 = Peak load at failure in Newtons
𝐴 = dowel cross sectional area in millimetres squared

Figure 9: load displacement profiles of four double shear
tests in steel frame.

Figure 10: Failure pattern of samples in steel double sharedapparatus.

Table 3 shows results of double shear guillotine
test, four dowel sections were tested and the average
failure load and shear strength of the dowels were
50.48 kN and 123.79 MPa respectively. These resultscompare favourably with the single shear test results
as reported in Table 2. The pattern of the shear
failures shown in Figure 10 is similar to the single
shear test results, but less pronounced as is shown in
Figure 6.
Table 3: Double shear guillotine test results.
Peak
shear
Single face peakSample Load (kN) load (kN)1
107.33
51.88
2
98.03
49.01
3
111.04
55.52
4
90.99
45.50
Average50.48

Shear Stress(single face)(MPa)
136.49128.94146.06
119.69132.79

3.3 Double shear tests in concrete
The double shear strength of fibre glass dowels
was investigated in three piece concrete blocks
consisting of a 300 mm long prism block,sandwiched between two 150 mm side cubes. 40
MPa, Uniaxial Compressive Strength (UCS) mortar
blocks were prepared with sand: cement ratio of 3:1.
Once mixed the mortar was poured into the internallygreased marine plywood mould, measuring 150 mm x
150 mm x 600 mm. The mould was divided into threecompartments separated by two metal plates. A
plastic conduit, 20 mm in diameter was set throughthe centre of the mould lengthways to create a holefor FG dowel installation. The cast mortar blocks
were left for 24 hours to set and harden. The set
blocks were then removed from the mould assemblyand kept in a moist environment for a period of 30days to cure. The central hole of the mortar block wasthen reamed rifle-shaped to 27 mm diameter, readyfor the installation of the dowel with cement grout.
Recently the process of mechanical reaming of 20
mm central hole was disbanded in favour of castingof profile holes using double core 3 mm thick electric
wire wrapped around the central steel bar. The central
steel bar and the wrapped wire were later removed
during semi-hardened stage of cast concrete. The
strength of the concrete blocks was determined fromtesting of the representative 100 mm diameter
cylindrical concrete specimens, cast at the time of
concrete preparation and pouring. Two different
cementitious grouts were used when installing andencapsulating FG dowels in concrete blocks:(a) Jennchem Top-Down 80 grout (TD80)(b) Jennchem Bottom-Up 100 grout (BU100)
The strength of both grouts varied depending on
the product composition and water content. In this560

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

study the level of water for each grout wasmaintained constant at six litres per 20 kg bag. The
FG concrete assembly was left to cure for a minimumof seven days before being tested.
A total of 11 tests were conducted in this study.
Dowels, for each category of grout used, werepretensioned to various loads up to 22.50 kN and thentested for shear. An attempt to apply pretension loadof 25 kN was not possible as extra load torqueapplied to the dowel nuts caused dowel ends to twist,
leading to lower shear loads. The applied axial
tension load due to subsequent shearing load, weremonitored using two 30 t capacity load cells shown in
the assembled setup in Figure 11. A 50 t capacity
Instron universal testing machine was used forshearing study. Clearly there were variations to theshear strength properties of the FG dowels based on
the level of pretension loads and grout type as shownin Table 4 and Figure 12. It was found that:a) The shear values of dowels were higher withincreased pretension loads.
b) Increased pretension loads, greater than 22.5 kN,
caused dowel ends to twist thus affecting double
shear strength values as is evident from the lower
value shear load of the dowel pre-tensioned at 25
kN,c) Shear load values of dowels were affected by thegrout type, with average shear values obtainedfor FG dowels tested with grout TD80 being

higher than test results with BU100 grout,despite the fact that BU100 grout has relatively
superior strength in comparison with TD80 grout,which is surprising, Further tests will be carriedout to verify theses findingsd) The shear value of each tested dowel was
determined taking into consideration the shear
strength contribution from 150 mm2 concrete
joint planes.

Figure 11: A double shear assembly mounted in the 500 kN
Instron testing machine.

Table 4: Single and double shear test results with different grouts.

a)Encapsulation Grout: BU100* Sample 6 - twisted dowelb)

Encapsulation Grout: TD80

561

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

（a）

(b)

Figure 13a: Punch shear apparatus, Figure 13b: Punch
shear apparatus.

Figure 12- Shear pretention loads versus verticaldisplacement of double shear testing of 11 dowels.

3.4 Punch Shear Test
Using the punch shear box, shown in Figure 13a,a series of punch shear tests were carried out on FG
dowel samples to determine the shear strength of FG
dowels. 3 mm thick discs were sliced perpendicular
to the dowel axis to examine the shear strength
properties of dowels parallel to the strands or FG
elements lay, while 3 mm strips were cut parallel tothe dowel axis to evaluate the shear strength of theFG elements bonding. These two types of cuts areshown in Figure 13b. Tables 5 and 6 show results ofpunch shear tests. Values of the shear strength were
determined by using the following equation;
τ =F
3.142 x T x D

Table 5: Punch Test Results of samples cut parallel todowel axis.
Sample MN
T (m)
D (m)
τ (MPa)0.00210.00249

0.012721.12

B0.00220.00253

0.012821.70

C0.00230.00279

0.012620.64

D

0.00280.003360.012620.98

E0.00400.00363

0.012727.97

F0.00110.001780.012715.38

G0.00390.003420.0127

28.67

Average

22.35

Table 6: Punch test results of samples cut perpendicular to
dowel axis.
Sample Punch loadTD
τ (MPa)
(MN)
(m)
(m)
A
0.012
0.00297
0.0128102.22where;
F = applied load, τ = shear strength, T = Sample
thickness and D = Punch diameter
From Table 5, the average shear strength value ofsix samples punch tested parallel to the direction of
the dowel is shown to be 22.35 MPa, and the average
shear strength value of testing three samples
perpendicular to the direction of the dowel axis asshown in Table 6 is 104.01 MPa. It is clear that there
is an obvious difference in shear strength in the ratioof 4.7:1 in favour of perpendicular to dowel axis or
dowel strands compared with parallel to dowel axis.
The low shear strength values parallel to the dowel
axis may be due to the resin shear strength holding
the fibres together, being lower than the strength of
the fibre glass. The average shear strength value
shown in Table 5 strikingly similar to the average
shear strength value of 21 days old standard oil based
resin used for bolting encapsulation bolting asreported by Gilbert (2014).

A

4.

B

0.012

0.003020.0127102.30C

0.013

0.003020.0129107.50

Average

104.01

CONCLUSIONSThis study demonstrated that the guillotine
method of testing dowels yields lower shear values
than results obtained from testing dowels by double
shear testing in concrete. Double shear testing in
concrete represent a realistic way of simulating thestrength property of the composite material in rockand in situ. The study also found that:a)

Shear values of the FG dowels were higher withhigher pretension loads.
b) Increased pretension loads greater than 22.5 kN
caused dowel ends to twist thus affecting double
shear strength values, and this is evident from thelower value dowels double shear load pretensioned to 25 kN.
c) The Shear load values of dowels were affectedby the grout type, with average shear values
obtained from FG dowels tested with grout TD80
being higher than test results with BU100 grout,562

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

despite the fact that BU100 grout has relatively
superior strength in comparison with TD80 grout,which is surprising. Further studies is planned toconfirm this finding.
d) Low shear strength results of testing dowel
parallel to the dowel axis and thus to FG strands
may be due to the resin strength holding thefibres together and resisting the shear force being
lower than the shear strength of fibre glass
elements. The shear strength values shown in
Tables 5 are comparable to the shear strength ofa typical oil based standard chemical resin used
for bolting installation.
5. ACKNOWLEDGEMENT
The authors wish to thank Colin Devenish, atechnical officer of the School of Civil, Mining, andEnvironmental Engineering, Faculty of Engineering
and Information Science, University of Wollongong
for his assistance. The project was partially funded by
Shandong Safety Industries Co., Shandong Ltd,
China.

6. REFERENCES
American Standard for Testing Materials (ASTM.
C-759), (1991). Standard test method for compressive
strength of chemical –resistant mortar, grouts,
monolithic surfacings and polymer concretes.
British Standard BS 7861- Parts 1 and 2 (2009):
Strata Reinforcement support system components
used in Coal Mines-Part 1. Specification for rockbolting and Part 2: Specification for Flexible systems
for roof reinforcement.
Gilbert, D. (2014). Study of fibre glass strength
properties, undergraduate thesis, University of
Wollongong.
International Standard ISO 10406-1 (2008).
Fibre-reinforced polymer (FRP) reinforcement if
concrete –test methods, part 1:FRP bars and grits,First edition, 40 p.
Lowenstein, K. L. (1973). The Manufacturing
Technology of Continuous Glass Fibers. New York:
Elsevier Scientific. pp. 2–94. ISBN 0-444-41109-7.
South African Standard SANS1534 (2004). Resincapsules for use with tendon based support systems,
published by Standards South Africa.

563

Paper No. 118

ISMS2016

Numerical simulation for propagation characteristics of outburst shock wave
and gas flow when outburst prevention facilities failZhou Aitaoa,*, Wang Kaib, Kong Yuyuc, Liu AngdaSchool of Resource & Safety Engineering, State Key Laboratory of Coal Resources and Mine Safety, China University of Mining& Technology, Beijing,China 100083
bSchool of Resource & Safety Engineering, State Key Laboratory of Coal Resources and Mine Safety, China University of Mining& Technology, Beijing,China 100083
c
Jincheng Zetai Safety Evaluation Center, Jincheng, Shanxi, China 048000
dSchool of Resource & Safety Engineering, State Key Laboratory of Coal Resources and Mine Safety, China University of Mining& Technology, Beijing,China 100083

ABSTRACT
In order to numerically simulate the propagation characteristics of outburst shock waves and gas flow when outburst
prevention facilities fail, the propagation characteristics model of outburst shock waves and gas flow was established,
and the mechanism of gas counter current was analyzed. The propagation characteristics of shock wave and gas flow
at two types of geometry models were numerically simulated by using Fluent software. The results show that most of
the gas flow produced by outbursts propagates to intake airways when crossheading with an excavation roadway at
the same level; however, when crossheading with an excavation roadway not at the same level, gas is mainly
discharged from the return airway, and the effect of the gas flow on the intake airway is small. The results haveimportant theoretical and practical significance for mine disaster rescue and preventing secondary accidents.
KEYWORDS: outburst prevention facilities; shock wave and gas flow; gas counter current

1. INTRODUCTION
Shock waves and gas flow are formed during
coal and gas outburst, which can induce casualties
and property loss. Scholars have performed extensive
study in this field. Cheng Wuyi (2004) made a simple
theoretical analysis and mathematical deduction
based on the forming process and propagation law ofoutburst shock wave and gas flow. For the dynamic
process of the flow, F. Otuonye (1998) proposed a
simplified mechanism of outburst and established thecorresponding physical model. Wang Kai et al., 2011,
Wang Kai et al., 2012, Zhou A.T(2012)
systematically studied the formation mechanism andpropagation characteristics of the shock wave andflow caused by outburst; based on theoreticalanalysis, experimental studies, and numericalsimulations, they systematically analyzed theattenuation characteristics of the shock wave and gas
flow from the outburst in a straight roadway, turning
roadway, bifurcation roadway, and variable crosssection roadway. It is well known that when outburst
prevention facilities fail, intake airway associate withthe excavation airway where outburst occurs and thenthe shock wave and gas flow pour out from thecrossheading into the intake airway (Zhang J, 2007).
This paper mainly studies the impact of outburst
shock waves and gas flow on the intake airway andproposes appropriate solutions. Firstly, the roadway*Corresponding author – email: cumtbzat@126.com

model after the outburst prevention facilities wasestablished and process of the shock wave and gas
flow was numerically simulated. Secondly, thevariation process with time of pressure, velocity, anddensity in observation points was monitored, and theconditions of pressure, velocity, density, andconcentration variation of gas within roadways at
different time were obtained. Thirdly, the impact ofoutburst shock wave and gas flow on the ventilation
system after the air door failure was analyzed. The
result obtained has important theoretical and practicalsignificance for mine disaster rescue and theprevention of secondary accidents.

2. ANALYSIS OF PROPAGATIONCHARACTERISTICS OF OUTBURSTSHOCK WAVE AND GAS FLOW
The propagation of outburst shock wave and gas
flow can be considered a one-dimensional
compressible gas semitropical unsteady continuous
flow, which is always accompanied by the movementof disturbance waves. When the disturbance waves
propagate through media, physical quantities ofshock wave and gas flow at any point change
dramatically overtime,
forming
unsteady
movements. Therefore, in order to study the unsteadycompressible flow of the shock wave and gas flow,
one must study the disturbance wave motion.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

When gas outburst occurs, the intensity of theshock wave is changed. In other words, the velocityof the outburst shock wave is unchanging, and thegas parameters of the wave-after change over time.
To convert the unsteady state to a steady state, it isnecessary to coordinate the observation with theshock wave motion, and set up three basic equations
for the control-body that surrounds the shock wave.
Because the shock wave is extremely thin, its volume
can be ignored. The rate of mass, kinetic energy,
momentum and internal energy variation over time of
the control-body and other items are equal to zero,and the variable intensity on both sides of the shock
wave can also be analyzed using the equation ofsteady flow. This is equivalent to dividing thevarying intensity movement process of a shock wave
into some limited short moments. Now every smallpart can be dealt with as a stationary flow process,and this steady flow is known as quasi-steady flow.
Figure 1 is a transient state of a shock wave inthe propagation process. The region where shockwaves through is called the wave-after, and theregion where there is no wave disturbance is known
as the wave-front. The rightward direction represents
the positive direction of flows. Velocity, pressure,density, enthral, and temperature of the wave-front
and wave-after were 𝑣1 , 𝑝1 , 𝜌1 , ℎ1 , 𝑇1 and 𝑣2 , 𝑝2 ,
𝜌2 , ℎ2 , 𝑇2 , respectively, and the velocity of shock
wave is 𝑣 . The dotted area is the control plane area
for the study of shock wave motion.
The shock wave
Wave-afterWave-front

v1

v2
1

2

p1
ρ1 ,h1 ,T1

p2vStanding vertical shock wave
Wave-afterWave-front

v2-v

v1-v
1

2

p1

p2

ρ1 ,h1 ,T1

ρ2 ,h2 ,T2

v=0
Figure 2: State model of standing vertical shock wave.

According to the state model of a standing
vertical shock wave, firstly establish the continuity
equation. According to the conservation of mass thecontinuous equation of a standing vertical shock
wave is as follows:ρ1 (v1 − v=
) ρ 2 (v2 − v)

(1)

Establish the momentum equation. The shock
wave within the roadway belongs to the onedimensional flow, and both sides of it are in the roleof air and gas pressures, respectively. Ignoring the
body force, the momentum equation of onedimensional steady flow can be written as:

p1 + ρ1 (v1 − v) 2 = p2 + ρ 2 (v2 − v) 2 (2)Establish the energy equation. Because airflow
through the shock wave can be considered anadiabatic process, the total temperature T of thewave-front and wave-after can be considered as
constant. Friction is negligible, and therefore theshock wave is very thin. For one-dimensional
unsteady flow without shaft work and potential role,and h= u + p / ρ , the energy equation is as follows:ρ2 ,h2 ,T2

u1 +

p1

ρ1

+

(v1 − v) 2p(v − v ) 2=u2 + 2 + 2
2
2
ρ2
(3)

Figure 1: Shock wave communication status model.

The three previous equations have seven
Through coordinate conversion, the movement
process of the shock wave is transited from unsteadyflow into steady flow, namely, the coordinate systemthat flows with the shock wave is selected forreference, and the velocity of the shock wave
becomes zero. At this time a standing vertical
impulse wave is formed; the wave-after velocity
becomes 𝑣1 − 𝑣 , direction to the left; the wave-front
velocity also becomes 𝑣2 − 𝑣 , direction to the left;parameters of wave-after and wave-front are
constant, as shown in Figure 2.

unknowns： 𝑝1 , ρ1, 𝑣1 , 𝑝1 , ρ2, v2 and v (Specificinternal energy, u, can be obtained using the state
equationu=1
1 p
derived by the
RT
=
γ −1
γ −1 ρ

the 𝑝 and 𝜌 ). Four parameters are independent.

Given any of these four parameters the rest can be
uniquely identified. For example, 𝑝2 , 𝜌2 , 𝑣2 , andanyone parameter of wave-after is given, then the restof the parameters and shock wave velocity can be
uniquely identified. When putting these parameters
into three equations the wave equation is obtained:565

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

ρ1 ρ 2− ρ12 (v − v1 ) 2 =− ρ 22 (v − v2 ) 2 ( p1 − p2 ) =ρ1 − ρ 2p1 (γ + 1) ρ1 − (γ − 1) ρ 2=p2 (γ + 1) ρ 2 − (γ − 1) ρ1ρ1 ( γ + 1) p1 + ( γ − 1) p2=
ρ 2 ( γ − 1) p1 + ( γ + 1) p2











p1 γ + 1+
T1 p2 γ − 1=
T2 p2 + γ + 1
p1 γ − 1（4）
Wave front Mach number is： Ma2 =Local sonic=
is: c2γ RT=v − v2;c2

γ p2 / ρ 2 . Thenthe shock wave equation can be expressed as follows:

p1
γ −1
2γ
Ma22 −=γ +1
p2 γ + 1γ +1 2Ma2

ρ1 v2 − v
2
（5）
=
=

γ
1
−
ρ 2 v1 − v 1 +

Ma22
2

2

T1
2(γ − 1)(γ Ma2 + 1)
2

=
−
1+
(
Ma
1)
2
T2
(γ + 1) 2 Ma22


Wave-after Mach number

pressure, density ρ1, and velocity are shown as
follows:

2 ρ2v 2
c22
p1 =
p2 +
(1 − 2 )γ +1v
ρ (γ + 1)
ρ1 = 022c2+ γ −1v2
c222vv1(1 − 2 )
=
v
γ +1

（6）
（7）

（8）

3. MECHANISM ANALYSIS OF GASADVERSE CURRENT
When the outburst occurs, the coal gas in the
body is released in an instant. Due to the large
emission and fast transport, relative movement
between high concentrations of gas and fresh airflows occurs. Due to the convection-diffusion
function, part of the gas is transferred from the highconcentration areas to the fresh air, which makes theconcentration of gas in the area of fresh air flow rise,causing gas adverse current, as shown in Figure 3.

Gas outburst area Qgas

Qair

Qhybrid

Intake airway Reverse flow direction

Return airway

1/ 2

 (γ − 1) Ma22 + 2 
Ma1 = 2 2γ Ma2 − (γ − 1) Figure 3: Schematic illustration of gas counter current after
outburst.

,

The above equations also show that the airflow
parameter relations before and after the shock wave
only decide the wave-front flow Mach number Ma2
and the specific heat ratio .
Non-ideal properties (such as heat conduction,
friction, viscosity) of the medium only affect the
thickness of the shock wave, without affecting its
strength. It is assumed in the process of gas outburstthat spewing gas can maintain the propagation of ashock wave, guaranteeing the continuous flow of theshock wave, therefore the simple shock wave is notattenuated. It is assumed that in the undisturbed
roadway area the air is in a stationary state, namely
v2=0 m/s, then Ma2 =v, and we can know thatc2parameters in the undisturbed roadway (roadwaypressure p2, density, specific heat ratio) are constant,c 2 = γRT = γP2 / ρ 2.

Expressionsof

The theoretical analysis shows that the formationof gas counter current includes two conditions; thevolume of gas emission is greater than the air volume
after the gas outburst, and the convection diffusion ofgas to air. When gas outburst occurs and the volume
of gas emission is greater than the volume of the air
within the intake airway, the volume within the returnairway increases. While in the intake airway, thereverse gas flow pour into the intake airway makes
flow volume reduction or flow static, leading to air
revering, which is an adverse gas phenomenon. When
there is a gas counter-current, there is convection
diffusion between fresh air and the highconcentration gas. Convective mass transfer between
fresh air and gas occurs, making part of the fresh air
gas concentration rise.
After outburst, the gas emission within the intake
airway varies. At first, since large coal crushes
release a lot of gas instantaneously along with a hugeamount of high-pressure gas emission, intake airway

566

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016airflow direction is reversed. Gas emission is greatly
reduced when outburst ends (Javier T. et.al., 2012).
In the absence of sustained energy support, gas flowof the intake airway stops moving or returning tonormal air flow. While there is convection diffusion
between fresh air and high-concentration gas, gas
mass transfers with the air, so the concentration ofgas in the fresh air flow rises and re-flux still exists.
When the volume of fresh air in the intake airway
and the gas emission of outburst areas is stable, theimpact scope of the gas to the intake airway isdetermined, and the concentration of gas within the
return airway continues to stabilize. Gas adverse
current can be divided into three phases, namely the
first stage—entering air retrograde phase, the second
stage—diffusion stage, and the third stage—stable
dilute phase.
The first stage—entering air retrograde phase:the gas emission is enormous (Wang E.Y. et al.,1996), far greater than the volume of the intake
airflow, so flow retrogrades. We can assume that thepressure within the gas flow minus the pressure
within the roadway is over-pressure, ∆p. In theentering air retrograde phase, we can approximate theretrograde process as the overpressure attenuation
process, where the relation is:∆p = p1 − p2 = δ W /( sx)
The relation for ∆p is as follows:（9）2δ 13  W  3 32
ρt （10）∆p = p1 − p2 =ε 2  s 
It is important to note that in the place where
outburst occurs, the pressure when outburst no longer
occurs should be smaller than the pressure at the inlet
so as to ensure that under normal circumstances themine ventilation process, so the pressure difference
between the intake airway and the outburst location,is positive. After outburst, the pressure of theoutburst shock wave and gas flow that pours into theintake airway is bigger than the pressure of the air
which is unaffected by the shock wave and gas flow.
The distance of gas retrograde is:=x δ W / ( sp1′ − sp0 )meets the conservation of mass and Fick’s first law ofdiffusion .(Jacek S.,2011).

J = − DAB

dc A
dx

（12）

where DAB is diffusion coefficient (m/s); CA isvolume concentration of gas (/m or kg/m);

dc A
is
dx

concentration; “–” shows diffusion with theconcentration gradient in the opposite direction,
namely non-component diffuses from the region ofhigh concentration to areas of low concentration. The
unit of J is kg/m s.

Jt = J d + Ji + Jc

（13）where 𝐽𝑡 is variation of gas in micro-body perunit time, J t =∂c A
dx ; 𝐽d is the net mass flux∂t,through gas in the micro-body per unit time, ∂ ( uc A ) ∂J Jd =−+  dx ; 𝑢 is the velocity of
∂x 
 ∂x

air within roadway, u=0m/s; 𝐽𝑖 is the gas amountof increase or decrease, J i = χ c A dx ; χ is gas
flow attenuation coefficient, χ < 1; 𝐽c is due to achemical reaction the volume of gas increases ordecreases in the micro-body in unit time; while theoutburst process of this research does not involve
chemical reactions, so 𝐽𝑐 = 0 , then equation (13) can
be converted to:

∂c A
∂J
=
−
+ χ cA∂t∂x（14）

The third stage—stable dilute phase: in thisphase, the volume of fresh air is much greater thanthe volume of gas emission. Gas will flow out of the
return airway with the flow in a stable manner, andgas concentration tends to be stable after outburst, asshown in Figure 4.

（11）

The second stage—diffusion stage Flores M.,
1988: when the counter-current guided by thepressure of gas flow is over, the velocity of thecounter-current gas flow is close to zero (Hu W.M. etal., 1998). The phenomenon of gas adverse current ismainly for relative diffusion between gas flow andfresh air. In diffusion, gas flow and air flow can betreated as incompressible fluids. Such gas diffusion

567

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

B`inletD`outlet B

D

25m

Gas outburst area

Excavation
roadway10mc′crossheading

50m
4m

x
Figure 4: Curves of gas concentration in the laneway atstable dilution stage.

At this time, we focus on the analysis of gas
concentration in the return airway, which has certain
reference significance to for post-outburst mine
rescues. From the above figure, the last stable gas
concentration is 𝑐 ′ . We can know that:

c' =

Qgas

Qgas + Qair

（15）

4. THE PROPAGATION AND NUMERICALSIMULATION OF THE OUTBURST SHOCKWAVE AND GAS FLOW WHEN THE
OUTBURST PREVENTION DAMPERS
FAILS
4.1 Numerical simulation of crossheading andexcavation roadway associative(1)The geometric model
The model is shown as Figure 5. The geometryof the model: a outburst cavity length and breadth are
10 m3, the excavation roadway is 50 m long, both thetotal length of intake airway and return airway are
104 m and are relative to the crossheading symmetry.
The height of the roadway is 3 m and the width of the
roadway is 4 m. Section B − B ′ is the air inlet side,and section C − C ′ , section D − D′ and section
E − E ′ are airflow outlet port. Select a section at a
distance crossheading of 25 m as observation points
and monitor the change of air pressure, velocity, andgas density.

EE`outlet C

50m

4m

Intake airway

10m

Return airway

Return airwayc4m

Gas outburst area

Intake airway

Intake airway

Qhybrid

Qair

A`

A

25m

Return airway

Qgas

C`outletFigure 5: Geometric model numerical simulation ofcrossheading associated with excavation roadway.

(2) Initial conditions of numerical simulation
In the critical state of outburst, the initialcondition of high-pressure gas within outburst regionis supposed as:=
p1 10atm,=
u1 0,=
T1 300K,=
C1 1
Where 𝑃1 is gas pressure in the outburst region(pressure on the environment set to 1 am), atm; u1 isvelocity, m/s; T is temperature, K; C1 is relative massconcentration of gas (assumed to be pure methane).
In the critical state of outburst, the initialcondition of air within the roadway is supposed as:=
p0 0atm,=
u0 0,=
T0 300K,=
C0 0
Where 𝑃0 is gas pressure in the roadway, atm; u0
is initial velocity within the roadway, m/s. When
outburst occurs, due to the great pressure and speed
in the roadway, pressure and velocity within the
roadway can be approximated as zero; T0 istemperature within the roadway, K;C0 is relative
mass concentration of gas within the roadway.
The initial condition of the section is supposedas:=pi n 300=
Pa, Ci n 0
Where 𝑝𝑖𝑛 is relative pressure of cross-section
B − B ′ ; Cin is mass concentration of gas in the crosssection B − B ′ .
The initial condition of cross-section C − C ′ ,cross-section D − D′ and cross-section E − E ′ issupposed as:

pout = 0 Pa

Where pout is relative pressure of crosssection C − C ′ , cross-section D − D′ and crosssection E − E ′ .
(3) Analysis of results of numerical simulation

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 6 shows pressure, velocity, and gas
concentration variation at the cross-section.
200000Avareage pressure

15000010000050000
0-50000
0

150

300

450

600

750

900

1050

1200

1350

1500

Time

(a) Pressure variation at cross-section A-A`(a) Contour of pressure

300

Average velocity

250
200
150
100
50
0
0

150

300

450

600

750

900

1050

1200

1350

1500

Time

(b) Velocity variation at cross-section A-A`
Methane concentration

0.6
0.5
0.4

(b) Velocity vector
Figure 7: Contours of pressure and velocity in the roadway
at 0.156 s.

0.3
0.2
0.1
0
0

150

300

450

600
Time

750

900

1050

1200

1350

1500

(c) Gas concentration variation at cross-section A-A`
Figure 6: Pressure, velocity, and gas concentration
variation at cross-section A-A`.

As shown in Figure 6:• At 0.156 s, the maximum pressure of thecross-section is 185495.6 Pa, and the maximum
speed is 282 m/s.
• At 0.23 s, gas flow reaches the observation
point and the cross section of the gas concentration
reaches a maximum of 0.499.
• According to the analysis in the 900 crossroadway, gas flow in the concave point begins toreturn.
• According to the vertical cross-roadway
simulations conclusion, assuming that the adsorptionof methane in coal and coal powder during shockwaves and gas flows movement is no longer flooded,
then due to the impact of negative pressure, airflow
reflow speed will reach 150 m/s.
Pressure and velocity in the roadway are shownin Figure 7 when gas flow arrives at the observation
point section, namely 0.1565 s..

As can be seen from Figure 7, the influx of
airflow into the intake airway and the pressure andspeed of the airflow are greater than the pressure andspeed of the return airway. Exporting data can befound from Fluent. The pressure of the return airway
is between 0 Pa to 100000 Pa, while the pressure of
the intake airway is between 100000 Pa to 200000
Pa. In the return airway flow，the speed of the shock
front reaches 200 m/s. In the case of air door damage
failure, the impact on the intake airway is greaterthan on the return airway, but with the throttle prior
to the failure, the effects of the shock wave and air
flow would obviously be smaller than the returnairway in the model of a vertical cross roadway.
Because the throttle is damaged, the space of theshock waves and air flows increases and the intake
airway and return airway share the influence of shockwaves and air flows.
Gas flow reaches the observation point in 0.23 s
and leaves in 1.11 s. The concentration of gas within
the roadway at 0.23 s, 0.32 s, 0.564 s, and 1.11 schanges as shown in Figure 8.

569

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the gas into the return airway gradually becomes
diluted with air and the concentration reduced. Gas
flow eventually flows from the high pressure end into
the end with the lower pressure, and at this time theconcentration in the intake airway is about 0.5. The
gas enters the intake airway ultimately along the
airflow direction into the mine ventilation system,and the whole mine ventilation systems is subject tothe risk of gas explosion.

(a) Contour of gas concentration at 0.23 s(b) Contour of gas concentration at 0.32 s

4.2 Numerical simulation of crossheading andexcavation roadway no associative
In order to fix the damage caused by shock wave
and gas flow on the intake airway, the most direct
approach is to keep the crossheading with the
excavation roadway, which may occur not in thesame parallel position, and place the air door near theend. It is assumed that the crossheading has an
excavation distance of 10 m.
(1)Geometric modelling
The geometric model is shown in Figure 9. The
geometric dimensions of the model are described as:
the outburst cavity has a side length of 10 m cube; thelength of the excavation roadway is 50 m; the lengthof the intake airway and return airway are 104 m;
crossheading is located 10 m above the excavation
airway and the distance to section B − B ′ andsection C − C ′ are 40 m and 60 m respectively;
roadway width is 4 m and height is 3 m; section
B − B ′ is flow inlet side, section C − C ′ , section
D − D′ and section E − E ′ for flow outlet. Select thesection A − A′ as the object of observation,
monitoring the change of pressure, velocity and gas
concentration.
D`

B` Inlet

A

A`

15m

(c) Contour of gas concentration at 0.564 s

B

Outlet25m

Return airway

D

Excavation
roadway
10m

4m

10m

Gas outburst area

50m

As can be seen from Figure 8, the majority of thegas flows into the intake airway. Only a small part ofIntake airway

Return airway(d) Contour of gas concentration at 1.11 s
Figure 8: Contours of gas concentration in the road way at
0.23 s, 0.32 s, 0.564 s and 1.11 s.

OutletOutlet
E

60m

4m

4m

E`

C

C`

Figure 9: Geometric model numerical simulation ofcrossheading not associated with excavation roadway.

570

The initial conditions of the simulation areexactly the same as in the above example. In thecritical state of outburst, the initial condition ofhigh-pressure air gas within the outburst cavity is
supposed as:=
p1 10atm,=
u1 0,=
T1 300K,=
C1 1
Where 𝑃1 is gas pressure in outburst region(pressure on the environment is set to 1 atm), atm; 𝑢1
is velocity, m/s; 𝑇1 is temperature, K; 𝐶1 is relative
mass concentration of gas(assuming for puremethane).
In the critical state of outburst, the initialcondition of air within the roadway is supposed as:=
p0 0atm,=
u0 0,=
T0 300K,=
C0 0
Where 𝑃0 is gas pressure within the roadway,
atm; 𝑢0 is initial velocity within the roadway, m/s,
when the outburst occurs, due to the great pressure
and speed in the roadway, pressure and velocity
within the roadway can be approximated as zero;𝑇0 is temperature within the roadway, K; 𝐶0 is
relative mass concentration of gas within the
roadway.
The initial condition of section B − B ′ issupposed as:=
pi n 300Pa,=
Ci n 0

Where 𝑃𝑖𝑛 is relative pressure of cross-section
B − B ′ ; 𝐶𝑖𝑛 is mass concentration of gas in the
cross-section B − B ′ .
The initial condition of cross-section C − C ′ ,cross-section D − D′ and cross-section E − E ′ issupposed as:

Average velocity

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

180
160
140
120
100
80
60
40
20
0
0

150

300

450

600

750

900

1050

1200

1350

1500

Time

(b) Velocity variation at cross-section A-A`
Figure 10: Pressure and velocity variation at cross-section
A-A`.

From Figure 10 and Fluent simulation data we
can conclude:• At 0.19 s, the maximum pressure of the crosssection is 53215.86 Pa, and the maximum speed is106.7 m/s; compared with the conclusion of theprevious section, the gas pressure and speed are
greatly reduced, and outburst shock wave and gas
flow have less effect on the ventilation system androadway facilities.
• From the speed change curve in the crosssection it can also be found that when the velocity
reverses, namely at 0.57 s, the gas flow direction isreversed.
• After outburst, the counter current speed oftheoutburst shock wave and gas flow reaches 160
m/s, which is comparable to the previous section,
indicating that crossheading change has little impact
on the destruction of counter current air caused byshock wave and gas flow due to negative pressure.
Conditions of the pressure and speed within the
roadway are shown as Figure 11:

pout = 0Pa

Average pressure

Where𝑃𝑜𝑢𝑡 is relative pressure of crosssection C − C ′, cross-section D − D′ and crosssection E − E ′.
(2)Analysis of results of numerical simulation
Figure 10 shows pressure, velocity and gas
concentration variation at cross-section A-A`.
60000
50000
40000
30000
20000
10000
0
-10000-20000(a) Contours of pressure

0

150

300

450

600

750

900

1050

1200

1350

1500

Time

(a) Pressure variation at cross-section A-A`(b) Contours of velocity

571

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 11: Contours of pressure and velocity at 0.19 s.

As can be seen from Figure 11, if crossheadingwith the excavation roadway is not on the same level,
the pressure and velocity of the outburst shock wave
and gas flow in the intake airway are far less than in
the return airway, and are less affected by theoutburst shock wave and gas flow.
Figure 12 shows the concentration variation
curves with time at the roadway.

(d) Contours of gas concentration in the roadway at 1.105 s
Figure 12: Contours of gas concentration in the roadway at different times.

Figure 12 shows the migration process of gas
flow in the outburst. It can be found that most of theemission gas pours out from the cross-section. Due toreflux, gas within the intake airway also pours into
the return airway. This shows that if the crossheading
is separated from the roadway where outburst occurs
and placed near the inlet of the intake airway, thenthe intake airway is much less affected by the gas
flow.

5. CONCLUSIONS(a) Contours of gas concentration in the roadway at 0.19s(b) Contours of gas concentration in the roadway at 0.576 s

The methane adverse current was divided into
three phases: the entering air retrograde phase, thediffusion stage, and the stability of dilute phase. At
the different stages, a qualitative analysis of influence
scope of the methane adverse current, driving mode,and countercurrent process was performed.
After outburst prevention air door failure, therole of gas flow in mine air flow constantly spreads
and can easily induce intake airway gas explosion.
When the crossheading and the roadway where
outburst occurs are at the same level, most of the gas
flow produced by the outburst shock wave and gas
flow spreads to the intake airway. When the
crossheading and the roadway where outburst occurs
at different levels, the gas flow is mainly exhausted
from the return airway, and the influence of theintake airway is very small.

6. ACKNOWLEDGEMENTS
The authors are grateful to the State Key
Research Development Program of China(2016YFC0801402, 2016YFC0600708), National
Natural Science Foundation of China (51474219,
51304213 ).

7. REFERENCES(c) Contours of gas concentration in the roadway at 0.9 s

Cheng W.Y.,; Liu X.Y and Wang K.J.(2004).
Study on regulation about shock-wave-front
propagating for coal and gas outburst. Journal of
China Coal Society, vol. 29, no. 5, pp. 57-60.
Flores M. (1988). Coalbed methane: from hazard
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573

Paper No. 29

ISMS 2016

Influence of Fundamental Internal Parameters to Low-Temperature Critical
Temperature in Coal Self-Ignition Process
WANG Hai-yana,b,c,*, YAO Hai-feia,b, ZHENG Zhong-yaa,b, XU Chang-fua,b, ZHANG Quna,b,
ZHU Hong-qingcaMine Safety and Technology Branch of China Coal Research Institute Corporation Limited, Beijing, China, 100013;
National Key Lab of Coal Resource High Efficient Mining and Clean Utilization, Beijing, China, 100013;c
School of Resource and Safety Engineering, China University of Mining and Technology (Beijing), Beijing, China, 100083;b

ABSTRACTThe low-temperature oxidation process of coal self-ignition can be divided into two stages: the slow oxidation stage
and the fast oxidation stage. To study the effect of internal factors on low-temperature critical temperature in thecoal self-ignition process, eight fundamental internal parameters (volatile, ash, fixed carbon, C, N, S, H, and O) andthree characterization parameters of low-temperature critical temperature in the coal self-ignition process (TJR, TCO,
and TO2) were determined through theoretical analysis. Afterwards the self-heating characteristics in pure oxygen
atmosphere in the 40 to 180° range and gas releasing atmosphere in the 30 to 180° range for seven coal samples
were tested. Based on this, the values of fundamental internal parameters and characterization parameters for sevencoal samples were obtained. The relationship between fundamental internal parameters and that of characterization
parameters were compared. On grey relational analysis, five important influence parameters are filtered to make themathematical formula fit with the characterization parameters. The results show that characterization parametersreflect critical temperature from different aspects including temperature rising, CO releasing, and oxygen
consumption. These vary for the same coal sample, but are with the same tropism and confirm each other. Criticaltemperatures are negatively correlated with the contents of volatiles, H and O, have no determined relationship withthe content of S, and have small correlation with other parameters.
Keywords: coal self-ignition; critical temperature; fundamental internal parameter; temperature-programmed
experiment; heat oxidation experiment; grey correlation; numerical fitting.

1. INSTRUCTIONS
The occurrence of coal self-ignition is the resultof the interaction between external and internal
factors, and among them, the internal factors are
prerequisites (Liu and Zhou, 2012; Adamus et al.,2011). Low-temperature critical temperature is theintermediate link between the slow oxidation stage
and fast oxidation stage during the coal self-ignition
process. It is of practical significance for doing coalmine fire prevention and control that we grasp thecritical temperature of coal self-ignition and make thetemperature of coal below the critical temperature. In
the past, we primarily focused on monitoring the coaltemperature of danger zones through direct
temperature measurement or gas collection andtesting in terms of coal mine fire prevention (Xie etal., 2011). However, there is little research andapplication of nonlinear
characteristics
of
spontaneous fires. Currently, some research is being
done on the determination of critical temperature ofcoal self-ignition mainly through fixed stages
division, qualitative analysis, and the numericalfitting method (Sahay et al., 2007; Zhong et al., 2010;*Corresponding author – email : whycumtb@163.com

TAN et al., 2013; Beamish and Darren et al., 2005;
Ren et al., 1999; ZHU et al., 2014). These methods
mainly analyze the critical temperature of coal selfignition in one aspect. Researching the criticaltemperature form different aspects and contacting thenature and conditions of coal are necessary in order
to increase the practical applications and reference
significance.
The occurrence and development of the coal selfignition process can be manifested by different
forms, such as changes in temperature, gasconcentration, and so on. In this paper, a relationshipbetween coal temperature and gas concentration isestablished by experiments, the critical temperatureof coal self-ignition is determined by different
parameters, and the influence of some fundamental
parameters of coal, such as industrial components
and element composition, on critical temperature arestudied.

2. THEORETICAL ANALYSIS
Coal self-ignition is a non-linear evolution
process, which is not carried out in accordance with a3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

certain rate. Research shows that there is criticaltemperature during this process where the oxidationof coal will accelerate beyond this temperature.
However, the critical temperature of coal is limited
within a fixed range with no clear distinction between
the different kinds of coal. In recent years, scholars
have studied in depth the differences of coal selfignition process for different types of coal, and cometo realize the importance of distinguishing thedifferences in critical temperature. According to theprevious studies, the influence of internal andexternal factors on the occurrence and developmentof coal self-ignition is very complicated, and theinfluence of external factors is difficult to beexperimentally tested. Therefore, it is of guiding
significance to actual work to study the influence ofinternal factors on critical temperate of coal selfignition. Therefore, this paper mainly studies theimpact of fundamental internal parameters on lowtemperature critical temperature of coal self-ignition.

variation characteristics of coal heating rate underadiabatic conditions.
2) Mutation temperature of CO concentration in
the programmed temperature rising experiment (TCO).
CO is a sort of important indicator gases during coalself-ignition process, the concentration of CO can beused to characterize the reaction rate, so the mutation
temperature of CO concentration can be used tocharacterize the critical temperature.
3) Mutation temperature of oxygen consumption
rate in the programmed temperature risingexperiment (TO2). Oxygen consumption rate is adirect exhibit of the reaction rate, so oxygen
consumption rate can be used to characterize thecritical temperature.
To study the influence of fundamental internalparameters to critical temperature of coal selfignition, this paper will study the relationshipbetween the characterization parameters and theinternal parameters (TJR, TCO and TO2).

2.1 Fundamental internal factors
The study of coal self-ignition mechanisms
shows that the type and quantity of functional groups
plays a key role in the coal self-ignition process(Wang et al., 2012; Satoru et al., 2000; Olayinka,1992). However, it is difficult to explain the
difference between functional groups of different
types of coal quantitatively, and not operable inengineering practice. Various functional groups incoal are constituted by the respective elements,
industrial ingredient is a side reaction of coal
structure and composition of functional groups,
element composition and industrial components are
the basic parameters of coal, and can easily be tested.
Therefore, industrial components (volatile, ash, andfixed carbon) and element composition (C, H, O, N,
and S) are selected as influence factors, and theinfluence of these factors on low-temperature criticaltemperature in the coal self-ignition process isanalyzed. It should be noted that the moisture content
of coal is not selected as one influence factor in thispaper, because coal samples were dried prior to theexperiment.

3. EXPERIMENTAL PART

2.2 Characterization parameters of low-temperature
critical temperature
The coal self-ignition process shows varying
characteristics, especially at the critical temperature.
Changes of coal temperature and gas concentration
have a large effect on the coal self-ignition process,so this paper uses the following parameters ascharacterization parameters for low-temperature
critical temperature.
1) Mutation temperature of heating rate in the
adiabatic oxidation process (TJR), which reflects the

3.1 Experimental device
7
2

14

6
13
12

3

GC
4
5

11

1
8
PC

9
10
1-Temperature sensor 2-Three-way valve 3-Pressure gauge 4-Regulator valve 5-Pressure reducing valve
6-Dust collector
7-Mixing chamber for inlet gas
8-Reaction vesse l 9-Thermal insulation layer
10- Temperature control oven 11-Preheat copper pipe12-Heating pipe 13-Fan 14-Mixing chambe for outlet gas

Figure 1: Structure schematic diagram of the device.

This device consists of four parts: thegas
distribution part, reaction vessel, temperature control
oven, and control part. Figure 1 shows the structures
schematic diagram. The design of this device used
the adiabatic oven of the University of Queensland asa reference (Beamish et al., 2000). The temperature
control oven and its door are double skinned, andthere is glasswool in it for insulation. A 2.3 kW
heating pipe is used for heating, and there is a fan toforce gas flow to ensure temperature uniformity
inside the oven. There is a 16 m length of copper pipein the oven to ensure the temperature of gas is thesame as the oven before entering the reaction vessel.
Taking the vacuum flask as the adiabatic reaction
vessel can effectively reduce conduction andradiation heat transfer. The temperature programmed
reaction vessel is made of steel to ensure goodthermal conductivity, and type K thermocouples areused for monitoring temperature. The gas used in the575

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

experiment is provided by high-pressure gas
cylinders, and the gas is control by mass flow meter
after flowing through the pressure valve. The control
part is a PC, and the device is controlled by King
View software. The flow of gas and temperature of
the oven can be regulated and the date can berecorded by operating this software.

analysis. When the coal temperature reached 180°,
heating and the oxygen flow were automatically
stopped. The coal sample was removed from theadiabatic reaction vessel after the sample and oven
were cooled down to normal atmospherictemperature. The vessel was cleaned and theadiabatic device was checked.

3.2 Experimental procedure
1) Preparation of coal samples
The coal samples used in this study wereobtained from coal mines of different regions in
China. All the coal samples selected for testing wereobtained directly from bore holes, and then put into aplastic bag. After this, the coal samples were put intoa low-temperature closed container and transported to
the laboratory, then placed into a refrigerator until thestart of the experiment. Before testing, the coalsamples were divided into two parts (nearly thesame): one part was returned to the refrigerator after
rewrapping. The other part was sieved by jaw crusher
and closed grinding machine to select expectedparticle size for immediate testing.
2) Experimental procedure(1) Temperature programmed experiment
A 200 g coal sample was crushed into particles
with mixed diameters of 1.25-1.6 mm, 1.6-2 mm, 23.5 mm, 3.5-5 mm and 5-7 mm, each accounting for20%. The coal samples were put into the reaction
vessel, dried for 9 h in nitrogen environment (120ml/min) at 105°. After cooling down, nitrogenoxygen mixed gas (the concentration of oxygen is21%) was transported into the programmable
isothermal oven with a constant flow rate of 60
ml/min. Emission gases were collected once every
15°, and the oxygen concentration was analyzed witha gas chromatograph; the initial temperature andtermination temperature were 30° and 180°. In theheating process, temperature rise inside the oven was
15° with a rate of 1°/min, and the temperature kept
constant for 10 min, and then increased 15° with arate of 1°/min again. Similar procedures were carriedon until 180°.
(2) Adiabatic oxidation experiment
The granularity of coal samples are <212 μm. Allcoal samples were dried at 105° for 15 hours under
the protection of nitrogen to ensure that the coalsamples were dried completely and not oxidized.
Then the temperature was cooled down to 40° andallowed to equilibrate. The drying coal sample was
moved into the adiabatic reaction vessel quickly andstabilized at 40° under nitrogen atmosphere, thenswitched to “track temperature mode”. The nitrogen
input was cut off and open oxygen valve with aconstant flow rate of 60 ml/min. The change in coaltemperature was recorded by the control part for later

3.3 Experimental results
Based on the experimental method above, theconcentration-temperature curve of O2 and CO oftemperature
programmed
experimentandtemperature-time curve of adiabatic oxidation
experiment for seven coal samples can be obtained,
which are shown in Figures 2-4.
Temperature(℃)

190

1#
2#
3#
4#
5#
6#
7#

140

90

40
0

1000

2000

3000

4000

5000

t(min)

Figure 2: The coal temperature-time curve in isolated heat
oxidation experiments.
CO concentration(10-6)

40000

1#
2#

30000

3#
4#
20000

5#
6#
7#

10000

0
20

60

100

140

180

Temperature（℃）

Figure 3: The change of CO concentration withtemperature improving in temperature-programedexperiments.
Oxygen concentration(10 -6 )

25

1#
2#
3#
4#
5#
6#
7#

20

15

10

5

0
20

60

100

140

180

Temperature（℃）

Figure 4: The change of O2 concentration with temperature
improving in temperature-programed experiments.

576

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 201622

where n is porosity, %; S is cross-sectional areaxo2of the reaction vessel, m2; R (T ) is oxygen
consumption rate at position x, mol/(m3∙s); υg is gas
3

flow rate, m /s;xo2

C is oxygen concentration at3

 Ci 
υ g Ciln  L 
RO2( T ) =（）1 − n SL  CO2 (3)Depending on equation (3), the values of RO2
for seven coal samples are given in Figure 5.
300

Oxygen oconsumption
rate(10-10 mol/(cm3 ∙s))

3.4 Oxygen consumption rate analysis
The height of the reaction vessel is 0.25 m (coalsample height is 0.221 m, L), Cross-sectional area (S)is 0.007088 m2. The temperature of the reaction
vessel is considered to be changed evenly for low
heating rate and light coal sample weight. It is
assumed that the gas used is ideal gas. Depending on
the coal oxidation reaction equation (Srinivasan et al.,
1996; Copard et al., 2004), oxygen consumption rateequation of physical coal per unit length at a certain
position (x) is given by Formula (1):(1)−υ g dCox =(1 − n) Rox (T )Sdx

1#
2#

240

3#
4#

180

5#
120

6#
7#

60
0
20

60

100

140

180

Temperature（℃）

Figure 5: The change of oxygen consumption rate withtemperature improving in temperature-programedexperiments.

x

position x, mol/m ; dC o2 is variation of the oxygen
concentration, mol/m3.
According to chemical kinetics and equilibrium
theory (Kudynska and Buckmaster, 1996; Wang et al.,
2003; Baris et al., 2012), the average oxygen
consumption rate can be expressed as Formula (2).
Ci
(2)
RO2 (T ) = ROx2 T x
CO2where RO ( T ) is the average oxygen
consumption rate, mol/(m3∙s); Ci is oxygen
concentration of inlet gas, mol/m3. Substituting
equation (2) into equation (1), equation (3) reads:
2

4. PARAMETER CALCULATION AND
ANALYSIS
4.1 Internal parameters
Element contents (N, S, H, O, and C) andindustrial components (ash, volatile, and fixed
carbon) of seven coal samples are tested by vario
MACRO CHNS (with Oxygen kit) Elemental
analyzer and GF-A6 Automatic Industrial Analyzer.
The results are shown in Table 1.

Table 1: The result of industrial analysis experiments and element analysis experiments.
Volatile property
AshFixed carbon
NS
wt% ar
wt% ar
wt% ar
wt% daf
wt% daf
1.185
1.179
1#
21.42
19.86
57.52
1.206
1.01
2#
25.63
22.72
50.32
1.309
2.495
3#
33.18
8.84
52.57
1.239
0.582
4#
39.15
9.55
46.95
1.148
0.929
5#
30.23
11.34
52.68
1.281
0.852
6#
30.88
3.7
61.45
1.332
0.634
7#
12.95
8.07
77.72

3.2 Characterization parameters of criticaltemperature
According to Arrhenius equation (Bews et al.,
2001; Ronald et al., 1989; Anna et al., 2011), reaction
rate can be express as:

k = A exp(−

E
)
RT

(4)

where k is Oxidation reaction rate of coal; E is-1
; A is preapparent activation energy, ∙mol
KJ
-1
exponential factor, s ; R is universal gas constant,H
wt% daf
3.761
3.818
4.814
4.111
4.234
3.834
3.731

O
wt% daf
6.332
8.396
15.11
15.92
14.59
9.614
3.321

C
wt% daf
69.99
65.29
69.16
70.12
84.98
75.72
69.81

0.008314 KJ/(K•mol); T is thermodynamic
temperature, K.
Further analysis of the formula (4):E
ln k = ln A −(5)
RT
Replace the Oxidation reaction rate k withadiabatic heating rate, CO concentration and oxygen
consumption rate (denoted as k1, k2, and k3), therelationship between lnk and (-1/T) can be obtained.
Using linear analysis, the critical temperature can be577

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

1#
2#

-3

3#
lnk 1

-5

4#
5#

-7

6#
7#

-9
-0.0032-0.003-0.0028-0.0026-0.0024-0.0022-(1/T)

Figure 6: The relationship between lnk1 and (-1/T).

lnk 2

6
5

1#

4

2#

3

3#

2

4#

1

5#

0

90

灰分

固定碳

O

C

N

S

H

6

80
5
70
4

60
50

3
40
30

2

20
1
10
0

0
0

1

2

3

4

5

6

7

8

Coal samples/#Figure 9: Fundamental internal parameters and therelationship.

6#

-1

7#

-2
-0.0032-0.003-0.0028-0.0026-0.0024-0.0022-(1/T )

5.2
Relationshipbetweencharacterization
parametersThe
relationshipbetweenthethreecharacterization parameters is shown in Figure 10.

Figure 7: The relationship between lnk2 and (-1/T).
1#
2#

8

3#
4#

6

5#
4

6#

2
-0.00347#-0.003-0.0026

160
140

Temperature（℃）

10

lnk 3

挥发分

Contents（N、H、S）/%-1

5.1 Relationship between internal parameters
The relationship between the eight parameters isshown in Figure 9. Based on this, it can be seen thatthe relationship between the various parameters iscomplicated; however, it still can be clearly observedthat the trend of O and volatile property is similar,
and the trend of fixed carbon is contrary to them.
Contents（without N、H、S）/%

obtained by analyzing the changes of slope, which isshown in Figures 6-8.

TJR

120
TCO

100

TO2

80
60
40
0

2

4

6

8

Coal samples（#）-0.0022-(1/T )

Figure 10: Characterization parameters of coal spontaneous
combustion critical temperature.

Figure 8: The relationship between lnk3 and (-1/T).

According to the analysis results above, criticaltemperatures for seven coal samples are shown in
Table 2.
Table 2: Characterization parameters of coal spontaneous
combustion critical temperature.
Item
1#
2#
3#
4#
5#
6#
7#

TJR（℃）
110
105
80
95
80
95
120

TCO（℃）
105
105
60
75
60
90
135

5. INFLUENCE OF INTERNALPARAMETERS TO CRITICALTEMPERATURE

TO2（℃）
135
135
90
105
75
120
150

According to Figure 10, the changing trends ofthe three parameters for different coal samples arebasically the same. In accordance with the ascending
parameter values, coal numeral order is 5#, 3#, 4#,
6#, 2#, 1#, and 7#. The 3 parameters for the same
coal sample are different, for example, TJR, TCO andTO2 for 1# coal sample are respectively 110, 105 and135, which shows that the changing regulations forthe three characteristics are the same, but there islittle differences in temperature. Overall, values of
the three parameters for a certain coal sample arevery close and are valid parameters.
5.3 Gray relational grade analysis
The relationship between internal parameters andcharacterization parameters of critical temperature iscomplicated, and the influence is hard to obtain bydirect observation. Based on this feature, this paper
introduces the gray relational grade analysis method
to analysis the relevance of eight internal parameters578

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

and three characterization parameters. The
calculation is according to the literature (LIU et al.,2004), and the calculation methods and formulas are
not given in this paper. Based on data from Table 1
and Table 2, the calculation result is given in Table 3.
Table 3: Gray relational grade between characterization
parameters and fundamental internal parameter.
Mean
TCO
TO2
TJR
value
Volatile
0.68
0.69
0.65
0.67
property
Ash
0.55
0.70
0.64
0.63
Fixed
0.67
0.56
0.54
0.58
carbon
N
0.56
0.62
0.56
0.58
S
0.70
0.58
0.54
0.61
H
0.59
0.62
0.59
0.60
O
0.65
0.66
0.62
0.64
C
0.54
0.54
0.52
0.53

According to Table 3, the three highest relevanceparameters are contents of volatile property, ash, andO, the lowest ones are contents of fixed carbon, C,
and N. In decreasing order: volatile property, O, ash,
S, H, fixed carbon, C, and N, which reflects theinfluence level of parameters.
5.4 Numerical fitting analysis
To further analyze the influence of internalparameters to characterization parameters, this paper
makes a mathematical formula fitting to those two
sorts of parameters. The fitting expression is labelledformula (10). As in the analysis above, the contents
of fixed carbon, C, and N are the lowest relevanceparameters. They do not have an obvious influenceon the characterization parameters, and therefore we
only consider the three characterization parametersand five internal parameters (volatile property, O,
ash, S, and H).

y = p0 ( x1 ) p1 ( x2 ) p2 ( x3 ) p3 ( x4 ) p4 ( x5 ) p5

(10)where y is 3 characterization parameters TJR、
TCO and TO2, x1-x5 are 5 internal parameters, volatile
property, O, ash, S and H, p0-p5 are fit coefficients.
Using the date in Tables 1 and 2, the fitting
result is shown in Table 4.
Table 4: Numerical fitting results.
p0

p1

p2

p3

p4

p5

TJR

430.13-0.14-0.004

0.17

-0.50

-0.14

TCO

376.39

-0.23

0.05

-0.07

-0.17

-0.27

TO2

2317.83

-0.11

-0.04

0.28

-1.54

-0.19

According to Table 4, p1, p4 and p5 for thenumerical fitting of three characterization parameters
are negative, which shows that the criticaltemperature and contents of volatile parameter, O,
and H are negatively correlated; the absolute valuesof p2 are very small, which shows that criticaltemperature has very little correlation with thecontent of ash; p2 and p3 are positive or negative,
which shows that the influence of contents of ash and
S is not certain.

6. CONCLUSIONSTo study the effect of internal factors on lowtemperature critical temperature in coal self-ignition
process, eight fundamental internal parameters(volatile, ash, fixed carbon, C, N, S, H, and O) andthree characterization parameters of low-temperature
critical temperature in the coal self-ignition process(TJR,TCO and TO2) are selected, and the values for eachare determined via experiment and calculation. Then,the relationship between fundamental internalparameters and that of characterization parameters
are compared. Through grey relational analysis, fiveimportant influence parameters are filtered to make amathematicalformulafittingwiththecharacterization parameters. The conclusions are as
follows:(1) Based on the theoretical analysis of theoccurrence and development of coal self-ignition,
TJR, TCO, and TO2 are selected as characterization
parameters of critical temperature, which characterize
critical conditions for three aspects: heat rising, CO
generation, and O2 consumption.
(2) Depending on the Arrhenius equation, thevalues of characterization parameters for seven coalsamples were obtained by the segmented fitting
method, which shows that the changing regulations
for the three characteristics are the same, but there islittle difference on temperature; values for the threeparameters for a certain coal sample are very close,
and are valid parameters.
(3)
By analyzing therelevanceofcharacterization parameters and fundamental internalparameters, it is found that the critical temperatureand contents of volatile parameter, O, and H are
negatively correlated; critical temperature has very
little correlation to the content of ash; the influence ofcontents of ash and S are not certain, and theinfluence of contents of fixed carbon, C, and N to
critical temperature is the least significant.
(4) The accuracy of parameters and the numberof coal samples need to be improved to get moreaccurate results in future research.

7. ACKNOWLEDGEMENT

579

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The authors gratefully acknowledge thefinancial support provided by National Nature
Science Foundation of China (U1261214) and
Development Fund Project of China Coal ResearchInstitute (2014JC06).

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580

ISMS 2016

Paper No. 47

Experimental study of negative pressure gas drainage influences on coalmoisture content
Shaojie Chena,b,*, Longzhe Jinb, Xianglong Liuca

School of Safety Engineering, North China Institute of Science and Technology, Beijing, China, 101601
School of Civil and Environment Engineering, University of Science and Technology, Beijing, China, 100083
c
Safety Supervision Department, Shanxi Lu’an(mining) Group Co.Ltd, Changzhi, China, 046204b

ABSTRACT
In light of water loss phenomena of coal by negative pressure gas extraction, the relationship between time and coalmoisture content, and the rate of water loss in special conditions of temperature and negative pressure were studied
in the laboratory, and the water loss mechanism of coal was analyzed. Results show that the moisture content of
three coals decreased as the negative pressure reaction time increased. In the initial phase, the moisture content ofcoals descends quickly. Afterwards, the decrease trend slows, and finally the moisture content of coals trends to a
constant value. The maximum saturated water loss rate reaches 82.19% and the water loss of coal in experimental
conditions is larger. The negative pressure by gas extraction reduces the coal pore gas pressure, and the boiling point
and the saturated vapour pressure of water decrease; the free water vapourization (no boiling) rate of coals increases.
Adsorption water and liquid water can change from a liquid to a gas, and be extracted by negative pressure. Thisaction reduces the coal moisture content. The moisture of coal has great affects on dust quantity by mining. A longand continuous gas extraction will result in water loss of coal, and it is of great disservice to the prevention of coalmine dust, so it is necessary to perform water injection into coal seams or to take enhanced dust prevention measures
after gas extraction.
Keywords: dust; gas extraction; negative pressure; coal moisture content; water loss mechanism

1. INTRODUCTION
At present, China's coal mine safety production
situation is improving significantly. However, coalmine dust prevention is still a prominent problem,
and it leads directly to high pneumoconiosis cases for
operators (Fang H. et al., 2011; Tong R. et al., 2013).
Occupational safety and occupational health shouldbe equally important for workers. Great importanceshould be attached to gas disasters as well as dust
control. Aimed at low permeability coal seams,
closed drilling and long time gas drainage is the main
measure to control disasters, especially in high gas
mines and coal and gas outburst mines. Gas drainage
can lead to the loss of coal moisture content, dryingout the coal seam (Bao Q. et al., 2013). The amountof dust produced in mining is directly related to themoisture content of coal. The smaller the coalmoisture content, the more dust generation. Somescholars have studied the water vapourization of coalin natural environments (Jin L. et al., 2000; Cong X.
et al., 2010). In order to quantitatively study theeffects and mechanism of negative pressure drainage
on coal moisture content, the relationship between
time and coal moisture content, and the rate of water
loss in special conditions of temperature and negative
pressure, three coal samples were studied in the*Corresponding author – email: chenshaojie@ncist.edu.cn

laboratory, and the water loss mechanism of coal was
analyzed.

2. EXPERIMENTS
2.1 Coal samples
Three representative coal samples were taken as
the study and experiment object, and the samples
were collected from 6-2# coal seam of Kaida mine,
15# coal seam of Jiarui mine, and 8# coal seam ofXinjing mine. The three coal samples were numbered
1#, 2#, and 3#, respectively. The coal samples were
not influenced by gas drainage, and the sealed coalsamples were taken to the laboratory. The proximate
analysis and rank of coal samples are shown in table
1.
Table 1: Proximate analysis and rank of coal samples.
Moistur
Volatile
Ash
Sampl
e
componen componen Coal ranke IDcontent
t (%)
t (%)
(%)
Nonstick
1#
14.16
19.66
22.47
coal
Meager
2#
1.90
14.05
9.83
coal
Anthracit
3#
0.98
8.81
12.76
e coal3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The 300 g coal samples with the particle sizes of
0.1-0.18 mm of three coals (1#, 2#, and 3#) wereprepared by crushing and screening by
proximate analysis standard. The prepared coalsamples were enclosed in Ziploc bags to prevent
water vapourization in air. The samples are shown in
Figure 1.

The water loss rate of coals at different time
under constant temperature and negative pressure
were calculated by Eq. (1).
δ=(W0-Wt)/W0(1)

Where δ is the water loss rate of coal sample, %,W0 is the original moisture content, %, Wt is the
moisture content at certain time after negative
pressure, %.

3. RESULTS AND ANALYSIS
3.1 Relationships between moisture content and time
Under particular a experimental temperature andnegative pressure, the relationship between moisture
content of the three coal samples and time are shownin Figure 3.

2.2 Experimental device and process
Place the 40 g coal samples into a sealed tankand fix a constant temperature water bath at 30℃.
Connect the sealed coal samples tank to a vacuum
pump, and then turn on the vacuum pump. The sealed
tank was opened after 0.5 h, and the vacuum coalsamples were rapidly enclosed in the Ziploc bag andnumbered on the outside. According to the above
procedure, the coal samples were separately
vacuumed at 1 h, 2 h, 3 h, 4 h, and 5 h, and the
moisture content of six coal samples of different
negative pressure action times (including the original
coal sample) were acquired. The different moisture
content of coal samples was tested by TGA-2000
automatic industrial analyzer, and the date wasanalyzed. The three coal samples were tested basedon the above experimental method. The experimental
apparatus is sketched in Figure 2.

1# coal sample

12
9
6
3
0
0

1

2

3

4

5

4

5

Time/h(a) 1# coal sample
2

Coal moisture content/%

Figure 1: Experimental coal samples.

Coal moisture content/%15

2# coal sample
1.5

3# coal sample

1

0.5

0
0

2
7

7

8
3

2

3
Time/h(a) 2# and 3# coal samples
Figure 3: Relationships between moisture content and time.

4
5

1

6

1

1- vacuum pump；2-vacuum gauge；3-desiccator；
4-needle valve；5- sealed tank；6-waterbath；
7-sebific duct；8-flowmeter
Figure 2: Diagram of Experimental apparatus.

From Figure 3, the moisture content of the threecoal samples decreases as the negative pressure
action time increases. In the initial phase, themoisture content of the coal samples descends
quickly. Afterwards, the decrease trend slows andfinally the moisture content of coal samples tends to a
constant value. For the low metamorphic 3# coalsample, the original moisture content is 14.16%, andthe moisture content changes to 4.77% after 5 hnegative pressure action time. The water loss582

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

phenomena of coals by negative pressure wereserious.
3.2 Relationships between water loss rate and time
The relationships between the water loss rate of
the three coal samples and time are shown in Figure
4.
1

1# coal sample
2# coal sample
3# coal sample

Water loss rate/%

0.8
0.6
0.4
0.2
0
0

1

2

3

4

5

Time/hFigure 4: Experimental coal samples.

From Figure 4, the water loss rate of the threecoal samples enlarges as the negative pressure action
time increases. The water loss rates of the three coalsamples are all more than 70%. The relationships
between water loss rate and time are analogous to theLangmuir equation, and it has a saturated water loss
rate that can be expressed by Eq. (2).
δ=abt/(1+bt)(2)

Where δ is the water loss rate of coal sample, %,a is the saturated water loss rate, %, b is the water
loss constant, h-1, t is the negative pressure action
time, h.
The water loss rate curve equations of three coalsamples are shown in Table 2. Under the specificconditions of the experiment, the maximum saturated
water loss rate reached 82.19%. When the water loss
rate reached saturation, the coal moisture content nolonger reduced under increasing negative pressure
action time. This was primarily connected to theexisting water form, where the free water in coal was
easily lost but the combined water was not.
Table 2: Water loss rate curve equations of coal samples.
Saturated
SampleCorrelationwater loss
Fitting equationID
coefficient
rate (%)
1#
δ=1.02t/(1+1.27t)
0.978680.65
2#
δ=2.36t/(1+3.29t)
0.970171.81
3#
δ=0.74t/(1+0.90t)
0.966882.19

4. WATER LOSS MECHANISM ANALYSIS
Coal is a porous medium, and water exits in two
main forms: free water and combined water. Free
water exists in the coal mass pore in the form ofliquid water, and it includes the adsorption water
which exists in coal interior particles in the form ofphysical absorption. Combined water (also called
crystal water) binds with the mineral substance ofcoal in the form of combination. Combined waterneeds a high temperature to separate out. The micromechanism of coal adsorbing water is the result of
the attraction between water molecules and coalmolecules. These attractions include van der Waals
forces and hydrogen bonds (Nie B. et al., 2004).
The water saturation vapour pressure is thepressure when the gas phase water and liquid phasewater reaches equilibrium. There is a dynamicbalance between liquid water and vapourous water
under a particular pressure at the same temperature,and the molecular quantitative mutual transformationof the liquid water and vapourous water are equal inunit time. The water saturation vapour pressure isrelative to the escape of water molecules from liquidwater trend. The vapour pressure of liquid reflects theevaporation rate. According to the Clausius-Claperon
equation, the relationship between the boiling pointof water and the vapourization pressure can be
represented as follows:lg p=A+B/T(3)

Where p is the vapour pressure, Pa, T is theboiling point, K, A and B is the constant.
The formula shows that decreasing coal pore gaspressure (gas extraction) can lead to a decrease in theboiling point for free water and it can speed up theevaporation of the free water. If the gas drainage
negative pressure is 13 Kpa, the temperature of thecoal seam is 30℃, and the boiling point of water is
51 ℃ , the vapourization pressure of water is 4.24
Kpa. At this point the boiling point of water is still
higher than the temperature of the coal seam, and thevapourization pressure of water is still lower than thegas drainage negative pressure, so the water loss
process is vapourization rather than boiling.
Compared with the boiling point of water undernormal pressure, it has reduced 49% under negative
pressure. If we continue to improve the gas drainage
negative pressure, the boiling point of water can belower than the temperature of the coal seam, and thewater loss process changes to boiling.
For the actual gas drainage project in mines, thenegative pressure affected area around the borehole
widens as time goes on. Inside the negative pressure
affected area, coal pore gas pressure decreases. The
water vapourization is accelerated on account of thewater boiling point unloading, and the coal moisture
content has a marked loss.

583

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

5. CONCLUSIONSThe coal moisture content decreases as thenegative pressure action time increases. The saturated
water loss rate of three coal samples reaches 82.19%
and the water loss phenomena of coal by negative
pressure gas extraction are serious. The gas drainage
negative pressure reduces the coal pore gas pressure,and the boiling point and the saturated vapourizationpressure of water decrease; it increases the water
vapourization (no boiling) rate of coal. Free water(including adsorption water and liquid water) canchange from a liquid to a gas and be extracted bynegative pressure. This action would reduce the coalmoisture content. The moisture of coal has a great
affect on dust quantity in mining. Long andcontinuous gas drainage will result in water loss ofcoal, which is of great disservice to coal mine dust
prevention, so it is necessary to perform water
injection into coal seams or to take enhanced dust
prevention measures after gas drainage.

6.

control technique in underground coal mines. Metal
Mine. No. 12, pp. 131–134.

ACKNOWLEDGEMENT

This paper is Supported by the Fundamental
Research Funds for the Central Universities (Grant
no. 3142015105) and National Natural Science
Foundation of China (Grant no. 51074015).

7. REFERENCES
Bao Q. and Zhou S. (2013). Application researchof comprehensive dust control technology in heading
face. Mining Safety & Environmental Protection.
Volume 40, No. 6, pp. 43–46.
Cong X., Liu X. and Zhan S. (2010).
Experimental of water evaporation on the minesurface in natural environment. Journal of China Coal
Society. Volume 35, No. 1, pp. 93–96.
Fan H., Cui W., Yuan J., Chen Y., Xu Y. and G
W. (2011). Investigation study on current situation ofdust management in coal enterprises. Journal of
Safety Science and Technology. Volume 7, No. 5, pp.
47–51.
Jin L., Jiang Z., Ren B. and Wu K. (2000). Studyon phenomenon of water vaporization duringinfusing water into coal seam. China Safety Science
Journal. Volume 10, No. 3, pp. 58–62.
Nie B., He X., Wang E. and Zhan L. (2004).
Micro-mechanism of coal adsorbing water. Journal of
China University of Mining & Technology. Volume
33, No. 4, pp. 379–383.
Tong R., Cui Y., Liu X., Li X. and Wang W.
(2013). A health damage evaluation method for coalmine dust in its life cycle. China Safety Science
Journal. Volume 23, No. 10, pp. 126–131.
Wang H., Wang D., Ren W. and Xi Z. (2009).
Research status and development trend for foam dust584

Paper No. 222

ISMS 2016

The laws of gas-solid coupling of coal-bed gas in deep high gassy coal seams
Zhou Aitaoa, Wang Kaib,*, Shen shangkuncaSchool of Resource & Safety Engineering, State Key Laboratory of Coal Resources and Mine Safety, China University of
Mining & Technology, Beijing China 100083
bSchool of Resource & Safety Engineering, State Key Laboratory of Coal Resources and Mine Safety, China University of
Mining & Technology, Beijing China 100083
cSchool of Resource & Safety Engineering, State Key Laboratory of Coal Resources and Mine Safety, China University of
Mining & Technology, Beijing China 100083

ABSTRACT
In order to analyze the laws of gas-solid coupling of coal-bed gas in deep high gassy coal seams as well as toprevent the gas compound dynamic catastrophes of deep gas-filled coal-rock, a gas-solid coupling theoreticalmodel under the influence of ground stress, gas pressure, and mining depth is established and simulated by using
COMSOL Multiphysics software. Research results indicate that under the influence of factors such as highground stress and gas pressure, the mutual coupling interaction between coal and gas is much more significant,which leads to the emergence of new characteristics of gas compound dynamic disasters. Reducing the groundstress concentration in front of the working face can not only minimize the possibility of rock burst accidents
which are mainly caused by ground stress, but also weaken the role of ground stress as a barrier to gas, thereby
decrease the number of outburst accidents whose dominant factor is gas; The results have a great theoretical andpractical significance on the further optimization of accident prevention technique as well as safety protection ofmines, disaster prevention system design, and accident emergency plans.
KEYWORDS : deep mining; high gassy coal seam; gas-solid coupling; dynamic disaster

1. INTRODUCTION
Most of the coal mines in China have reacheddeep mining, and the interaction among theconstantly increasing coal seam ground stress, gas
content, and gas pressure is blamed for the increaseof gas compound dynamic catastrophes as well assome new emergent disaster characteristics.
On the basis of investigations concerning gas
compound dynamic catastrophes in high gassy coalseams that have occurred in recent years, it has been
discovered that there are obvious rock burst
manifestations such as roof collapse, floor heave, androadway deformation (often accompanied by highlevels of gas gushing) at the scene of this new type ofgas compound dynamic disaster. Moreover, there aresome gas outburst holes at the scene and coal rock is
thrown far away from these holes. Several distinctive
features of gas outburst can be found in these
accidents. All these illustrate that the couplinginteraction between coal and gas in deep high gassy
coal seams is more significant, which results in theemergence of new features of gas compound dynamic
disasters.
Investigations aimed at coupling laws were madeby domestic and foreign scholars. Litwiniszyn et al.

*Corresponding author – email : safety226@126.com

studied the coupling interaction between coal and gas
as well as gas migration law from different angles.
Liu Jishan et al. built a mathematical model of gassolid coupling which takes gas-coal’s swellingdeformation into account. Scholar Zhao Yangsheng
took the lead in proposing a new mathematical modelof the coupling reaction between coal rock and gas
and further analyzed the numerical method. Zhao
Guojing, Ding Jihui et al. came up with the instability
theory of gas outburst and established a mathematicalmodel based on the coupling relationship of a gassolid two-phase medium. Liang Bing et al. set up a
coal rock constitutive model which takes the gasinteraction into account from the intrinsic time angle.
Meanwhile, they proposed the destabilization theoryof gas outburst/rock burst and established themathematical model. Considering the fracture
evolution process of coal, Yang Tianhong et al.
developed a gas-solid coupling model of coal seamcontaining damage, and then simulated the gas
drainage process in a deep coal seam. Tang Chunan,
Xu Tao, Yang Tianhong et al. studied the numericalsimulation of coal and gas outburst by using therelevant theory of fluid-solid coupling. S.Valliappan
established a fluid-solid coupling model for the flow

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016of coal-seam gas and compiled the corresponding
finite element computer program to simulate theprocess of coal and gas outburst.
Mainly aimed at the characteristics of high gassy
coal seams in deep mining, this paper simulated thelaws of gas-solid coupling of coal-bed gas under the
influence of gas pressure, mining depth, and otherfactors and then analyzed the influencing factors ofgas compound dynamic disasters of coal rock in highgassy seams. The results have great theoretical andpractical significance on the further optimization of
accident prevention techniques as well as the safety
protection of mines, disaster prevention systemdesign, and accident emergency plans.

For ideal gas, the content of adsorbed gas
satisfies the Langmuir equation and the gas seepage
process conforms to Darcy's law, ignoring the effectof gravity and according to the law of conservation ofmass at the same time, the following equations canbeen drawn.
1) The state equation of gas
The state equation of gas can be obtained basedon the state equation of ideal gas.
𝑀𝑔 𝑝
(1)
𝜌𝑔 =
With temperature being constant, then𝜌𝜌𝑔 = 𝑝𝑛 𝑝𝑛(2)Where 𝑝 is gas pressure, MPa ; 𝜌𝑔 is gas density
when the pressure equal to p, kg/m3; 𝑀𝑔 is molar
volume of gas, mol/L; 𝑅 is molar gas constant,
kg/(m3*MPa); 𝑍 is compressibility factor, the value isapproximate to 1 when the temperature variation is
not vast; 𝑇 is absolute temperature, K; 𝑝𝑛 is gas
pressure in standard state, MPa; 𝜌𝑛 is gas density instandard state, kg/m3.
This can be simplified as:
𝜌𝑔 = 𝛽𝑝(3)2) Gas content model
Gas in coal beds can be divided into two states;
absorbed gas (Q1), that is absorbed between
micropore surface and coal particles, free gas (Q2),which flows freely in pore fissure space.
When adsorbed gas content satisfies theLangmuir equation, then absorbed gas content
formula of unit coal can be written as:

𝑄1 = 𝑐𝜌𝑐 𝜌0

𝑎𝑏𝑝

1+𝑏𝑝

𝑄 = 𝑄1 + 𝑄2 = 𝑐𝜌𝑐 𝜌0

𝑎𝑏𝑝

1+𝑏𝑝

+ 𝜙𝜌𝑔

(4)

Where 𝜌𝑐 is the density of coal, kg/m3; 𝜌0 is thedensity of gas under normal atmospheric pressure,kg/m3; 𝑎 and 𝑏 are Langmuir adsorption coefficient,the dimension of 𝑎 is m3 /t , the value of 𝑎 ranges
from10 to 60, the dimension of 𝑏 is MPa−1 , the value(6)

The operator form of which is shown as follows:𝜕𝑄(7)= −𝛻�𝜌𝑔 𝒖� + 𝑄𝑚
𝜕𝑡

Gas seepage process conforms to Darcy’s law
and ignores the effect of gravity, then:𝑘

2. GAS-SOLID COUPLING THEORY OF
COAL-BED THEORY

𝑅𝑇𝑍

of 𝑏 ranges from 0.5 to 5; 𝑐 is correction coefficientwhen consider factors such as coal moisture and ash
temperature，the value of 𝑐 ranges from 0 to 1.
Free gas content of unite coal can be expressedas:𝑄2 = 𝜙𝜌𝑔(5)
Where 𝜙 is coal porosity, dimensionless.
Above all, total gas content of unite coal is:𝒖 = − 𝛻𝑝(8)𝜇Where 𝑘 is permeability of coal seam, m2; 𝜇 is
gas viscosity, Pa*s.
3) Porosity evolution model
Ignore the change of temperature and gas
adsorption, evolution equation for coal porosity is:

𝜙 =1−

1 − 𝜙0(1 − 𝐾𝑌 ∆𝑝)
1 + 𝜀𝑣

Where 𝜙 and 𝜙0 are coal porosity and original
porosit, dimensionless; 𝐾𝑌 is coefficient of volume
compressibility, dimensionless; ∆𝑝 is pressurechanges of gas, MPa; 𝜀𝑣 is volumetric strain ofcoal, dimensionless.
4) Permeability evolution model
Coal is a dual-porosity reservoir where gas ismostly stored in the coal matrix and Darcy fluid flow
occurs in the natural fracture system. The flow
capacity of fracture media depends almost entirely on
the number and width of fractures and theircontinuity in the direction of flow. Permeability, ameasure of the flow capacity, is directly related to arange of pore characteristics including pore size,
continuity, and connectivity. It is generally believedthat the change of coal permeability is decided bycoal porosity. The Kozeny - Carman equation which
is set up on the basis of the capillary model is mostwidely used. The permeability evolution model is:

𝑘=

𝑘0

1+𝜀𝑣

𝜀

�1 + 𝑣 +𝜙0(1−𝜙0 )𝐾𝑌 ∆𝑝 3
𝜙0

�

(9)

3. NUMERICAL SIMULATION OF GASSOLID COUPLING IN DEEP HIGH GASSYCOAL SEAMS
The general finite element analysis software
COMSOL Multiphysic was adopted to make acalculation of the established gas-solid coupling
model. The geometric model is 80 m long, 30 m high,the roof height of which is 15 m, floor height is 10 m,
and coal seam height is 5 m. The excavation block
whose length is 5 m is set at the far left of the coal586

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

seam.
3.1 Model parameter
According to the actual situation of high gassy
mines in China and taking some relevant literatures
as a reference, the model parameters are set up as
shown as in Tables 1 and 2.
Table 1: Parametric values of coal and surrounding rock.
N
Value
Description
r1
1250[kg/m3]
Coal density
E1

2713[MPa]

Coal elastic modulus

po1

0.339

Coal Poisson's ratio

co1

1.25[MPa]

Coal cohesivenesstheta137π/180 [rad]3

Coal inner friction angle

r2

2640 [kg/m ]Surrounding rock density

E2

33400[MPa]Surrounding rock modulus

po2

0.235

co2

3.2[MPa]

Surrounding rock Poisson's
ratio
Surrounding rockcohesivenesstheta2π/6[rad]Figure 1: Distribution of vertical stress before
excavation.

Excavate the preset block excavation. A transient
solver is chosen to solve the gas-solid model of coalbed gas. The duration is set at 0 to 60 minutes and thestep size is 5 minutes. The parameters cloud maps are
set at 30 minutes, and the results are as follows:

Surrounding rock inner
friction angle

Table 2: Parametric values of gas.
Name

Value

Description

rg

0.714[kg/m3]

e0

0.01
-15

2

k0

1.0×10 [m ]mug

1.84×10-5[Pa*s]a3

26[m /t]Gas density in standard
state
Initial porosity before
excavation
Initial permeability before
excavation(a)

Gas viscosity
Adsorption coefficient 1-1b0.714[MPa ]Adsorption coefficient 2c0.9957

Adsorption coefficient 3
3

beta

7.14[kg/(m *MPa)]

Gas state coefficient

alpha

0.99

B-W coefficient

3.2 Simulation scheme and results
Mining depth is set at 800 m and initial gas
pressure is 2 MPa. The gas-solid coupling laws ofcoal-bed gas are studied under the influence of great
ground stress and gas pressure.
Firstly, the corresponding body load and edge
load are exerted on the model, and the initial state
before excavation is obtained. The distribution ofvertical stress is shown in Figure 1.

(b)
Figure 2: Distribution of vertical stress and horizontal
stress after excavation.

From Figure 2, it can be seen that:
1) Obviously stress unloading area, stressconcentration area, and initial stress area exist in thecoal beds.
2) The maximum peak of stress lies in the stress587

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

concentration area, close to the coal wall.
3) Obviously pressure-released region exists at
upper and down floor of excavation roadway, theheight of which is 10 m.

(a)

(a)

(b)
Figure 4: Distribution of porosity and permeability
after excavation.
(b)
Figure 3: Distribution of volumetric strain andvolumetric plastic strain after excavation.

From cloud maps of strain after excavation in
Figure 3, we can see:1) The stress of coal mass near the coal wall
passes over the yield strength, plastic strain occurs,
and the length of the plastic strain area is about 3 m.
2) Coal mass near the wall is forced anddamaged, obvious dilatancy effect and volume
expansion occur, then in the elastic region of stressconcentration area coal mass is compacted andvolumetric strain reaches the minimum.

As cloud maps of porosity and permeability
shown in Figure 4:
1) Porosity and permeability are all influenced
by the strain of coal seams and the gas pressure, they
have the same changing trend.
2) Because of the dilatancy effect, the porosityand permeability of coal mass near the coal wall arelarger and reach the maximum at the coal wall, thengradually decrease along with the coal seam extends
to right. Coal mass is forced and compacted in theelastic region of stress concentration. Porosity andpermeability reach the minimum and then gradually
recover to the original value.

588

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

accident in Laohutai Fushun is taken as an example,
and the results are shown in Table 3.
Table 3: Rock burst and gas emission situation in Laohutai
Fushun Mines.

(a)

(b)
Figure 5: Distribution of gas pressure and gas content
after excavation.

What we can see from cloud maps of gas
pressure and gas content are as follows:
1) Gas pressure and gas content share the same
trend. They sharply reduce near the coal wall andreach the minimum there. They reach the maximum
at areas where stress is concentrated, slightly greaterthan the initial values.
2) Due to the dilatancy damage of coal，gas iseasy to outflow from coal seam in the pressurereleased region. While at the stress concentrationarea, the compacted coal mass impedes the process ofgas seepage and forms significant gradientdifferences of gas pressure and content.

4. GAS COMPOUND DYNAMIC
CATASTROPHES OF DEEP GAS-FILLED
COAL-ROCK
In order to analyze the effect of high groundstress and gas pressure on disasters, several gas
compound dynamic catastrophes of deep gas-filledcoal-rock are studied in this paper. The rock burst

Ming
depth
/m

Total
number ofrock burst
accident

<580

165

1

630

224

13

680

269

34

730

135

10

780

337

83

830<

87

40

Sum
up

1217

181

Total numberof gasconcentration
overrunPercentage ofgas
concentration
overrun /%
0.61
5.80
12.64
7.41
24.63
45.98
100

According to the analysis of the accident, it has
been discovered that there are obvious rock burst
manifestations such as roof collapse, floor heave, androadway deformation (often accompanied by highlevels of gas gushing) at the scene of gas compound
dynamic disasters. Moreover, there are some gas
outburst holes at the scene, and coal rock is thrown
far away from these holes. Distinctive features of gas
outburst can be found in these accidents. The gas
gushing quantity per ton of coal is not very large, andthe airflow reversal phenomenon is not significant.
Rock burst intensity is in direct proportion toconcentration and duration of gas emission.
Furthermore, in the coal seam that applied gas
drainage measures, the frequency and strength ofrock burst significantly increased. For the deep highgassy coal seams under the influence of high groundstress and gas pressure, the coupling interaction
between coal and gas is more significant, which
results in the emergence of new features of gas
compound dynamic disasters.

5. CONCLUSIONS
1) A simulation of the laws concerning the gassolid coupling of coal-bed gas was made byestablishing a theoretical gas-solid coupling model
under the influence of gas-pressure, mining depth,
and using COMSOL Multiphysics software.
2) For deep high gassy coal seams under the
influence of high ground stress and gas pressure, thecoupling interaction between coal and gas is moresignificant, which results in the emergence of newfeatures of gas compound dynamic disasters.

589

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3) Reducing the ground stress concentration in
front of the working face can not only work wonders
for minimizing the likelihood of rock burst accidents
which are mainly caused by ground stress, but also
weaken the role of ground stress as a barrier to gas,
thereby reducing the number of accidents whose
dominant factor is gas. For deep high grassy coalseam, coal seam water infusion is the best method.

6. ACKNOWLEDGEMENTS
This research is financially supported by theState Key Research Development Program of China(2016YFC0801402, 2016YFC0600708), National
Natural Science Foundation of China (51474219).

7. REFERENCES
Liang B, Zhang MT and Wang YJ (1995) The
endochronic constitutional model of coal containing
gas, Rock & Soil Mech., vol. 03, pp. 22-28.
Litwiniszyn J (1985) A model for the initiationof coal-gas outbursts. Int. J. Rock. Mech. & Min. Sci.
& Geomech. Abstracts. , vol. 22(1), pp. 39-46.
Liu JS(2010) Linking gas-sorption inducedchanges in coal permeability to directional strains
through a modulus reduction ratio. Int. J. Coal Geol.,
vol. 83(1), pp. 21-30.
Valliappan S and Wohua Z (1996) Numericalmodeling of methane gas migration in dry coalseams. Int. J. Numer. Anal. Meth. Geomech., vol.20,
pp. 571–593.
Xu T, Tang CA and Yang TH (2005) Numericalsimulation of coupled gas flow in failure process ofgassy coal-rock. Chin. J. Rock. Mech. & Eng., vol.
10, pp. 1667-1673.
Yang TH (2001) Study on infiltrate character andcoupling analysis of seepage and stress in rock failure
process, Shenyang, China: Northeastern University.
Zhao GJ and Ding JH (1998) Non-linear
numerical simulation of coal and gas outburst as acoupling instability problem of solid-fluid biphase
media. Journal of China University of Mining &Technology, vol. 02, pp.103-107.
Zhao YS (1994) Mathematical model of coalmass and gas coupling and its numerical method,
Chin. J. Rock. Mech. & Eng., vol. 03, pp. 229-239.

590

Paper No. 124

ISMS 2016

Grey Correlation Model of influence factors analysis of ventilation timein single-way tunnel
Yang Cao*, Hongguang Ji
Department of Safety Science and Engineering, University of Science and Technology Beijing, Beijing, China, 100083

ABSTRACT
Ventilation time is an important parameter in the process of heading face ventilation. Shortening ventilation
time has great significance in improving the efficiency of tunneling work. This paper analyzes the influence
factors affecting the heading face ventilation time and establishes the grey correlation model based on theventilation time data of a -118m single-way tunnel in a golden mine. Calculations of the correlation degree
between the four influence factors are as follows: blasting fume throwing length (X0), distance of air duct totunneling face (X2), length of tunnel (X3), initial concentration of CO (X4), and evaluation of the sensitivity.
Results show that tunnel length and blasting fume throwing length are more sensitive to ventilation time of
the four influence factors, the distance from the duct to the diving face is less sensitive to ventilation time, andthe influence factor of initial concentration is the least sensitive of all. The analysis results can help create
practical and instructive effects on ventilation work in single-way tunnels.
KEYWORDS: Single-way tunnel; ventilation time; influence factors analysis; Grey correlation; correlation
degreeis needed to satisfy the requirement of ventilation
INTRODUCTION(Q means volume of ventilator, t means ventilation
Driving takes place extensively in mining,time). Practically, there are a number of influencetunnels, and underground excavation. As a way offactors and complicated interactions which cause
digging tunnels, blasting plays a major role in
the extension of ventilation. Several scholars foundunderground engineering (JI Hong-guang, 2014).
that volume of air, length of blasting fume throwing,
Hazardous gases and dust, collectively called
distance of duct to tunnel face, length of tunnel, andblasting fumes, are produced during the explosions.
original concentration of blasting fume have an
After blasting, it is necessary to ventilate in theinfluence on ventilation time (WU Li-zhong, 1959;
one-way tunneling in order to disperse the blasting
WANG Yin-min, 1993; WU Chao, 2008). In
fumes for preparation of slag removal. Ventilation
practical engineering, carrying out weighttime is defined as duration time from blasting toevaluation through introducing proper methods inwhen the toxic gas concentration is lower than theorder to analyze the sensitive degree between thestate standards to ensure the health and safety of
influence factors and ventilation time has a vitally
workers. Ventilation time not only marks the
instructive effect on ventilation in one-way tunnels.
efficiency of ventilation, but also provides aIn the past, researchers have focused on thereference for the arrangement of the tunneling cycle.
mathematical model of removal of blasting fumes
Shortening the ventilation time can enhance thein tunnels (SU Li-jun, 2000; YANG Li-xin, 2000).
work efficiency of tunneling and eliminate toxic
Accurate mathematical models have beengas poisoning accidents (YANG Zan-cheng, 2011).
established that depict the movement of blasting
Theoretically, the nature of ventilation infumes and the volume of air. The authors have paid
one-way tunnels is mixture and dilution between
less attention to the weight influence factors
fresh air and blasting fumes and drainage with aanalysis of ventilation. Although statistical methods
method of turbulent flow deformation. For a given
show priority on sensitive analysis, these methods
blasting fume volume and regulated standard
need abundant data (WANG Yang, 2004). Applying
concentration of toxic gases, fresh air volume (Q·t)
the grey correlation model to the analysis of*Corresponding author – email: wwwcaoyang@126.com

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016sensitive influence factors of ventilation time canobtain better advantages. The grey correlation
model not only can fit with less data, but it also
avoids the problem of the difference of parameter
units and magnitude (WU Ai-you, 2005). Therefore,
in this article the grey correlation model is built tocarry out weight analysis on the influence factors.

1.

INTRODUCTION
OF
CORRELATION MODELγ 0i ( k=)(5) Correlation degree:
γ=
0i

GREY

2.

2.1 System feature sequence and influence factors
sequence matrix
Select system feature sequence as X0,
influence factors as X1 、X2 …Xi showed in theformulas below.

1

0

1

1

0

1

⋅⋅⋅⋅⋅⋅=Xi( x (1) , x ( 2 ) , ⋅⋅⋅, x ( n ) , )iii

2.2 Calculation Process of Correlation Degree(1) Sequence original image:=
X i' X=i xi (1)

x (2)
x 1,
( n2,
)) n
( x (1)，，…，，=0,
'
i

'
i

GREY

Table 1: Original data of feature sequence and influence
factors sequence.

⋅⋅⋅, m'i

APPLICATIONOF
CORRELATION MODEL

3.1 Calculation steps
Take forced auxiliary ventilation in asingle-way tunnel at a golden mine as an example.
Select X1, X2, X3, X4 as the influence factors
sequence, and X0 as the feature sequence.
Ventilation monitoring tests were conducted toacquire relevant test data in single-way tunnel after
blasting according to the practicality.
X1 stands for length of blasting fume throwing, m;
X2 stands for distance of duct to working face, m;
X3 stands for length of tunnel, here is instead of the
distance of test point to working face, m;
X4 stands for original concentration of blasting
fume, ppm;
X0 stands for ventilation time, min.

( x (1) , x ( 2 ) , ⋅⋅⋅, x ( n ) , )=X( x (1) , x ( 2 ) , ⋅⋅⋅, x ( n ) , )01 n=i 1, 2 ⋅⋅⋅ m .
∑ γ 0i ( k )，，n k =1

Correlation degree is the metric that weights
the correlation extent between the influence factor
and feature sequence. Its value ranging interval is[0,1]. The closer to 1 the correlation degree is, thehigher the influence on the feature sequence thefactors have; On the contrary, the closer to 0 thecorrelation degree is, the lower the influence on thefeature sequence the factors have.

The grey correlation model is established via
three steps as follows: Firstly, confirm the system
feature sequence and influence factors sequence;
Secondly, obtain the correlation degree by
calculating the influence factors sequence; Thirdly,
perform a correlation analysis according tocorrelation degree (LIU Si-feng, 2013).

=
X0

m + 0.5Μ
，=1,k 2,；，⋅⋅⋅ n =
i 1, 2 ⋅⋅⋅ m∆ i ( k ) + 0.5Μ

Sample

X0

X1

X2

X3

X4

(2) Difference value of sequence:

ID

(min)

(m)

(m)

(m)

(ppm)

∆i (k ) = x0' (k ) − xi' (k ) ，，，，∆i = ( ∆i (1) ∆i (2) ⋅⋅⋅ ∆i (n) ) i = 1,2, ⋅⋅⋅, m

1

82

21.4

20

48

3693779.3

2

70

20.6

23

53

859406.7

3

150

15.8

12

42

1648480.3

4

176

19.8

14

36

1443225.6

5

105

21

18

38

1629622.8

6

186

22.2

17

50

6289709.5(3) Maximum and minimum differences:M=
max max ∆ i ( k )， m= min min ∆ i ( k )
i

i

k

k

(4) For ξ∈(0,1)
kx k + ξmaxmax x k
x k
minmin x（）-（）（）-（）x（）-（）（）-（）
kx k + ξmaxmax x k
x k

7

50

18.2

10

31

508339.4

i

8

54

20.6

19

35

491464.1

When ξ=0.5, the formula can be transformed as

9

81

19.8

24

40

443655.8γ ( x（），（）
xi k ) =
0 k

0

i

i

0

k

0

i

i

0

i

i

k

k

follows:592

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
(1) Calculation of sequence original image:'=
X i' X=xi' (2)
xi' 1,( n2,) ) n
i xi (1) ( xi (1)，，…，，=0,⋅⋅⋅,9

1 0.854 1.829 2.146 1.281 2.268 0.610 0.659 0.988 
1 0.963 0.738 0.925 0.981 1.037 0.851 0.963 0.925 TX ' = ( X 0' , X 1' , X 2' , X 3' , X 4' ) = 1 1.150 0.600 0.700 0.900 0.850 0.500 0.950 1.200 
1 1.104 0.875 0.750 0.791 1.041 0.646 0.729 0.833 
1 0.233 0.446 0.391 0.441 1.703 0.137 0.133 0.120 (2) Calculation of differences of sequence:
 0 0.109 1.091 1.221 0.299 1.231 0.241 0.304 0.626 
0 0.296 1.229 1.446 0.381 1.418 0.110 0.291 0.212 ∆i = ( ∆1 , ∆ 2 , ∆3 , ∆ 4 ) = 
 0 0.251 0.954 1.396 0.489 1.227 0.036 0.071 0.155  0 0.621 1.383 1.756 0.839 0.566 0.472 0.526 0.868 Tmodel, shortening the length of tunnel (X3) shouldbe the most effective. However, this is not practical.
Therefore, lessening the length of blasting fume
throwing (X1) is another good way to shorten
ventilation time. Limited explosives should be usedin every explosion to decrease the original
concentration of blasting fumes. Because thecorrelation degrees of these influence factors show
big relativity to ventilation time, enhancing one orseveral factors can effectively shorten theventilation time.

3.

CONCLUSION

The grey correlation model has better effects
ontheweight analysis of influence factors to(3) Calculation of maximum and minimum
ventilation
time. Through making use of the grey
differences:
correlation model, the qualitative analysis can be=
M max max ∆ i (=k ) 1.756
expressed in quantitative results, clarifying theikmajor and minor influence factors for ventilation
time. This provides rewarding instruction andm= min min ∆ i ( k ) =0ikreference to ventilation management during theprocess of tunneling.
(4) Calculation of correlation coefficient:
The grey correlation model was applied tom + 0.5Μ
0.878
analyzeseveral independent influence factors.
=
γ 0i ( k )==，=1, 2,；k⋅⋅⋅ 9 i 1, 2,3, 4∆ i ( k ) + 0.5Μ ∆ i ( k ) + 0.878
Therefore, the selection of influence factors and theuse of data sequences has some influence on the
Then the corresponding grey correlation matrix is:
accuracy and reasonability of the results of the1 0.890 0.446 0.418 0.746 0.416 0.785 0.743 0.935 model evaluation.

1 0.748 0.417 0.378 0.698 0.382 0.889 0.751 0.805 
R0i = The ventilation system in the tunnel can be1 0.778 0.479 0.386 0.642 0.417 0.961 0.926 0.850 


equal
to forcing auxiliary ventilation with a1 0.586 0.388 0.333 0.511 0.608 0.650 0.626 0.503 
constant air volume. As another influence factor,(5) Calculation of grey correlation degrees:
the extent of air volume to ventilation time has
important value in research. For exhausted
1 nγ==
i 1, 2,3, 4 =k 1, 2, ⋅⋅⋅,9∑ γ 0i ( k )，；0i
ventilation and combined ventilation, whether andn k =1
how much the influence factors above are related to—ventilation time remains to be researched and
R0i = ( γ 01 , γ 02 , γ 03 , γ 04 ) =( 0.709, 0.674, 0.715, 0.578)
confirmed.
3.2 Results analysis and practical application
4. ACKNOWLEDGEMENT
Results were acquired through the greyFirst and foremost, I would like to show mycorrelation model. The correlation degrees of the
deepest gratitude to my supervisor, Dr. Ji
four influence factors (X1, X2, X3, X4) are 0.709,
Hongguang. He is respectable, responsible and0.674, 0.715, and 0.578. The length of the tunnel
resourceful scholar who provided me with valuable(X3) shows the maximum influence on ventilation;
guidance in every stage of writing of this paper.
the second influence factor is the length of blasting
When establishing the index system, calculating thefume throwing (X1); the third influence factor is thenumerous indexes, he put forward the valuable
distance from the duct to the working face (X2); thecomments for the selection of the index andoriginal concentration of blasting fume (X4) has thecalculation method. I shall also extend my thanks tominimum influence on ventilation time.
my scientific research team for their kindness andIn order to shorten the ventilation time inhelp. Finally I wish a great success of ISMS 2016.
single-way tunnels, the most effective approach is
to improve the influence factor which has the
maximum influence on ventilation time. According
5. REFERENCE
to the results calculated through the grey correlation
JI Hong-guang, CAO Yang, ZHANG Ge

593

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016(2014). Study on prediction of drain-fume time ofsingle-end roadway in tunneling process. Metal
Mining, Volume 5, No 254, pp. 142-145.
LIU Si-feng, XIE Nai-ming(2013). Grey
System Theory and Its Aapplication. Science
Press,167p.
SU Li-jun, LU Wen-bo(2000). Techniqueduring construction of underground tunnel.
Blasting. Volume 17, No1, pp.1-6.
WANG Yin-min(1993). Ventilation andDust-prevention in Mine. Metallurgical industry
press, 45p.
WANG
Yang,
YIN
Kun-long,An
Guan-feng(2004). Landslide sensitive influence
factors of grey correlation analysis. Rock and Soil
Mechanics, Volume25, No1, pp.91-93.
WU
Li-zhong(1959).
Ventilation
insingle-way tunnel after blasting. MetallurgicalIndustry Press,46p.
WU
Ai-you,XIAO
Hong-fei(2005).
Establishment and application of weights and grey
association model based on coal and gas outburst
controlled influence factors assessment. Journal of
Coal China Society, Volume 30, No1, pp.58-62.
WU Chao(2008). Mine Ventilation andAir-condition. ZhongNan University press,26p.
YANG Zan-cheng, YANG Peng, LV
Wen-sheng,(2011). Numerical simulation on
diffusion law of blasting fume during roadwaytunnel across a vein in an alpine mine. Journal of
University of Science and Technology Beijing.
Volume33, No5, pp. 521-525.
YANG Li-xin, LU Mao-cheng, ZHAO
Jun-xi(2000).
Discussion
onventilation
smoke-drain calculation in tunnel construction after
blasting. West-China Exploration Engineering,
Volume23, No1, pp.55-57.

594

ISMS 2016

Paper No. 133
Numerical research on the airflow distribution in mine tunnels
Cui DING a,*, Xueqiu HEb,c, Baisheng NIE ca

Department of Safety Engineering, China Institute of Iindustrial Relations, Beijing,China, 100048
School of Civil and Environment Engineering, University of Science and Technology Beijing, Beijing, China, 100083
cSchool of Resource &SafetyEngineering, China University Mining &Technology(Beijing), Beijing, China,100083b

ABSTRACT
Based on 3D modelling of typical tunnels in mines, the air flow structure in the three hearts arch-section tunnel wasinvestigated and the influence of air velocity and cross section on air flow distribution in tunnels was studied. The
average velocity points were analyzed quantitatively. The results showed that the feature of the air flow is similar
with the shape of the three hearts arch-section under different ventilation velocities and cross section areas. The
shape of the tunnel cross section and wall were the critical factors influencing the air flow structure. The averagevelocity points were mainly close to the tunnel wall. Characteristic equations were developed to describe theaverage velocity distribution, and provide the theoretical basis for accurately measuring the average velocity in minetunnels.
KEYWORDS: mine tunnel; turbulence; air flow structure; three hearts arch; average velocity

1. INTRODUCTION
Mine ventilation is the process of continually
inputting fresh air and outputting polluted air. The
ventilation system is the basic system in mines. It isestimated that many mine disasters, including fire,coal gas, and dust explosions occur as a result of
failures of the mine ventilation system.
Nowadays, the air flow velocity and volume intunnels are detected by on-line monitoring systems.
However, because of the non-uniform distribution of
air flow, the velocity measured by sensors is not the
average velocity in each section. As such, it isnecessary to study the air flow structure, especiallythe average velocity distribution, so as to calculate
the air flow volume accurately. At present, the air
flow distribution in cross-sections is macroscopicallydescribed with numerical simulation in several
studies (Parra et al., 2006; Chen and Yu, 2008; Jia,
2011; Hao et al., 2011). Only a few havequantitatively studied the average velocity
distribution in circular and rectangular tunnels, by
experimental and theoretical methods (Ma et al.,2007; Yin et al., 2008; Zhou et al., 2012; Wang et al.,2013; Tan et al., 2013; Zhao et al., 2014). However,
the relations among the air flow structure, the averagevelocity, and the cross-section shape and sizes havenot been developed and described successfully. The
characteristic equations of the average velocity
distribution close to the roof have been developed in
the three hearts arch-section tunnels and trapezoidal
cross section tunnels (Ding et al., 2015; Ding, 2016).
The other areas of the average velocity distribution
on three hearts arch-sections were not developed*Corresponding author--email:cui_ding@163.com

quantitatively. This study aims to present the air flow
distribution and develop the characteristic equationsof the average velocity distribution in three hearts
arch-section tunnels.

2. NUMERICAL SIMULATION
2.1 The physical model of the tunnel
Ding et al. adopted the numerical analysis
method to simulate the air flow distribution in threehearts arch-section tunnels and testified on theaccuracy of the numerical analysis method. In thispaper, the tunnel length is 8 m, the width is 260 mm,
and wall height is 113 mm. The small arch radius is
66 mm, and the large arch radius is 183 mm, as
shown in Figure 1.

Figure 1: The physical model of the tunnel.

In order to analyze the air flow structure intunnels quantitatively, the model in Figure 1 wasamplified by 2 times, 3 times, 4 times, and 5 times.
The sizes of the five three hearts arch-section tunnels
are shown in Table 1. The air flow in the tunnels was
set to be turbulent, which was similar to the actual
ventilation conditions. The air flow distribution was

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 1: The sizes of the five three hearts arch tunnels .
Tunnelnumber
1
2
3
4
5

large
archradius(mm)
183
366
549
732
915

Smallarchradius(mm)
66
132
198
264
330

then studied under different air flow velocities anddifferent tunnel sizes.
2.2 Mathematical model and sssumptions
According to the fluid dynamics theory, the air
flow in tunnels can be described by using thefollowing equations.
The continuity equation:∂ρ ∂�ρuj �
+
=0
∂t
∂xj
The momentum equations(i direction):∂uj∂(ρui ) ∂�uj ui �
∂
+
=
�μ
�
∂xj
∂t
∂xj
∂xj
The energy equation:∂(ρh) ∂�ρuj h�
∂h
∂
−
=
�Γ
�
∂t
∂xj
∂xj h ∂xj

The standard k-ε model was used to calculate
the turbulence and diffusion of the air flow.
k equation:∂∂�ρk� +
�ρkui �
∂t
∂xi
=

μ ∂k
∂
��μ + t � � + Gk − ρε
∂xj
σ ∂xj
k

− YM

ε equation:∂∂�ρε� +
�ρεui �∂t∂xi=

μ ∂ε ⎤ε∂ ⎡⎢⎛μ + t ⎞ ⎥ + C
G
1ε k k∂xj ⎢σ ∂xj ⎥
ε⎠
⎣⎝
⎦

−C ρ

2

ε

k
In these equations, Gk represents thegeneration of turbulence kinetic energy due
to the mean velocity gradients, Gk =�����́ ∂uj . YM represents the contribution of−ρuı ú ȷ
2ε∂xi

the fluctuating dilatation in compressible
turbulence to the overall dissipation

Tunnel parameters
width(mm)Wall height(mm)length(m)

260
520
780
1040
1300

113
226
339
452
565

8
16
24
32
40

rate, YM = 2ρεMt2 . μ represents the turbulent
viscosity, μ = ρC
t

C

1ε

, C

1.44 , C

2ε

2ε

k2

μ ε

t

.

and C

μ

are

constants. C= 1.92 , C = 0.09 . σ
μ

k

and σ

ε

1ε

=

are

the turbulent Prandtl numbers for k and ε,respectively. σ = 1.0, σ = 1.3.
kε

ρ represents the density, kg/m3. u represents thevelocity, m/s. k represents the turbulence kinetic

energy, kJ/kg. ε represents the turbulencekinetic

energydissipation

rate,

m2/s3.

μrepresents the molecular (dynamic) viscosity, Pa·s. t
represents the time, s. h represents the static enthalpy,k. Γ

hrepresents the transport coefficient.

When developing the mathematical model, thefollowing assumptions were made: the air flow wasincompressible; the wall was adiabatic; there were noworkers and vehicles in the tunnels, and the presenceof smoke and dust were ignored.
2.3 Boundary Conditions and Parameters
The tunnel inlet was set to be the velocity-inlet
and the air flow velocity was set to 1m/s, 2m/s, 3m/s,
4m/s and 5m/s respectively. The tunnel outlet was set
to be the pressure-outlet and the relative pressure was
0 Pa. The air flow distribution in the three hearts
arch-section tunnels of five sizes were simulated
under the different air flow velocities.

3. ANALYSIS OF THE AIR
STRUCTURE IN TUNNELS

FLOW

The air flow distribution on fully developed
turbulence cross sections were studied. In this paper,the distance between the cross sections analyzed andthe tunnel inlet was set according to fluid mechanics
theory, and the distance between the analyzed crosssections and the tunnel inlet was 5.6 m (Z1), 11.2 m(Z2), 16.8 m (Z3), 22.4 m (Z4), 28 m (Z5),596

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

respectively. The velocity profiles on the above fivecross sections (Z1, Z2, Z3, Z4, Z5) were analyzed asshown in Figure 2.

1m/s
5m/s
The first three hearts arch-section tunnel

air flow velocity reached its maximum value in thecenter of the tunnel and decreased from the center tothe tunnel wall. The average velocity points weremainly close to the tunnel wall under different air
flow velocities and the air flow velocity which was
smaller than the average velocity would decrease
more quickly when it was closer to the tunnel wall.
According to the above analysis, the tunnel wall was
also a critical factor influencing the air flow
distribution.
4.

1m/s
5m/s
The second three hearts arch-section tunnel

ANALYSIS OF AVERAGE VELOCITY
DISTRIBUTION

The average velocity points are critical toachieving an accurate measurement and monitoringof ventilation volumes in tunnels. According to Ding
(Ding et al., 2015), the distribution of the averagevelocity points in any three hearts arch-section tunnelshows as an annular ring and the ventilation velocity
has little influence on the above distribution feature.
In order to further analyze the distribution of theaverage velocity points and develop its characteristic
equations, the distribution curve has been separated
into six parts as shown in Figure 3.
0.35
0.30

1m/s
5m/s
The third three hearts arch-section tunnel

1

y/m

0.25
0.20

6

2

0.15

5

0.10

3
4

0.05
0.00
0.0

0.1

0.2

0.3

0.4

0.5

x/m

1m/s
5m/s
The fourth three hearts arch-section tunnel

Figure 3: The average distribution curve on three heartsarch cross-section.

According to Ding (Ding et al., 2015), thecharacteristic equation of the first part can be
described by equation 1-1, and in this paper, thecharacteristic equations of the other five parts aredeveloped.
2

1m/s
5m/s
The fifth three hearts arch-section tunnel
Figure 2: Velocity profiles on fully developed turbulence
sections in five tunnels.

It can be concluded from Figure 2 that the air
flow structure showed a circular distribution which
was similar to the shape of three hearts arch-section
under different ventilation velocities and crosssection sizes. The shape of the cross section was thecritical factor influencing the air flow structure. The

d
−2 
−1.84
( y − 0.6142r1 + 0.0138)2 = 1
3.2819r1  x −  + 8.408r1
2


（1-1）

r1 —— radius of the top circular arc, m；d ——width of the tunnel, m。
As shown in Figure 3, the curve is symmetrical,so the feature of the fourth, fifth, and sixth parts will
be analyzed quantitatively.
(1) The fourth part
Based on an analysis of relationships between
the length of the fourth part curve, the tunnel size andthe distance between the curve and the tunnel floor, it597

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

0.35
0.30
0.25

y/m

has been found that the length of the fourth part curve
and the distance between the curve and the tunnel
floor had perfect linear relations with the width of thetunnel as shown in Figures 4 and 5, respectively.

0.20
0.15
0.10

-1.0152y = 0.037x
2

R = 0.9658

0.05
0.00
0.00

0.10

0.20

0.30

0.40

x/m

The fifth three hearts arch-section tunnel
Figure 6: Part 5 curve fitting diagram of three hearts
arch-sections in five tunnels.
Figure 4: Relationshipbetween the distance fromthe bottom edge to part4
and the length ofbottom .edge

Figure 5: Relationshipbetween the length of part4
and the length of the bottom
edge

Based on the above analysis, the characteristic
equations of the fourth part can be described as
equations 1-2 and 1-3.

d1 = 0.085d − 0.0034
d 2 = 0.5324d − 0.0728（1-2）

By combining the above five equations and thewidth of different tunnels, the five equations can benormalized into one equation, equation 1-4.

y = 0.0236d 1.965 x −1

（1-4）

d ——width of the tunnel, m；
x ——x-coordinate,m,x ∈ [ 0.2219h − 0.0014 ，0.2338d + 0.0364 ]y —— y-coordinate, m。

（1-3）

d ——width of the tunnel, m；
d1 —— distance between the fourth part curve
and the tunnel floor, m；

d 2 ——length of the fourth part curve, m。

(3)The sixth part
The feature of the sixth part has been studied
using the above method. The length of the curve andthe distance between the curve and the leftwall have aperfect linear relation with the height of the tunnel
wall, as shown in Figures 7 and 8.

(2) The fifth part
Numerical fitting methods have been used todevelop the characteristic equations of the fifth partas shown in Figure 6.
0.07

0.16
0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00

0.06
0.04

y/m

y/m

0.05
0.03

y = 0.0016x-1.0122

0.02

2

R = 0.9746

0.01
0
0

0.02

0.04

0.06

-0.9965

y = 0.0067x
2

R = 0.9703

0.00

0.08

Figure 7: Relationshipbetween the distance frompart6 to the left edge and theheight of the wall.

0.05

0.10

The first three hearts archsection tunnel

The second three hearts
arch-section tunnel
0.30

0.25

0.25

-0.9539y = 0.016x

0.10

R = 0.9682

0.05-0.9862y = 0.0251x
2

0.05

0.00
0.00

0.15

2

0.10

0.15

0.20

0.25

x/m

The third three hearts archsection tunnel

0.00
0.00

R = 0.9616

0.05

0.10

Based on the above analysis, the characteristic
equations of the sixth part can be represented byequations 1-5 and 1-6.

h1 = 0.2219h − 0.0014
h2 = 0.4879h − 0.0183

0.20

0.15

y/m

y/m

0.20

0.05

0.20

x/m

x/m

0.10

0.15

Figure 8: Relationshipbetween the length of part 6
and the height of the wall.

0.15

0.20

0.25

x/m

The forth three hearts
arch-section tunnel

0.30

（1-5）
（1-6）

h ——height of the tunnel wall, m;h1 ——distance between the sixth part curve
and the leftwall, m;h2 ——length of the curve, m。
Based on the above analysis, the characteristic
equations of all the six parts have been developed asshown in Table 2.

598

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Table 2: Characteristic equations of three hearts arch-section tunnel.
SerialCharacteristic equations
number
2

1
2

d
−2 
−1.84
2
3.2819r1  x −  + 8.408r1 ( y − 0.6142r1 + 0.0138) = 12
x = d − 0.2219h + 0.0014(d − x )−1

3

f ( x) = 0.0236d

4f ( x) = 0.085d − 0.0034

5f ( x) = 0.0236d

6x = 0.2219h − 0.0014

1.965

1.965

x

−1

5. CONCLUSIONSIn order to understand the air flow distribution
in tunnels and measure the average velocity andventilation volume accurately, the air flow structure
and the average velocity points in different sizes ofthree hearts arch-section tunnels were investigated.
The conclusions were as follows:
1) The air flow structure showed a circular
distribution which was similar to the shape of threehearts arch-section under different ventilation
velocities and cross section sizes. The shape of thecross section was the critical factor influencing the
air flow distribution. The air flow velocity reached its
maximum value in the center of the tunnel anddecreased from the center to the tunnel wall.
2) The average velocity points were mainly
close to the tunnel wall under different air flow
velocities and the air flow velocity which was smaller
than the average velocity would decrease more
quickly when it was closer to the tunnel wall. The
tunnel wall was also a critical factor influencing the
air flow distribution.
3) Characteristic equations were developed todescribe the average velocity distribution, which
provide the theoretical basis for accurately measuring
the average velocity and ventilation volume in minetunnels.

6.

ACKNOWLEDGEMENT

This research has been funded by the central
university basic business expenses(15zy012)

7.

span of the parameters

REFERENCES

Chen W,Yu X.(2008) Wind flow field
simulation on wind pink piping basing on
FLUENT.Jiangsu Electrical Engineering, Volume 27,
No.6, pp.72-75.
Ding C, He X, Nie B. (2015)Numerical andexperimental research on “key ring” distribution ofventilation in mine tunnels. Journal of Liaoning
Technical University （ Natural
Volume34, No. 10, pp.1131-1136

Science ） ,y ≥ 0.9932h − 0.0087
y ∈ [0.5053h + 0.0096,0.9932h − 0.0087]

x ∈ (0.7662d − 0.0364, d − 0.2219h + 0.0014)

x ∈ [0.2338d + 0.0364,0.7662d − 0.0364]

x ∈ (0.2219h − 0.0014,0.2338d + 0.0364 )y ∈ [0.5053h + 0.0096,0.9932h − 0.0087]
Ding C. (2016) Numerical and experimental
research on the average velocity distribution in the
trapezoid tunnels. Journal of Safety Science andTechnology, Volume12, No. 1.
Hao Y, Chen K, Jiang Z et al. (2011) Study on
Amendment of AirflowVelocity in Roadway Basedon CFD.Safety in Coal Mines, Volume42, No. 2, pp.
1-4.
Jia J. (2011) Simulation analysis on mine windmonitoring .Coal,Volume 20, No.12, pp. 73-74.
MA Y, Dong B, Zhang X et al. (2007)Study on
Vent Mean Wind Velocity Measuring of Solar
Collecting Wall in Solar House. Building
Energy&Enviroment,Volume26, No. 4, pp. 60-63.
M.T. Parra, J.M. Villafruela, F. Castro, C. Me′
ndez. (2006)Numerical and experimental analysis ofdifferent ventilation systems in deep mines. Building
and Environment, Volume 41, pp. 87-93.
Tan X, Wang Z, Zhao Y. et al. (2013)Study on
Velocity Profile of Turbulent Fluid in Narrow DeepType Rectangular Channel.Journal of Sichuan
University(Engineering Science Edition), Volume45,
No. 6, pp.67-73.
Wang B, Luo Y, Zhao Y. (2013) Wind Tunnel
Simulation
on
Wind
Speed
Distribution
Characteristic in Rectangle Roadway Section Laid
With Conveyor.Safety in Coal Mines, Volume44,
No. 5, pp. 42-45.
Yin J, Lv H, Luan W. et al. (2008)Experimental
research on velocity distribution law of trapezoidal
channel section.Yangtze River, Volume39, No. 12,
pp. 67-69.
Zhao D, Huang F, Chen S.et al. (2014)
Relationship between point air velocity and average
air velocity in circular roadway. Journal of Liaoning
Technical University(Natural Science), Volume33,
No. 12, pp.1654-1659.
Zhou X, Meng L,LI C.et al. (2012)Experimental
study on determination and correction method ofwind speed in circular pipe .Journal of Liaoning
Technical University: Natural Science, Volume31,
No. 6, pp. 801-804.

599

ISMS 2016

Paper No. 163

Application of a Ventilation Management Program for improved air quality
Euler De Souza*
Department of Mining Engineering, Queen’s University, Kingston, Canada, K7L3N6ABSTRACTThe purpose of Ventilation Management Systems is to ensure the health and safety of underground workers bycreating and incorporating structured Plans, Procedures and Processes on the day-to-day operations of the mine
ventilation system. Application of Ventilation Management Programs consists of audit, verification and corrective
action procedures used to, i) ensure adherence to regulatory standards or to ii) return to compliance and safety
standards when an upset condition arises. The present study describes how a Ventilation Management Program canbe developed and implemented to ensure regulation compliance, to increase safety, to improve operational
efficiency and to reduce the operating costs of an operating mine. A case study is presented in which air quality
conditions have been substantially improved with the development and implementation of a Ventilation
Management Program for an operating underground hard rock mine.
KEYWORDS: mine ventilation; ventilation management; air quality; ventilation efficiency
1.

INTRODUCTION
Mine ventilation systems must not only provide
for the health and safety of underground personnel,
but also operate in compliance with regulatory
bodies. Studious day-to-day management of the mine
ventilation system is crucial to meet all the objectivesof the ventilation system. A Ventilation Management
System is used to provide, measure, and control thequantity and quality of airflow throughout the mine
ventilation network.
The Ventilation Management System consists ofa series of documents describing means of auditing
and controlling the mine ventilation system in orderto ensure the system meets all regulatory and safety
requirements.
Five main document types form the structure of a
Ventilation Management System: Standards andGuidelines, Code of Practice, Procedures, Work
Instructions and Directives (Figure 1). These
documents provide guidelines for applying audit,
verification and correction processes used to ensure
the mine ventilation system operates withincompliance standards.
The Standards and Guidelines constitute thefoundation of the management program.
This
support documentation is a handbook providing adetailed description of the ventilation system,
including all design and operational aspects of theventilation network. The Code of Practice isdocumentation that defines the minimum operating
standards and action levels based on regulatory
bodies, and provides appropriate corrective andemergency action plans when an upset condition*Corresponding author – email:: Euler.desouza@queensu.ca

exists. Procedures is documentation that explainsinter-departmental activities and each department's orindividual's role in specific work procedures. Work
Instructions is documentation describing the processof a specific procedure and task; including who is
involved, how to do the task, and what materials or
supporting documentation is needed. Directives is
documentation issued for any changes to theventilation that will ensure the correct installation orchange to any design, equipment or condition.

2. EXECUTION OF A VENTILATIONMANAGEMENT PROGRAM
Execution of a Ventilation Management Program
follows an iterative process, as illustrated in Figure 2.
Management Plans, which are carried out on adaily basis, are an audit of the state of the entire mine
ventilation system. They include detailed inspectionsof all components and appliances, pressure and flow
surveys of the network and air quality surveys.
Verification Programs are used to assess theinformation collected from the management plans inorder to verify if the ventilation system is incompliance and if it meets all defined objectives ofthe program. If the verification process indicates thesystem not to be in compliance, then action plans andventilation directives are initiated to restore thesystem to compliance. Action Plans andcorresponding directives can also be directly
launched in response to upset ventilation conditions
or when problems are encountered during aninspection.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

STANDARDSAND GUIDELINESCODES OF PRACTICE

PROCEDURESWORK INSTRUCTIONSDIRECTIVES

Figure 1: Typical structure of a Ventilation
Management System.
UPSET CONDITION

MANAGEMENT PLANS

VERIFICATION PROGRAMSREGULATORYCOMPLIANCE

yes

VENTILATIONCOMPLIANCE?

noACTION PLANS

VENTILATIONDIRECTIVES
VERIFICATION OFCOMPLETION

Figure 2: Execution process of a Ventilation
Management Program.

3. OPPORTUNITIES AND BENEFITSThe easy to implement iterative framework of a
Ventilation Management Program (Figure 2) allows
mining operations to efficiently and consistently
audit the mine ventilation system.
Significant benefits can be gained from day-to
day management of the mine ventilation system. It
ensures: that the ventilation system performs
according to design; that all ventilation appliances
operate efficiently and economically; an adequate air
supply to all active workings; that the mine
atmosphere meets quality conditions; compliancewith all regulatory requirements; safety; improved
system economics.

4. CASE STUDY
A case study is presented in which air quality
conditions have been substantially improved with thedevelopment and implementation of a Ventilation
Management Program for an operating undergroundhard rock mine.
A two-phase integration approach of theManagement Program was successfully completed
for the mine. The first phase involved regional
leakage control, resulting in an increase in airflow
volume in the main production blocks by 28% andthe second phase involved improvements in local
ventilation installations in the main production levels,
resulting in substantial improvements in undergroundenvironment conditions (air quality, dust and heat).
This permitted uninterrupted production with much
improved safety, reduced re-entry times and lower
costs.
The underground mine applies sublevel stopingwith backfill to mine gold at a rate of 900 tonnes perday. Mining activities exist at the lower levels of themine (below 1030 level) with 7 upper levels being
mined out. Overall underground flow requirements at
the underground production blocks approximate 118
m3/s, determined from the production rate andoperating diesel fleet. The mine utilizes a pushsystem with a primary surface air fan installed on a
dedicated fresh air raise. Figure 3A presents a
distribution of mine flows through the dedicated fresh
air raise prior to application of the Management
Program.
A detailed ventilation audit was conducted toassess the primary fresh air system prior to
implementation of the first phase Ventilation
Management Program.
Over the years, prior to application of theVentilation Management Program, the mine had tolimit use of its available diesel fleet and also had tocurtail development and production activities due tolimitations in fresh air supply to the active levels(available 94 m3/s versus required of 118 m3/s) andalso had to limit stope blasting and mucking cycles
due to excess concentrations of NO2 (well above thelimit of 3 ppm).
The fresh air system consisted of a surface fresh
air fan of 2.13 m casing diameter and 1.27 m hub
diameter. It had a 597 kW motor installed, operating
at 1200 rpm. The fan was delivering 142 m3/s at a
static pressure of 1.84 kPa. The brake power was 539
kW and the annual operating cost was $377,650. The
fan operating point is shown in Figure 4. With the fandelivering 142 m3/s, the flow reaching the activemining area was 94 m3/s; leakage was estimated at
33.6% (Figure 3A). As previously mentioned,
leakage occurred at raise connections to 7 mined out
levels, above the active mining levels.
As part of the Ventilation Management Program
execution, extensive work was conducted to reduceleakage by sealing off and shotcreting all bulkheaded
raise connections to the 7 upper inactive levels.
Leakage was reduced to 7.2% from 33.6% (Figure3.B) Where level access was required, appropriate
door locks were installed. With the sealing off of theraise connections, the surface fan was now delivering
130 m3/s at a static pressure of 2.38 kPa (Figure 4).

601

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3.A - Flow Distribution Before Leakage Control

3.B - Flow Distribution After Leakage Control
129.79 m3 /s

141.58 m3 /ssurfacesurface3

80 level 10.11 m3 /s

80 level 1.49 m /s
121.90 m3 /s

3280 level 8.86 m /s
113.04 m3 /s

3480 level 5.25 m /s
107.79 m3 /s

3630 level 5.07 m /s
102.72 m3 /s

3780 level 4.49 m /s

3

126.55 m /s

3

280 level 1.02 m /s
3

125.53 m /s

3

480 level 0.97 m /s
3

124.57 m /s

3630 level 0.85 m /s
3

123.72 m /s

3780 level 1.74 m /s
3

98.24 m 3/s

3

128.30 m /s

3

130 level 1.75 m /s

Mined-Out Levels

130 level 9.57 m3 /s

Mined-Out Levels

3

131.47 m3 /s

121.98 m /s

31030 level 4.22 m /s

1030 level 1.56 m /s
94.02 m 3/s

lower active levels 94.02 m 3/s

120.42 m 3/s

lower active levels 120.42m3 /s
3leakage = 47.57 m 3/s - 33.6%

leakage = 9.36 m /s - 7.2%

Figure 3: Mine ventilation schematic.
5

Static Pressure (kPa)

3.7

75%

80%

70%

84%

2.5

after

65%

before
1.3

o

o

12

0
0

47.2

o

22o

17
94.4

27

141.6

o

32

o

37

188.8

o

42
236

283.2

3

Volume (m /s)

Figure 4: Main fan operation before and after leakage control.
The brake power was 502 kW and the annual
operating cost per fan was $352,018. With the fan
now delivering 130 m3/s, the flow reaching the activemining area was maintained at 121 m3/s, above theproduction based requirements of 118 m3/s. Leakage
was estimated at 7.2%.
The reduction in air leakage to 7.2% from 33.6%
permitted an overall annual savings in fan operating
cost of $25,630 or a 7% reduction in operating costs.
Even though the reduction in fan operating costs is

relatively small, the operation now meets the flow
requirements at all active levels, being able to safely
achieve and maintain full production activities.
Having successfully improved the mine overall
flow conditions, the second phase of system
implementation was initiated. This Ventilation
Management Program phase aimed at improving
safety and air quality conditions in all producing
faces.

602

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

First, a quality assessment of ventilation
installations and airflows in all production stopeaccess drawpoints was performed. To meetproduction requirements, 10 active faces wereventilated at the mine. All access crosscuts to thesublevel stopes were ventilated with auxiliary
ventilation. Face ventilation requires a flow of 9 m3/s
per cross-cut, based on the production equipment
utilized. Flow surveys at all active faces indicatedflows ranging between 5 m3/s and 7.4 m3/s, with 3
faces meeting the minimum flow requirements. The
auxiliary fans are 1.22 m in diameter with 0.69 mhubs, operating with 22.4 kW motors and running at
880 rpm. Layflat duct of same diameter are utilized.
Detailed inspections and surveys of the 10 duct
installations classified the installation practices as‘poor’, with much higher than desired static pressure
losses along each duct column. Some fans were notcorrectly hung and duct-to-fan connections were very
leaky. Several of the duct columns were not installedstraight and had severely damaged sections.
The fan operating point for one of the surveys ispresented in Figure 5. The system produced 7.4 m3/s
at the face with the fan operating at 17 m3/s. Leakage
was estimated at 57%. The fan total pressure was
0.72 kPa and the brake power 15.4 kW. The fanannual operating cost was $11,943. High diesel
exhaust gas concentrations were measured at thefaces due to insufficient dilution ventilation air
volumes.

0.87

0.75
75%

before82%
80%

Total Pressure (kPa)

0.62

70%
65%

after
0.50

60%

50%

0.37

0.25

0.12

10o

0
0

4.72

9.44

o

15

o

20

14.16
18.88
Volume (m3 /s)

25o

o

30

23.6

35o

28.32

o

40

33.04

Figure 5: Auxiliary fan operation before and after system installation improvement.
The auxiliary system installation was improved(duct column repaired, column straightened,
connections tightened, etc.) to reduce resistancepressures and minimize leakage. The fan blade pitch
angle was changed from 30° to 20°. The systemproduced 9.44 m3/s at the face with the fan operating

at 12.75 m3/s (Figure 5). Leakage was estimated at
26%, a reduction of more than half the original
leakage. The fan total pressure was 0.52 kPa and thebrake power decreased to 8.77 kW. The annual
operating cost for the single fan was reduced to$6,822, representing a reduction in cost by 43%.

603

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Having now achieved the required flow at the
production face the mine could operate safely and in
regulatory compliance.
Following this successful application of theVentilation Management Program, all additional 9
drawpoint auxiliary fan installations were similarly
investigated and improved, with annual savings in
fan operating costs approximating $93,000,
representing a 58% reduction in operating costs.
The successful application of the 2-phase
Ventilation Management Program resulted in overall
annual cost savings of $118,650 for the mine. More
importantly, the mine was now operating safely andin compliance with regulations.
The mine continues to incorporate theManagement Program in its day-to-day production
operations, resulting in increased safety, improved air
quality, reduced post blast re-entry times, regulatorycompliance and cost savings.

5. CONCLUSIONSThe structure and process implementation of a
Ventilation Management Program have beenpresented in this paper.
Day-to-day application of the Ventilation
Management Program ensures the mine operation
meets all regulatory requirements and cares for thehealth and safety of all personnel working
underground.
A case study for an operating underground hardrock mine has been presented to demonstrate thefunctionality of the management program and thesafety, efficiency and economic benefits realized by
the mine.

6.

REFERENCES

De Souza, E. (2015) Mine Ventilation System
Management. Section 19. Mine Ventilation Course
Notes. Kingston, ON. 16p.

604

ISMS 2016

Paper No. 178

Numerical Study of simultaneous methane and coal dust dispersion in a roomand pillar mining face
Yueze Lu a, Saad Akhtar a, Agus P. Sasmito a,*, Jundika C. Kurnia ba

Department of Mining and Materials Engineering, McGill University, Montreal, Canada H3A0E8
Department of Mechanical Engineering, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak Darul Ridzuan,
Malaysiab

ABSTRACTIn underground coal mines, uncontrolled accumulation of methane and fine coal dust often leads to serious accidents
such as explosions. Therefore, methane and dust dispersion in underground mines is closely monitored and strictly
regulated. Accordingly, significant efforts have been devoted to study methane and dust dispersion in undergroundmines. In this study, methane emission and dust concentration are numerically investigated using the computational
fluid dynamics (CFD) approach. Various possible scenarios of underground mine configurations are evaluated. The
results indicate that solitary existence of a continuous miner adversely affects the airflow and leads to increases inboth methane and dust concentrations. Nevertheless, it is found that the negative effects of a continuous miner
presence on concentrations can be minimized or even neutralized by operating the scrubber fan on suction mode. In
addition, it was found that the combination of scrubber fan on suction mode and brattice results in the best
performance of methane and dust removal from the mining face.
KEYWORDS: dust; methane; mine ventilation; mining machine

1. INTRODUCTION
Coal mining is considered one of the world’s
most dangerous operations. There are many hazards
associated with coal mining: explosion, structure
collapse, hazardous gasses and particulates, moving
vehicles, and lack of respirable air. Among thesehazards, the most severe is explosion. Firedamp
explosions, majorly caused by methane, can trigger
more dangerous coal dust explosions, which lead tocollapsed areas, trapped personnel, and worker death.
Even in developed countries, coal related fatalities
are considerably high. For example, more than one
hundred thousand coal mine explosion fatalities havebeen recorded in the U.S. (U.S. Department ofLabour, 2015). The situation is more alarming indeveloping countries, as indicated by the increase of
the occurrences and casualties in China (Zheng, et al.,2009). This situation has encouraged the worldwide
mining community to explore and evaluate solutions
to reduce/eliminate the hazards causing the
explosions. A vast number of studies have been
conducted and reported. The majority of research has
been focused on mine ventilation, as it directly
affects the hazardous methane and dust
accumulations in the mining face.
Pioneer studies on mine ventilation weredirected at the fundamental aspect of mine
ventilation. Kaliev and Akimbekov (1990) developed
an air motion model based on Bernoulli equation andRunge-Kutta method. The results revealed that

*Corresponding author – email: agus.sasmito@mcgill.ca

theoretical and experimental airflow rates differ byless than 10%. Riley and Edwards (1991)
experimented on the methane drainage system inmining. It was found that the methane drainage
system is more efficient at advanced mining as
compared to that at retreat mining. Subsequently,
computational fluid dynamics (CFD) are widely
utilized in mine ventilation studies due to its
capability to predict methane dispersion. Some
examples are studies conducted by Srinivasa et al.
(1993), Uchino and Inoue (1997), and Tomate et al.
(1999).
Recently, research has been directed at
exploring ventilation methods and designs. This ismainly attributed to the fact that fundamentals havebeen established and significant advancement incomputational power allows CFDs simulations to be
run at significantly reduced cost. Parra et al. (2006)
examined ventilation near mining faces and foundthat blowing ventilation, in terms of dust control,
offers better dust dispersion than exhaust ventilation
if the setback distance is 6m or more. Wu et al.
(2007) studied three-dimensional gas transfer in coalmining and discovered that gas concentration along
the intake side is lower compared to the return airway
side. Later, Torano et al. (2009) justified thatsimulations are consistent with experimental data,
and also demonstrated that CFDs are necessary toanalyze ventilation systems. Rodriguez and
Lombardia (2010) found that different stone types

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

result in different methane emissions. Sasmito et al.
(2012) examined four different turbulence models:
Spallart-Almaras, k-epsilon, k-omega and Reynolds
Stress Model (RSM). It was found that the SpallartAlmaras model, which consumes the least
computational power, would be sufficient to predictflow behavior. Another finding is that in typical roomand pillar mining, flow stopping design can largely
affect methane concentration. It is also found that thebrattice-exhausting system leads to the lowest
methane concentration. Kurnia et al. (2014)
numerically examined the relation between methane
sources and methane dispersion as well as methane
distribution within the mining tunnel. Later, Kurnia etal. (2014) investigated intermittent ventilation
systems and discovered a possible electricity saving
plan. Zhou et al. (2015) simulated scenarios with theexistence of a continuous miner. The important
findings from their study are 1) only very limited
airflow could reach the mining face compared to total
airflow, 2) methane release efficiency is notconsiderably affected by different source locations,however, it is strongly influenced by the amount ofmethane released.
Dust concentration is another attractive research
topic. Inhaling respirable dust can adversely affectworkers’ health. Moreover, high dust concentration
can trigger dust explosions that be a disaster to themine. The water spray system has been widely used
due to its simplicity and effectiveness. As early as
1988, Aziz et al. discovered the system and thus,
water is used to reduce dust content. Recent results
show that water can reduce dust concentration up to
60% (Colinet et al., 2010). Tornao et al. (2010)
extended their own research from methane to dust
and developed a CFD model to match with field data.
Wei et al. (2011) simulated different scenarios ofdifferent exhausting pipe locations and diameters to
reduce dust concentrations. Dong et al. (2012) tested
a methane-air explosion mechanism with theexistence of coal dust and obstacles in a pipe, butlacked theory to explain the results. Zhou et al.
(2013) investigated dust diffusion in a specificforced-exhaust hybrid tunnel with a continuous
miner. Wang et al. (2015) also did similar dust
investigation in a forced-exhausted hybrid tunnel fora rectangular-shaped laneway. Kurnia et al. (2014)
investigated different ventilation tools on dust
removal and energy saving perspectives and foundthat brattice generally have the best dust removing
efficiency, at the cost of more energy consumption.
Kurnia et al. (2015) investigated brattice setup anddust control in a typical mine tunnel. Hu et al. (2015)
simulated respirable dust characteristics in anothertypical mine tunnel.

Many studies have investigated methane anddust concentrations separately. However, none ofthem have focused on the existence of both methaneand dust despite them both being critical pollutants incoal mines. This study investigates the flow behavior
and methane and dust dispersion characteristics in themining face of an underground coal mine. Moreover,a continuous miner and also ventilation tools areincluded in the study since the mining machine takes
up a very large area inside the active mining end,
which is likely to cause flow changes (compared toscenarios without a continuous miner) and possibly
dead zones for both methane and dust.

2. MODEL FORMULATION
A three-dimensional model is developed toimitate the mining region, as shown in Figure 1.
Ventilation air is supplied from inlet at a speed of 2
m/s. At the active mining face, methane js leaking
into the tunnel at a speed of 0.002874 m/s and dust is
generated by continuous miner at speed of 1 m/s withflow rate of 0.0062 kg/s. Detailed properties are
summarized in Table 1.

Figure 1: Schematics of mining face with mining machine
and auxiliary ventilation: blowing-exhausting (left) andbrattice-exhausting (right) (Kurnia, et al., 2014b).
Table 1: Geometric and operating parameters used.
Property
Value
Injection typeDensity (kg/m3)
Diameter distribution
Diameter range (m)Mean diameter (m)Spread parameter
Dust velocity (m/s)
Total flow rate (kg/s)
Air curtain width (m)Jet velocity (m/s)
Air velocity (m/s)
Tunnel height (m)Tunnel length (m)Tunnel width (m)Brattice space (m)Surface (Mining surface)
1400 (Coal high value)
Rosin–rammler
1×10-6 to 1×10-4
1×10-52.78
10.0062
0.2
12
2
2.9
20
4
0.5

For the sake of brevity, the mathematicalformulation is not repeated here. The interested

606

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

reader may refer to earlier publications (Kurnia et al.,2014a; Kurnia et al., 2014b) for details.
2.3 Boundary Conditions
The boundary conditions are prescribed asfollows:(i) Inlet: air flows into the tunnel is set to havevelocity of 2 m/s(ii) At the mining face: methane is released at total
flow rate of 0.05 m3/s and dust is generated at
total flow rate of 0.0062 kg/s(iii) At the outlet: stream-wise gradient of thetemperature is set to zero and the pressure is set
to standard atmospheric pressure (1 bar).
(iv) At walls: the standard wall function is used inall simulations.

the present study, as reflected in Figure 2a. As
mining machinery is added, the flow behavior at theface changes. Figure 2b demonstrates that thepresence of machinery presents flow obstruction thus
inducing flow separation resulting in increased
recirculation. Case 3 depicts the flow field with the
scrubber fan turned on, which creates high air
velocity flows to the face. Closer inspection reveals
that the blowing air from the scrubber is not
sufficient to push air leaving the working area andthus creates a recirculation zone (Figure 2c). In Case4, on the other hand, the scrubber fan is in exhausting
mode and is found to be able to provide sufficient
flow from mining face to the laneway tunnel, andthus no recirculation is observed.

3. RESULTS AND DISCUSSION
In this study, a total of nine possible scenarios
are explored under both constant methane emission
and dust emission from discrete sources. Table 2
illustrates the detailed case configurations andfeatures with respect to their specific case numbers.
For abbreviation purposes, only case numbers arepresented in the figures afterward. The standard k-ε
turbulence model is used in this study since it
provides the required balance between computationaltime and accuracy. Flow validation for a similargeometry has been performed in another study(Kurnia, et al., 2014a).
Table 2 Cases with their features.
Case 1
No continuous miner, no ventilation tools
Case 2
Continuous miner with scrubber fan off, noventilation tools
Case 3
Continuous miner with scrubber fan on
injection mode, no ventilation tools
Case 4
Continuous miner with scrubber fan on suctionmode, no ventilation tools
Case 5
Continuous miner with scrubber fan on suctionmode, with ventilation fan blowing air intomining face
Case 6
Continuous miner with scrubber fan on suctionmode, with ventilation fan sucking air out of
mining face
Case 7
Continuous miner with scrubber fan on suctionmode, with brattice installed
Case 8Continuous miner with scrubber fan on suctionmode, with brattice and suction fan
Case 9Continuous miner with scrubber fan on suctionmode, with blowing fan and suction fan

Figure 2 shows the velocity distribution at themining face for cases 1 to 4. Previous work by
Sasmito et al. (2013) shows that for cases with noauxiliary ventilation, the ventilation air is unable toreach the mining face. The same trend is observed in

Figure 2: Velocity contour at height of 1 m from the tunnel
floor.

Figure 3: Contour of methane concentrations at 1 m, 3 m, 6
m, 9 m, 12 m, 15 m, 18 m away from mining face.

The presence of recirculation flow, mining
machinery and a scrubber fan is expected to have a
direct impact on methane and dust distributions.
Figure 3 shows the distribution of methane
concentration along the active mining tunnel. For
instance, the presence of mining machinery and607

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

recirculation flow increases methane distribution at
the face as can be inferred from Figure 3a, 3b, and3c. Case 2 is found to have highest methane
concentration, whereas the lowest methane
concentration is found in Case 4 where the scrubber
fan is in exhausting mode. Note that as compared toearlier work by Sasmito et al (2013), the methane
concentration in this case is up to 30% higher. This
discrepancy can be attributed to the fact that themining tunnel used in this study is longer (20 m) as
compared to 12 m used in Sasmito et al. (2013).
Hence, it can be concluded that extra length in active
room and pillar mining significantly reduces
ventilation efficiency.

because a continuous miner takes up a large space inthe tunnel and obstructs ventilation air which resultsin smaller volume in the active mining tunnel
resulting in increased methane concentrations. Trends
in Figure 4a also reveal that Case 3, in which the
scrubber fan is turned on in blowing mode, increases
the concentrations in the mining tunnel as compared
to Case 2 where the scrubber fan is turned off. Thiscan be explained by the fact that a blowing fan
creates stronger recirculation flow while it is unable
to push the methane out towards the main tunnel.
Therefore, Case 3 is non-effective or can even be
concluded as counter-productive to reduce methane
concentration in the tunnel. Conversely, Case 4 isfound to be beneficial in reducing methane
concentration.
The average dust concentration along the tunnel
is presented in Figure 4b. Case 1 shows the highest
dust concentration among others, as there isinsufficient airflow to remove dust from the mining
face. The cases with a continuous miner in generalyield lower dust concentration due to higher flow
recirculation, which somehow is effective indispersing the dust. Case 2, in contrast to methane
control, gives rise to the dust concentration, as there
is no auxiliary ventilation turned on. Case 3 with ablowing scrubber fan has a positive effect on dust
control, however the exhaust scrubber fan performs
best in mitigating dust concentration.

Figure 5: Contour of methane concentrations at 1 m, 3 m, 6
m, 9 m, 12 m, 15 m, 18 m away from mining face.

Figure 4: (a) Average methane concentration, (b) Average
dust concentration, along the tunnel.

Figure 4a presents the average methane
concentration at various distances along the tunnel.
The result clearly demonstrate that Case 4, where thefan is in suction mode, provides the best effectivenessin terms of low methane concentration. The percent
increase in methane concentration for Cases 2 and 3
is quite significant as compared to Case 1. It is

Figure 6: Air outflow from mining face, colored by dust
concentration.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 5 shows the performance with regard tomethane concentration for Cases 4 to 9. Note that all
the cases in Figure have the continuous miner on
suction mode and Case 4 serves as the base case to
the rest of Cases 5 to 9. Compared to Case 4, Case 5
is found to be counter-productive as it yields higher
methane concentration due to recirculation flow
created by an additional blowing auxiliary fan. Thisobservation is mirrored in Figure 6b. Case 6 iseffective in reducing methane at 6-20 m range frommining face but it is found less effective in reducing
the most critical area at the mining face due torecirculation flow (Figure 6c). Cases 7, 8 and 9 are
relatively
effectivein
reducing
methaneconcentration close to the mining face, which can be
attributed to there being no recirculation flow in theworking area for these cases.

concentrations (Figure 7a), Case 7 gives the best dust
removal ability followed by the blowing-exhaust
configuration (Case 9) and brattice-exhaust (Case 8).
From the average dust concentration perspective,
Figure 7b shows that brattice exhaust configuration(Case 8) performs best in removing dust from themining face, followed by brattice, which has aslightly inferior performance.
4.

CONCLUSIONS

A three-dimensional CFD model for a mining
face with mining machinery and auxiliary ventilation
have been developed and presented. To take into
account the turbulence effect, the standard k-epsilonmodel is used and selective computational results fornine different cases are presented. The effect of acontinuous miner presence as well as additional
ventilation are evaluated and discussed with the focus
being methane and dust dispersion and accumulation.
Several important findings of the study are that(i) higher air flow rate generally yields lower
methane and dust concentrations (ii) the presence of acontinuous miner negatively impacts the airflow inactive mining tunnel and increases concentrations bytaking up a large volume in the tunnel and blocking
almost half of the tunnel section area, and (iii) a
scrubber fan turned to suction mode could counterthe continuous miner impact by reducing a significant
amount of methane and dust.
Moreover, it is found that brattice cases (Cases
7 and 8) along with the blowing exhaust case (Case9) are more effective in reducing methane and dust
concentrations whereas the solo use of blowing or
exhausting fan is not effective. Future studies will befocused on reducing methane concentration to evenlower levels as current cases contain quite high levelsof methane at places near the mining face. In addition
more tunnel geometries will be evaluated and filters
for fans will be added into the simulation model toinvestigate their effectiveness in reducing dust
concentrations.

5. ACKNOWLEDGEMENT
The high performance computing (HPC) facility
and financial support from McGill University and
NSERC-Discovery Grant RGPIN-2015-03945 is
gratefully acknowledged.
Figure 7: (a) Maximum dust concentration and (b) Average
dust concentration along the tunnel.

Looking at the maximum and average dust
concentrations, Error! Reference source not found.
reveals that the maximum dust concentration is about
one order-of-magnitude higher than that of average
concentration.
From
themaximum
dust

6.

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ISMS 2016

Paper No. 120
Reducing Heat Stress Exposure in Mines
Ryan Andersona,*, Euler De Souzaᵇa
K2 Mine Production, Mosaic Potash, Esterhazy, Canada, S0A2A0
Department of Mining Engineering, Queen’s University, Kingston, Canada, K7L3N6ᵇ

ABSTRACTHeat management must be maintained within the mine working environment to minimize stress on equipment andpersonnel. Proper application of engineering protocols and work practice controls will have a direct impact on thehealth and safety of workers and on productivity. Using monitoring stations placed in strategic locations throughout
the mine to capture the environmental conditions, various strategies can be used in the planning and prevention ofpotential hazard exposure. Economic analysis is used to select the most feasible strategy for heat stress control.
1. INTRODUCTION
Heat management is an important factor as mines
expand to meet the demand of their growing
workforce and extraction rates. The introduction of
new equipment and manpower puts additional
demands on the ventilation system that is often the
primary means of heat control. When mines plan toplace additional significant heat sources into theventilation system a proper methodology used tomonitor, establish, and control heat stress witheconomically viable solutions must be established.
This paper presents a step by step methodology
for 1) identifying heat sources, 2) establishing a heatmonitoring program, 3) calculating heat loads
underground, 4) applying heat management
strategies, and 5) selecting engineering solutions toheat control.
A detailed case study, based on a heat stressmanagement study conducted for an undergroundpotash mine is presented to illustrate the applicationof the proposed strategy.
2. HEAT MANAGEMENT METHODOLOGY
A proposed methodology for establishing a heat
management program is presented. In themethodology, heat sources are identified, data iscollected from environmental monitoring stations andcalculated heat loads are assessed using ventilation
modelling software. Application of specificmanagement control strategies allows one toeliminate heat stress and improve safety.
2.1 Identification of heat sources
All heat sources must be identified in the area ofinterest and quantified in terms of heat load. Suchsources include strata heat, auto-compression, groundwater, machinery (loaders, trucks, drills, conveyors,
scrapers, pumps, fans, transformers), blasting, rockmovement, oxidation, cables, pipelines, lights, humanmetabolism, etc.
2.2 Establishment of a heat monitoring program
There is a wide range of environmental
monitoring programs that are commonplacethroughout the mining industry. Mining regulations
typically set minimum standards regarding themonitoring and recording of the environment factors
relating to heat found within the undergroundenvironment. The basic method frequently employedis the use of handheld monitoring equipment, which
is checked and recorded at predetermined locations
and on a set schedule. Additional monitoring often
only occurs as the result of a change to the ventilation
conditions. This type of monitoring often presents alevel of accuracy that is sufficient to meet regulatory
requirements, but may not provide enough detailed
information to account for fluctuating conditions thatcan range from acute cases to seasonal in nature.
When an area within the mine is identified as apotential hazard from heat accumulation, additional
monitoring is required to ensure the conditions theworkforce is entering into are managed to minimize
heat stress exposure. Additionally if there is heatsensitive equipment, reducing the environmental heatconditions will often promote equipment function as
well as extend equipment life. In order to capture
enough information to accurately describe theconditions found within the subject area of concern aminimum monitor recording frequency must be met
based on potential daily and in some cases hourly
fluctuations. Currently there are a number of standalone environmental monitors that can be set tomonitor conditions at intervals set by the user andplaced in the field for real time observation and datacollection.

*Corresponding author – email : ryan.anderson@mosaicco.com

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2.3 Calculating heat loads underground
In order to assess the heat load within theunderground environment, there are different
methodologies that may be employed in order to use
the appropriate heat management technique. Heat
stress is often considered as a factor of the wet bulb
globe temperature when considering the effects ofheat on the workers in the mine.
Wet bulb globe temperature (Cº) WBGT, can becalculated within the mine environment with thefollowing equation;
𝑤𝑒𝑡 𝑏𝑢𝑙𝑏 𝑔𝑙𝑜𝑏𝑒 𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒 = 0.3𝑡𝑔𝑡 × 0.7𝑡𝑤𝑏
Where, 𝑡𝑔𝑡 (Cº) is the globe temperature and 𝑡𝑤𝑏 (Cº)
is the wet bulb temperature.
In order to assess the energy that is contained
within the air in the underground environment, theenthalpy of the system can be calculated, which takes
into account the moisture content of the air.
Additionally the sigma heat can also be calculated,which takes into account the energy content less the
moisture content. Both of these methods to describe
the energy contained within the air are considered on
the dry basis (kJ/kg dry air).
In order to calculate the enthalpy of the system
the enthalpy of the air (kJ/kg) (ℎ𝑎 ) and the enthalpyof the vapour (kJ/kg) (ℎ𝑣 ) must be combined.
ℎ = ℎ𝑎 + ℎ𝑣
= 1.005 𝑡𝑑𝑏 + 𝑊(2501.6 + 1.884 ∗ 𝑡𝑑𝑏 )In order to calculate the apparent specifichumidity 𝑊 (kg/kg dry air) the following equationmust be used;𝑃𝑠
𝑊 = 0.622
𝑃𝑏 − 𝑃𝑣
17.27 ∗ 𝑡𝑑𝑏)
𝑃𝑠 = 0.6105 exp (237.15 + 𝑡𝑑𝑏
𝑃𝑣 = 𝑃𝑠 − 0.000644 ∗ 𝑃𝑏 (𝑡𝑑𝑏 − 𝑡𝑤𝑏 )In the above equations, 𝑡𝑑𝑏 (Cº) is the dry bulb
temperature, 𝑃𝑠 (kPa) is the saturation vapour
pressure, 𝑃𝑏 (kPa) is the barometric pressure, and 𝑃𝑣(kPa) is the vapour pressure.
The enthalpy can then be applied to the mass
flow (kg/s) (𝑀𝑓 ) in order to find the heat flow (Watt)( 𝑞𝑓 ) in the system. The following calculation
assumes no change in moisture to the system.
𝑞𝑓= 𝑀𝑓 (∆ℎ)
𝑀𝑓= 𝑄 ∗ 𝑤
Where Mf is the mass flow (kg/s), ∆ℎ is thesigma heat change (kJ/kg), Q is the flow rate (m3/s),
and w is the air density (kg/m3).
In a ventilation system where there is a change inmoisture the heat flow can be found using the sigma
heat on a dry basis (S).
𝑞𝑓= 𝑀𝑓 (∆𝑆 + 𝐵)
𝑆 = ℎ − 4.187 ∗ 𝑊 ∗ 𝑡𝑤𝑏

Where, B (Cº−1 ) is a term which depends on theprocess involved and on the change in moisture
content.
Another method of calculating heat loads within
the mine environment is by calculating the heat load
losses, based on equipment found within the
excavation of concern. This method is useful forboth reactive heat management planning andpredictive heat management. In order to assess theheat losses from equipment, a detailed equipment
survey must be conducted on the equipment foundwithin the area of concern. This included thestationary and mobile equipment, the infrastructureused to power the system, and the utilization of thecomponents within the area. It is advisable to break
down the area of concern into smaller segments basedon changes in features contained within the
excavations, or physical changes in the excavation
itself. The strata, the excavation, and the changes inmoisture content can also have significant impacts on
the heat load prediction based on equipment heatlosses, so it is important to understand the behaviourof the rock type as well as any significant changes inmoisture content within the excavations.
This
process is described in section 3.
2.4 Applying heat management strategies
The application of a heat management strategy
will serve to limit the level of health risk associatedwith the total heat load imposed on a worker
underground. Heat management strategies include
refrigeration (bulk air cooling), localized refrigeration(spot coolers), ventilation, administrative controls (airconditioned cabins, cooling vests, acclimatization,
rest
areas),
andengineering
controls(controlling/reducing heat at source, shielding,insulation).
2.5 Comparing and selecting engineering solutions
on heat control
Selection of the ideal solution for heat control
requires an engineering and economic analysis ofalternatives. The solution is more likely acombination of strategies and available technologies.
The combined application of engineering andadministrative controls, together with selected work
practices are effective means of reducing excessive
heat exposure.

3. CASE STUDY
3.1 Area of study
A management program of heat generated frompumping infrastructure in a Saskatchewan potashmine has been established. The study area is 5.6
kilometers of underground excavations within series612

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

ventilation and recirculation circuits. There are over
20,515 kW of electric motors resulting in 305,000
Watts of lost energy to atmospheric heat. In addition
to these motors there are 49.6 kilometers of electrical
power cables and the associated electrical controls
and transformers, which also lose energy to heatthroughout the area.
3.2 Identification of heat sources
In order to identify the locations and sources ofheat, the study area was broken down in 14 zones.
Each zone was further broken down into 20 meter
sections to be used for future computationalmodeling. Within each section the heat sourcecomponents were identified. The Heat Management
Study Area and zone locations are identified in
Figure 1. The primary sources of heat include strata,electrical cable, transformers, motors and settlingtanks.

selecting the appropriate locations to monitor was
critical. The study area was broken down into zones
that were considered heat source areas and heat sumpareas. Observing the areas that had the greatest
impact on the area allows for targeting of heat control
applications. In addition to the supply air, thesurrounding stratum also has an impact on theenvironmental conditions. To better observe the rockbehavior on the air, it was necessary to capture thetransfer of heat both into and out of the rock as it
behaves as both a source of supply and removal ofheat. In order to do this, heat fluctuation plates were
installed against the strata to monitor the transfer ofheat in and out of the rock. To further improve upon
the observation of the rock characteristics, the virginrock temperature can aid in the identification of thelimits to which the rock can act as a source or sumpof heat. In the study of the potash mine, 15.25 mlong vertical and horizontal bore holes were
established to capture this information. Temperatureprobes were located at 1.5 m, 3 m, 6 m, and 15 m tomonitor heat fluctuation with depth.
3.4 Heat load calculations
To calculate the energy lost to the atmosphere asheat, the efficiency of the equipment was calculated
at full load and continuous use. This was applied toall sources of heat with the exception of the electricalcables, which are based on 60% of full load. The
primary sources of heat energy result from losses
with transformers and pumping equipment. The
estimated flow of heat is summarized in Table 1.

Figure 1: Heat Management Study Area.

3.3 Monitoring program
In the case example used within the potashmine, due to the relatively close proximity to theincoming shaft air there are hourly fluctuations as aresult of changes to the surface temperature supply
air. As a result of the required high frequency ofrecordings, a network of environmental monitoring
stations were essential in order to capture thecharacteristics of the air as it moved throughout the
study area.
The installation of 14 Accutron
Climatrax stations in conjunction with data loggers
allowed for the monitoring of the following
environmental factors: dry bulb temperature, wetbulb temperature, relative humidity, and barometricpressure. These parameters are then applied todetermine all important pyschrometric properties. In
order to find regional changes within the study area,

Table 1: Summary of heat load study.
Summary of Heat Load StudyArea Number Total Loss (W) Total Loss (BTU/hr)
1
187,435.5
639,556.6
2
202,534.2
691,075.5
335,620.1
121,541.0
482,022.8
279,873.4
56,710.6
22,897.6
6
129,160.3
440,713.1
7
224,794.4
767,030.4
8
17,166.5
58,574.59150,918.0
514,953.6
10485,040.0
2,227,047.1
11
20,239.0
69,058.4
12
10,212.1
34,845.2
13
10,815.3
36,903.3
14
19,789.0
67,522.7
Total Heat Loss 1,582,457.88
5,971,592.33

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Survey data was collected at the beginning andend of each zone in order to calculate the change inenthalpy and sigma heat for each zone. The data thatwas required in order to do the calculations included:
dry bulb, wet bulb, relative humidity, pressure, anddensity. The environmental monitors that were set up

with the areas were programed to record this data on
a 10 minute interval that could then be averaged atintervals that best suited the needs of the mine. Thisdata could then be used to calculate the heat loads
within the system (Table 2)

Table 2: Survey Data.
Survey Data
Location Dry Bulb (Cº) Wet Bulb (Cº) RH (%) Pressure (kPa) Density (kg/m³) Ps (kPa) Pv (kPa) W (kg/kg dry air) Cp (kJ/kg mix) h (kJ/kg dry air) S (kJ/kg dry air)
1 in
32.9
20.7
33
107.8
1.21 5.0053877 4.158425
0.025162215 1.052405613
97.57
94.10
1 out 2 in
33.5
21.1
33.3
107.8
1.23 5.1765363 4.315689
0.026157355 1.054280456
100.7597.08
2 out 3 in
37.4
22.7
28.6
107.7
1.23 6.417911 5.398337
0.033152608 1.067459513
122.86117.67
3 out
31.7
21
38.4
107.8
1.23 4.6777726 3.934944
0.023734315 1.049715449
92.65
89.50
4 in
28.1
19.7
45.6
107.9
1.23 3.8040593 3.220363
0.019242499 1.041252868
77.40
75.13
4 out
29.6
19.8
41.3
107.8
1.23 4.1491112 3.468764
0.020815751 1.044216875
82.98
80.40
5 in
29.5
19.3
38.7
107.8
1.23 4.1252894 3.417173
0.020501446 1.043624724
82.07
79.54
5 out
29.8
19.5
38.4
107.8
1.23 4.197114 3.482055
0.020905192 1.044385382
83.42
80.81
6 in
30
19.6
38.4
107.8
1.23 4.245599 3.523598
0.021164507
1.04487393
84.29
81.63
6 out 7 in
32.3
20.1
32.6
107.8
1.23 4.839173 3.99221
0.024117469 1.050437312
94.26
91.00
7 out 8 in
32
20.4
35
107.7
1.22 4.7578784 3.953316
0.023886847 1.050002821
93.36
90.15
8 out 9 in
31.7
20.3
35.3
107.8
1.22 4.6777726 3.886348
0.023441198 1.049163217
91.90
88.79
9 out 10 in
32.9
20.9
33.8
107.7
1.21 5.0053877 4.173082
0.025275494 1.052619031
97.86
94.38
10 out
34.1
21.3
31.9
107.7
1.21 5.3527408 4.464948
0.027135048
1.05612243
103.89100.02
11 in
30.9
19.9
36.2
107.7
1.23 4.4698588 3.706912
0.022335524 1.047080126
88.23
85.34
11 out
30.1
19.5
37.2
107.8
1.23 4.2700237 3.534138
0.021232823 1.045002639
84.57
81.89
12 in
30.1
19.5
37.1
107.8
1.23 4.2700237 3.534138
0.021232823 1.045002639
84.57
81.89
12 out
29.5
19.4
38.4
107.8
1.23 4.1252894 3.424115
0.020543097 1.043703194
82.18
79.64
13 in
31
20.5
36.9
107.8
1.23 4.4954007 3.766457
0.022677948 1.047725254
89.21
86.27
13 out
31.8
20.6
36.9
107.8
1.23 4.7043434 3.926804
0.023691316
1.04963444
92.64
89.49
14 in
29.2
19
38.2
107.8
1.23 4.0545363 3.34642
0.020063268 1.042799196
80.64
78.19
14 out
28.1
19.7
45.6
107.9
1.23 3.8040593 3.220363
0.019242499 1.041252868
77.40
75.13

3.5 Heat management strategy application
In order to manage the heat produced within theworkings, there are two goals that should be met.
Firstly, minimizing heat stress conditions topersonnel, and secondly reducing heat exposure toequipment.
In order to minimize heat stress conditions topersonnel, a work plan that decreases work in highwet bulb globe temperatures according to heat stressguides may be a viable option. The heat stress guide
listed in Table 3, outlines working time lengths andjob type that can safely be performed based on theenvironmental conditions. There are limitations tothis type of heat management plan, as it does not
lower heat exposure to heat sensitive equipment andmay not be economically or practically feasible basedon the length or type of work being performed.

Table 3: Wet bulb Globe Temperature Index (Section 70, Occupational Health and Safety Regulations, 1996, Saskatchewan).
Wet Bulb Globe Temperature (WBGT) Index
Work Rate
Work Load
15 minutes rest perContinuous
30 minutes rest per hour 45 minutes rest per hour
hour
Heavy
up to 25Cº
25Cº up to 26Cº
26Cº up to 28Cº
28Cº up to 30CºModerate
up to 27ºC
27Cº up to 28Cº
28Cº up to 29Cº
29Cº up to 31CºLight
up to 30Cº
30Cº up to 30.6Cº
30.6Cº up to 31.4Cº
31.4Cº up to 32.2Cº

A second option may be setting up spot coolingwithin the workings to remove the additional heatproduced by the equipment. In the case study thelocation that would see the largest local benefit and to
air traveling downstream is zone 2.
In order to set up a cooling plant in zone 2 thefollowing parametric design is conducted.

The mass flow (𝑀𝑓 ) entering into zone 2 is 29.6 kg/s
The specific humidity entering into zone 2 (𝑊1 ) is
0.025 kg/kg
The enthalpy entering into zone 2 (ℎ1 ) is 95.04 kJ/kg
Air to be cooled to 27.8°C

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Using a psychometric chart and 27.8°C as thechosen output, the following outgoing enthalpy andspecific humidity were found.
The specific humidity leaving zone 2 (𝑊2 ) will be
0.20 kg/kg
The enthalpy leaving zone 2 (ℎ2 ) will be 78kJ/kg
The specific enthalpy of water (ℎ𝑤2 ) at 27.8°C is
123.5 kJ/kg
By installing the temperature probes into therock, the ambient virgin rock temperature of both thesalt and potash members were found to be 27.1°C,
this is the lower limit of the attainable cooling before
the rock becomes an additional heat source for the
excavation, limiting the effectiveness of the cooling.
The cooling load requirement (Q) can be foundusing;
𝑄 = 𝑀𝑓 ∗ [(ℎ1 − ℎ2 ) − (𝑊1 − 𝑊2 ) ∗ ℎ𝑤2 ]The resultant cooling load is 489kW or 139.2
tons of cooling by an installed cooling plant.
With the installation of a chiller plant within theunderground environment, the cost of the plant must
be taken into consideration. The initial capital
expenditure is the upfront cost, but the cost ofoperation should be assed.
The cooling plant
efficiency can be assed based on the coefficient of
performance (COP). This allows a basic assessmentof the cost of running the plant.
A typical cooling plant that could be used within
this location is a water cooled electrically operated
positive displacement cooling plant. According toEnergy Design Resources the COP for this type ofplant, would be approximately 4.20. The energy
requirements to run the plant would be;𝑒𝑛𝑒𝑟𝑔𝑦 𝑟𝑒𝑞𝑢𝑖𝑟𝑒𝑚𝑒𝑛𝑡𝑐𝑜𝑜𝑙𝑖𝑛𝑔 𝑝𝑙𝑎𝑛𝑡𝑐𝑜𝑜𝑙𝑖𝑛𝑔 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑟𝑒𝑞𝑢𝑖𝑟𝑒𝑚𝑒𝑛𝑡𝑠=
𝐶𝑂𝑃
This results in 116.4 kW of energy required to
run the plant. The annual cost of operation can thenbe calculated based on continuous operation at thecost of delivery and kWh usage. The cost ofcontinuous usage at this mine for the case study is
0.065 $/kWh.
𝑐𝑜𝑠𝑡𝑐𝑜𝑜𝑙𝑖𝑛𝑔 𝑝𝑙𝑎𝑛𝑡= 𝑒𝑛𝑒𝑟𝑔𝑦 𝑟𝑒𝑞𝑢𝑖𝑟𝑒𝑚𝑒𝑛𝑡𝑐𝑜𝑜𝑙𝑖𝑛𝑔 𝑝𝑙𝑎𝑛𝑡∗ 𝑒𝑛𝑒𝑟𝑔𝑦 𝑐𝑜𝑠𝑡𝑐𝑜𝑛𝑡𝑖𝑛𝑢𝑜𝑢𝑠 𝑢𝑠𝑎𝑔𝑒 ∗ 𝑟𝑢𝑛 𝑡𝑖𝑚𝑒
As a result the annual cost of running a coolingplant in this location will be $66,278.
It is also possible to estimate the cost of cooling
any future additional equipment to the area. Based on
the equipment survey, a common motor that is usedwithin zones 2, 7, and 10 has a heat loss of 15 kW
based on motor efficiency. Using the same principle
the cost of cooling additional motor installs would
approximate $8,541 per motor. This would allow for

the estimate of the additional cost of cooling thezones as additional equipment is added.

4. CONCLUSIONSHeat management plans are growing inimportance when it comes to the health and safety of
the workforces within the mines. There are strategies
that can be used to minimize the effects on bothpeople and equipment, but the costs of the plans must
be realized. There are costs associated with both theefficiency of the work being done as a result of theheat conditions through avoidance. There are also
costs that occur as the result of actively attempting tocool the working areas. These costs must be
understood and assed to achieve the greatest impact
on the environmental conditions within the mine
environment.

5. REFERENCES
De Souza, E. (2011), Mine Ventilation
Practitioners Guide.
https://energydesignresources.com/media/1681/edr_designbriefs_chillerplant.pdf?tracked=true
Section 70, Occupational Health and Safety
Regulations, 1996:Working Under Hot Conditions,Saskatchewan

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ISMS 2016

Paper No. 232
Effect of hydrogen on explosion of methane-air mixture

YANG Chunli a,*, LI Xiangchun b,c, Xu Teng b,c, Qu Wenzhong b,c, Liu Yanli b,caSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, China, 100083
School of Resource and Safety Engineering, China University of Mining & Technology(Beijing), Beijing, China, 100083
cState Key Lab of Coal Resources and Safe Mining, Beijing, China, 100083b

ABSTRACTGas explosion is one type of coal mine accidents in China. The main composition of the gas in coal seam ismethane, but hydrogen is contained in some coal seams and increases the risk of gas explosion. The main reaction
path of methane-air mixture explosion process and elementary reactions characteristics at high temperature are
analyzed using detailed mechanism of methane combustion. Different fraction of H2/CH4/Air mixture explosion issimulated, and temperature, pressure, mole fraction of different species and elementary reactions rate are analyzed.
The simulation results show that hydrogen will reduce the priming induction period of gas explosion and has
influence on the temperature and pressure of gas explosion.
KEYWORDS: hydrogen; methane-air explosion; hydrogen; elementary reaction; induction time; reaction rate

1. INTRODUCTION
Gas is produced in the process of coal-forming.
The main component of gas all over the world ismethane, and there are also C2H6, C3H8 and othercombustible gases of heavy hydrocarbon in somecoal seams（ Zhou,1999 ）. In addition, there is asmall amount of hydrogen in some coal seam because
thermal decomposition of coal at a high temperature(Yu and Wang, 2005). Meanwhile, combustible gasesof CO, C2H4, C2H6, C3H8, etc. are produced in theprocess of coal spontaneous combustion (Xiao et al.,2007; Zhang, 2000). So in addition to main specie
methane, there may be a small amount of H2, CO,C2H4, C2H6 and C3H8 and other combustible gases incoal seam. Explosion limits and severity of gas
mixture explosion depends on species and fraction of
the gas mixture. Combustible gas mixture in methane
will influence explosive limits and increase risk of
explosion (Pan et al., 2008; Guo, 2002).
Although there is a little hydrogen in methane,risk of explosion can increased greatly because lower
explosive limit (LEL) of hydrogen is very low
compared to methane. H2/CH4/Air mixtures havelower LEL compared to CH4/Air methane when mole
fraction of CH4 is same, and it is easy to explode.
Explosion power and explosion hazard will increase
even if there is little hydrogen in CH4/Air mixture(Ma, 2015).
Many research had been carried out on explosion
characteristic of H2/CH4/Air mixture(Li et al.2008;
Shrestha,1999).Ma(2015) showed in their publicationthat temperature and pressure of H2/CH4/Air mixture
explosion is very different when using different*Corresponding author–email: yangcl_1980@163.com

mixing ratios. Pan et al. (2008) demonstrated thathydrogen influences LEL of H2/CH4/Air mixture andcan increase explosion risk. Luo et al. (2015) showedin their publication that combustion gas CO, H2, C2H4
and C2H6 affect explosion limit of CH4/Air mixture.
Ren et al. (2013) conducted methane explosion
experiment and found that explosion limit range was
extended with fraction of H2S, CO and H2 increasing.
Jia et al. (2016) analyzed effects of different
concentration CO and H2 mixture on the gas
explosion by numerical analysis. Hu et al. (2010)
analyzed pressure waves of H2/CO/CH4/air mixture
explosion and found that hydrogen is key element
affecting the explosion. Mahdi et al. (2016) obtained
maximum pressure rise rate and deflagration index ofmethane, hydrogen and their mixtures and examined
influence of equivalence ratio, initial temperature andinitial pressure on the maximum pressure rise rateand deflagration index. Li et al. (2012) found that thepresence of molecular hydrogen yield from coalspontaneous heated process would significantly
increase the maximum explosion pressure andpressure rise rate of H2/CH4/air mixtures. Li et al.
(2015) carried out the explosion experiments ofhydrogen/air and methane/air for different gas
volumes and found that the flame propagation speedof hydrogen/air explosion is higher than that ofmethane/air, while the flame duration of methane/air
is longer than that of hydrogen/air.
In this paper, the influence of combustible gashydrogen in coal mine on the explosion mixture ofmethane air was studied using the chemical kinetic
software CHEMKIN. Pressure, temperature and free
radicals of mixture gas explosion are analyzed, and3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the influence of the mixed combustible gas on
methane-air mixture explosion is obtained.
CHEMKIN developed by Sandia laboratory and Kee
R.J et al. can solve the problem of gas-phasechemical reaction in the combustion process.
Subroutine of Senkin is used in this simulation.
Senkin is a Fortran computer program block, which
can simulate the tendency of premixed homogeneousgas reaction with time charge in a closed container(Li, 2011). Detailed chemical reaction mechanism of
H2/air mixture is relatively simple, which is included
in GRI-Mech 3.0, so the simulation of H2/CH4/air
mixture explosion reaction is calculated by data files
GRI-Mech3.0.

2. CHARACTERISTICS OF CH4/AIR
MIXTURE EXPLOSION
2.1 The Main Elementary Reaction of CH4/air
Mixture Explosion
Methane has a tetrahedron molecular structure
and bond energy of C-H, which make methane
oxidation process complex (Stephen, 2015). In theearly 20th century, people have confirmed that all gas
phase reaction are conducted by a series of
elementary reaction, the complex chain reaction ofgas explosion reaction is composed of the elementary
reaction (Lin et al., 2013). At present, there are morethan a dozen of detailed chemical mechanisms, but
methane combustion reaction mechanism by theLawrence Livermore National Laboratory is
generally accepted, which includes 53 species and
325 elementary reactions. Methane combustion
process is very complex, but there is only one key
oxidation path, and some key elementary reactions.
According to detailed mechanism, in the processofgas
explosion,
elementary
reactions
HO2+CH3=O2+CH4
H+CH3(+M)=CH4(+M) andproduce free radicals and initiate reaction. Wheninitial temperature is low, HO2+CH3=O2+CH4
initiate reaction mainly, and H+CH3(+M)=CH4(+M)
initiate reaction mainly when the initial temperature
is high. Lin et al. (2012)shows that when temperature
is more than 2000T, explosion is initiated by
H+CH3(+M)=CH4(+M) only.
CH4 is mainly consumed by following threereactions: H+CH4=CH3+H2, OH+CH4=CH3+H2O andO+CH4=OH+CH3.Compared with H and OH, amountof CH4 consumed by O is much smaller (Peter, 1985).
So O+CH4=OH+CH3 is less important comparedwith other two reactions. CH3 is mainly oxidized bythefollowing
reactions:
O+CH3=H+CH2O,
OH+CH3=CH2(S) +H2O, OH+CH3=CH2+H2O andHO2+CH3=OH+CH3O. Compared with OH and HO2,
CH3 is mainly consumed by reaction with O.
Combination reaction of CH3+CH3=C2H6 generates

hydrocarbon of C2 series, which is important whenCH4 is rich. CH2O is mainly oxidized by the twoandreactions
H+CH2O=HCO+H2
OH+CH2O=HCO+H2O. HCO is mainly oxidized by
the two reactions HCO+M=H+CO+M andHCO+O2=HO2+CO. CO is oxidized essentially by
the reaction OH+CO=H+CO2, and the reaction of COwith O and O2 can be in general neglected. The
consumption of oxygen and the formation of radicalby the reactions H+O2=OH+O, OH+H2=H+H2O,
2OH=O+H2O and O+H2=H+OH. The last three ofthese are linearly dependent. Reaction H+O2=OH+O
is very important as a chain branching reaction since
it produces more radicals than it consumes. Finally,
chain breaking occurs mainly through three bodyandreactions
H+O2+M=HO2+M
otherrecombination
H+OH+M=H2O+M.While
reaction can be neglected.
2.2 Heat Production of Elementary Reaction
In a reaction, energy produced by old chemicalbond breaking and new chemical bond forming cancause heat release. In the process of gas explosion,
lots of elementary reaction release heat for a second,which cause temperature and pressure rise
immediately and lead to disaster.
Detailed mechanism includes 325 elementary
reactions. Some absorb heat and some releaseheat .Because all the reaction is reversible, a reaction
may release heat and absorb heat in different time.
But release heat or absorb heat can be identified bypositive and negative of a reaction total heat release.
Except for 106 elementary reactions which nitrogenoxides participate in, there are 175 heat release
reactions and 44 heat absorption reaction during theprocess of gas explosion. In the process of gas
explosion, chain initiation elementary reactions
absorb heat when meeting heat source, and produce
free radical. So at first, gas explosion system absorbs
heat. And then lots of elementary reactions releaseheat, and there is a peat point of heat release.
CHEMKIN software and closed homogeneousmodel are used to simulate heat release of mixture
CH4/Air explosion. Initial temperature is 1300K, andinitial pressure is 1atm.Reactor volume is 1cm3, andmole fraction of CH4 is 0.095.
Fig.1 shows system heat releases at different
time during explosion process. The total heat releaseis 0.5124J. Fig.2 shows top ten total heat release ofdifferent elementary reactions. In the process of gas
explosion, reaction
HCO+O2=HO2+CO 、
O+CH3=H+CH2O and CH3(+M)=C2H6(+M) are top
three heat release reactions.The total heat releases of
the three release is 0.0489J、0.0435J and 0.0358J
respectively. Total heat release of the three releases

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016account for more than twenty percent of system totalheat release.Key absorbtion heat release reaction is
H+O2=O+OH, total heat release is 0.072J.

Figure 1: System heat releases at different time

Figure 2: Total heat release of different elementary
reactions

CHEMKIN software and closed homogeneousmodel are used to do the simulation. Initial
temperature is 1300K, and initial pressure is 1atm.
Tab.2 shows max temperature, pressure andpercentage increase of temperature and pressure of
the five schemes. Max temperature and pressure
increase with increase of mole fraction hydrogen, but
percentage increase is low. When mole fraction ofhydrogen is 4%, percentage increase of temperatureand pressure are 2.79% and 2.24% respectively.
Table 2: Max temperature, pressure and percentage
increase of temperature and pressure
schemes12345Temperature(K) 2776 2787 2798 2819 2853
Temperature
Percentage
0.41
0.8
1.53
2.79
increase( %)Pressure(atm)
2.20
2.21
2.21
2.23
2.25
Pressure
Percentage
0.33
0.65
1.24
2.24
increase (%)

Fig.3 shows explosion induction of the fiveschemes. As can be seen from Fig.3, induction timedecreases with the increase of initial hydrogenconcentration. Percentage decreases are 45%, 64%,
81% and 92% respectively when the mole fractionsof hydrogen are 0.5%, 1%, 2% and 4%.Hydrogeninfluence induction time of explosion greatly. When
there is little hydrogen in CH4/Air, induction time
will change greatly.

3. CHARACTERISTICS OF H2/CH4/AIR
MIXTURE EXPLOSION
3.1 Characteristics of H2/CH4/air Mixture explosion
Considering actual situation, when designingsimulation schemes, mole fraction of hydrogen in
every scheme should be small because there is littlehydrogen in coal seams. Five schemes are designedin the simulation, as is shown in Tab.1. In the fiveschemes, mole fraction of methane is 8%, mole
fraction of hydrogen are 0, 0.5%, 1%, 2% and 4%
respectively. Air is assumed consisting of 79%
nitrogen and 21% oxygen by volume.
Table 1: Mole fraction of each species of five schemes
species
1
2
3
4
5
CH4
0.08
0.08
0.08
0.08
0.08
O2
0.1932 0.19215 0.1911
0.189
0.1848N20.7268 0.72285 0.7189
0.711
0.6952
H2
0
0.005
0.01
0.02
0.04

Figure 3: Explosion induction time of the five schemes

Fig.4-Fig.6 is the main free radical change curvewith time of different schemes. As is showed in
Fig.4-Fig.6, when explosion occurs, the mole fractionof each free radical increases for a section andreaches the peak point, and then decreases rapidly toa stable condition. The mole fraction of O reducesslightly with H2 increasing. Because with hydrogen
increasing, the reactions rate of O+H2=H+OH and
OH+H2=H+H2O increase, and H increase, whichcause chain reaction rate of H+O2=O+OH increase.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Because OH is mainly produced by the reaction
H+O2=O+OH, free radical OH increase. But with theincrease of hydrogen content, the total content ofoxygen in the mixture decreased slightly, so the O
produced by the explosion is slightly reduced, whichcause the rate of OH increase less than H.

of CH3 will increase too. CH3 is mainly oxidized by
the reaction O+CH3=H+CH2O. With the increase of
H2 content, the content of O decreases, so the CH2O
generated by the explosion is reduced. Oxidation
reaction of CH2O is mainly reacted by the elementary
reaction H+CH2O=HCO+H2. Mole fraction of H
increase
lead
to
the
reaction
rateof
H+CH2O=HCO+H2 increasing, so mole fraction of
HCO increase.

Figure 4: Time-H curve of different hydrogen mole fraction
Figure 7: Max mole fraction CH3, CH2O, HCO of differenthydrogen mole fraction

Figure 5: Time-O curve of different hydrogen mole fraction

Final products of explosion are mainly CO, CO2
H2O, and the mole fractions of each product are not
the same. In the explosion, the mole fraction of H2O
and CO2 reaches the maximum value at the momentof the explosion and then remains the same; but themole fraction of CO reaches the maximum value atthe moment of the explosion and then reduces to acertain value. Therefore max mole fraction of H2O
and CO2 of each scheme are analyzed, as is shown in
Fig.8, but mole fraction of CO varying with time isanalyzed, as in showed in Fig.9.

Figure 6: Time-OH curve of different hydrogen mole
fraction

The free radicals of CH3, CH2O, and HCO reachthe maximum value at the moment of explosion, andthen reduced instantly to zero after the explosion, theprocess is very fast. Fig.7 is the maximum mole
fraction CH3, CH2O, and HCO of different scheme
during explosion. Fig.7 shows that mole fraction of
CH3 and HCO increase with the increase of hydrogenconcentration, but mole fraction of CH2O reduce
reduces with the increase of hydrogen concentration.
Because CH4 is mainly oxidized by the reaction
H+CH4=CH3+H2.And in the reaction, CH3 will be
produced. Because mole fraction of H increases with
the increase of hydrogen concentration, mole fraction

Figure 8: Max mole fraction of H2O, CO2 of differenthydrogen mole fraction

Fig.8 shows that mole fraction of H2O increases
with the increase of hydrogen, but CO2 decreases. As
showed in Fig.9, the maximum value of CO is almost
same at the moment of explosion, but final value of
CO decreases with the increase of hydrogen. Because
H2O is mainly produced by the elementary reaction
OH+H2=H+H2O and CO is mainly oxidized by theelementary reaction OH+CO=H+CO2, and they
compete for OH. Therefore, reaction rate of
OH+H2=H+H2O increases and OH+CO=H+CO2

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

decreases with hydrogen increasing, so mole fraction
CO2 will decrease

Figure 9: Time-CO curve of different hydrogen mole
fractionFig.10 is the maximum values of mainelementary reactions rate. As shown in Fig.10, thereaction rate of each elementary reactions increase
with the increase of hydrogen concentration, sohydrogen can improve mail elementary reaction rate
in if there are some hydrogen in methane-air mixture.

if there are hydrogen in it. For example
H2+M=H+H+M, O+H2=H+OH and H+O2=O+OH et
al.. These branched chain reactions make the mole
fraction of free radicals O, OH and H increase ingeometry level, and will accelerated the explosion.
Therefore, induction period of explosion will be
shorter if there is some hydrogen in methane-air
mixtureThe mail oxidation path of methane-air
explosion are through the elementary reactions
O+CH3=CH2O+H,
H+CH4=CH3+H2,
H+CH2O=HCO+H2 and OH+H2=H+H2O, the rate ofwhich are influenced by hydrogen and rate of thesereaction will increase with the increase of hydrogenconcentration. Max temperature and pressure are notinfluenced very much by hydrogen because low heatrelease of hydrogen explosion. Besides, some oxygenis used in the process of hydrogen oxidation, whichcauses lower oxidation degree of CH4.

4. CONCLUSIONS(1) Main oxidation path of methane-air explosion
is CH4-CH3-CH2O-HCO-CO-CO2. Except for 106
elementary reactions which nitrogen oxides
participate in, there are 175 heat release reactions and
44 heat absorption reaction during the process of gas

Figure 10: Maximum rate of main elementary reaction ofdifferent hydrogen mole fraction

3.2 Effect of hydrogen to gas explosion
Gas explosion which is a kind of special reactionis the chain reaction, and is also called the linked
reactions. These reactions include free atoms orradicals. Free radicals are unpaired electron atoms orgroups. Besides, it has a highly reactive chemical
speciation, which can react with other molecules andform new free radicals, and the new free radicals
quickly take part in the reaction to produce other new
free radicals. These processes link together closely,
until reactions come to end. Chain reactions include
the straight chain reaction and the branched chain
reaction. Gas explosion is branched chain reaction.
In the process of explosion, breakup reaction are
H+CH3(+M)=CH4+CH3(+M) and HO2=O2+CH4, thisreaction forms actively free radicals which can causes
and accelerates explosion reaction, but rate of the two
chain initial reaction are slow, so the gas explosion
needs a certain induction period. The oxidation rateof methane to form hydrogen is slow, because CH4need dehydrogenation at first, then through a series of
elementary reaction to form hydrogen. The gas
explosion branched chain reaction will be accelerated

explosion. HCO+O2=HO2+CO 、 O+CH3=H+CH2O
and CH3(+M)=C2H6(+M) are top three heat release
reactions.
(2) If there are some hydrogen in methane-air
mixture, branch chain reactions O+H2=H+OH andH+O2=O+OH will be accelerated in the process of
explosion, and will produce more active free radicals,
which will accelerate other main elementary
reactions. Rate of main reaction of explosion will be
increased(3)Hydrogen influences induction period of
H2/CH4 /Air explosion greatly. And with the mole
fraction of hydrogen increase, the induction period
will be shorter. But hydrogen has little influence on
max temperature and pressure.

5. ACKNOWLEDGEMENTS
This research is supported by National Natural
Science Funds of China (51304212). The authors
would like to express their gratitude to thefoundation.

6. REFERENCES
Guo Y L. (2002) Abnormal effect on safety
production of coal seam gas component, Journal of
Longyan Teachers College, Volume 20, NO. 3, pp. 9
Hu R, Wu X H, Hu Y Y, (2010)
Compartmentalization of Explosive Morphology andWaveforms of Multicomponent Gas Mixture620

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Consisting of H2, CO, CH4 and Air, Acta Chimica
Sinica, Volume 68, No. 7, pp. 623-632
Jia B S; Li C M; Hu R X. (2016) Study on
Synergistic Effect Mechanism of CO, H2 mixed gas
on Methane Explosion, World Sci-Tech R & D,
Volume 38, No. 1, pp. 35-39
LI B Q. (2012) Gas Explosion Mechanism andControl Technology in Goal Mines, China Universityof Mining and Technology Press, Xuzhou, 468 p.
Li D, Zhang Q, Ma Q J, Shilei Shen. (2015)
Comparison of explosion characteristics betweenhydrogen/air and methane/air at the stoichiometricconcentrations, international journal of hydrogenenergy, Volume 40, pp. 8761-8768
Li Q Z, Lin B Q, Dai H M. (2012) Explosion
characteristics of H2/CH4/air and CH4/coal dust/air
mixtures, Powder Technology, Volume 229, pp. 222228
LI Y H. (2011) Reaction Kinetics Characteristic
Research on chain Reaction Mechanism of Gas
Explosion in Enclosed Space, Liaoning Technical
University, Anshan, 77 p.
Li Z H, Lin B Q, Zhang L J, Pan S K, He Y H.
(2008) Effects of Hydrogen Production on Gas
Explosion, Journal of China University of Mining &Technology, Volume 37, No. 2, pp. 147-151
Luo Z M; Lin J J; Guo Z C. (2015) Influence ofVarious other Flammable Gases in Coal Mine on
Explosion Limits of Methane, China Safety Science
Journal, Volume 25, No. 1, pp. 91-97
Mahdi F, Guo X L, Chen Z. (2016) The
explosion characteristics of methane, hydrogen andtheir mixtures: A computational study, Journal of
Loss Prevention in the Process Industries, Volume
40, pp. 131-138
Ma Q J. (2015) Multicomponent Gas Explosionin Confined Space and the Mechanism of Eplosion to
Combustion Transition. Beijing Institute ofTechnology, Beijing, 113 p.
Pan S K, Li Z H, Lin B Q. (2008) Experimental
Studies on the Effect of Hydrogen and Heavy
Hydrocarbon on Lower Explosion Limits of Gas,
Journal of Hunan University of Science &Technology (Natural Science Edition), Volume 23,
No 3, pp. 23-27
Peters N. (1985) Numerical and asymptotic
analysis of systematically reduced reaction schemes
for hydrocarbon flames, Proceedings of the
Symposium, Volume 241, pp. 90-109
Ren S R; Li H K; Li L B. (2013) An
Experimental Study of Effects of Inert and Special
Flammable Gases on Methane's Explosion
characteristics, Natural Gas Industry, Volume 33, No.
10, pp. 110-115
Shrestha S.O., Karim G.A. (1999) Hydrogen as
an Additive to Methane for Spark Ignition Engine

Applications, International Journal of Hydrogen
Energy, Volume 24, No. 6, pp. 577-586
Stephen R T. (2011) An Introduction to
Combustion Concepts and Applications(Third
Edition), McGraw Hill Higher Education, New York,752 p.
Xiao Y, Ma L, Wang Z P. (2007) Law of Index
Gases Adsorption and Condensability of Coal
Spontaneous Combustion, Journal of China Coal
Society, Volume 32, No. 10, pp. 1014-1018
Yu B, Wang Y A. (2005) Manual of Coal MineGas Disaster Prevention and Control andUtilization(Revised Edition). China Coal Industry
Publishing Home, Beijing, 789 p.
Zhang G J. (2010) Ventilation and safety. China
University of Ming and Technology Press, Xuzhou,
456 p.
Zhang L J, Li Z H, Lin B Q. (2009) The
Influence of Oil Gas on Gas Explosion, Journal of
Hunan University of Science & Technology(Natural
Science Edition), Volume 24, No. 1, pp. 18-21
Zhou S. (1999) The Theory of Gas Flow andStorage in Coal Seams. China Coal Industry
Publishing Home, Beijing, 195 p.

621

ISMS 2016

Paper No. 131
Drilling escape and rescue system in Wangjialing coal mine
Zhiling Huang*, Longzhe Jin, Yuntong Ma, Hongmin Zhu

Civil & Environment Engineering School, University of Science and Technology Beijing, Beijing, China

ABSTRACT
Many problems are faced in the construction of emergency refuge systems, including the poor reliability of hedging
facilities, the contradiction between hedge and escape, the high time consumption, high cost, and the big risk ofdrilling rescue technology. Shaft drilling escape and rescue systems are a combination of emergency refuge
technology and drilling rescue technology. The key parameters of drilling escape and rescue systems are tested
through man-loading and live sheep lifting experiments. Key parameters include no-supply guarantee time, response
time, and human survival environment. This paper also examines the comfort and physiological parameters ofexperimenters and the influence drilling has over refuge chamber air supply systems.
KEYWORDS: mine shaft; emergency rescue; escape drill hole; emergency refuge; lifting experiment

1. INTRODUCTION
Ever since 33 miners were rescued from a 700mdeep shaft 69 days after a coal mine accident inChile, countries with mining industries have paid
great attention to the construction of undergroundhedging facilities. Continuous improvements infacilities and technology have been made. Although
existing hedging facilities can provide trapped miners
with hedge for some time after an accident happens,
they cannot guarantee a successful rescue. There arelimitations to the protective capabilities, and thecontradiction between hedge and escape still exists.
Drilling rescue technology has recently become
an emergency rescue method for coal mine accidents.
It was adopted and resulted in success for the 2002
US Quebec Creek mine water penetration accident
and the 2010 Chile coal mine accident. Ground andunderground drilling, drainage, delivery of fresh air,and a liquid diet were adopted in the 2010 Shenhua
Camel Mountain and Wangjialing mine water
penetration accidents, with good effect. However,many of the current drilling rescue technologies canonly be done after an accident occurs, and are timeconsuming, high in cost, and risky. Most of theexisting studies aim at problems like the accuracy ofafter-accident quick-hole and drilling.
This paper examines the combination of
emergency refuge and drilling technologies toconstruct a shaft drilling escape and rescue system
and realize miners’ safe refuge and quick andefficient rescue. What’s more, key parameters likeno-supply guarantee time, response time, and humansurvival environment are studied through manloading and live sheep lifting experiments.

*Corresponding author – email : bkdhzl@163.com

2. CONSTRUCTION OF WANGJIALINGDRILLING ESCAPE AND RESCUESYSTEM
2.1 System Constitution
The drilling escape and rescue system iscomposed of the self rescuer, refuge chamber, supply
drill hole, escape drill hole, vehicle mobile supply
station, emergency rescue vehicle and emergency
rescue capsule. It is closely connected to six systems
and is not dependent on any existing systems. The
refuge chamber is connected to five systems, and istherefore is facilitated with exclusive monitoring,
compressed-air, and a water-supply system by thevehicle mobile supply station, as seen in Figure 1.

Figure 1: Composition of system.

The system is based on the refuge chamber. A
φ244.5 mm supply drill hole is set up in chambertransition zone. Air-supply, water-supply, electricitysupply, and communication pipes are installed in the
supply drill hole. A φ790 mm escape drill hole is set
up in the survival zone. A vehicle mobile supply

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

station, emergency rescue vehicle, and rescue capsule
are deployed on the ground.
The vehicle mobile supply station has many
functions, including air-supply, electricity-supply,
communication, and lighting. Its output interface isconnected to the supply drill hole inner pipe. The
emergency rescue vehicle is a unification of a winch,
longmen frame, Jack, monitoring system, andoperating board. It boasts a hoisting height of 500 m
at maximum and a lifting speed of 1.5 m/s. The
rescue capsule is a cylinder structure of 540 mm indiameter whose main material is Q345 steel. It boasts
multiple functions like monitoring, communication,
emergency oxygen supply, and emergency treatment.
2.2 System Operating Principle
In the case of a sudden accident underground,the staff should be evacuated from the wellhead using
an established route to avoid the disaster area. The
priority in case of a difficult situations should be
evacuation to the refuge chamber, and entry into therescue capsule should the need arise.
It is the ground command center’s responsibility
to organize rescue personnel from the wellhead tocarry out rescue operations, as well as arranging
personnel and rescue equipment to quickly drill theground, in order to get the indoor refuge personnel
from the chamber to the ground in time.
Under the premise of determining theenvironmental
safety andthe surrounding
environment of the underground and the tunnel,
rescue workers can be arranged from the borehole
into the refuge chamber, improving the efficiency of
the rescue.

3. HOLE RESCUE SYSTEM EXPERIMENT
3.1 General Situation of Refuge Chamber in
Wangjialing Coal Mine
The Wangjialing refuge chamber is located in
the 20106 working face of the outer auxiliarytransport roadway between the machine and the big
Lane. It has a rated service number of 100 people.
The tunnel section has a 4 x 2.8m rectangular crosssection. Both ends of the transition region are 9 m,
and the living area is 36.5 m and space size is 410 m3.
3.2 Test Instrument
The chamber internal oxygen concentration,
carbon dioxide concentration, temperature, andhumidity are tested with CD7 type, which is seven in
one multifunctional environment parameter sensor.
The wind speed was measured by JFY-4 ventilationand multi parameter detectors. Noise was tested via a
AWA6270 type noise analyzer. The blood pressure
and the pulse produced from a laboratory test areused in the ABP-A091V type multifunctional
electronic blood pressure meter.
3.3 Experiment Process
There were 100 experimental personnel in thelaboratory. The escape drill used live sheep toenhance the simulation. The tests were carried out for
8 hours and divided into three stages:
1) 4 h no supply experiment - at this stage, there
is no oxygen supply and carbon dioxide removal in
the chamber. The escape hole and refuge chamberback to the outlet are closed.
2)1 h oxygen supply experiment by drilling - inthis stage, the ground supplies the wind by drilling,
and air supply is set to 300 m3/h;
3）3 h lift up living creatures test - in this stage,
the experiments are carried out by using the escapedrilling and ground lifting equipment.

4. ANALYSISRESULTS

OF

EXPERIMENTAL

4.1 Analysis of Environmental Parameters in Refuge
StationThe changes of oxygen concentration, carbon
dioxide concentration and temperature-humidity inthe refuge chamber during the experiment are shownin Figures 3 and 4.

Figure 2: Emergency rescue process based on borehole
rescue system.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

1.3 m, which is also the ear height whenexperimenters are seated. From Figure 6 we can seethat when air supply volume is 600 m3/h, themaximum noise intensity is 102.3 dB, and noise
intensity is mainly in the range of 50-70 dB.

Figure 3: Change of oxygen and carbon dioxide
concentration in refuge station during experiment.

Figure 5: Environmental noise inside refuge station when
air supply volume was 600 m3/h.

Figure 4: Change of temperature and humidity in refuge
station containing experimenters.

By analyzing the changes of environmental
parameters inside the refuge station, we can conclude
that:1） System support time without any supply is
longer than 4h. In the first 4 hours of the experiment,
100 individuals exercised in an isolated refuge station
with no supply. During this time, oxygen
concentration in refuge station reduced from 20.6%
to 18.7%, carbon dioxide concentration increased
from 0.07% to 1.34%, and temperature rose from295.45 K to 297.05 K. These parameters are within
the safety range for human bodies.

4.2 Analysis of Environmental Parameters Inside
Rescue Capsule
The changes to the environmental parametersinside the rescue capsule during the lifting and falling
process are shown in Figures 6 and 7, respectively.
From Figure 6 we can conclude that during the lifting
process, the concentration of oxygen and carbon
dioxide inside the rescue capsule is similar to that offresh air with less fluctuation, while the change oftemperature is influenced by the temperature the ofrefuge station and ground of drilling.
Tests of noise in the rescue capsule (which is
unloaded and loaded with sheep many times during
the lifting and descending process indicate that noise
intensity is mainly in the range of 45-70 dB, and the
maximum value is no more than 115 dB, which isshown in Figure 8. The noise intensity in the rescue
capsule with sheep is slightly less than that without
sheep.

2 ） An air supply volume of 0.05m3/min perperson can satisfy survival needs. During the drilling
and air supply process, which is the second stage ofthe experiment, when the volume of air supply is 300
m3/h (0.05 m3/min per person), oxygen concentration
increases from 18.7% to 20.8%, carbon dioxide
concentration reduces from 1.34% to 0.04%, andtemperature decreases to 295.65 K in 60 min.
The results of noise measurement in the refuge
station are shown in Figure 5. The height of themeasure point from the floor of the refuge station is624

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 6: The change of temperature inside rescue capsuleduring lifting process.

levels were then calculated according toquestionnaires and the results are shown in Figure 10.
In Figure 10, -2, -1, 0, 1, and 2 represent very
uncomfortable, uncomfortable, average, comfortable,
and very comfortable, respectively. From Figure 9 we
can know that most individuals felt comfortable andsatisfied with the survival environment of the refuge
station. Even after the 4 h experiment without any
supply, an uncomfortable reaction does not occur
among individuals and few of them feel very
uncomfortable.

Figure 7: The change of temperature inside rescue capsuleduring falling process.

Figure 9: Comfort levels in experiment.

10 other individuals were randomly selected tohave their blood pressure and pulse measured 0.5 h,
3.5 h and 6.5 h after the beginning of the experiment.
The results are shown in Table 1. From Table 1 wecan see that the blood pressure and pulse ofexperimenters showed no abnormal phenomena.
During three measurements, the average value ofblood pressure was 130.1/88.5 mmHg, and that ofpulse was 71.3.
There were no abnormal phenomena for the
sheep, except for two sheep crying and panicking due
to fear after each sheep went through the lifting andfalling process 4 times. Video monitoring systems
showed that sheep behaved quietly with no obvious
agitated activity.

Figure 8: Noise intensity in rescue capsule when lifted.

4.3 Analysis of Experimenters’ Comfort Levels andState of Sheep
Several questionnaires were conducted among
50 randomly selected experimenters 0.5 h, 3. 5h and6.5 h after the beginning of the experiment. The
questionnaires included questions probing thesatisfaction with environmental comfort levels andstatus of individual physical conditions. Comfort
Table 1. Results of blood pressure and pulse measurement.
Blood Pressure/mmHg

Pulse/times per minuteSystolic Blood Pressure，SBP

Diastolic Blood Pressure，DBP

Min

Max

Avg±StdMin

Max

Avg±Std

Min

Max

0.5h

123

138

129.9±4.86829688.6±4.48

65

80

3.5h

125

135

130±2.98849488.1±3.03

67

81

6.5h

124

135

130.4±3.63849788.8±3.65

65

78

Time

Average

130.1

88.5

Avg±Std71.2±5.25
71.9±4.61
70.8±4.69
71.3

625

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.4 Tests of System Response Time
Response and preparing time of the emergency
lifting truck were tested and the results are shown in
Table 2. From the time workers inside the refuge
station sent distress signals until the time thatemergency lifting trucks and the mobile supply
station arrived at the ground of drilling holes,

debugged the system, and prepared for rescue, the121 min had elapsed. This is much less than survival
time without any supply. Additionally, test results ofhoisting speed indicate that it takes approximately
14min to lift one person, in which fall time makes up
7min and hoisting time makes up 6.3 min.

Table 2. Measurement of system response time.
NO.
Project
1
Time consumed for mobile supply station to arrive
2Time consumed to prepare for system
3Time consumed to preheat diesel generating set and screw air compressor
4Time consumed to set up gantry
5
Average one-way fall time of capsule
6
Average one-way lift time of capsule

4.5 Influence Borehole Has on Air Supply System
In order to study the borehole’s influence on the
air supply system, wind speed of the return air outlet
and borehole were tested. The results are shown in
Table 3. Negative wind speed indicates that windflows from the refuge station to the ground ofdrilling.

Time/min
74
23
13
11
7
6.3

As it is illustrated in Table 3, when return air
outlet is open, escape drilling holes can work as air
supply holes, with wind speed at 1.61 m/s. When
return air outlets are closed and the compressed air
supply is open, escape drilling holes can work as
return air outlets, with wind speed at 0.25 m/s underthe volume of 300 m3/h and at 0.56 m/s under thevolume of 600 m3/h.

Table 3.Wind speed of borehole and return air outlet under different working conditions.
equipment condition
Compressed air
supplyNone
None
Volume of 300 m3/h
Volume of
600 m3/h

wind speed（m/s）

ClosedOpen
Open
ClosedBorehole
Open
Open
Open
Open

ClosedOpen

air outlet

5. CONCLUSIONS
From previous experiments and fromsummarizing the authors’ analyses, the following
conclusions are drawn.
(1) The proposed drilling escape and rescue
systems consista of emergency refuge facilities,
which includes a self-rescuer, refuge chamber, andrefuge station, and drilling rescue facilities, which
include a rescue capsule, emergency lifting truck,
mobile supply station, and escape borehole. The
process of emergency rescue based on the system
was studied. The system can actualize safety and thehigh efficiency of escape and rescue in catastrophic
conditions.
(2) According to experiments with individuals,
the system support time with no supply was 4 h andtime to debug and prepare the system was about 2 h.
Individuals in the refuge station could get rescued
with no supply outside.

Bore-holeoutlet1

outlet 2

0.05
1.61
1.43
-0.25

—
7.24
6.8
—

—
7.33
8.28
—

-0.56

—

—

(3) An air supply volume of 0.05 m3/h perperson could satisfy survival needs for individuals in
the refuge station. When air supply volume was 0.05
m3/min per person, oxygen concentration rose from
18.7% to 20.8%, and carbon dioxide concentration
reduced from 1.34% to 0.04% in 60 min.
(4) Through the lifting experiment with sheep,
environmental parameters inside the rescue capsulewhen it was lifted in the rescue borehole were
measured. The reliability of animal lifting by adrilling escape and rescue system was verified.

6. ACKNOWLEDGEMENT
I would like to express my gratitude to all those
who helped me during the writing of this thesis.
My deepest gratitude goes first and foremost toProfessor Jin Longzhe, my supervisor, for his
constant encouragement and guidance. He has
walked me through all the stages of the writing of626

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

this thesis. Without his consistent and illuminating
instruction, this thesis could not have reached its
present form.
Last my thanks would go to my beloved family
for their loving considerations and great confidence
in me all through these years. I also owe my sincere
gratitude to my friends and my fellow classmates
who gave me their help and time in listening to me
and helping me work out my problems during thedifficult course of the thesis.

7. REFERENCES
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(2012).Study on oxygen supply system of mine
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system in Xu Zhuang Coalmine of Da Tun[J]. Journal of Liaoning Technical University(Natural Science),Volume 2,pp.53-57.
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627

Paper No. 134

ISMS 2016

Effects of immediate roof thickness on lower sub key strata movement in endsof large mining height panel
Chuang LIU a, Huamin LI a,*, Dongjie JIANG a, b, Huigui LI a, Junfa FENGaabSchool of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, Henan, Peoples R China
Department of Safety Science & Engineering, Henan Institute of Engineering, Zhengzhou 451191, Henan, Peoples R China

ABSTRACT
Based on the 58 geological drill holes around panel 42105 in the Ordos coal field, a 3D geological model and 2D
numerical model with real strata conditions were established. With the models, the effect of the immediate roof
thickness on the ground pressure as well as the roof movement patterns under the varying immediate roof thicknesses
were explored. Mechanical models of the lower sub key strata under differing immediate roof thickness wereachieved through the use of field measurement, theoretical analyses, and numerical simulation methods. Meanwhile
the effect of immediate roof thickness on lower sub key strata movement in ends of large mining height coal faces
was studied. The discrimination formula of the movement patterns was deduced. The results show that when theimmediate roof is relatively thick, the fractured lower sub key strata can be hinged to form a stable “Voussoir Beam”
structure, which makes the ground pressure not severe and the shield pressure small in the ends of the panel. Whenthe immediate roof is thin, the arc triangular of the lower sub key strata in the ends of the panel loses mechanicalcontact to the caved immediate roof and assumes a “Cantilever Beam” structure, which makes the ground pressure
severe and shield pressure large in the ends of the panel.
KEYWORDS: immediate roof thickness; large mining height; lower sub key strata movement; ground pressure

1.

INTRODUCTION

The mining object is an opaque and changeable
geological body. Due to the large spacing among
geological exploration drill holes, the changes in rockstrata thickness are difficult to find before mining
begins. There are many scholars who research the
movement patterns of roof strata, mostly based on
simplified geological conditions with equal thickness(Yuan et al. 2015; Yang et al. 1999; Fu et al. 2009;
Wang et al. 2015; Wang et al. 2014). However, in actual
geological bodies, the rock strata are often not of equal
thickness. Along with changes in the geologicalconditions, the movement patterns of the roof strata
also change. Thus, it is not accurate to predict the roof
strata movement patterns of the whole working faceaccording to data from a single borehole, especiallywhen the thickness of the rock strata varies greatly.
To address this issue, a new method of GMS ANSYS - CDEM modelling and calculation is put
forward, in which a relatively accurate geologicalmodel is established based on the geological drill holesdata. In order to master the change of the thickness ofrock strata, study the determination and prediction of
the movement patterns of the roof strata and themodelling of the numerical simulation, the following
steps were followed. Firstly, the 3D geological model
was established by using the GMS 3D geologicalmodelling software according to the geological drill
hole data. Then, the geological model was imported*Corresponding author-email: lihuamin2007@163.com

into the ANSYS software to complete the meshgeneration. Finally, the node data information of themeshed model was imported into the CDEM simulation
software for calculations. As a result, this method
makes up for the shortage of CDEM simulation
software in modelling and realizes a quick and accurate
method for modeling complex geological bodies. The
ANSYS - CDEM - GMS modelling and simulation
method can reflect the change trend of the rock strata
thickness in complex geological bodies, which greatly
improves the accuracy and reliability of numericalsimulations.
The existing typical patterns of rock strata
structure are the “Transferring Beam” structure (Songet al. 2002), “Voussoir Beam” structure (Qian et al.
1995, 1998) and “Key-Layer” theory (Feng et al. 2008;
Ju et al. 2011; Shen et al. 2011; Yang 2008). These
theoretical analyses demonstrated the several possible
movement patterns of rock strata under certain
geological conditions. The roof structure is greatly
influenced by the change of the overlying rockconditions and mining technical parameters. For thelarge mining height panel the mining space is relatively
large, leading to a great increasing of the caving andfractured zones of the roof strata. When the thickness of
the immediate roof is not the same, the filling degree ofthe caved immediate roof for the gob will be different.
Eventually, the overlying strata movement patterns andthe ground pressure distribution are changed (Huang3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the rock C and arc triangular A, of which the arc
triangular A is the main part (Yang et al. 2012).
Tailentry of 42104
longwall panel

M

2005; Huang et al. 2004; Wu 2014; Zhang et al. 2013).
Based on the geological conditions of panel 42105 andthe recorded data of shield pressure and the 3D
geological model, the current study researched theformation mechanism of the mechanical structure of thelower sub key strata under the large mining height, anddeduced the calculation formula of the movement
patterns.

Tailentry of 42106
longwall panel

Direction of miningArc
triangular A
Arctriangular B

Rock CRock D
NN

M

Pillar2.

BACKGROUND

Gob ofpanel 42104
Headentry of 42105 longwall
panel

Tailentry of 42105 longwall panel

2.1 Panel overview
The width of panel 42105 is 230 m, with anaverage depth of 440 m. Using the caving coal mining
method, it has 3.7 m cutting height and 3.0 m top coalcaving height. Panel 42105 is covered with the upper
gob of 2-2 coal seam.
2.2 3D geological model
In order to grasp the thickness of the overlying
strata in the 42105 working face, the GMS geologicalmodelling software was used to establish the 3D
geological model of panel 42105 on the base of the 58
geological drill hole data around this panel, and madethe tailgate profile along the advancing direction.
According to the 3D geological model, thethickness of the immediate roof varies greatly. The
immediate roof sandy mudstone along the working faceadvancing direction first follows a thinning and thenthickening trend. The profiles were exported to CAD
format and then the strata thickness was measured. The
immediate roof thickness gradually reduced from 6.2 m
to 4.3 m in the first 280 m. The immediate roof
thickness gradually thickened to 5.6 m during theadvancing distance between 280 m and 350 m. The
thickness of the lower sub key strata changed little,
with an average of 10.2 m.

3. IMMEDIATE ROOF THICKNESS AND
STRUCTURE
In the process of coal mining, the shape andstability of mechanical structure formed by the lower
sub key strata directly affects the distribution of theground pressure in the working face. The typicalresearch findings are the “Voussoir Beam” and“Kichhoff Plate” mechanics models (Qian et al. 1995;
Zhu et al. 1987). According to the breaking rules ofoverlying rock, the periodic fracture rocks of the lower
sub key strata can form the “Voussoir Beam” structurein the middle part and arc triangular structure in the end
region of the panel (Figure 1) (Qian et al. 1998). The
thickness of the immediate roof and lower sub key
strata determine the structure movement patterns of thebroken rocks. The ground pressure in the panel ends
region is mainly affected by the deformation motion of

Figure 1: Schematic diagram of the broken form of the lower
sub key strata.

3.1 Steady rock structure
When the immediate roof is thick, the caved
immediate roof can basically fill the gob. Rock B, C, D,
and arc triangular A form the “Voussoir Beam”
structure, in which the rock C is the key block in the
middle part of the panel. As shown in Figure 2, due tothe hinge relationship among rock A and B, C, D, thesliding and rotational deformation instability will not
happen for arc triangular A.
A
triangurclarAArc
triangular B(a) M-M profileqRock CArc tria

ngularGob of 42104 Headentry of 42105
longwall panel
longwall panel

PillarA

Tailentry of 42105 Gob of 42105
longwall panel longwall panel(b) N-N profile
Figure 2: “Voussoir Beam” structure (thick immediate roof).

3.2 Instable rock structure
When the immediate roof is thin, the caved
immediate roof cannot fill the gob. Arc triangular A
loses the mechanical contact among rock B, C, D, andthe “Voussoir Beam” structure cannot be formed, butinstead turns into a hanging plate between the coalwalls (Figures 1 and 3). Since a structure with carrying
capacity cannot be formed from arc triangular A, thepressure of the rock strata in the ends region is mostlytransferred to the shield and the roof of gateroads.

629

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

When the arc triangular A experiences sliding
instability, the ground pressure in the ends of panel issevere.

a=1( hi − l sin θ )
2

(1)

ql 2
hi − l sin θ

(2)

T=

Extrusion stress at the hinged points can be
determined by:A
triangurclarAArc
triangular Bσ=pq
Arc tr

iangu

lar A

Tailentry of 42105 Gob of 42105
longwall panel longwall panel(b) N-N profile
Figure 3: “Cantilever Beam” structure (thin immediate roof).

3.3 Calculation of roof structure movement
An arch structure is formed after the caving oflower sub key strata. When the hinge at the arch centeris higher than those of the two ends, the rock block canmaintain equilibrium. When the center hinge and thoseat the two ends are in the same plane, the rock block
reaches the state of limit equilibrium, as shown in
Figures 4 and 5. In view of the plastic state of the hinge
point, the contact length of the unit width of the rockmass is a, the failure condition for any rock strata
above the coal seam can be solved and the limit ofsubsidence Δmax determined (Jiang, 2015).
¦ ¤
max
h3

¦ ¤

(1 − i sin θ )q=

K1 (1 − i sin θ ) σ cmFigure 4: Schematic failure of lower sub key strata.

ql

T

2

2i

(4)

2

When the beam is at ultimate fracture span, therelationship between its load q and tensile strength σt
can be determined by:
6l 2
6 K 2 qi 2=
σ t K=
2q
hi 2

(5)

Where:
a= Contact length of broken rock block, m;
θ= Rotation angle of broken rock block, °;T= Horizontal force required to keep the limiting
state, Pa·m;
hi= Thickness of ith rock layer above the coal seam,m;l= Broken interval of ith rock layer above the coalseam, m;q= Weight and load of ith rock layer above the coalseam, Pa;
K2= General value 1/3 ~ 1/2;
n= Ratio of compressive strength σc to tensile
strength σt.
Limit of subsidence Δmax can be determined by:
1 ∆ max =hi 1 −
3nK1 K 2 ∆ hi =m − ( K p − 1) ∑ h

h1

θ

(3)

2qi 2

(6)

Where, Δmax=lsinθ.
After the failure of the immediate roof, thesubsidence of lower sub key strata Δhi can be
determined by:h4

h2( hi − l sin θ )

=

2

2

Rock C

Pillar2ql 2

Where, i=l/hi.
Let the ratio of bearing strength σp to compressive
strength σc be K1, the maximum allowable load q can be
determined by:(a) M-M profile

Gob of 42104 Headentry of 42105
longwall panel longwall panel

T
=
a

Δmax
a
T
hi

l

Figure 5: Limit equilibrium condition when the hinge
contacts of rock blocks are in plastic state.

(7)

Where:
m= Mining height, m;
Kp= Bulking factor;
σci= Compressive strength of ith rock layer above
the coal seam, Pa;∑h= Thickness of the first to (i-1)th rock layer
above the coal seam, m.
Using the overburden strata mechanics parametersof Panel 42105 (Kp=1.25, ∑h=4.1～6.2m), the Δhi oflower sub key strata can be determined between 5.15 m
and 5.68 m.
According to Kong et al. (2010), there is arelationship between the extrusion stress σp andcompressive strength σc of the rock block at the hinge630

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
point: σp=0.36～0.45σc. Generally σp=0.4σc is used.
According to the simply supported beam model, K2=1/3,
the ratio of compressive strength σc to tensile strength σtof siltstone is 12 in panel 42105. Therefore, the limit ofsubsidence Δmax=5.54 m.
Compared to the subsidence of lower key strata Δhi
and the limit of subsidence Δmax, when the immediateroof is more than 4.64 m, the fractured lower sub key
strata can form a stable “Voussoir Beam” structure;when the immediate roof is less than 4.64 m, thefractured lower sub key strata will assume a “CantileverBeam” directly baggy falling form.

lower sub key strata caving, the broken rock can hinge
to each other and form the “Voussoir Beam” structure(Figure 7). Compared to the results of “CantileverBeam” structure, the vertical displacement range of theupper strata and coal seam is relatively small at thistime.

“ Voussoir Beam”
structure

Lower sub key strata
Immediate roof

3.4 Numerical simulation
Based on the 3D geological model established by
the GMS software，a numerical model was built tosimulate the geological cross-section along the panel
advancing direction. The model was 400 m long by 464
m high. The model contained the full overburden
thickness from the coal seam to the surface. The
vertical loading was the full overburden gravity load
and the boundaries of the bottom, left and right sides ofthe model were fixed. CDEM (Continuum-based
Distinct Element Method) software was used to
calculate, in which the Mohr-Coulomb strength
criterion was chosen as the material yield criterion ofcoal and rock mass. By the numerical calculation
results, the change of the lower sub key strata structureduring the mining process was analyzed with the
thickness change of the immediate roof.
(1) Thin immediate roof
When the face has advanced 270 m, the immediateroof is 4.34 m. Simulation results show that the caved
immediate roof cannot basically fill the gob. The arc
triangular of the lower sub key strata in the ends of thepanel lost mechanical contact to the caved immediate
roof. The original lower sub key strata can be formed
with a load-bearing structure due to the increasing ofrotation angle, forming a “Cantilever Beam” structure(Figure 6).

Caved lower sub key strata
Caved immediate roof

“ Cantilever Beam”
structure

4-2 coal seam

Figure 7: “Voussoir Beam” structure (230 m advancing).

4.

SHIELD DATA ANALYSIS

Panel 42105 was equipped with an electric
hydraulic control monitoring system that can
automatically and quickly upload the shield pressure to
the ground control room. Surfer 8.0 was used to draw
the 3D map of the relationship among working face,shield pressure, and advancing distance from June 16th
- 23th (Figure 8).
Since roof pressure usually varies continuouslywith time, time-weighted average pressure (TWAP) is
more appropriate to illustrate the overall conditions of
the shield in a whole cycle and is defined by thefollowing equation (Syd S. Peng, 2013; 2011):
1

=
Pt

1

1

1

(P + P )t + (P + P )t + (P + P )t + (P + P )t
Pt
∑
2
2
2
= 2
i i

tt

a

s

a

b

a

b

c

b

c

d

c

d

（8）

t a + tb + t c + t d

Where, Pi is the average shield pressure during theperiod of ti. In other words, Pt is the ratio of the area
under the pressure variation curve to the total time in amining cycle.
460
440
420
400
380
360
340
320
300
280
260
240
220
200
180
160
140
120
100
80
60
40
20
-0

4-2 coal seam

Figure 6: “Cantilever Beam” structure (270 m advancing).

(2) Thick immediate roof
When the face has advanced 230 m, the immediateroof is 4.81 m. Simulation results show that after the

Figure 8: 3D map of the relationship among working face,shield pressure, and advancing distance.

The TWAP and standard deviation of 100# shield631

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

near the tailgate was analyzed in the panel 42105 from
June 16th - 28th (Table 1). The results show that: (1)The TWAP and standard deviation of 100# shield were
floating large on June 17, 19, 21, 22, (due to theworking face being off production on June 18th, theshields weren’t moved, resulting in great pressure on
the roof), indicating great intensity of the roof strata
activity. In these days, 70% of the all shields opened theyield valve, meanwhile the rib spalling was serious,with an average depth of 0.3 m. (2) When theimmediate roof thickness decreases, the TWAP andstandard deviation increase. On June 22th, theimmediate roof thickness was the smallest and thestandard deviation reached the maximum of 10.90 MPa.
When the immediate roof thickness increases, theTWAP and standard deviation decrease.

Table 1: TWAP and standard deviation of 100# shield at different advancing distance.
Date

Pt/ MPaσ/MPa(Pt+σ)/ MPa

Advancing distance/m

Immediate roof thickness /m

6.16
6.17
6.18
6.19
6.20
6.21
6.22
6.23
6.24

29.39
29.41
37.04
36.02
29.29
29.29
26.58
28.78
28.96

5.38
6.30
7.91
9.87
3.46
6.14
10.90
3.65
5.27

34.77
35.71
44.94
45.89
32.76
35.43
37.48
32.43
34.23

218.6
236.5
239.2(Off production)
250.9
251.7(Off production)
266.0
278.5
289.0
301.6

4.84～4.98
4.64～4.84
4.61～4.64
4.47～4.61
4.46～4.47
4.32～4.46
4.16～4.32
4.16～4.76
4.76～4.92

When the immediate roof is thick, the lower sub
key strata actual subsidence is less than its limit
subsidence, the fractured lower sub key strata can behinged to form a stable “Voussoir Beam” structure. This
structure bears part of its own weight, so that theweight of the rock on the shields is reduced. When theimmediate roof is thin, the lower sub key strata actualsubsidence is more than its limit subsidence. The arc
triangular of the lower sub key strata in the ends of thepanel loses mechanical contact to the caved immediateroof and assumes a “Cantilever Beam” structure.
Therefore, the most weight of the lower sub key strata
through the immediate roof directly acts on the shield,
which makes the shield pressure large in the ends of theworking face.
The influence factors of the shield pressure are
related not only to the thickness of the immediate roof
and the movement patterns of the lower sub key strata,
but also to the shield frame, the advancing speed, andthe mining height. However, the above data analysis
shows that there is a correlation between the change ofshield pressure and the immediate roof thickness. Thatis, when the immediate roof becomes thin, the TWAP
and standard deviation show an increasing trend, andvice versa.

pressure. The following conclusions were obtained:(1) When the thickness of the lower sub key stratachanges little, the immediate roof thickness is an
important factor that affects the structure and theground pressure distribution.
(2) Compared to the actual subsidence of lower
key strata Δhi and its limit subsidence Δmax, whenΔhi<Δmax, a stable “Voussoir Beam” structure can beformed in the fractured lower sub key strata; when
Δhi>Δmax, the lower sub key strata assumes a“Cantilever Beam” structure.
(3) The stable “Voussoir Beam” structure bears
part of its own weight, so that the weight of the rock on
the shields is reduced and ground pressure is not severe,and the TWAP and standard deviation is small. Under
the “Cantilever Beam” structure conditions, the mostweight of the lower sub key strata through theimmediate roof directly acts on the shield, which makes
the ground pressure severe and TWAP and standard
deviation large.

5.

7. REFERENCES

CONCLUSIONSThis paper concentrates on the effect of immediateroof thickness on the lower sub key strata movement in
the ends of panels. A 3D geological model wasestablished and used to deduce the formula of the
movement patterns of roof structure under different
immediate roof conditions, and analyzed the numericalsimulation results and the monitoring data of the shield

6.

ACKNOWLEDGMENT
This research was funded by the Chinese
Natural Science Committee under grant No.
U1261207.

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on the mechanism of the face contacted blocks structure
in overlying strata above the longwall face. Journal of
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Fu, Y., Song, X., Xing, P., Yan, G. and Li, Z.
(2009). Stability analysis on main roof key block in632

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large mining height workface. Journal of the China
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law on key roof and its structure upon mining faceunder thick sandy layer. Journal of China University of
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Huang, Q. and Zhang, P. (2004). Study on dynamic
load distribution on key roof blocks of under thicksandy soil stratum. Chinese Journal of Rock Mechanics
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Jiang, D. (2015). Research on Overburden
Structure and Shields Stability of Fully Mechanized
Top Coal Caving Mining Face with Large Mining
Height. Henan Polytechnic University, 19-21.
Ju, J., Xu, J. and Wang, Q. (2011). Cantileverstructure moving type of key strata and its influence onground pressure in large mining height workface.
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Kong, L., Jiang, F., Liu, J. and Wang, C. (2010).
Relationship between Support and Strata in Extra-thick
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in longwall mining. Chinese Journal of RockMechanics and Engineering, 02:97-106.
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fractures in the overlaying strata. Journal of China Coal
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structural system of roof in fully mechanized top coalcaving. Applied Mechanics and Materials. v 90-93,
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Xuzhou, pp. 310-312.
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Press, Beijing, pp. 131-138.
Wang, J. and Wang, Z. (2015). Stability of main
roof structure during the first weighting in shallow
high-intensity mining face with thin bedrock. Journal of
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Wang, J., Yuan, Y., Tu, S. and Li B. (2014). Roof
structure characteristics in fully mechanized coalface
with large mining height and reasonable loading of
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31, n 4, 512-518.
Wu, F. (2014). Study on the Law of Roof Broken
and Instability and the Control of Mining Height Fully

Mechanized Mining in Thick Coal Seam. China
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Mining & Safety Engineering, 01:26-32.
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633

ISMS 2016

Paper No. 150

Study on the performances of a protective door in coal permanent refuge
havensGao Na*, Jin Long-zhe, Fan Lin-yu, Shen Jie, Wang Wei-xiang, Liu Jian-guo
Civil and Environmental Engineering, University of Science and Technology Beijing, Beijing, China, 100083

ABSTRACTAn effective protective door for an underground refuge haven must have anti-explosion properties, anti-pressure
properties, and sealing capabilities. In this study, Wulan Coal Mine’s situation and the technical requirements for theprotective door in the permanent coal refuge haven were analyzed and a numerical simulation analysis for the antiexplosion performance was performed. The materials, structure, and the sizes of the protective door were confirmed.
Further, two experiments on the protection and waterproof abilities of the door were conducted. The results showedthat a 15 mm thick 16 manganese steel plate door meets anti-blast and economical requirements. In addition, amanual wedge-shaped lock structure, a single-cast door wall, and a welding steel supporting structure can satisfy theairtight sealing and anti-pressure requirements. In the numerical simulation of the blast effect, it was observed thatthe maximum displacement was at the centre of the door, and the region of the highest stresses was around the door.
The protective door could bear a 1 MPa explosion impact, and it could withstand a 1.86 MPa static pressure loadwith a deformation of 5.8 mm. Further, the door maintained good sealing performance until the hydraulic pressure
exceeded 1.6 MPa with a deformation of 14 mm.
KEYWORDS: Refuge haven; protective door; anti-blast; finite element analysis; performance test

1. INTRODUCTION
Coal is an important basic energy source, andcoal reserves account for more than 85% of China’s
energy resources (Wang and Ji, 2012). At present,
Coal mining in China is mainly manual andmechanical. The underground mining environment iscomplex, therefore, mining safety has become asignificant concern. Moreover, owing to the lack ofmechanization, mining efficiency is low. In order toensure the safety of coal miners, the research on
refuge havens is of great significance both
domestically and globally. The research on refuge
havens in developed countries such as the UnitedStates, Canada, Australia, South Africa, and others
started early, and has achieved fruitful results onunderground haven refuge sites, basic protection
parameters, and internal oxygen supply for theminers. Further, they have successfully rescued
several miners via refuge havens. In August 2010, theState Administration of Coal Mine Safety in China
issued on the construction and improvement of coalmine safety hedging "six systems". This document
provides a complete set of requirements for theconstruction of the underground safety hedging
systems. Based on the most common types ofunderground accidents, a refuge haven should include
features such as anti-fire, anti-blast, sealing isolation,and oxygen supply (Rick and Graham, 1999). In*Corresponding author – email :aggie198308@163.com

China, research on refuge havens is in its infancy. At
present, China has formed a research system thatcomprises research institutes, universities, andenterprises. This system has progressed on the basisof the international research achievements, and has
gradually developed equipment needed for refuge
havens and the related technical requirements (Sun,2011; Li, 1989; Zhao and Wang, 2007; Michael,
2007; Yang, 2010).
However, studies on protective doors for fire
protection, explosion protection, and door sealing are
not comprehensive. In this study, the protective door
in the Wulan Coal Mine refuge haven is analysed.
The stress conditions on the protective door surface
are calculated, and the door sealing and blast
protection requirements are analyzed to determine therequirements for the door plank material, overall
structure, lock structure, supporting structure, and thedoor size. Further, the capabilities of the anti-blast,anti-stress and waterproofing for the refuge havenprotective door are determined through simulationsof the anti-blast, and experiments of anti-pressure,and waterproofing on the door. This study provides
evidence and verification for the protective featuresof the protective door under different conditions. The
conclusions made provide important reference tobuild a complete life protection system and support
related technical research.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

2. MATERIALS,DIMENSIONSSTRUCTURES,AND

2.1 Protective door materials
Blast-proof materials commonly used forprotective doors include Q235 steel, Grade 45 steel,
Grade 70 steel, and 16 manganese (16Mn) steel. The
mechanical strengths of these materials are listed inTable 1. Among them, Grade 70 steel has thestrongest yield strength and can withstand greatpressure; however, the product is easy to break,which leads to door deformation. The anti-pressure
ability of Grade 45 steel is superior to that of Grade
70 steel, but its corrosion resistance is lower thanother materials. The anti-pressure and corrosion
resistance abilities of 16Mn steel outperform Q235;
however, it is more expensive than other materials.
After a comprehensive analysis, for the Wulan Coal
Mine refuge haven, it was decided that the 16Mn
steel would be used as the material for the protective
door plank of the refuge haven, Q235 for the rest
materials of the door structure, and the door surface
would be sprayed with fireproof and corrosionresistant paint.
Table 1: Door materials to anti-blast strength comparison.
Material
Yield Strength
Modules of(MPa)
Elasticity (GPa)
Q235
235
210
45 steel
355
204
70 steel
420
210
16Mn
350
206

2.2 Protective door shape
The Wulan Coal Mine refuge haven was built in
the wall of a tunnel, therefore, the pressure that thedoor withstood came from the blast wave with a side
impact. The door plank could be flat or curved
according to the blast shock. The stress analysis iscarried out as follows.
Flat door force analysis: the stress process of aflat door is shown in Figure 1. The impact of the
explosion is calculated by the following formulas(Yang, 1996; Jian, 2003).
R =D =X 2 + Y 3 = 0.5PS 2 − 2cos2α （1）（2）
0.5PS 2 − 2 cos 2α= P sin α 2 − 2 cos 2α
0.5S / sin α

where, α is the angle between the incident direction
and the flat door plank,°; β is the incident angle andreflection angle of the shock wave,°; P is the average
stress of the shock wave on the flat door, Pa; S is thesurface area of the door, m2; X, Y are the reaction
and the perpendicular reaction to the shock wave, N;
R is the total reflection, N; D is the equivalent stressthat the door can bear, Pa. According to formulas (1)and (2), when α has an optimal value of π/2, R is P·S.
When D is 2P, the reflection and equivalent stressdecrease as α increases.

Figure 1: Flat protective door pressure handling

Curved door force analysis: the stress process ofa curved door is shown in Figure 2. The impact of the
explosion is calculated by the following formulas(Luo et al, 2007; Lin et al, 2008).

R =X2 + Y2 =

D =

5
R
P
=
3π
πS

5
PS
3

（3）
（4）

where, α is the angle between the incident direction
and the tangential direction of the curved door
plank, °; β is the incident angle and reflection angle
on the tangential direction of the curved door plank, °;P is the average stress of the shock wave on thetangential direction of the curved door plank, Pa.

Figure 2: Curved protective door pressure handling.

By comparing the flat door with the curved door
in terms of the explosion impact and equivalent stress,
it can be seen that both the curved doors and flat
panels meet the blast-proof requirements. In
particular, the curved door received 25% less impact
than the flat door, and the equivalent strength
increased to approximately 50%. However, theproduction of a curved door requires a specialized
mold, the processing is more complex, and the cost is
relatively high. Therefore, the Wulan Coal Mine
eventually selected the flat door for its permanent
refuge haven.

2.3 Sealed locking structure635

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The sealed locking structure of a protective door
determines its sealing capability. Common sealing
methods include pressure, hydraulic, electric, andmechanical locks. After considering the undergroundpower, air environment, and required door reliabilityof the Wulan Coal Mine, the mechanical manual lock
structure shown in Figure 3 was selected for the
refuge haven. The structure adopted the door and four
wedge locking devices on the frames. Sealing iscarried out by manually rotating the lock against thedoor frames, with the fire retardant material applied
between the flashboards.

The height of the protective door should be
decided based on the worker’s height and the size ofthe equipment. It should enhance the door’s anti-blast
function, yet reduce its exposed area. Through datacollection, analysis, and calculations, the averageheight of the Wulan Coal Mine underground digging,mining, installation, withdrawal, and other operating
personnel was determined to be 1730 mm. The
largest equipment was the oxygen control device,whose dimensions were 550 × 280 × 1250 mm.
Therefore, the protective door height of the Wulan
Coal Mine permanent refuge haven was set to 1600mm.
(2) Protective door width
Through data collection, analysis andcalculations, the average shoulder width of theunderground workers was determined to be 700 mm.
The oxygen purifiers have a maximum width of 600
mm. The width required for equipment transport wasalso considered, and the width of the protective door
was finalized to 950 mm. The overall dimensions of
the protective door are as shown in Figure 5.

Figure 3: Sealing structure of the protective door.

2.4 Supporting structure
In order to increase the anti-blast ability of theprotective door, the overall connection of the door to
the wall must be strengthened. To do this, the Wulan
Coal Mine permanent refuge haven adopted a weldedsteel support structure, as shown in Figure 4, for its
protective door. The protective door usedferroconcrete, and the wall used concrete casting tocreate an overall anti-blast airtight seal. When an
explosive blast strikes the protective door, the impact
would pass through the door supporting structure andbe dispersed throughout the wall, which diminishes
the effect of the impact (Tian, 1997).

Figure 4: Protective door supporting structure.

2.5 Protective door dimensions
The protective door dimension of the Wulan
Coal Mine refuge haven included the door’s height,
width, and thickness.
(1) Protective door height

Figure 5: Protective door dimensions.

(3) Protective door thickness
The thickness of the protective door in the
Wulan Coal Mine refuge haven was determinedbased on the incident pressure, reflecting pressure,and static load pressure of the blast (Zhu et al., 2013).
The reflecting pressure of the protective door and thestatic load pressure were determined by the incident
pressure. The door thickness (Silvestrini et al, 2008)
was calculated using the following formulas.
0.196r（5）∆Pλ = K( M 2 − 1)
r +1
2

D =

6∆Pλ
KK d B（2∆Pλ +）
2σ D
0.7 + Pλ（6）636

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Where, K is the safety factor; r is the air specific heatratio; m is the ratio of the blast wave speed to themean speed of sound; Kd is the dynamic coefficient;
B is the width of the protective door, σD is the pulling
stress on the door, and ΔPλ is the incident pressure.
The calculation result showed that the door thickness
was 13.2 mm; therefore, the door thickness was set as
15 mm.

the door could take and its deformation conditions
were recorded.

3. ANTI-EXPLOSIONNUMERICALSIMULATION ANALYSIS
Based on the door size and material study, 15mm thick 16Mn steel was selected for the protective
door. For the 16Mn steel, the modulus of elasticity is
206 GPa, Poisson's ratio is 0.31, and the yieldstrength is 350 MPa. A physical model was of aprotective door was developed and meshed throughfinite element numerical simulation analysis. The
door load was set to be 1 MPa. The force anddisplacement on the door were simulated by software
ANSYS. Then, the material, thickness, and structureof the protective door in the Wulan Coal Mine refuge
haven were assessed to ensure they met theprotection requirement (Liao and Ding, 2009; Tan etal., 1997; Lu and Jian, 2003).

4. EXPERIMENT
4.1 Static pressure test
The test door was installed in a doorframe madewith ferroconcrete, and it was placed at the groundlevel with the door suspended in the air. A 10 cm
layer of fine sand was placed on the door surface, andit was loaded with high-pressure gasbags to distributethe weight pressure. Next, the airbags were inflated
and a static pressure load was placed on the door. At
the same time, a CYG712-5 MPa type soil pressure
sensor and a BWG2-100 mm displacementtransducer were used to measure the door pressureand deformation.
4.2 Airtight and waterproofing test
Two test doors were welded to both ends of awater container, and it was ensured that the welding
was sealed and leak proof (as shown in Figure 6).
Next, at the bottom of the container, a water valve,pressure gauge, piping, and pressure pump wereplaced, and a pressure gauge and an air vent wereplaced on the top to measure internal pressurechanges, i.e., the pressure handling capacity of thedoor. Then, water was added to the sealed container,
thus adding pressure into the container. The door
deformation and the pressure at the top were
measured until the door experienced plastic
deformation. Finally, the level of hydraulic pressure

Figure 6: Protective door and sealed container for water
proofing test.

5. RESULTS AND DISCUSSION
5.1 Numerical simulation analysis(1) Protective door structure displacement
Figure 7 shows the displacement transformationsof the protective door after it was loaded. An analysisof the displacement of the protective door after itbore a 1 MPa load showed that the greatest
displacement was elliptical and occurred at the door’s
centre. The displacement became smaller as it moved
from the inside toward the door’s borders; the door’s
centre had larger displacements than the parts aroundthe sealed borders.

Figure 7: Protect door displacement transformations.

(2) Protective door force
Figure 8 shows the pressure distribution of theprotective door model after it was loaded. Based on
the door pressure distribution results of numerical637

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

simulation, the pressure at the edge was larger thanthat in other areas after it bore a 1 MPa load.
Although the door was depressed after bearing thepressure, it did not become plastically deformed. Thisshows that if the load added is less than the yieldstrength that 16Mn steel can handle, then the door
does not undergo plastically deformation.

Figure 9: Protective door static pressure load test time pressure curve.

Figure 8: Protective door pressure distributions.

Finite element analysis of the protective door
proved that the Wulan Coal Mine’s 15 mm thick
16Mn steel flat door could resist a 1 MPa explosion
without damage, and it met the 0.3 MPa requirement
for anti-fire and anti-blast abilities specified in thecurrent regulations. In order to protect the sealing
function from door displacement, a ferroconcrete
structure was added and the doors anti-pressure
ability was reinforced in order to reduce door
deformation.
5.2 Anti-pressure performance of the protective door
Figure 9 shows the hydrostatic load change in
the gasbags on the top of the protective door. The
pressure and deformation conditions are shown in
Table 2. This test proved that the protective door wascapable of withstanding a maximum static pressureload of 1.86 MPa, and the corresponding deformation
was 5.8 mm.

Table 2: Protective door static pressure load pressure deformation relationship.
Static Pressure
Deformati Deformation
Time(s)Load (MPa)on (mm)Speed
Steadily0-18000 -0.350-3.0
increased
Obvious1800-6900
0.35-1.50
3.0-4.4
increase
Slowly6900-8100
1.50-1.86
4.4-5.8
increased
8100Slowly
1.86-05.8-2.2
10000
decreased

5.3 Water proof performance of the protective door
Figure 10 shows the relationship between thewaterproof feature under pressure and deformation.
The hydraulic pressure change for a sealed container
filled with water was 0–1.6 MPa. As the hydraulicpressure increased, the door began to deform as
follows:“obvious
deformation-fundamentally
unchanged-slowly increased-maximum deformation” .
When the pressure reached 1.6 MPa, the door had amaximum deformation of 14 mm. In the test, there
were no leaks or unusual sounds. This test provedthat the protective door of the Wulan Coal Mine
permanent refuge haven could withstand 1.6 MPa
hydraulic pressure and maintain a good seal.

Figure 10: Protective door pressure – deformation.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

6. CONCLUSIONSThis study confirmed that the protective door in
the permanent refuge haven of Wulan Coal Mine wasmade with 16Mn steel, with a flat door structure, andused a manual wedge-shaped locking system. The
doorframes and walls were supported withferroconcrete and cast concrete to ensure the ability
for anti-blast and airtight sealing. The dimensions of
the door were 1600 mm (height), 950 mm (width),
and 15 mm (thickness).
Finite element analysis proved that in thepermanent refuge haven of Wulan Coal Mine, thedoor centre had the greatest displacement with thelargest pressure at the edges, when it born the blast
shock in the tunnel, and it could withstand a 1 MPa
explosive impact without plastic deformation. In
order to increase the anti-blast protection, the door
was reinforced with a ferroconcrete structure.
A static pressure load test confirmed that thedoor withstood a maximum static pressure load of
1.86 MPa, which corresponded to a deformation of
5.8 mm. The sealed waterproof test confirmed thatthe largest anti-pressure of the protective door was
1.6 MPa, which corresponded to the deformation of
14 mm with a good seal.
7.

ACKNOWLEDGEMENT

This work is financially supported by the
National Natural Science Foundation of China (No.
51504017), the Fundamental Research Funds for theCentral Universities (No. FRF-TP-15-043A3), theChina Postdoctoral Science Fundation (No.
2014T70039), the Doctor Science Research
Foundation of the Education Ministry of China(No.20130006120020), the China Postdoctoral
Science Fundation (No.2013M540666), which is
gratefully acknowledged.
8.

REFERENCES

Jian, C.G. (2003). Research on methane
explosion propagation character in duct and factors.
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pp. 20-26
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The propagation rule of methane explosion inbifurcation duct. Journal of China Coal Society,
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Luo, Z.M., Deng, J.W., Wen, H., Zhang, H.
(2007). Experimental study on flame propagation
characteristics of gas explosion in small-scale duct.
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Volume 12, pp. 2-5
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F.J.L. (2008). Flame acceleration and DDT run-up
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system in underground mine. Coal Science andTechnology, Volume 39, No. 1, pp. 69 -71
Tan, D.W., Chen, S.H., Liu, W.H. (1997).
Application of finite element analysis in dynamics of
explosion. Explosion and Shock Waves, Volume 4,
PP. 40-46
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Volume 11, pp. 6-9
Yang, Y.L. (1996). The overpressure calculationand prevention of gas and coal dust explosion. CoalEngineer, Volume 2, pp. 32-37
Zhao, L.A., Wang T.L.(2007). The application
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Zhu, C.j., Lin, B.Q., Jiang B.Y., Liu, Q., Hong,
Y.D., Sun, Y.M. (2013). Multiphase destructive
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explosion. Journal of China University of Mining andTechnology, Volume 9, No. 5, pp. 718-725

639

ISMS 2016

Paper No. 177
Numerical modelling of the goaf: methodology and application

Samar S. Ahmeda*, Marwan ALHeibb, Yann Gunzburgera, Vincent Renaudb, Jack-Pierre Piguetaa GeoRessources, Université de Lorraine, CNRS, Ecole des Mines de Nancy, Nancy, 54042, Franceb INERIS, Ecole des Mines de Nancy, Nancy, 54042, France

ABSTRACTThe mechanical behavior of the goaf is a critical issue that may affect the efficiency of longwall mining. Goaf
numerical modelling as a continuous material is a challenge, especially because its large-scale mechanical properties
are not precisely known. Many different values of the elastic modulus may be found in the literature to be used for
representing the mechanical behavior of the goaf area. In the present study, the elastic numerical modelling is shown
to be a useful tool for simulating the stress redistribution and displacement due to longwall mining, while taking into
account the goaf geometry and its equivalent mechanical properties. The analysis is applied on the Provence coalmine,in the south of France, which had been in operation for more than 50 years, using the longwall mining method wasused. A finite difference numerical model of the mine is constructed and two approaches are carried out in order tosimulate the goaf area above the excavated panels where the panels have various length to width ratios. In the first
approach, the caved zone and the fractured zone have different but homogeneous elastic modulus, both zones haveelastic modulus lower than the unaffected host rock. In the second one, their elastic modulus varies linearly with thevertical distance above the panel, up to the elastic modulus of the host rock. In both cases with and without goaf, thesubsidence at the ground surface is calculated and compared with in-situ measured values. Results show that
attributing to the goaf area a low elastic modulus increases the vertical stress within the rib pillars as well as thesubsidence at the surface. The elastic modulus for the direct roof above the panel after excavation has found to be 225≤ Eimmediate-roof (MPa) ≤ 180 in order to satisfy the total convergence between the roof and the floor. Representing thegoaf area as a material with linearly varying elastic modulus gives rational results in terms of convergence and groundsurface subsidence.
KEYWORDS: Numerical modeling; goaf simulation; longwall mining; stress redistribution
Figure 1: Three zones of disturbance due to longwall

1. INTRODUCTION
The longwall caving mining method is widely usedin underground mines and fundamentally in coalminesthat involve the exploitation of large rectangularpanels. When the coal seam is extracted, three zones
of disturbance due to longwall mining can be definedm
as shown in Figure 1 (Peng and Chaing, 1984). The
caved zone corresponds to the immediate roof that
totally collapses onto the floor. The fractured zone lies
above the caved zone, where the rock strata are broken
into blocks by essentially vertical and horizontal
cracks associated with bed separation. The continuous
deformation zone is only slightly influenced by the
excavation. In the three zones, even if major cracks
will appear, the rock mass behaves essentially as acontinuous medium at large scale. In order tonumerically simulate the whole mining process, theirgeometry and mechanical properties must first be
determined. For example, Peng and Chaing (1984)
proposed the thickness of the fractured zone to be 28 –42 times the thickness (t) of the mined seam. Recently
Shabanimashcool et al. (2012) found that the height ofthe caved zone is equal to 4t.

caving mining method (Peng and Chaing, 1984).

Assessment of the mechanical behavior of the goaf
is very difficult due to the inaccessibility to thedamaged area in the mine, as well as the heterogeneityof the goaf material. Much research has been
undertaken on this topic, which is essential todetermine the stress redistribution within the goaf area
itself or onto the ribsides.

*Corresponding author – email: samar.ahmed@univ-lorraine.fr

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Wilson (1980a) suggested that, after consolidationof the goaf, the vertical stress within the goaf increases
linearly from zero at the ribside to the pre-mining
vertical stress at a distance from the ribside equal to
0.3 – 0.4 times H where H is the mining depth. Wilson(1982b) also suggested that the peak vertical stress on
the ribside (the “abutment pressure”) might be as highas six time the initial one. The generally acceptedstress re-distribution developed by Wilson (1982b) is
as shown in Figure 2. However, Wilson proposed a 2D
estimation and he did not consider the effect of thethird direction that may play an important role. Also,
he did not refer to the material properties and its effectin stress redistribution.
Figure 2: Vertical stress distribution within the goaf andgoaf material. 𝜀𝜀𝑚𝑚 is given by equation (4) using thebuckling factor BF:
𝐵𝐵𝐵𝐵 − 1
𝐵𝐵𝐵𝐵(4)

10.39 𝜎𝜎𝑐𝑐 1.042
𝐵𝐵𝐵𝐵 7.7(5)𝜀𝜀𝑚𝑚 =

E0 (MPa) can be calculated as a function of thecompressive strength of the intact rock, 𝜎𝜎𝑐𝑐 , and thebuckling factor (Pappas and Mark, 1993; Yavuz,
2004):
𝐸𝐸0 =Salamon’s model is valid for cave-in materials under
hardening condition, and (non-elastic) behaviour. E0and 𝜀𝜀𝑚𝑚 must be detected firstly then the hardening
table will be estimated by using equation (3).
In this research, the elastic mechanical model will
be used in order to simulate numerically the goaf area
above the excavation as well as to assess themechanical consequences of longwall mining.
Immediately after excavation, the goaf area will be
substituted by less stiff material whose properties will
be calibrated by the total convergence between theroof and floor of the panel and the ground surface
subsidence.

2. CASE STUDY
the ribside (Wilson, 1982b).

Sheory (1993) developed equations (1) and (2) toevaluate the elastic and bulk modulus (E and K) overthe goaf span from his experience at Singareni
coalfield in India:𝑥𝑥

E(x) = 600( )𝑝𝑝
𝐿𝐿

Kgoaf = 0.0256 Khostrock

(1)
(2)

where x is the distance from the ribside, L is the halfspan of the goaf measured perpendicularly to the work𝑥𝑥
face and p = 13(1 − )0.29 . Sheory’s model is very
𝐿𝐿
effective to estimate the elastic modulus a long thepanel span after excavation, but we could not estimate
the modulus within the caved volume itself.
Salamon (1990) defined the stress strain
relationship of the goaf material as:𝜎𝜎 =𝐸𝐸0 𝜀𝜀1 − (𝜀𝜀/𝜀𝜀𝑚𝑚 )The case study for this paper is the Provence
coalmine, located in the south of France. It had been
exploited between 1984 and 2004 using the longwall
mining method, with a panel width of 200 m withvarious lengths, as shown in Figure 3.
Figure 3 represents the exploited panels between
1984 and 1994. The average thickness of the exploited
coal seam is t=2.5 m, at a depth of 700 to 1100 m. The
overburden is mainly composed of Fuvelian limestone
and Begudo-Rognacian limestone and marl, as shownin Figure 4. The stiffness of the Rognacian layer is low
compared with the adjacent Fuvelian layer because it
contains a high percentage of marl and clayey
limestone (Gaviglio, 1985). The initial mechanicalproperties of the different layer within the rockmass
are given in Table 1 (Gaviglio et al., 1996).

(3)

where, 𝜀𝜀 and 𝜎𝜎 are the vertical strain and stressrespectively and E0 is the initial elastic modulus of the641

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

to the excavated area and is increased by ratio 1.2 until
the model borders. Four different rock types are
specified: the coal seam, the Fuvelian, Rognacian withheight 400 m and 600 m above the coal seam, andJurassic limestone beds. The overall dimensions of themodel are 4600 m in the x- direction, 6020 m in the ydirection and 2270 m in the vertical direction (z). The
top of the model coincides with the ground surface atlevel z=0.0 while the excavated panels lies at depth of1000 m below the surface. The model boundaries are
fixed except the top.

Figure 3: Excavated Panels in Provence coal mine (19841994).
Table 1: Rock mass mechanical properties (Gaviglio et al.,1996).
Rock type
E (GPa)𝜈𝜈𝜌𝜌 (kg/m3 )RognacianFuvelianLignite coalJurassic

1
8.4
3
17

0.25
0.24
0.32
0.25

2400
2400
1500
2400

3. GOAF SIMULATION METHODOLOGY
In the current study, the goaf simulation iscomposed of two different steps. The first step is toestimate the geometry of the goaf (caved zone andfractured zone), the height of the goaf is taken as 32t
where t (coal seam thickness) = 2.5m (i.e. hcaved-zone=4t,
Shabanimashcool et al. and hfractured-zone=28t Peng andChaing, 1984). The second step is to estimate
numerically the mechanical properties within the goaf
area. The elastic modulus within the goaf will becalibrated with the convergence between the roof andthe floor for only one panel with minimum width (W)
200 m and length (L) varies between 400 m to 1400 m.
Then, once the convergence is fulfilled, the model will
be calibrated with the in-situ ground surface
subsidence for multi-panel with maximum width (W)1000 m and maximum length (L) 1400 m.
Two different approaches were developed topresent the mechanical properties of the goaf (Model
1 and Model 2).
A 3D numerical model of the mine was constructedusing the finite difference code FLAC3D (Figure 4).
The model contains approximately 2.5 million meshelements. The mesh density is adjusted to be fine near

Figure 4: 3D view of the model showing the mining panel
and the goaf area.

3.1 Model 1
In this model, we consider that the goaf area ispresented by the caved zone and the fractured zone asshown in Fig. 5. The elastic modulus (E) of thefractured zone is assumed to be half of the host rockwhich is mainly composed of Fuvelian limestone
because it is overlying layer above the coal (i.e.
Efactured-zone= Efuvelian /2 = 4.2 GPa). Nevertheless,iterations were carried out to estimate the caved zone
modulus for various length to width ratios (L/W = 2 7) that satisfy the total convergence between the roof
and floor. At first, the elastic modulus of the cavedzone is as same as the host rock (i.e. Ecaved-zone =Efuvelian) which is called “without goaf”. The last
iteration is carried out with Ecaved-zone = 225 MPa. For
all of the performed iteration the Poisson ration has notbeen changed (i.e. 𝜐𝜐factured-zone= 𝜐𝜐caved-zone=𝜐𝜐 hostrock).

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4. RESULTS AND DISCUSSION
In order to compare the applicability of each of the
proposed models each of them were initially calibrated
with the total convergence between the roof and floorof the excavated panel that has W=200 m and L =1400
m. After that, further panels will be exploited withmaximum width of 1000 m in order to calibrate themodel with the ground surface subsidence. Then, thestress changes due to longwall caving mining will beobserved.
Figure 5: Isometric 3D view of the caved zone and thefractured zone above one panel (W = 200 m and L=1400 m)(Model 1).

3.2 Model 2
In this model, elastic modulus (E) of the goaf isassumed to vary linearly with the goaf height (32t), as
shown in Figure 6. The elastic modulus begins from acertain value Eimmediate-roof, which is the value of theelastic modulus of the first few meters in the roof
directly above the opening, and increases linearly
within the goaf until Ehostrock at 32t where is the end of
the goaf geometry as defined before. Eimmediate-roof isdifferent than Ecaved-zone in Model 1, while it is for few
meters (not more than 3 m (zone height)), however,
Ecaved-zone has 4t height.
Equation (6) was fitted to estimate Egoaf at any
point within the goaf, by assuming that the Poisson
ratio is 𝜐𝜐 goaf = 𝜐𝜐 hostrock and the direct roof above the
excavation has Eimmediate-roof. The only value that could
be changed in this model is the Eimmediate-roof, for that,
we tried to operate the model with different values ofEimmediate-roof. Four different values have been tried,
600, 450, 225 and 180 MPa respectively. Then, theelastic modulus Egoaf could be estimated at any point(ℎ𝑔𝑔 .t) within the goaf by using equation (6):Egoaf(hg.t) = �roof

𝐸𝐸ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 − 𝐸𝐸𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖−𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟
𝑥𝑥.𝑡𝑡. ℎ𝑔𝑔 . 𝑡𝑡 � + Eimmediate-

4.1Ccnvergence between roof and floor
In the mine, when a panel is totally mined out, theroof and floor get totally in contact (full closure).
However, in the numerical model, due to the
hypothesis of elastic behaviour, the convergence
between roof and floor might be less than the coalseam thickness. This happens in particular when the
stiffness of the roof is equal to that of the host rock(case called “without goaf”).
Figure 7 shows the convergence between roof andfloor by using different elastic modulus’ within the
caved zone. We can see that the convergence isaffected by length to width ratio (L/W = 2 - 4),
however, for ratio more than 4, the convergence stays
nearly constant. Decreasing the elastic modulus (E) of
the caved zone in (Model 1) to 225 MPa (i.e. Ecaved-zone= 225 MPa) is sufficient to produce total closure of thecoal seam. The convergence remains constant whenthe modulus is further reducing.

(6)

where 80, (32t = 32*2.5 = 80 m), is the maximum
height of the goaf that corresponds Egoaf(32.t) , (ℎ𝑔𝑔 .t) is
the height corresponds to Egoaf(hg.t), ℎ𝑔𝑔 ranges between(1 – 32) and t is the coal seam thickness.

Figure 7: Convergence between roof and floor for different
panel lengths with 200 m width (Model 1).

By using Model 2, Figure 8 shows that decreasing
the Eimmediate-roof until 180 MPa is sufficient to produce
total convergence between the roof and floor of thepanel. For that, in order to get the total touch between
the roof and floor (i.e. convergence = mining seam
thickness (t)), equation (6) must be written as:
Figure 6: Linear variation of elastic modulus within thegoaf area (Model 2).

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
𝐸𝐸

Egoaf(hg.t)= ( ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜
80

− 180

. ℎ𝑔𝑔 .t) + 180(7)

Figure 8: Total convergence between the roof and floor fordifferent panel lengths (Model 2).

values for each panel width to mining depth ratio. For
example, for 400 m panel width at 1000 m depth, the(max. subsidence/t) = 25, so the max. subsidence is
25*t= 25*2.5 = 62.5 cm.
It is clearly shown that simulating the goaf by using
less stiff material has its effect on the surface even with
exploitation at very high depth. the influence of thegoaf appears on the surface for the panel width (W) /mining depth (H) ratio greater than 0.4. Representing
the goaf elastic modulus (E) by using equation (7)gives a rational surface subsidence between the
maximum and the minimum in-situ measured
subsidence curves. The model without goaf is not able
to reproduce even the minimum subsidence curve. The
adopted goaf behaviour gives an acceptablesubsidence prediction. An improvement can besuggested for large mining areas (W/H>1). In addition,
Model 2 will be applied in another future studies toverify its ability to predict the surface subsidence.

Based on the two proposed models, we can findthat in case of total convergence after exploitation byusing longwall caving, the first damaged few meters in
the roof (immediate roof) will have an elastic modulus(E) as:225 ≤ Eimmediate-roof (MPa) ≤ 180(8)

Although, the two models give approximately avery close range of Eimmediate-roof and Ecaved-zone in orderto satisfy the total closure of the opining, Model 2 ispreferable than Model 1 for simulating the goaf area.
Because, the stiffness difference between two adjacentzones should not exceed 10 times, while in Model 1
the difference between the fractured zone and the
caved zone is reached to 18 (i.e. Efractured-zone / Ecaved-zone= 4200/225 = 18).
4.2 Ground surface subsidence
One of the very clear observations due to longwall
mining is the increasing of the surface subsidence. The
panel width has been extended until 1000 m bykeeping the maximum length at 1400 m. The proposedmodel (Model 2) was calibrated with in-situ
measurement of the surface subsidence. Figure 9
illustrates the maximum and minimum measured
surface subsidence for panel width (W) from 200 m to1000 m. Model 2 has been applied within various
panel widths and the surface subsidence has beenmeasured at the center of the panel. The groundsurface subsidence produced by numerical modelling
by applying Model 2 is as shown in Figure 9.
The surface subsidence may vary greatly fromcountry to country and from location to location. In
case of Provence coalmine, the surface subsidence has
been monitored at each excavation step. Figure 9shows the minimum and the maximum subsidence

Figure 9: Surface subsidence in case of with and without
goaf.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.3 Stress redistribution
When replacing the goaf area with less stiff
material than the host rock, the vertical stress willtransfer to the surrounding high stiff materials. The
stress distribution due to panel excavation with andwithout goaf is shown in Figures 10 (a) and (b),respectively. The induced vertical stress within theribside is 2.5 times the initial one, which is much lessthan the values given by Wilson (1982b). The induced
vertical stress due to goaf has a higher influenced zone
horizontally than the case without goaf. Also, thedestressing zone is higher in case of the goaf.

200 m rib pillar between them. In case of the goaf theinfluenced zone (horizontally and vertically) within
the rib pillar is larger than the case without goaf. By
increasing the panel width, the vertical stress will
increase at the center of the panel. The induced verticalstress to initial stress ratio is assigned to different panel
widths in Figure 12. The results show that when thepanel width increases the induced to initial verticalstress ratio increases at the center of the panel. For
panel 1000 m width with fully filled mining area, theinduced to initial vertical stress ratio is 0.2 at the panel
corners until 0.9 at the center without consolidation.

Figure 11: Ratio between induced vertical stress andinitial vertical stress within the ribpillar (a) without goaf (b)with goaf (Model 2).

5. CONCLUSION

Figure 10: Ratio between induced vertical stress and initial
vertical stress (a) without goaf (b) with goaf (Model 2).

As shown in Figure 3, there are rib pillars between
two parallel panels. Figure 11 shows the ratio between
the induced vertical stress and the initial one in case of
excavating two parallel panels with 200 m width andThis research examines the simulation of the goaf
area associated with the longwall caving panels of
Provence coalmine by using FLAC3D. Two distinct
models, Model 1 and Model 2, have been represented
to simulate the goaf area after exploitation. Within
Model 1 the goaf area is treated as two separated parts(the caved zone and the fractured zone), which havedifferent elastic modulus values.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

≤ 180 MPa in order to satisfy the total convergence
between roof and floor.
Substituting the goaf area with less stiff material
has an effect on the ground surface subsidence forpanels whose has width to depth ratio greater than 0.4.
Model 2 expresses sufficiently the variation of theelastic modulus within the goaf area. It gave a rationalsurface subsidence compared with the ‘without goaf’model. By exploiting a longwall caving panel, thevertical stress within the ribside will increase by 2.5
than the initial value. The vertical stress at the centerof a panel whose width to depth ratio is 1 approaches
the initial vertical stress value.

6. REFERENCES

Figure 12: Induced Vertical stress to initial vertical stress
distribution within the goaf area for different panel widths.

In Model 2, the goaf area is treated as a one zone
with linearly increasing elastic modulus from thedirect roof up to the host rock. From the two model,
we found that the elastic modulus of the few meters
above the panel is ranged between 225 ≤ Eimmediate-roof

Gaviglio P., 1985. La deformation cassante dansles calcaires Fuvéliens du basin de l’arc (Provence).
PhD thesis. University of Provence, Marseille, France.
Gaviglio P, Bigarre P, Baroudi H, Piguet J.P andMonteau R. (1996). Measurements of natural stresses
in a Provence mine (Southern France). Journal
Engineering Geology. Volume 44, pp. 77-92.
Pappas DM and Mark C., 1993. Behaviour ofsimulated longwall gob material. Report ofinvestigation no. 9458, US Department of the Interior,
Bureau of Mines, 39 p.
Peng S.S. and Chaing H.S. (1984) Longwall
Mining. John Wiley & Sons Inc., New York; pp. 1773
Salamon MDG. (1990). Mechanism of caving in
longwall mining. In: Hustrulid W, Johnson G, editors.
Proceedings of the 31st US rock mechanicalsymposium, Golden, Colorado. Rotterdam: Balkema,
pp. 161–68.
Shabanimashcool, M. and Charlie, C.L. (2012)
Numerical modelling of longwall mining and stability
analysis of the gates in a coal mine. International
Journal of Rock Mechanics and Mining Science.
Volume 51, pp. 24–34.
Sheorey P. R. (1993) Design of coal pillar arrays
and chain pillars. Comprehension Rock Engineering,Vol. 2. Pergamon Press, Oxford.
Wilson A. H. (1982). Pillar stability in longwall
mining. State of the Art of Ground Control in
Longwall Mining and Mining Science, Y. P. Chughand M. Karmis (eds.), SME, New York; pp. 85-95.
Wilson A.H., 1980. The stability of undergroundworkings in the soft rocks of coal measures.
Unpublished Ph.D Thesis, Univ. Nottingham.
Yavuz H. (2004) An estimation method for coverpressure re-establishment distance and pressure
distribution in the goaf of longwall coal mines.
International Journal of Rock Mechanics and Mining
Science. Volume 41, pp. 193–205.

646

Paper No. 190

ISMS 2016

A coal enterprise scientific-technical progress evaluation system based on theInternet
Shanyang Wei*, Longlong Yang, Zhongbei Li, Shiwei Ding
Safety Engineering College, North China institute of science and technology, Sanhe, China, 065201

ABSTRACTThe evaluation of coal enterprises of scientific-technical progress is a big problem in technology management. Until
now in China or abroad there has been no mature and recognized coal scientific-technical progress evaluation
system that can make a wide range of evaluations about the coal scientific-technical progress of the whole country
or region in the quantitative measurement aspects of scientific and technological progress to economic growth，although there were quite a few successful applications. Under the present conditions of a lot of coal enterprise
output decline, laid-off personnel, and asset reorganization, using the traditional production function method isdifficult for measuring the effect of technological advances. On the basis of investigation and study, according to theactual situation and balance of payment structures of coal enterprises and with reference to relevant policies andregulations of the national science and technology evaluation, and with the application of universality and agility of
the Internet, we constructed a system for the scientific-technical progress evaluation of coal enterprises. According
to the computing applications of part of the state-owned key coal mines and local state-owned coal mines, goodresults have been achieved.
KEYWORDS: Coal enterprise; scientific-technical progress; system of information; comprehensive assessment
From the point of view of the development of thetheory of the scienctific process, the basic theory ofscience and technology progress has experienced threestages; ① The theoretical stage of traditional
scientific-technical progress (Li, 2002; Wang, 1993);② The theoretical stage of classic scientific-technicalprogress in the 1950-1960’s (Poter, 1980; Miler, 1999);③ The theoretical stage of modern scientific-technicalprogress since the 1960’s. China also formed two
waves in the aspect of scientific-technical progressevaluation. The first wave lasted from the late 70’s oflast century to the 10 years before the 80’s. Because of
the high and rising economic growth targets, themeasurement and evaluation method of scientific andtechnological progress that conforms to the target werein urgent need. The research results meet the needs ofdecision-making at all levels. After 1986 research andapplied work made no progress until after the 90’s. At
this point the role of science and technology in socialand economic development received extensive concern
and attention. The research and application teamcontinued to expand and then formed another wave,
providing a good environment for the evaluation ofscientific-technical progress. However, research in thefield of evaluation of scientific and technologicalprogress in China is still very shallow, and ,methods
that can transform theories of scientific and*Corresponding author – email: weishanyang@126.com

technological progress of western developed countries
into what are suitable for China's national conditions
and industry characteristics are few (Li, 2009).
At present, literature and data that specializes inthe evaluation of progress of science and technology ofcoal enterprises are few. The main methods are AHP(Analytic Hierarchy Process), DEA (Data Envelopment
Analysis) bonding, the connotation and structure
method of the system of coal enterprisescientific-technical progress (Chen, 2011; Zhang, 2002)
and the method of interval valued intuitionistic fuzzy
set (Jing, 2014). However, a system that can evaluate
coal scientific-technical progress objectively, accurately,
and comprehensively has not yet been seen. As a result,
it is important to keep up with the development ofscience and technology, make full use of modern
Internet technology to build the whole of China, even
the world evaluation system of coal enterprisescientific and technological progress, and advance coalscientific and technological progress universally inorder to realize the safe, healthy, green, and advanced
system of coal production.

1. THE TECHNICAL ARCHITECTURE AND
FUNCTION OF THE SYSTEM.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

The front page with HTML 5 + jquery + the

Backend server using

The Mysql database

PHP，PHALCONHTTP and the reverse proxy serverusing Nginx

Centos operating system
Figure 1: Information system architecture diagram.

The front page uses the popular HTML5 that can
support more of the browsers new features and provide
a rich expressive ability for display. Jquery andbootstrap is a scripting language framework and thepage layout framework, respectively, which provide astrong compatibility with most of the major browsers,
and a strong code maintainability.
The backend http server using nginx, which hasstrong stability, rich feature set, and low system
resources.
The server-side language uses PHP and phalcon
framework. PHP provides good operational
characteristics for the system. There is no need torestart the system to change, ensuring high availabilityof the system. Phalcon is a plug-in framework usingcompile PHP zend engine by C language editor. Using
the framework, the calculation of the PHP language
and the corresponding performance can achieve around2000 requests per second, which is 120000 requests per
minute under the conditions of the hardware resources.
The database using the MySQL server. The
system has the characteristics of open source and highperformance. A single data reading and writing is in the
microsecond, and support the cluster, which greatly
improves the system reliability and availability andperformance.
Operating system uses the cento Linux system.
The system is the open source community edition
maintained by Redhat company, and basically has
functions like the Redhat system. The system has
running stability and it does not need to restart therunning perennially.
The use of the technical architecture can savemany costs for thw operating system and databasesystem, and the cost savings can be used for theconstruction of an information system to produce morevalue, without spending the budget of the operating
system and database system on licensing fees.
The role of the system function modules is mainlyto: (1) Fully calculate and display the coal enterprisecomprehensive evaluation results, ranking among
participant coal enterprises in the mine technology state,choosing "top fifty scientific and technologicalprogresses in coal enterprises" and "top ten hi-tech coalenterprises". (2) "Business analysis" to fully reflect thestructural character of the health of the enterprise, andputs forward corresponding measures and management
scheme. (3) Enterprise contribution rate of science andtechnology, the contribution rate of labour, statisticallycalculated capital contribution, and conclude industry
scientific-technical development state. (4) The
enterprise environment system can be checked, toconclude whether to belong to the green mining
enterprises. (5) To achieve wide interaction, allparticipants of "the forum" can communicate in all
problems of the coal production and management. It isa convenient platform for a thorough understanding ofcoal mines.

2. DATA COLLECTION METHOD
The data collection method uses the cloud system
of science and technology, the function of the databasecluster and disaster preparedness, the characteristics ofthe computing speed, large storage space, and theemergency ability. This method is convenient for theapplication of coal industry management andsupervision department. The data acquisition method ofdesign was as shown in Figure 2.
The cloud system of scienceand technology

Database cluster

Disaster database

Figure 2: Data acquisition method of design.

Data collection methods use a cloud platform thatcan expand the system performance in real-timeaccording to the need. The advantage is that it canadequately cope with a large increase of users of thesystem. It does not need to make changes, and instead
applies for an increase in the performance of thesystem. In the aspect of saving data, the database uses
the cluster and disaster mode. When used by a large
number of users at the same time it can minimize theimpact of database performance bottlenecks. If masterdatabase collapse occurs, it can quickly switch to thedisaster database to ensure high availability.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

3.
COMPREHENSIVEEVALUATIONINSTANCES OF MINE SCIENTIFIC ANDTECHNOLOGICAL PROGRESS
3.1 Mine evaluation index statistics table
According to the comprehensive evaluation systemstandard of coals scientific-technical progress, we
calculated part of the state-owned key coal mines andlocal state-owned coal mines.
3.2 The comparison of the mine comprehensive
evaluation
The indicators and index weights calculated
through the application of the computer evaluation
system were compared to arrive at four mine scoresand rankings that are shown in Table 1.
Since all indicators calculation results were
calculated according to the actual situation, the scores
were not controlled. The final calculation and ranking
was performed, getting enough space for the expansionof the evaluation system.
Comparing the calculation results can provide theimage of the evaluation results and knowing the coalmining conditions provides strong support for coalmine supervision departments and coal enterprises.
The establishment of a comprehensive network
evaluation system was carried out for Ping Coal LTD
Ten Mine, Ping Coal LTD Six Mine, Bai Yuan Coal
Mine, and LiZi Ping Coal Mine. The results of theevaluation and comparison are shown in Table 1:
Table 1: Part of the mine comprehensive evaluation andranking
Rank

Report nameCompanyName

Statistical table ofindicators of Coalenterprisescientific-technicalprogress
evaluation

Ping Coal
LTD TenMine
Bai Yuan
Coal
Mine
Ping CoalLTD Six
Mine
LiZi Ping
Coal
Mine

1

2

3

4

Year

Score

2014

12.64

2014

10.97

2014

10.72

2014

9.33

Comparison of the calculation results and software
analysis finds that the two have the same results.
Therefore, the application and popularization of the
network evaluation system must provide a good
platform for the evaluation of coal enterprisescientific-technical progress, and can provide good

support for the country and regulators to accurately
grasp the dynamic coal enterprise technology. This
makes great contributions to regulating the coal market
economy.

4. CONCLUSIONS AND OUTLOOKThis text was based on coal scientific andtechnological progress as the research object, inreference to the research results of scholars both athome and abroad, and in combination with the present
situation in the coal industry and the progress ofscience and technology leve. An evaluation andin-depth study of the progress of science andtechnology systems of coal enterprises was carried out
using data acquisition methods based on the Web andthe comprehensive index evaluation system method to
calculate science and technology progress in four coalenterprises, given a ranking order.
The establishment of this system provides a goodbasis for further studies of coal industry scientific andtechnological progress evaluation systems. There is
still a lot of room for development, and further study
should focus on the following:(1) Continue to study the synthetic evaluation
system of scientific-technical progress, which should
be scientific, reasonable, and comprehensive, and makethe system more complete and feasible.
(2) Research the relationship between thecomprehensive
evaluation
systemofcoalscientific-technical progress and the evaluation systemof other industries’ scientific-technical progress.
Explore a kind of formula or conversion rule that canbe used generally. Make greater breakthroughs in theevaluation system of scientific and technologicalprogress for China and all over the world, and canreflect the actual situation of the evaluation of scientificand technological progress in all walks of life
objectively, authentically, and accurately.
(3) Combine the data collection methods basedthat was applied in this paper with the evaluation
system of scientific-technical progress, and make a setof coal management information systems of scienceand technology, then apply it to the coal industry,different regions and coal mining enterprises, coalsupervision departments, the department manager ofsupervision and inspection, and the China coal industry
associations’
strengthofcontrolonthescientific-technical progress of coal industry, and tostrengthen the promotion of coal science andtechnology.

5. REFERENCES
Jing. (2014) Research on Green Mine Evaluation
Index System of Underground Mining.[D]. Beijing：
Beijing China University of Mining and Technology.
Li. (2002) Researching the Valuation System of649

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016
Science and Technology Progress of Coal Enterprise.
[D]. Hebei：Hebei University of Technology.
Li and Huang. (2009) Empirical Analysis of theContribution of Scientific and Technological Progress
to China’s Economic Growth [J].Science & Technology
and Economy,6. 22（129）:65-68. Chen.(2011)Measure
the Level of Modernization of Coal Industry [D].
Miler，D．& Whitney， J．Beyond Strategy. (1999)
Configuration
asa
Pillarof Competitive
Advantage．Business Horizons．
（42）：8-ll.
Poter, M．E．(1980) Competitive Strategy．New
York：Free Press，（23）：8-ll.
Wang.(1993)
Data
Envelopment
Analysis
Approach on the Industrial Efficiency and scales and
Its Application in Shandong[J]．Journal of Systems
Science＆Systems Engineering.（7）：5-7.
Zhang.(2002) System and Evaluation Research of
the Progress in Science and Technology of CoalEnterprise .[D].Liaoning ： Journal of Liaoning
Technical University.

650

Paper No. 195

ISMS 2016

Simulation of strata behaviour laws of a coal mine in Jungar Coalfield
Zhu Bina,b,*, Li Gea, Kou Weifengc , Li HaibinaaSchool of Architecture and Civil Engineering, Xi’an University of Science and Technology, Yan Ta Street, Xi'an, China
School of Highway, Chang'an University, South 2nd Ring Road, Xi'an, Chinac
Beijing Urban Construction Design & Development Group Co. Limited,No.5, Fuchengmen Beidajie, Xicheng District, Beijing, Chinab

ABSTRACTThe present study uses a similar material experiment to systematically examine the performance of the law of overlying
strata caving, mine ground pressure, and crack development when the first coal mining face in Jungar coalfield was
exploited. The overburden movement, roof collapse, severe wall caving, and a range of other issues related to mine groundpressure caused by the exploitation process in Jungar coalfield are considered. The results prove that the pace of theimmediate roof caving of the first coalface was about 15.0 m. The pace of the first weighting of the rock stratum of main
roof was 45 m, with an average pace of periodic weighting of 17 m. The maximum loading-increasing factor of firstweighting was 1.40, and the value of loading-increasing factor for the whole weighting period was 1.32. For the distributionof the three zones of the overlying strata on the first coalface, the height of the caving zone was about 4.5 times the averagemining height, the height of the fissure zone was about 14.5 times the mining height. The bending zone is the stratum over
43 m from the coal roof, which takes on the features of overall down movement. Therefore, a reasonable choice of mining
method to reduce the thickness of the mining working face should be taken to reduce the disturbance from exploitation to
overlying strata of the upper goaf and the earth's surface.
KEYWORDS: Mine pressure; Similar material simulation; Bending zone; Fissure zone; Caving zone; Overlying strata
failure1. INTRODUCTION
Jungar coalfield is located in the southwest of the
Inner Mongolia Autonomous Region, and is an importantpart of the Ordos coal-accumulating basin, which is a
Neopaleozoic permo-carboniferous oversize coalfield. Dueto the coal properties in the Jungar coalfield featuring
naturalconditionsofespeciallylow-sulfur,
low-phosphorous, high ash-melting, high calorific powerand high volatile, it is the most appropriate power coal andfossil fuels. Therefore, Jungar coalfield is the largest
comprehensive energy base in western China (Cui et al.,2002). In recent years, with the intensity of coal mining
increasing, damage to coal mining is increasingly serious
and the incurred engineering problems such as goaf
overlying strata movement, surface deformation, and theacute weighting and pouring of water and sand of working
faces are continuously compounded (Jin et al., 2010).
Chuancao Gedan coal mine is located in the midwestof Jungar coalfield. The recoverable reserve of the wholemine is 1205.57 Mt, with a designed production capacity of
10.00 Mt/a, and a length of service of 86.1 a. However,since there are many minable seams within the mine field,
and the hydrogeological conditions are complicated underthe mine, coal mining causes a series of negativeenvironmental geology effects, such as overlying strata
movement, roof collapse, water resources oversight, andecological environment deterioration.
At present, there are many major research methods
concerning the mine ground pressure and rock stratum*Corresponding author – email: diskzhu@sina.com

displacement law (Liu, 2015; Tu et al., 2011; Wei et al.).
However, it is difficult to accurately predict and analyze its
settlement law. Therefore, this paper adopts the method ofsimilar simulation test (Wu, 2013; You, 2000; Zou, 2004)
to perform a preliminary study on the law of overlying
strata caving, fracture development and mine groundpressure of 4101 first coalface mining of Chuancao Gedan
coal mine, which not only has theoretical and practicalsignificance to working face safety mining design andcontrolling strata movement, but also provides a reference
for the safe construction of similar projects in the future.

2.
GEOLOGICAL BACKGROUND OF THE
MINE PROJECT
Chuancao Gedan coal mine is affiliated with
Changtan Township and Xuejiawan Town of Jungar Banner.
The mine field is a polygon, with an east-west length ofabout 8.9 km, north-south width of about 5.5 km, and anarea of 42.64 km2. The first-mining coal seam isdetermined as No. 4 coal seam in the first level of the firstpanel, and the first-mining working face is determined as4101 working face. The results of a rock mechanicalproperties test show that the overall intensity of the rockwithin the mine field is such that fine grained rock has
greater crush resistance and shearing resistance than coarse
grained rock. The rocks whose crush resistance ≤30 MPa
account for 68%, and those between 30-60 MPa accountfor 32%. It indicates that for all kinds of rocks in coalmeasure strata of this mine field, they are mostly weakrock, or secondarily are half-hard rock.

Material used for the model includes quartz sand as
aggregate, gypsum and calcium carbonate as the cementing
material. This is then mixed with water in accordance witha certain proportion, laid in the model frame in layers, andmica powder is scattered between levels (Figure 1).
A self-developed multiple pressure computer dataacquisition system conducts real-time monitoring on thecoal column variation of stresses. 57 pressure sensors arearranged at the bottom of No.4 coal seam of the firstmining simulation 4101 working face, and the simulation
stands to confirm the rational supporting intensity of theforce piece. Displacement monitoring is conducted for roof
strata. Five measuring lines are arranged at 10 m, 30 m, 50
m, 70 m, and 90 m away from the coal seam roof. The
displacement changes of roof strata and the advance of theworking face are monitored.

3. SIMULATION EXPERIMENT
According to the data on coal mine drill, one mustselect representative regional strata as the geological modelfor the similar simulation test, conduct merging
homogenization to the stratum stratification character, andestablish an engineering geological model reflecting theroof and floor conditions of the coal seam.
The experiment adopts a self-developed plane stressframe model. The model frame is designed with a length of
3 m, height of 2 m, and width of 20 cm. The geometricsimilarity ratio is 1:100. Based on the histogram of No.Y14
drill hole of this mine, geometric similarity constant of themodel is αL=100, density similarity constant is αY=1.56,
and the stress similarity constant is α=αLαY =100×1.56.

200

300m

Coal No.3

Sandy mudstone

Alternation

Siltstone

Mudstonsandstone
Loose

of

fine
and

Fine

MediumCoarseMedium-thi

Figure 1: Profile map of simulation working face.

4. ANALYSIS OF EXPERIMENTAL RESULTS
4.1 First mining stage
4101 working face ranges from 2.55 - 3.95 m inthickness, with an average of 3.09 m. The coal property ishard, and the immediate roof is sandy mudstone of 1.5 2.1 m. In order to reduce the influence of refuse content
during recovery and study the effect of the setting ofroof-coal in working face advanced stages on the stabilityof roadway maintenance, coal seam thickness when fillingthe model ranges from 3.09 - 3.95 m, the full-seam miningof the working face in the first mining stage is 3.2 m withreserve, and roof supporting coal is set to 0.5 - 0.75 m, andsupport resistance is set according to 5 times the mining
height.
Leave 30 m a boundary pillar when exploiting
simulating mining the working surface, with an open-off

cut width of 6 m. When advancing the working face to 12
m, microcracks appear in the coal roof of the roof
supporting coal; when advancing the working face to 14 m,
the microcracks extend further. When advancing theworking face to 16 m, microcracks appear in immediateroof stratum 1.5 m away from the coal roof along with thestratum direction. When advancing the working face to 22
m, microcracks in immediate roof stratum 1.5 m awayfrom coal roof extend continuously. When advancing theworking face to 26 m, the coal roof of the roof supporting
coal generates an obvious separation layer, as shown in
Figure 2 (a). When advancing the working face to 32 m,
the roof supporting coal with has a suspended length of 7
m after support collapses (Figure 2 (b)). Advancing theworking face to 40 m leaves no roof supporting coal in theworking face advance, full-seam mining is 3.85 m, thelower stratum of the immediate roof and main roof in the652

back of the stand fractures, and the upper end of thefracture line is 6 m away from coal roof. The lower end of
the fracture line extends to the upward side in front of thestand, and the collapsed rock of fracture rock and goaftakes on a splicing structure with the advancing front of theworking surface, and the support load shows no obvious
lifting (Figure 2(c)).

(a) Separation layer of coal roof (the working face is to 26 m)

It is held that the first caving pace of the immediate roof
for first coalface is about 15.0 m. The experiment also
shows that when the immediate roof first collapses, thesupport load has no obvious rise; under the condition ofusing the comprehensive mechanized coal mining, as longas the stand is in normal operating condition, there is nodanger for first caving of the immediate roof, and it isunnecessary to take special protective measures.
4.2 Main roof (upper roof) first weighting
Synthesis analysis shows that the range of firstweighting of the basic rock strata is between 44 - 48 m,
confirming that the pace of the first weighting is 45 m - 50
m. During first weighting the dynamic load factor is 1.40,
showing acute weighting. The caving zone height of thestratum is 14 m, which is about 4.5 times the averagemining height. The fracture line of coal wall side is locatedat the upside of the support front, showing that the setting
load of the simulation support designed according to 5
times of mining height is insufficient.
4.3 Periodic weighting of main roof(b) Separation layer of coal roof (the working face is to 32 m)(c) Separation layer of coal roof (the working face is to 40 m)

Figure 2: Deformation and failure process of roof strata
in first mining stage.

Simulation test results show that when advancing theworking face to 12.0 m, the reserved roof supporting coal
starts to generate damage, until the advance reaches 36.0 m,
when immediate roof stratum completely collapses. On thisbasis, it is deduced that under the circumstance of leaving
the roof supporting coal, the first caving pace of theimmediate roof is about 20.0 - 25.0 m. Since thisexperiment belongs to the “plane stress model” and there isno constraint in the front and back of the model, when
fitting the model, the immediate roof is inclined to be hard.

4.3.1 Weighting pace
The simulated working face is totally advanced at 192
m, showing 1 first weighting and 8 periodic weighting.
When excluding the 6 m starting cut width, from theposition of starting advancing for the working surface, thepace of the first weighting of basic rock strata is 45 m - 50
m. During 8 periodic weightings, the maximum weighting
pace is 20 m, the minimum weighting pace is 14 m, and theaverage weighting pace is 17 m.
4.3.2 Loading-increasing factor
Based on the working resistance of the whole support,
the loading-increasing factor during the weighting ofworking face is as shown in Table 1. Before periodic
weighting, setting load of the support is calculated
according to 5 times the mining height, and rises to 8 times
the mining( height after the first weighting. The maximum
loading-increasing factor of the first weighting is 1.40, andthe mean value of loading-increasing factor during thewhole weighting is 1.32, according to mining pressure
theory, the weighting approaching is “relatively strong”.
4.3.3 Roof cutting phenomenon
During the advance of the working face, though there
is no roof strata cut falling along with the coal wall in frontof the support, during the first, sixth and eighth weightings,
the fracture line of roof strata of the coal wall side extends
to the upside of the support, causing support load to rapidly
increase; it is suggested to further raise the setting load on
the basis of the calculation for 8 times the mining height,
and adopt hydraulic supports with high resistance.

653

Table 1: Weighting loading-increasing factor of
the first mining face

Loading
Indicator weighting-increasing
factorFirst weighting

1.40

1 periodic weighting

1.32

2nd periodic weighting

1.32

3rd periodic weighting

1.33

4th periodic weighting

1.22

st

th

5 periodic weighting

1.28

6th periodic weighting

1.37

7th periodic weighting

1.30

8th periodic weighting

1.35

Mean
value

1.32

measures. Meanwhile, it is important to ensure the setting
load of the support to effectively maintain the roof of thehead face.
For the main roof (upper roof) stratum, the firstweighting pace is 45 m - 50 m, and average pace of
periodic weighting is 17 m. The maximum
loading-increasing factor of first weighting is 1.40, and themean value of loading-increasing factor of the whole
weighting period is 1.32. According to mining pressure
theory, the weighting approaching is “obvious”.
In the distribution of the three zones of the overlying
strata on the first coalface, the height of the caving zone is
14 m, which is about 4.5 times the average mining height.
The range of the fissure zone is 14 - 43 m, the height of thewhole fractured zone is 43 m, which is about 14.5 times themining height. The bending zone is the stratum over 43 m
away from the coal roof, which takes on the feature ofoverall downward movement.

6. ACKNOWLEDGEMENTS
This paper was supported by Shaanxi Provincial
Departmentof
Education Science
Research
Project (11JK0779) and the National Natural Science
Foundation of China (41402265, 51508462) .

7. REFERENCES
4.3.4 Distribution of three zones
The height of the stratum caving zone is 14 m, which
is about 4.5 times the average mining height. The range ofthe fissure zone is 14 - 43 m, the height of the wholefractured zone is 43 m, which is about 14.5 times theaverage mining height; the area that is over 43 m from thecoal roof is the bending zone, and the stratum takes on thecharacteristic of overall downward movement (Figure 3).

Figure 3: Distribution of vertical three zones ofthe overlying strata.

5. CONCLUSION

Cui ,X., Miao, X. and Su, D.(2002). Error analysis in
similar material simulation test of the movement of rockstrata and surface. Chinese Journal of Rock Mechanics andEngineering, Volume 21, No. 12,pp. 1827－1830．
Jin, L., Jin, W. and Wang, H.(2010).
Multi-environmental time similarity theory and its
application. Journal of Zhejiang University (Engineering
Science),No. 4 , pp. 789－797
Liu, Y.(2015). Research on Surrounding RockMigration Law of Working Face with Similar Material
Simulation. Coal Technology, Volume 34, pp. 93-95
Tu, S.，Dou,F. and Wan, Z. (2011). Strata control
technology of the fully mechanized face in shallow coalseam close to the above room-and-pillar gob. Journal of
China Coal Society, Volume 36, No. 3 ,pp. 366-370
Wei, J., Li, Z. and Guo ,J. Mining Safety &Environmental Protection,Volume 37,No. 4, pp. 11－14．
Wu, Z. (2013). Discussion on features of high alumina
coal resources in zhungeer coalfield. Journal of Coal Mine
Engineering, Volume 10, pp. 115-118
You ,C.(2000). Analysis of bond-type bolt stress withoverall length. Chinese Journal of Rock Mechanics andEngineering, Volume 19, No. 3,pp. 339–341.
Zou, J.，Li,L. and Ruan,B. (2004). Analysis ofdisplacement and deformation of anchor bolt under elastic
state. China Railway Science, Volume 25, No. 5,pp. 94–96.

Simulation results show that the first caving pace of
the immediate roof of first coalface is about 15.0 m. Whenthe immediate roof first collapses, support load has no
obvious rise, As long as the stand is in normal operating
condition, there is no danger for caving of the immediateroof, and it is unnecessary to take special protective

654

ISMS 2016

Paper No. 6

Goaf area exploration in Anjialing surface mine based on the C-ALSWANG Jun*, ZHOU You, ZHAO Ruhui
Mine Safety Technology Branch, China coal research institute, Beijing 100013，China；
State Key Laboratory of Coal Mining and Clean Utilization（China Coal Research Institute）, Beijing 100013，China；
Beijing Mine Safety Engineering Technology Research Center, Beijing 100013.

ABSTRACT
In order to ensure safety in production, a 3D model is established in the mining boundary of the Anjialing surface mineby using C-ALS to explore goaf. The roof height of the mined out area is consistent with the results of a 3D laser
scanner that verified the model by drilling exploration. The coal seam is shallow in the Anjialing district. Small-scalecoal mining has a long history. A small kiln mining area in the centre of the first mining area damaged the 4th and 9th
coal seam severely. Goaf 3D laser scanning technology has been widely used at home and abroad as an advanced goaf
measuring instrument. C-ALS is used for the 1302 and 1316 levels in Anjialing district to carry out goaf exploration;
the results show that the volume of the goaf is 21138m3. Through carrying out data processing and 3D modelling forthe goaf, a basic idea for subsequent safety evaluation of goafs, disaster warning, and governance programs for thegoaf are provided.
KEYWORDS: Goaf area; C-ALS; surface mine; 3D model

1. INTRODUCTION
The mined out area is a cavity produced byartificial digging or natural geological movement underthe earth's surface. The goaf of the small kiln is anunderground man-made activity site formed by previous
mining behaviour. It not only includes the undergroundspace of the well lane and resource exploitation, but also
includes secondary space produced by the movement ofrock strata caused by mining, as well as the space for theformation of secondary disasters after mining (Liu,2008; Sun, 2009). The goafs formed by undergroundmining have a certain influence on the groundenvironment, and at the same time threaten the life andproperty safety of residents in the mining area.
Three dimensional laser scanning technology ofgoaf is a 3D precision detection method based on laser
ranging. It can detect the goaf through scanning bystretching a rotating head which can be integrated with alaser distance measuring instrument in the inner goaf.
Compared with the traditional geophysical prospecting
and drilling methods, C-ALS can accurately grasp
information like the three-dimensional shape, spaceposition, the actual boundary, the area of the top floor,
and the volume of the goaf (Liu, 2012; Ren et al., 2013;
Xia et al., 2009). The information could be used toverify the results of geophysical prospecting and drillingin the goaf, and to guide the further development ofgeophysical prospecting and drilling in the mined out
area of the mine.

2. CAVITY-AUTOSCANNING
SYSTEM（C-ALS）LASER*Corresponding author – email: 81905778@qq.com

MDL developed a robotic laser exploration
system", that can fquickly and safely explore theworking area in the mine through a hole drilled
beforehand. This system is called “Cavity automatic
laser scanning system”(C-ALS) (Ma et al., 2013; Ma etal.). THe C-ALS system is a kind of self-navigation,"mechanical" robot probe. It can enter into the dry waste(in use) within the working area of the mine exploration.
The diameter of the device is only 50 mm, therefore it
can be placed into pre drilled holes whose diameter areat least 65 mm. Using a front micro laser scanner, itmeasures the three-dimensional shape of the cavity andthe surface reflection. C-ALS can be lowered to a depthof 300 m, and the distance between the upper and thehorizontal detection is 100 m.
C-ALS has the following advantages:(1)Prospecting dangerous underground mine areas
in a safe way.
(2) 3D results available within a few minutes, noneed to wait for a few days.
(3) Automatic scanning operation.
(4) Flexible use method.
(5) Small size and convenient transportation.
(6) 360 degree scanning coverage with no “blindspot”.
(7) High precision and accuracy of goaf and spacemeasurement.
The device structure is shown in Figure 1.

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

mining area damaged the 4th and 9th coal seam
severely. The destroyed area of No. 4 and No. 9 seams is
3.5 km2 and 0.275 km2, respectively. Additionally, thesurface subsidence and cracks increase rainwater
infiltration. The water in the goaf is in a dynamic
process where the no-water area may gradually becomea water area. As a long-term collapse area, there is
probably a small amount of hydrocele.

Figure 1: Equipment structure of C-ALS.

Below are the field devices and operating
conditions, as shown in Figure 2.

3.2 Goaf Scanning
To grasp the characteristics of the goaf in Anjialing
accurately, China Coal Research Institute has used a 3D
laser scanner to scan the drillings that exposed the goaf.
From June 3rd, 2013 to June 6th, 2013 and July 16th to
18th, technicians detected a goaf for the 1302 and 1316
face. In total they scanned 18 drillings and a natural
collapse pit (scanned the pit 5 times). 15 of the drillings
are successfully scanned while the others are failed. The
pit was successfully scanned 5 times. As a result, there
were a total of 20 successful scans. The results are
satisfactory.

Figure 2: Three-dimensional laser scanning equipment
working drawing.

3. EXPLORATION IN ANJIALING
3.1 General Situation of Anjialing Surface Mine
Anjialing surface mine is located in the south
central Pingshuo mining areaConstruction began in
April 1998, and the design and production capacity is
10.0 Mt/a. In 2003, it reached design production
capacity when the production of Anjialing Surface Minereached 32 million tons. The major minable seams areburied from 100 m to 200 m. From top to bottom therecoverable coal seams are No. 4, No. 9 and No. 11.
They have an average thickness of 29.5 m. The present
mining stope is shown in Figure 3.

Figure 4: Anjialing three-dimensional laser scanning site.
Table 1: Probe hole information.
Sample
ID
1
2
3
4
5
6
7
8
9
10
11
12
13

Figure 3: Stope situation.

14

The coal seam is shallow in the Anjialing district,and small-size coal mining has a long history. A small
kiln mining area distributed in the centre of the first15

location
East

North

Height11703.7
11712.011564.1
11564.6
11547.7
11538.6
11542.811531.4
11537.6
11529.511693.2
11676.711648.5
11678.411675.611676.4
11687.871356.5
71345.7
71292.5
71292.071304.071303.671309.3
71304.6
71250.971251.2
71356.6
71359.2
71341.2
71348.771344.3
71340.871331.6

1316.81316.61302.11302.21302.71302.71302.81302.51302.71302.71316.71315.11302.41314.81314.41314.91317.8Resultofdrilling

Discovergoaf ornot

AppearYes

AppearYes

AppearAppearAppearAppearAppearAppear

No
No
Yes
Yes
Yes
Yes

AppearYes

AppearYes

656

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

location

Sample
ID

East

North

Height16
17
1811690.011650.011648.871334.971317.4
71326.01317.91302.71302.6

Resultofdrilling
AppearAppearAppear

Discovergoaf or
not
Yes
Yes
Yes

3.3 Description of goaf
According to the recent scans, the goafs exposed bydrillings are connected. Descriptions of the goaf are as
follows:(1) The roof and floor are higher in the north andlower in south, which is similar to the coal seams. As aresult of the fact that the dip of the floor is increases
gradually in the southward direction, the goaf is higher
in the south and lower in north.
(2) In the north of the proved area, the lowest heightof the roof is 15 m. In the southwest, the highest heightof the goaf is 32 m. The longest axis is nearly 60 m. The
vertical height is low in the north and high in thesouthwest. In proved area the lowest vertical height is 5
m and the highest vertical height is 15m. The width of
the goaf is about 15 m.
(3) The volume of the proved area in the goaf is21139 m3.
(4) In the goaf, there is dust and gas of water. The
temperature is low. It is judged that there is no water orfire in the goaf.

Figure 6: Anjialing goaf three-dimensional laser scanning theoverall situation point cloud (Front view).

According to scanning of the caved pit, it was foundthat there is a goaf around the pit that is connected to thepreviously discussed goaf. 6 drillings, F(01)，F(02)，G(01) ， G(02) ， G(03) ， and G(04) were drilled bytechnical personnel. The locations of the drillings areshown in Table 1. The drilling showed that there was agoaf around the drilled area. The height of the roof issimilar to the scanned results.

4. GOAF MODELLING AND DISPOSAL
4.1 Goaf modelling
Goaf 3D modeling was performed using the
Geomagic Studio software using the data from the 3D
laser scans (Liu et al., 2009; Wang et al., 2010; Chen etal., 2012). The volume of the goaf was calculated at thesame time. The whole goaf and volume are shown in
Figure 7..

Figure 5: Anjialing goaf three-dimensional laser scanning theoverall situation point cloud (Overlook).

Figure 7: Anjialing goaf 3D modelling view.

Scanning results accurately determined the trend of
the goaf. The distribution of goaf is in line with the basic
characteristics of small coal mining. The effect is verysignificant, and therefore provides an accurate basis forthe further processing of the goaf.

657

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

4.2 Goaf disposal
The blasting method is the most commonly usedmethod in the production process of handling goafs insurface mining. According to the relationship between
the mining area and flat bench, the loose blasting
method is suggested to treat goafs. The specificpractices are as follows:
Blasthole
Goaf（a）Sectional view

Blasthole
End slope

Goaf（b）Front view

Filling area
End slope（c）Front view¡ ªAfter blasting

Figure 8: Loose blasting in goaf disposal.

The results of loose blasting in the goaf inAnjialing surface coal mine are as shown in Figure 9.

Figure 9: The goaf after blasting.

5. CONCLUSION(1) There are many goafs in Anjialing surface mine.
Exploring and disposing of the existing goafs has great
importance to guarantee safe production in the surfacemine.
(2) By using the "cavity automatic laser scanningsystem", the Anjialing surface mine area goafs were
found. A large scale drilling scan discovered that thegoafs were connected. By drilling verification, it was
found that the gob roof elevation is the same as the 3D
laser scanner elevation.
(3) An accurate computation of the goaf's volume
was made via goaf 3D modeling. It was prove that the

3D laser scanning results give an accurate judgment of
the goaf trends.
(4) Based on the goaf 3D model, the goaf wasdisposed of with loose blasting to lay a foundation forsafe production in the surface mine.

6. REFERENCES
Chen Kai,Yang Xiaocong, Zhang Da(2012). Studyon cavity 3D laser scanning deformation monitoring test.
Non-ferrous Metal, Volume 64, pp. 1-5.
Liu Xiling(2008). Research for stability analysis
and safety forewarning of cavity based on laser 3D
detection[D]. Central South University.
Liu Jun, Wand Di(2009). Integrated Application of
GPS and 3D technology in Detection of Mined-out Area.
Metal Mine. suppl, pp. 512-515.
Liu Kewei(2012). Study of 3D laser scanningvisualization and analysis of the stability of hazardous
cavity under open-pit mine[D]. Central South
University.
MA Yutao ， Peng Wei(2013). Study on
Cavity-Autoscanning Laser System (C-ALS) and its
application in Anqing Copper Mine(Non-ferrous Metal).
Volume 65, pp. 9-12.
MA Haitao, LIU Yongfeng, HU Jiaguo. Study on
gob detection and visualization of three-imensionalmodel based on C-ALS. Journal of Safety Science andTechnology. Volume 6, pp. 38-41.
Ren Hongwen, Liu Zhaofu, Han Zhiyao Wang
Jinghai, Deng Guoping.(2013) Application of 3D Laser
Scanning Technology in the Surveying and Mapping.
Gold Science and Technology. Volume 21, pp. 64-68.
Sun Shufang. Analysis and Processing of Goaf
dimensional laser scan data[D]. Kunming University ofscience and technology,2009.
Xia Yonghua, Fang Yuanmin, Sun Hongsheng,
Zuo Xiaoqing WA Xuekun Chen Jie(2009). Error
Analysis and Calibration of 3D Laser Monitoring
System Survey in Finished Stopes. Bulletin of
Surveying and Mapping. Volume 18, pp.18-21.
Wang Guotao，Luo Zhouquan，Liu Xiaoming,
Zhu Qingling(2010). Application of 3D monitoring andmines based on visual modeling cavities in metallic
cavity features. The Chinese Journal of Geological
Hazard and Control. Volume 21, pp. 104-109.

658

Paper No. 49

ISMS 2016

Application of the strength reduction method in coal mine roof support design
Gabriel Esterhuizena,*, Ihsan Berk Tulubab

Principal Research Engineer, NIOSH Office of Mine Safety and Health Research, Pittsburgh, PA, USA
Associate Service Fellow, NIOSH Office of Mine Safety and Health Research, Pittsburgh, PA, USA

ABSTRACT
Ground falls represent a significant proportion of injuries and fatalities in underground coal mines in the US. During
2013, ground falls were responsible for 4 of the 14 fatalities and 16.6% of the 1,577 reportable lost-time injuries. In
addition, each year about 400 to 500 large roof falls are reported that can extend up to or above the bolted horizon.
Support design for coal mine entries is largely based on past experience and a trial-and-error approach. A numericalmodel-based approach for support design is presented in which calibrated models are used to determine a stability
factor for a supported entry. The stability factor is determined using the strength reduction method (SRM). Applying
this technique, the relative merits of various support systems can be evaluated. The numerical models allow thecontribution of individual support units to overall stability to be assessed. Two case histories are presented. In thefirst case the SRM approach is applied to assess the use of passive cable anchors as primary support in a room-andpillar coal mine. The second demonstrates how the SRM approach was used to evaluate the impact of angled bolts at
the rib-roof corner on roof stability. It is concluded that the SRM approach provides useful information to assess theoverall degree of stability achieved by a support system, and allows support elements to be optimized for particulargeological and stress conditions.
KEYWORDS: FLAC3D; coal mine roof support; strength reduction method; cable bolts

1. INTRODUCTION
Ground falls remain a significant cause of
fatalities and injuries in underground coal mines.
Over the ten-year period of 2005 through 2014, fallsof ground were responsible for 32% of all fatalities inunderground coal mines (Mine Safety and HealthAdministration(MSHA),
2015).
While
improvements are continuously being made insupport technology, design, and application,
underground mine workers remain exposed to thehazard of ground falls on a daily basis. Factors
contributing to ground falls may include naturalplanes of weakness within the rock mass, unfavorable
loading conditions, low rock strength, unusual
depositional features, and dynamic loading events.
Furthermore, a specific roof fall may be related tomore than one contributing factor. Ground falls canbe reduced by supporting the excavation walls and bymodifying the excavation layout to improve groundstability.

2. SUPPORT DESIGN APPROACHES
Mine operators in the United States are expected
to develop and follow a roof control plan, approvedby the MSHA district manager, which is suitable tothe prevailing ground conditions and mining
methods. The roof control plan specifies theminimum support requirements such as bolt spacing,length, and type that will be used to support the roof

Corresponding author – email: eee5@cdc.gov

and ribs of coal mine entries. The support design
procedure for roof control plans is left open to themine operator, allowing innovation and developmentof new technologies.
Current roof support technology makes use ofrock reinforcement principles to improve the strengthand stability of the rock through the installation ofroof bolts. This type of support is called intrinsic
support, because it is located within the rock mass,
providing internal reinforcement. In some situations
where it may be difficult to install intrinsic support orwhere excessive deformation is expected, external
supports in the form of standing supports may be
used.
During the early years of the application of
intrinsic support systems, in-mine trials and theobservational approach were used to determine
support requirements (Mark, 2000). Limited support
system analysis was conducted, typically using
analytic equations based on beam theory (Fairhurst
and Singh, 1974). Over the years significant
improvements were made in the types of support
units and the understanding of the interaction of therock mass with the support units.
At present there is more than 50 years ofexperience of the application of intrinsic support
systems in coal mines that forms the basis for support
design. This experience is captured in many of the
support rules found in the mining regulations and3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

published in MSHA guidelines. The NIOSHdeveloped Analysis of Roof Bolt Systems (ARBS)(Mark et al., 2001) is an example of a design
approach based on a statistical analysis of successful
and unsuccessful applications of support systems.
As a result of this wealth of empiricalknowledge, the support system for a new mine cansimply be based on a support system that was
successfully implemented under similar conditions
elsewhere. However, the reliance on empiricalexperience does have limitations. As new support
technologies become available, mining techniqueschange, and as mining depths increase, the historicalexperience may no longer be applicable. This
shortcoming can be solved by following anengineering approach to support design. The
engineering approach makes predictions about thestability of a system through the analysis of thestrength and expected loads that the system will be
subjected to (Hoek et al., 2003).When considering asystem that consists of brittle rock materials, bedding
planes, rock joints, steel bolts, and resin grout, thestability analysis can become complex. As
computational methods have become more efficientand affordable, numerical models are increasingly
used to conduct the analysis of excavation stability inrock materials. There are many computational models
commercially available that can assist in conducting
these types of analysis. However, at present no single
engineering-based analysis method has found wide
acceptance in U.S. coal mines (Mark, 2000; Tadolini
et al., 2006).

estimation of coal mine entry stability factors(Esterhuizen, 2012).
3.1 Applying the strength reduction method
The numerical models of coal mine entries
simulate a slice perpendicular to the axis of the entry.
The thickness of the slice is equal to the support row
spacing, typically 1.2 m. The various rock layers aremodelled with appropriate strength parameters. The
contacts between various units of rock in the roof aremodelled as discrete interfaces. The bedded rockwithin each unit is modelled as a layered material,using the ubiquitous joint material type available in
FLAC3D. Support units are also modelled explicitly.
The FLAC3D software has the capability torealistically model grouted steel supports, with orwithout pretension.
The SRM is applied by first conducting astability analysis using average rock strength
properties. Depending on the outcome, the analysis isrepeated using either a decreased or increased rockmass strength until the point of collapse issatisfactorily bracketed. Strength adjustments areachieved by simultaneously reducing or increasing
the cohesion, tensile strength, and the coefficient offriction of the rock mass. The stability factor issimply calculated as the inverse of the strength
adjustment factor at the point of collapse of themodeled excavation. For example, if collapse occurs
when the strength is reduced by a factor of 0.8, thestability factor would be 1.25.

3. DEVELOPMENT AND VALIDATION OF
THE STRENGTH REDUCTION METHODFOR ROOF SUPPORT DESIGNThe need for a standardized method to conduct
engineering analysis of coal mine roof support
systems has been addressed by making use ofnumerical models that are able to realisticallysimulate the rock mass response to excavations andthe interaction of the support systems with the rockmass. The FLAC3D finite difference code (Itasca,2014) was selected to conduct the model analyses.
The modeling approach allows a “stability factor”(SF) to be determined for a supported entry. The SF
is determined by using a modeling technique known
as the strength reduction method (SRM)(Zienkiewicz et al., 1975). The SRM has a long
history in numerical modeling and has often been
applied in rock slope stability engineering todetermine the safety factor of rock slopes (Lorig andVarona, 2000), but has not been widely used forunderground excavation analyses. The classic SRM
approach was adapted and modified to allow the

Figure 1: Model results showing a supported entry: a) when
the rock strength has been reduced to a point of criticalstability, and b) when further reduction of the rock strength
causes roof collapse.

The occurrence of collapse is indicated by theinability of the model to reach a state of equilibrium
after an extended number of solution cycles. Usually,
this means that a section of the roof is accelerating
downwards and equilibrium could not be reached.
Figure 1(a) shows a plot of a numerical model of an
entry in which the rock strength has been reduced tothe critical point where collapse is about to occur.
Figure 1(b) shows how the roof collapses when therock strength is reduced by a further 5%.

660

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

When applying the SRM to underground coalmine excavations, it was found that floor heave wassometimes the mode of ultimate instability. This
would occur if the floor rocks are weaker than theroof rocks. All analyses were therefore conducted byonly reducing the rock mass strength above the roofof the excavation while leaving the coal and floor
rocks unadjusted. Analyses may be conducted inwhich the effect of floor instability is assessed.
3.2 Model validation
The outcome of the modeling procedures wasvalidated against empirical design methods that areused in US coal mines (Esterhuizen et al., 2014). The
model results were initially assessed to determine ifthey are able to capture variations in roof stability
predicted by the coal mine roof rating (CMRR)(Molinda and Mark, 1996; Mark et al. 2002).
Additional verification was conducted by comparing
SRM-calculated stability factors to the empirically
based ARBS method (Mark, 2000; Mark et al.,2001). The CMRR and ARBS methods are based on
extensive observation of entry stability in operating
mines, capturing decades of empirical experience of
the authors. These empirical methods are used toevaluate potential stability or instability in operating
coal mines and are suitable for validating the SRM
calculated stability factors.

ARBS calculated SF

5
R² = 0.7605

4
3
2
1
0
0

1

2

3

4

5

SRM calculated SF
Figure 2: Comparison of stability factors
calculated using the ARBS empirical method and the SRM
for 120 cases of entries supported by 1.8-m bolts.

The relationship between SRM-calculated and
ARBS-calculated SF values for the 120 models of
entries supported by 1.8-m fully grouted bolts isshown in figure 2. The results show that the two
methods predict similar trends, with a coefficient ofdetermination of 0.76. At lower SF values the scatterof results is small, which is important for design.

The similarity of results achieved by themechanics-based SRM and the statistically-based
ARBS for this wide ranging set of conditions
demonstrates that the SRM captures the essential
factors affecting entry stability.

4. APPLICATION OF THE SRM TO
EVALUATE SUPPORT ALTERNATIVESThe SRM has been applied to evaluate support
systems for various operating coal mines. Two casehistories are presented here in which support
alternatives were evaluated to improve theunderstanding of the contribution of support elements
to overall stability, and to quantify the degree ofstability achieved.
4.1 Case history 1: Room-and-pillar mining withcable bolt support
Cable bolting is sometimes used as primary
support in coal mines experiencing difficult roof
conditions. In low-seam mines, the flexibility of thecable bolts allows greater length supports to beinstalled near the advancing face without the use of
couplers. When used as primary support, the cables
are typically installed in the same row as fully
grouted bolts, replacing two or more of the bolts ineach support row. A heavy steel channel may be used
as a strap to spread the support load over a greater
portion of the roof. Historically, MSHA has notallowed widespread use of partially grouted untensioned cable bolts for primary support.
At the case study mine, fully grouted rebar bolts
with pre-tensioned cable bolts were used as primary
support. It was found that when a large roof falloccurred, the cable bolts may be contained within thedome of fallen rock. As problematic roof conditions
continued to exist, the mine management decided tomodify the system using passive cable bolts as part ofthe primary support system. The cable bolts werelocated near the ribs of the entry, to increase thelikelihood that they would be anchored outside thedome of potentially unstable roof. The modified
system resulted in considerably improved stability
conditions in the mine. However, the mine engineer
was uncertain whether the modified system wasindeed better than the original system for controlling
the roof, or whether the improved conditions wererelated to changes in the geology or other factors. An
analysis using the SRM was conducted to identify thedifferences between the two systems.
4.1.1
Geotechnical Conditions
The case study mine extracts the Lower
Kittanning coalbed. The mine uses the room-andpillar method in a mining height of about 1.2 m. The
depth of cover is approximately 120 to 150 m. In

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

certain locations the roof consists of 10-m-thicklaminated dark gray silty shale that is associated withdifficult ground conditions. It is overlain by astronger interbedded sandstone and shale unit.
Observations of the rock exposed in roof falls showthat it tends to delaminate in thin slabs that are about
2 to 6 cm thick, as shown in Figure 3. The uniaxial
compressive strength of the intact shale is 55 to 60
MPa. The available rock strength and bedding
information were used to classify the rock mass using
the coal mine roof rating (CMRR) (Molinda andMark, 1996). The CMRR classification of the silty
shale roof is estimated at 45.

Figure 3: Typical roof fall showing laminated nature of thesilty shale roof rocks and steep-sided collapse cavity.

Stress measured in the vicinity of the mineshows results typical of Northern Appalachia with arelatively high pre-mining horizontal stressassociated with regional tectonic loading (Mark andGadde, 2008; Dolinar, 2003). The major horizontal
stress is estimated to be oriented at N80E. Where
possible, the mining direction is oriented so that thedevelopment is directed favorably relative to thestress field.
4.1.2
Support systems analyzed
The original and modified support systems used at
the mine were evaluated using the SRM approach.
The support layouts are shown in figure 4.
The original support system consisted of fully
grouted conventional bolts and tensioned cable bolts
as part of the primary support, installed on-cycle.

Cable bolts are partially grouted, with 1.2 m of resin
grout forming the anchorage zone. Each support row
was installed through a heavy T3 channel. The firstrow of the pattern consisted of two, 1.8-m-long, No.
5 tensioned rebar bolts through the center section of
the entry and two, 3.6-m-long, 15-mm-diameter cablebolts on the outside. The second row reverses theorder. Bolt tension is nominally 5 t. The support rows
are 1.2 m apart. Entries are 5.5 m wide.
The modified support system consisted ofsupport rows with four 1.8-m-long No. 5 tensioned
rebar bolts and two 3.6-m-long un-tensioned cables
installed on a 4.3-m-long T3 channel. The cables arelocated about 50 cm from the ribs, near theextremities of the channel. Additionally, the entry
width was reduced to 4.9 m.

Figure 4: Support systems analyzed at case study 1 mine,showing a) the original system with tensioned cable bolts,
and b) the modified system with passive cable bolts.

4.1.3
Results of SRM analysis
The original support system was simulated andthe SF was determined to be 2.21. This SF value
would be considered to be adequate for most roomand-pillar mining. However, the thinly laminatednature of the roof and relatively high horizontal stressappears to require a higher value of the SF to prevent
large-scale roof falls. The modified system, using thegreater intensity of fully grouted bolts and passive
cable bolts produces a SF value of 2.84. Thisconfirms that a significant increase in support
capacity and stability is achieved by the modified
system. The increase in stability can be attributed toboth the increase in support and the reduction in entry
width.
A closer look at the numerical modeling results
showed that for the original system, instability occurs

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

when the roof yielding extends above the top of thecable bolts that are located near the center line of theentry. Under these conditions the cable bolts do notachieve their full load capacity, and collapse while
encapsulated inside the failing roof. Under these
conditions, the pretension does little to prevent thecollapse.
With the alternative system, the location of thecable bolts outside the collapsing dome of rock helps
to provide anchorage in the stable rock. In addition,
the T3 channel is shown to act as a sling that holds
the failing rock in position. The sling-action is able tocontrol the roof over a much greater range of roofsag.
The results also showed that the fully groutedbolts would load up quickly as the roof sagged, but
once roof failure developed above the bolts, thepassive cable bolts would start to load up, acting
almost like a tandem system that controls the roof
after the fully grouted bolts started to shed load.
In practice it was found that the mine operational
staff could readily identify areas which had sagged
when using the modified support system. When thiscondition was observed, cribs or other types ofstanding supports were typically installed to arrest
further movement. So although roof sag occasionallyoccurred, the support system was able to control thedamaged roof, allowing remedial actions to be taken
to prevent collapse.
4.2 Case history 2: Longwall Gateroad Support
Changes
Longwall gateroads provide access to theworking area of a longwall mine. The gateroads are
subject to increased loading as the coal is extracted
and loads are transferred to the adjacent unminedcoal. Gateroads are expected to remain stable during
these changing stress conditions. Gateroads are
typically provided with primary support during
development consisting of roof bolts. Secondary
support in the form of cable bolts and screen may
also be installed. Various forms of standing supports
may also be required to maintain the integrity of theroof rocks under the severe loading conditions near
the longwall face.
At the second case history mine, fully groutedbolts are used as primary support and two additionalbolts are installed at 45° in the rib-roof corner, as
shown in figure 5. These bolts were originallyintended to help support friable roof if stress-related
roof damage occurs in the corners. However, as
experience was gained it was found that the cornerbolts did not appear to be required. In this case themine management was interested to know if locating
the corner bolts 30 cm away from the corner andinstalling them vertically would improve the support
efficiency.
4.2.1
Geotechnical Conditions
The mine also extracts the Lower Kittanningcoalbed using the longwall mining method. The
mining height is about 2.1 m and the depth of covervaries between about 150 m and 240 m. The roof
rock is a sand shale with an average uniaxial
compressive strength of 76 MPa. The CMRR for thisroof rock is estimated to range between 47 and 52.
The horizontal stress at this mine is expected to be
typical of Northern Appalachian mines. Some stressrelated roof-cutter formation was observed in themine roof. The orientation of the longwall panels was
optimized to minimize horizontal stress impacts.
4.2.2
Support Systems Analyzed
The support system evaluated consisted of 1.8m-long fully grouted bolts with 180 kN capacity
installed in rows 1.2 m apart. Each row consisted offour vertical bolts and two 45° angled bolts at the ribroof corner. In addition, two supplementary cablebolts 3 m long were installed in rows 2.4 m apart.
The cable bolts were installed on a T3 channel. The
entry width is 4.9 m.
This support system was evaluated with cornerbolts installed at 45° and with corner bolts installedvertically, located 30 cm from the entry ribs.

Figure 5: Central portion of a numerical model showing
entry and support types evaluated.

4.2.3
Modeling results
The modeled SF against roof collapse for thebase case, with the 45° corner bolts, was determined
to be 1.85. Inspection of the bolt loading in the model
showed that the corner bolts did not attract much loadas the roof sagged. The load in the corner bolts only663

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

increased to about 40 kN while the vertical bolts
would load up to about 200 kN, which is theirultimate capacity. The cable bolts loading was more
gradual, owing to the free length of about 1.8 m.
Cable bolts approached their ultimate load after about
150 mm of roof sag.

model outputs can be evaluated further to determine
the contribution of individual support elements tooverall stability.
Two case histories demonstrate the applicationof the method to assessing support alternatives at
operating mines. The calculation of a stability factor
allows direct comparison of the overall efficiency ofeach support alternative.
Insight was also gained into the mechanics of the
support-rock interaction, showing how the fully
grouted supports are initially loaded-up, followed byloading of the passive cable bolts.
The studies demonstrate that numerical modelbased analysis of coal mine entry support systems
allows support alternatives to be evaluated andimproves understanding of support element
contributions. The optimized support systems provide
improved safety for mine workers.
6.

DISCLAIMER

The findings and conclusions in this paper are thoseof the authors and do not represent the views of
the National Institute for Occupational Safety and
Health (NIOSH). Mention of any company name,product, or software does not constituteendorsement by NIOSH.
Figure 6: Bolt loads vs. roof sag for the support system inwhich the corner bolts are installed vertically.

When the corner bolts were located 30 cm fromthe rib and installed vertically, they attracted loads of
up to 130 kN, and maintained a load of about 80 kN
as the roof sagged. Figure 6 shows the bolt loads androof sag for a case in which the rock strength has
been reduced to the point of critical stability. The
vertical corner bolts clearly contribute moresignificantly to the overall stability of the roof. The
calculated SF was increased to 2.25 by the change incorner bolt location and orientation.
With this configuration, the cable bolts are able
to control the roof sag up to about 130 mm when load
shedding starts to occur.
These results provided confirmation that the 45°
corner bolts were not as effective in contributing tothe overall stability of the entry roof, and that theadjusted support system was likely to be more
effective.

5. CONCLUSIONS
A numerical modeling approach has beendeveloped that allows the stability factor of supported
coal mine entries to be estimated. The numericalmodels have been calibrated against field-measured
rock mass response and support interaction. The

7. REFERENCES
Dolinar, D. (2003). Variation of Horizontal
Stresses and Strains in Mines in Bedded Deposits inthe Eastern and Midwestern United States, inProceedings 22nd International Conference on
Ground Control in Mining, 6–7 August 2003,
Morgantown, USA, pp. 178–185.
Esterhuizen, G.S. (2012). A Stability factor for
Supported Mine Entries Based on Numerical Model
Analysis, in Proceedings 31st International
Conference on Ground Control in Mining,
Morgantown, USA, 9 p.
Esterhuizen, G.S., Murphy, M.M., and Bajpayee,
T.S. (2014). Analysis of geotechnical and support
parameters on coalmine entry stability using thestrength reduction method. AusRock 2014: Third
Australasian Ground Control in Mining Conference,
November 5-6, 2014, Sydney, New South Wales,
Australia. Australasian Institute of Mining andMetallurgy, 2014 Nov; pp. 383 –391
Fairhurst, C. and Singh, B. (1974). Roof Boltingin Horizontally Laminated Mine Roof, Engineeringand Mining Jour., pp. 80–90.
Hoek, E., Kaiser, P.K., and Bawden, W.F.
(1995). Support of Underground Excavations in Hard
Rock, 300 p, (CRC Press).
Itasca Consulting Group (2014). FLAC3D Fast
Lagrangian Analysis of Continua in 3 Dimensions,
Itasca Consulting Group, Minneapolis, MN.

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Lorig, L. and Varona, P. (2000). Practical Slope
Stability Analysis using Finite-Difference Codes, inProceedings Slope Stability in Surface Mining, W.A.
Hustrulid, M.K. McCarter and D.J.A. van Zyl (eds),
pp. 115–124 (Society for Mining Metallurgy andExploration, Littleton, USA).
Mark, C. (2000). Design of Roof Bolt Systems,in New Technology for Coal Mine Roof Support,
NIOSH Open Industry Briefing, NIOSH IC 9453,
2000, pp. 111–132.
Mark, C., Molinda, G.M., and Dolinar, D.R.
(2001). Analysis of Roof Bolt Systems, inProceedings 21st International Conference on Ground
Control in Mining, WV University , Morgantown,
USA, 7–9 August 2001, pp. 218–225.
Mark, C., Molinda, G.M., and Barton, T.M.
(2002). New Developments with the Coal Mine Roof
Rating, in Proceedings 21st International Conferenceon Ground Control in Mining, Morgantown, USA, 6–
8 August, pp. 294–301.
Mark, C. and Gadde, M. (2008). Global Trends
in Coal Mine Horizontal Stress Measurements, inProceedings 27th International Conference on
Ground Control in Mining, WV University,
Morgantown, USA, pp. 319–331.
Mine Safety and Health Administration (2015).
Web Page: http://www msha gov/stats/statinfo htm
Molinda, G.M. and Mark, C. (1996). Rating theStrength of Coal Mine Roof Rocks, U S Departmentof the Interior, Bureau of Mines IC 9444, Pittsburgh,
Pennsylvania 36 p.
Tadolini, S.C. and Mazzoni, R.A. (2006).
Twenty-four conferences; more than one-hundredand seventy papers; understanding roof bolt selection
and design still remains priceless. Proc. 25th
International Conference on Ground Control in
Mining, West Virginia University, Morgantown,
WV, pp. 382–389.
Zienkiewicz, O.C., Humpheson, C., and Lewis,
R. W. (1975). Associated and Non-Associated ViscoPlasticity and Plasticity in Soil Mechanics,
Geotechnique, Vol 25, pp. 617–689.

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ISMS 2016

Paper No. 98

Numerical simulation of the migration laws of supports and surrounding rockfor coal seams of large dip angle
Huang Zhian, Feng Caiyun, Wang Hui*, Zhang Yinghua, Gao Yukun
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing, China, 100083

ABSTRACTSDIC Nileke mine district is located in Xinjiang and it contains 6 minable seam layers. The 45ºaverage dip angleof the mine results in the complex processes of the mining working face. Processes such as support moving andmining working face advancing are restricted. The lateral stress of the roof increases, and at the same time theproblem of controlling the working face roof becomes serious. Based on practical conditions, the process of
excavation and support of the mine working face are simulated using FLAC 3D. The results can provide technicalsupport for safety production through the reasonable support mode obtained through the simulation of mine pressure
behaviour of the working face.
KEYWORDS: steep seam mining; numerical simulation; support resistance; hydraulic support stability
Deep inclined seam refers to coal seams with aninclination between 35° and 55°. In China, deep
inclined seams account for about 15%-20% of allcoal resources. Over 50% of the deep inclined seams
are high-quality coking coal and anthracite. As we allknow, high-quality coking coal and anthracite is a
scarce coal in China. (Xie, P. S. et al., 2015a ; Wen,
M. M. 2014b; Qu, Q. Y. 2014c). The mine pressure
behaviour changes significantly when compared togently inclined seams while mining. Problems suchas the increasing of roof lateral stress and theincreasing possibility of dumping and sliding of
hydraulic support are highlighted. It is of particularimportance to study the relative movement of the
support and the surrounding rock of deep inclined
coal seams. To solve this problem, much research has
been carried out by scholars. For example, theinteraction characteristics between surrounding rockmovement and support system in large mining height
fully-mechanized faces in steeply inclined seams
were analyzed by Xie Panshi (2015). The pressure of
the surrounding rock of A6 coal seam was analyzed inthis paper using FLAC3D. A6 coal seam is a part of
SDIC Nileke mine

1.

MINE INTRODUCTION

SDIC Nileke mine is located east of Nilka
county town. The production capacity of the mine is
1.2 Mt/a. The mining district contains 6 coal seams.
It is about 2.15-8.06 km from east to west and 1.214.38 km from north to south, for a total area of about
28.01 km2. This paper mainly discusses the A6 layer,
which is characterized by:*Corresponding author – email : wanghuiustb@live.cn.

(1) The average thickness is 6.42 m. It is a stablecoal seam. The roof of the coal seam consists ofcarbonaceous mudstone, mudstone, and silty
sandstone, and the bottom plate consists ofcarbonaceous mudstone, silty sandstone, and finesandstone. It can be concluded that its structure isrelatively simple.
(2) The average thickness of A6-lower is 2.94 m.
The number of the gangue layer is from 0 to 2, andthe gangue layer is mainly composed ofcarbonaceous mudstone. The roof of the coal seam
consists of carbonaceous mudstone, mudstone, andsilty sandstone, and the bottom plate is composed ofcarbonaceous mudstone and mudstone.
2.

MODEL ESTABLISHMENT

After the coal resource is exploited, thesubsidence of overlying strata occurs. The numericalmodel is built by using FLAC3D, and MooreCoulomb criterion were used to judge the destructionof rock.
The depth of N11 working face is 150-350 m. To
be safe, the thickness of the overlying rock was set to
350 m in the simulation. The weight of the overlying
strata is 2.5 MPa/100 m. A distributed load is set to
the top of the model to simulate the overlaying
strata’s weight. The vertical pressure of theoverlaying strata is 8.75 Mpa. The scale of module is
100×130×180 m. The inclination of the coal seam is
45°. The model is built using the 8-points method, it
contains 14400 units and 17702 nodes. The four sidesof the model are displacement boundaries and cannot
be moved in the horizontal direction. The bottom side

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016of the model is a fixed boundary. The fixed boundary
means it cannot be moved either in a horizontal
direction or in a vertical direction. The thickness ofthe coal seam is 8.7 m, and the mining height andcaving height were set to 4 m and 4.7 m, respectively.

The roof thickness of the working face is 25.2 m andthe height of the bottom floor is 10.2 m. The modeland the mesh are shown in Figure 1. Other
parameters were obtained by an experiment, asshown in Table 1.

Table 1: Numerical simulation parameters
Thickness Density ρ0 Compressive Elastic modulus Poisson'sRock properties
3
E（GPa） ratio/μ（m） （kg/m ） strength（

Cohesivestrength/C（

Internal

Tensilefriction angle strength（

Fine sandstone

3.40

2660.00

MPa）
75.13

18.92

0.23

MPa）
14.50

（°）
47.60

MPa）
7.67

Powder sandstone

2.00

2540.00

74.17

17.00

0.22

14.70

47.40

9.97

Middle sandstone

2.00

2580.00

68.52

29.20

0.18

15.31

45.25

11.60

Powder sandstone

3.60

2540.00

74.17

17.00

0.22

14.70

47.40

9.97

Coarse sandstone

4.80

2620.00

105.63

33.87

0.16

21.95

48.69

7.89

Powder sandstone

1.60

2540.00

74.17

17.00

0.22

14.70

47.40

9.97

Middle sandstone

4.20

2580.00

68.52

29.20

0.18

15.31

45.25

11.60

Conglomerate

2.40

2500.00

49.78

14.23

0.28

17.80

45.30

7.22

Powder sandstone

1.00

2540.00

74.17

17.00

0.22

14.70

47.40

9.97

A6 minelayer

8.70

1400.00

7.26

3.65

0.29

4.05

41.00

4.19

Powder sandstone

10.20

2540.00

74.17

17.00

0.22

14.70

47.40

9.97

According to Moore - Coulomb criterion (Wu J.
B., 2010), the intensity of rock is calculated asfollows:
1 + sin ϕ
1 + sin ϕ− 2c
σ 1 −σ 3fs =1 − sin ϕ
1 − sin ϕ（1）

f=1 σ 1 − σ 3（2）Where: σ1—— the maximum principal stress.
σ3—— minimum principal stress.
C——material cohesion.
φ—— internal friction angle
Figure 1: Themodel andσt is the tensile strength of rock. If fs≤0, shear

Figure 2: Excavation
model: ① goaf ②stent locationh③ advanced direction.
.

In the simulation, 25 meters of coal were left inthe starting side in the direction of the working face.
The excavating speed along the working faceadvanced direction was 5 meters per time step, andthe mining height was 4 meters. Until it came to abalance, the iteration was stopped. During the
calculation, the caving coal was 30 to 60 meters the
supporting area of the working surface 60 to 65
meters, and the top coal did not collapse. The
excavation model is shown in Figure 2.

failure of rock will occur; if f1≥0, rock tensile failure
will occur (Wang H. W., 2010).
Due to the complicated rock properties of SIDC
and the effect of weak surface structure, laboratory
calculated parameters are inconsistent with theengineering practice. In order to fit the actual
situation, the elastic modulus of coal and rock is set
to 50% of the test values from the laboratory.

3.

RESULTS ANALYSIS

3.1 Analysis on the trend of surrounding rock before
supporting
The vertical direction stress of the surroundingrock after excavation is shown in Figure 3. From667

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 3 it can be seen that stresses wereconcentrated in the front of the working face. In theposition 6 meters ahead of the coal wall, themaximum stress is 2.24 MPa. However, in the middleof the goaf, the roof undergoes tensile stress becauseof the damage of rock layer.

coal wall, the third is 2.5 meters behind the coal wall,and the last one is 5 meters behind the coal wall. The
monitors were set to study the deformation of theinclined plane along the coal seam. The specificdisplacement is shown in Figures 5 and 6.

Figure 5: Vertical displacement along coal seam 5 meters
ahead coal wall and on the coal wall.
Figure 3: Stress of section along trend.

The change of vertical displacement along thedirection of the goaf after excavation without support
is shown in Figure 4. Due to the influence of cavingcoal behind the working face, the maximum
displacement of the working face is 4-5 meters fromthe coal wall, and this is the contact zone of goaf andsupport. The distribution of maximum displacementboundary looks like a triangular, and the maximum
displacement is 36 cm. While the distribution of roof
subsidence is arched, the maximum shift is 28.43 cm.
In the middle bottom, the maximum displacement is
14.98 m while vertical displacement decreases onboth ends at the goaf bottom. The floor may bebulged in the process of excavation. Effective
measures should be taken to solve the problems of
the roof.

Figure 6: Vertical displacement along coal seam 2.5 metersbehind the coal wall and 5 meters behind the coal wall.

As can be seen from Figure 7, the subsidence of
top coal is different at different positions of the coalwall. The subsidence is less than 10 cm in front of thecoal wall. While the subsidence of top coal in thecoal wall is greater than 5 meters ahead of the coalwall, the maximum is 26 cm in the middle of theworking face, and the minimum is 5 cm on two sidesof the working face. The displacement is about 37 cm
in the middle of the working face, while on both sidesof the working face the displacement is 8 cm. Fivemeters behind coal wall, the greatest subsidence of
top coal is 47 cm in the middle of the working face,
while on both side of the coal wall the subsidence is
10 cm.

Figure 4: Displacement nephogram of section along trend.

3.2 Analysis on the inclination of surrounding rockbefore supporting
According to the analysis of Figure 4, fourmonitor points were set in the model. The first one is
5 meters in front of the coal wall, the second is on the668

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 7: Cures of subsidence of top coal in different
positions without supporting.

It can be concluded that the law of subsidence ofthe top coal along the direction of the working face isthat the position of largest subsidence is 5 meters
around the coal wall, and the subsidence of 2.5
meters behind the coal wall is the second, and, thesubsidence on the coal wall is the smallest. The lawof subsidence of the top coal on the inclination of theworking face is complicated. In the middle of theworking face the displacement is the largest, while on
both side of the working face the displacement is thesmallest. However, due to the slipping of the fallingrock, the bottom of the goaf is filled. This will
inevitably lead to less subsidence of the top coal in
the bottom of the working face than for the top.
Therefore the subsidence of the top coal of theworking face is the largest in the central partial, thesecond largest on the upper, and the smallest on thelower. When the working face is excavated,not only
the top coal will have a subsidence, as the coal wall
will also produce a displacement. The horizontal
displacement of the coal wall is shown in Figure 8.
From Figure 8, it can be seen that the coal wall
will have greater levels of horizontal movement
without supporting. It is close to 28 cm in the middle
upper of the working face, which is the maximum
amount. However, the minimum amount is about 10
cm on the both ends. Some measures should be taken
to prevent spalling when supporting.

baseboard is mainly compressive stress. The
compressive stress of the baseboard is about 3.0 MPa
in the middle of the working face

Figure 9: Analysis on the stress distribution along the dipof layer 2.5 m away from coal wall without supporting.

3.3 Analysis on the change of surrounding rock withsupporting
From Figure 10 it can be known that thesubsidence of the roof is reduced with supporting.
The maximum displacement is 37.97 cm without
supporting, while the displacement reaches only
28.29 cm with supporting. When comparing thesetwo kinds of situations, the vertical displacement 2.5
meters away from the coal seam is shown in Figure
11.

Figure 10: The vertical displacement nephogram along thecoal seam 2.5 meters away from coal seam.
Figure 8: The horizontal displacement of the coal wall
ahead supporting.

From Figure 9, it can be seen that the low stress
distribution is similar to the law of displacement in
the working face 2.5 meters away from the coal wallwithout supporting. The law is that the roof of theworking face is mainly subject to tensile stress, whichis arched. In the lower of the working face, the tensilestress is 2.396 Mpa, which is the largest. On bothsides of the working face the stress gradually
decreases and eventually becomes compressive
stress. Due to the weight of rock, the stress of the

Figure 11: Vertical displacement curve of the support beamalong coal seam 2.5 meters away coal wall.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

From Figure 11, it can be concluded that thesubsidence of the roof noticeably decreased, but thevertical displacement of the top coal is still arched.
The maximum displacement is 37.97 cm without
supporting in the lower working face, but it becomes
3.2 cm with supporting. At both ends of the working
face, the minimum displacement is 3.2 cm. This
explains how support can effectively reduce thesubsidence of top coal.

Figure 13: The stress distribution of the support region
along the seam 2.5 meters away from coal seam.

As can be seen from Figure 13, the pressure of
the support beam is 0.72 MPa in the lower working
face. However, the pressure gradually decreases inboth ends of the working face, and the smallest
vertical stress is 0.28 MPa in the bottom layer. The
minimum pressure is 0.21 MPa in the upper layer.
Figure 12: Displacement of coal wall near the working facewith supporting.

Just as Figure 12 shows, the horizontal
displacement of the coal wall reaches the largest
value of 15 cm in the middle of the working face, andthe minimum displacement is 4 cm on both sides of
the working face with supporting. The maximum
displacement of the coal wall is 26 cm without
supporting. The supports can effectively reduce thedisplacement of the coal wall, but effective protective
measures for mining should still be taken.
3.4 Analysis of the stress of the supporting bracket
In the simulation, the three-dimensional unit isused to simulate the supporting bracket, and the unit
size is consistent with the support size. The length of
the unit is 5.0 m, width is 1.5 m, and height is 4.0 m.
The elastic modulus of the model is 1/15 of the coallayer, which is 581 MPa. The Poisson’s ratio is 0.01.
According to formulas (3) and (4), the bulk modulus
and shear modulus of the unit can be calculated. The
bulk modulus (K) is 197.73 MPa, and the shear
modulus (G) is 287.79. The capacity (d) is 7500
kg/m3. The support force is shown in Figure 13.
K=E
3(1 − 2 µ )EG=2(1 + µ )（3）
（4）

3.5 Determination the supporting resistanceAccording to the results of the simulation, theintensity of the supporting bracket from top coal is0.72 MPa, and the supporting resistance wascalculated according to the following formula (Wu, J.
Y. et al., 2010a; Wu, Y. P. et al., 2007b; Zhao, Y. F.
et al., 2007c):
P = n ⋅ q ⋅ cos α ⋅ a ⋅ b（5）

Where: n——safety factor, take 1.4.
q——supporting intensity, take 0.72MPa.
α——angle of coal seam inclination, take 45°.
a——maximum control distance, take 5m.
b——centre distance of supporting, take 1.5m.
The supporting resistance is 5346 KN, so theworking resistance of the support should be greaterthan 5346 KN in practice.

4.

CONCLUSIONS

Through the numerical simulation by FLAC3D,
the change of the surrounding rock and the bracket
forces with and without support was analysed. The
following conclusions can be made:(1) For deep inclined seams, the roof subsidence
could be effectively reduced with stents supporting.
The maximum displacement of the roof is 37.97 cm
without supporting, while the amount of
displacement reduced to 28.29 cm with supporting.
(2) The deformation of coal walls could also be
effectively reduced through the use of stents
supporting. The largest deformation of the coal wallis 26 cm without supporting. The largest horizontal
displacement of the coal wall reaches 15 cm in the
middle of the working face, and the minimum670

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016displacement of the two ends is 4 cm withsupporting.
(3) By numerical simulation, it is concluded thatthe supporting intensity should be 0.72 MPa. The
reasonable supporting resistance desired by A6 coallayer is 3818 KN without considering the safety
factor, and if the safety factor is taken to be 1.3, thefinal support resistance is 5346 KN.

and support system around large mining height fullymechanized face in steeply inclined seam. Journal ofmining and safety engineering, Volume 32, No. 1, pp.
14-19.
Zhao, Y. F., Zhang, X. Y., and Tu, M. (2007).
Roof caving characteristic and strata behavior in
exploiting steep coal seams. Journal of Mining &Safety Engineering. Volume 24, No. 2, pp. 231-234.

5. ACKNOWLEDGEMENT
It is with great pleasure that we acknowledge thegenerous financial support of National Natural
Science Foundation of China (project number:
51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).

6. REFERENCES
Li, Z. (2013). Analysis of surrounding rocks
movement on long wall large height mining method
along the strike in steeply dipping seam. Xi`an
University of Science and Technology, 33p.
Ma, J. K., Liu, J., and Yue, G. W. (2013).
Research on mechanical behavior of surroundingrock in steeply dipping seam mining. Mining safety&environmental protection, Volume 40, No. 4, pp.
27-30.
Qu, Q. Y. (2014). Study on mine pressure law ofmining coal face with large angle and height in
Huashan coal mine. China Coal Research Institute,
19p.
Wen, M. M. (2014). Study on strata moving laws
and adaptability of Supports in fully mechanized coalface of high inclined coal seam. China University ofmining &technology (Beijing), 11p.
Wang, H. W. (2010). Analysis of overburden
structure feature in steeply dipping seam mining.
Xi`an University of Science and Technology, 14p.
Wu, J. B. (2010). Numerical simulation on strata
behavior regulation in steeply dipping seam mining.
Coal Engineering. No. 5, pp. 80-82.
Wu, J. Y., Huang, W. P., and Ma, P. P. (2010).
Study on the rule of stope roof movement and strata
behavior in large inclined coal seam. Safety in Coal
Mines. Volume 6, No. 22, pp. 6-9.
Wu, Y. P., Xie, P. S., and Yang, Y. G. (2007).
Numerical simulation and complexity analysis ofstrata movement in exploiting steep coal seams
group. Journal of Mining & Safety Engineering.
Volume 24, No. 4, pp. 391-395.
Xie, P. S. (2011). Response of overburden
structure and its stability around the long wall mining
face area in steeply dipping seam. Xi`an Universityof Science and Technology, 16p.
Xie, P. S., Wu, Y. P., and Wang, H. W. (2015).
Interaction characteristics between strata movement671

Paper No. 104

ISMS 2016

Theoretical analysis of support stability in large dip angle coal seam minedwith fully-mechanized top coal caving
Zhang Yinghua, Ji Yucheng, Huang Zhian*, Gao Yukun, Ji Yuchen
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing, China, 100083

ABSTRACTSupport stability is one of the problems in mining at large dip angle coal seams with fully-mechanized top coal caving.
Support stability such as anti-dumping, anti-slip, and anti-rotation at support tail assembly were analyzed on the basisof the mechanic model of large dip angle coal seam along face dip and strike. The relations between each factor andstability were researched, which shows that firstly, the support stability was negatively correlated with dip angle along
the face dip, secondly, higher top caving means lower anti-rotation at support tail assembly, and thirdly, with initialsupport force and working resistance of support enhanced, the support anti-slip, and anti-rotation at tail assembly canrise significantly. Along the strike, support strike critical tilting angle is proportional to dip angle, mining height,
support weight, support width, and support force. Similarly, support strike critical slip angle is positively correlatedwith support force, friction coefficient of the roof, and metal support. According to the results of the mechanicalanalysis, support stability in large dip angle can rise efficiently and support slipping, dumping, and rotation can be
avoided by selecting proper technological methods such as enhancing initial support force appropriately and choosing
fit-designed support.
KEYWORDS: large dig angle; hydraulic support; stability
anti-dumping, anti-slip and tail anti-rotation along the
1. INTRODUCTION
face dip and strike.
Fully-mechanized caving is the current development
direction of mining, especially large dip angle mining.
2. STABILITY ANALYSIS OF HYDRAULIC
Hydraulic support is the key equipment in
SUPPORT AT LARGE DIG ANGLE ALONG
fully-mechanized caving (Zhizeng et al, 2010). The
FACE DIP
efficiency and safety will rise if support stability can beensured. Under the influence of dip angle, the working
2.1 Anti-dumping stability analysis of support alongload of the working face supporting system will
face dip
decrease while external load resulting in support system
The complexity of the stress of the support at the
instability will increase. Also, the probability of support
working surface is caused by the complex ore pressureslipping at the working face and extrusion between
in large dip angle caving. The stability of hydraulicsupports will be raised. The stability of hydraulicsupport can be affected by the dig angle, degree ofsupport is one of the problems in mining in large dip
crushing, support moving technology, mining andangle coal seams with fully-mechanized top coal cavingcaving process, and hydraulic support structure and(Zhiyan, 2007). Before this paper, the fracture mode of
properties (Yuan et al., 2008; Changxi, 2014).
large inclined seam roof (Changyou et al., 2014), theTo analyze the stability of hydraulic support, a
support stability (Fengfeng et al., 2014), and themechanical model was built in which the hydraulicworking resistance of support (Buzilo et al., 2010) were
support was assumed to be under uniform load. The
researched, mainly choosing supports and wall rock as
hydraulic support mechanical model of anti-dumping
the study objects at large dip coal seam. These studies
along the face dip is shown in Figure 1.
and mainly focused on support stability along the facedip. The support stability in strike needs to beresearched further.
In this paper, the hydraulic support is selected as thestudy object and its stability is analyzed via judging the*Corresponding author-email: huang_za@qq.com

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

should be on the point O, and each overturning moment
and anti-overturning moment caused by every
component force of the support to point O should meet
the torque limit equilibrium.
Hence, we can write:

P

p

Ps

Q

q

𝐵

h

a

PSh+Ph·sinα=𝑃𝑋 h+p· cosα+Wb

Px
W

Dynamic SupportO2

𝐵

b= ·cosα-c·sinα

c

(2)

2

b

R

α

B

Figure 1: The hydraulic support mechanic model ofanti-dumping along face dip.

When the large dip coal seam is mined, the actual
movement of the roof is a curve that is close to thedirection of gravity, and the force of the roof is also
close to the direction of gravity, just as in Figure 1.
Considering the simplification of the mechanical model,
it is simplified to the gravity direction in this paper.
During the mining period, the hydraulic support isinclined to the pressure P, which is also influenced by
the support gravity W, the extrusion pressure Ps, Px,
initial support force q, and the supporting force R. The
simplified model is shown in Figure 2. When the
support is stable, the mentioned force should be in themechanical equilibrium.

h: height of the support
B: width of the support baseb: horizontal distance between gravity direction andedge of support basec: height of centre of gravity
Due to formulation (2), horizontal distance
between gravity direction and edge of support base b has
negative correlation with the dig angle α. When thehorizontal distance between gravity direction and edgeof support base b and anti-dumping torque increases, theheight of centre of gravity c , height of the support h anddumping torque of support decreases, and the stabilityof the support can be enhanced.
2.2 Anti-slip stability analysis of support along face
dip

P

P

Ps

Q
Ps

Q

(1)

h

a
Px
h

a

W

Px

c

Dynamic Support
WO

c

Dynamic Support

R
O

α

b
R

α

b

B

Figure 2: The simplified hydraulic support mechanical modelof anti-dumping along face dip.

In the process of mining, the component force oneach support changes. When the point of resultant force
on the support is beyond the contact surface between the
support base and floor, the support will dump. When the
support along the face dip is at critical equilibrium state,
it means that reaction force, of the floor to the support,

B

Figure 3: The simplified hydraulic support mechanic model ofanti-slip along face dip.

As in Figure 3, the anti-sliding stability of support
along the face dip is mainly by the influence of its own
gravity W and roof pressure P, whose component force
play a main role in causing the support slipping down.
To ensure the anti-slip stability of support along the facedip, anti-slip fore Fkh must be greater than slip force Fh.
Fkh≥FhWhich means673

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016[(W+P)cosα+Q]·f ≥ (W+P)sinα+(PS-PX) (3)
Fkh: anti-slip force
f: coefficient of kinetic friction
According to the formulation, the existence of theinitial support force increases the anti-slide force, anddoes not increase the downward force. So, the anti-slide
capacity of the support can be significantly improved if
the initial support force is improved.
Assuming that the support is only influenced by its
own gravity, and the initial support force and the roofpressure are zero. Due to the equation mentioned, we
can know:
Wf cosα≤W sinα and tanα≥f(4)
The related research shows that the friction
coefficient of metal and coal seam is 0.35-0.40(ZHIYAN, 2007). From the formulation, we can draw
the conclusion that the support will slip if the dig angle
is more than 15° (tanα is greater than the friction
coefficient of metal and coal seam). As a result, theanti-slip measures should be taken if the dig angle isbeyond 15°.
2.3 Anti-rotation stability analysis of support tailalong face dip
When using low caving coal process, thepossibility of skew angle at the support tail should beconsidered. In the processing, the component force of
caving coal will affect the support tail beam. If theanti-torque is less than the torque, the tail beam will
rotate and result in support skewness. The anti-rotation
mechanic model of support tail beam is shown in Figure
4.
p
D
Fn
G

R

α

(a)
M2
P

F
M1

W

The torque and anti-torque, which are generated by
the twisting force Fn and the anti-twisting force, should
be kept in balance. This ensures that the dynamic
support won’t rotate.
The gravity of the coal mass G, which is acting on
the cover of the support beam, the torsional force of theshield beam Fn, which is the component in the coal seam
dip direction of the sliding friction force that the coalmass acts on the cover beam, and the torque of the shield
beam M1 are calculated as follows:
G=lBHρ
(5)
l=Dsinθ(6)(7)
Fn=Gf2cosα sinθ cosβ(8)
M1=Fn(L+l/2)
f1: coefficient of kinetic friction
α+β: stopping angle
f2: the friction coefficient of coal mass and shield beam
L: the distance from the base of the outer support to thegeometric centerl: the projection length of the cover of the support beam
H: coal rock mass height
D: tail beam length
Q: density of bulk coal rock mass
Furthermore, we can know:
M1= Gf2(L+l/2)cosα sinθ cosβ(9)When the friction force Fkn, which is generated by
the pressure between the support, the floor and the roof
interacts with Fn, the torsional force acting on the shieldof the support beam, support to rotate point is influenced
by the roof pressure and pillar working resistance, andthe distance L (from geometric center of the support tothe outer edge of the base) is related with the roofpressure distribution and pillar working resistance. The
related research shows that the working resistance of the
support is generally greater than that of the rear column(Zhongming et al, 2004). As is shown in Figure 4, due tothe measurement of working resistance of the support
column, and assuming the roof pressure in the roof has alinear uniform distribution, the model can be simplified
to the mechanical equilibrium model of the load on asimply supported beam, and the position of theequivalent action can be determined.
Anti-rotation moment M2 of the friction force
between the base and the top plate is used to obtain the
integral of the uniform load friction torque. We can
know:

β

H

M2=(

α

F

(b)

Figure 4: The anti-rotation mechanic model of support tail
beam.

(c)

Lg: length of beam

2𝑃+𝑊𝑠𝑖𝑛𝛼
4

)Lgf3

(10)

674

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

f3: coefficient of kinetic friction between the support andthe top floor
Conditions to ensure no skew is M1≤M2, torsional
stability coefficient is K3.
K3= M2/M1=(2𝑃+𝑊𝑠𝑖𝑛𝛼)𝐿𝑔 𝑓3

8𝐺𝑓2 (2𝐿+𝑙)𝑐𝑜𝑠𝛼 𝑠𝑖𝑛𝜃 𝑐𝑜𝑠𝛽

(11)

From the analysis of the K3, when caving height isincreased, the tail bracket torsional stability coefficientis a nonlinear decreasing trend. When the support
working resistance increases, K3 shows a linear
increasing tendency. Hence, the working resistance ofthe support is significantly affected by increasing theanti-rotation stability of the support and the torsion of
the support.

3. STABILITY ANALYSIS OF HYDRAULICSUPPORT AT LARGE DIG ANGLE ALONGSTRIKE
3.1 Anti-dumping stability analysis of support along
strikeThe stability of hydraulic support is a common
problem in the mechanical mining of large dip angle
coal seam in the inclined direction of the working face.
In fact, the hydraulic support is influenced by the angleof the coal seam, and the stability of the hydraulicsupport is also influenced by the trend of the direction of
the slope and the angle of the back (Dongsheng et al.,2013; Panshi et al., 2012).
When the first weighting, periodic weighting, androof fall occurs in the mining process, the roof becomes
more and more fragmentary due to stress increasing, andthe roof will trend to be downward. At the same time,
under the influence of the inclined angle, the lateralstress of the support will also be increased, which
greatly reduces the stability of the large dip angle coalseam. The mechanic model of support along the strike inthe processing of downhill-mining was built to analyze
the support stability of anti-slip and anti-dumping.

Figure 5: The support mechanic model of anti-dumping along
strike when downhill-mining.

Figure 5 shows the support mechanic model ofanti-dumping along strike when downhill-mining.
According to the mechanical equilibrium conditions, we
can know that:(12)
f21-F1+F=W3(13)
R21=W2+R22(14)
f21=μR11(15)
R22(L-M)+(F-F1)h+2W2L/3-W3h/2=0
Solving that equation, the critical tilting angle ofthe support along strike β:β=arcos3ℎ�𝑁−36𝑀2 −24𝐿𝑀
𝑁𝑐𝑜𝑠𝛼

(16)

In the equation：
M=LR22+Fh-F1h-R2m; N=W(16L2+9h2)
W3: The component force of the support gravity W,
which is parallel to the surface along the seam to thebottom of the support direction
F1: Lateral force of roof
F: Support force of coal wall to support
μ: Friction coefficient between the support and the rockd: length of the beam
m: The distance from the base of the outer support to thegeometric center
L: length of support basex: the distance from the center of gravity to the base of
the support，L/3。
Due to the equation, in the process of mining, if thebroken roof trends to slide, the roof lateral force F1 along
strike has a negative correlation with the critical slipping
angle. The critical angle is proportional to the dig angle,
mining height, support weight, width, and support force.
3.2 Anti-slip stability analysis of support along strikem
R22 F1
x
F

d

W3

h

W2

R22 m

h/2

F1
F

d

x

h

W3

f21
R21

L

Figure 6: The support mechanic model of anti-slip along strikewhen downhill-mining.

W2
h/2
β

β

f21 R21

L

According to Figure 6, we can know the equations:(17)
f21-F1+F=W3

675

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

So, the critical slip angle α:α=arccos�

R21=W2+W22
f21=μR21

𝜇𝐹1 −𝜇𝐹−𝜇 2 𝑅22 +�𝑊 2 (𝜇 2 +1)−(𝐹1 −𝐹−𝜇𝑅22 ）（𝜇 2 +1）𝑊𝑐𝑜𝑠𝛽

(18)
(19)
2

�

(20)
As a conclusion, raising the support force, or thefriction coefficient between the support and the roof or
floor, could lead to the increasing of critical slip angle.
The support stability of anti-slip could be enhanced.
Also, decreasing the support weight or the angle of thecoal seam strike could have the same results.
4.

CONCLUSIONS(1) The mechanical model of anti-dumping,anti-slip and anti-rotation at the support tail along the
strike at the large dig angle coal seam is established.
When the dig angle of coal and caving height rises, thestability and anti-rotation at the support tail decreases.
Also, it is significant to enhance the stability of anti-slip
and anti-rotation by raising the initial support force andworking resistance.
(2) The anti-dumping and anti-slip mechanicmodel was built and the equations of dumping angle andslip angle of support along the strike were derived.

5.

ACKNOWLEGEMENT

It is with great pleasure that we acknowledge thegenerous financial support of National Natural Science
Foundation of China (project number: 51474017) andNatural Science Foundation of Xinjiang Uygur
Autonomous Region of China (2014211B013).

6.

LIU, C.Y., YANG, J.X., Yu, B., and Yang, P.J.
(2014). Destabilization regularity of hard thick roofgroup under the multi-gob . Journal of China Coal
Society, Volume. 39, No, 3, pp. 395-403.
Liu, Z.M., Chen, Z.H., Xie J.W. et al. (2004)
Stability analysis and control measures of powered
supports in greater inclined full-mechanized coal seam.
Journal of China Coal Society, Volume 29, No. 3, pp.
264-268．
Wu, F.F., Liu, C.Y., Li, J.W.(2014) Combination
hydraulic support stability of working face in large
inclined and “three-soft” thick seam. Journal of Mining& Safety Engineering, Volume 31, No.5 pp. 721-725,
732.
Xie, P.S., Wu, Y.P., Wang, H.W., Gao, X.C., Ren,
S.G., and Zeng, Y.F. (2012). Stability analysis of incline
masonry structure and support around longwall mining
face area insteeply dipping seam．Journal of China Coal
Society, Volume 37, No. 8, pp. 1275-1280.
Yuan, Y., Tu, S.H., Dou, F.J., et al. (2008). Support
instability mechanism of fully mechanized top coalcaving face with steep coal seams and its control.
Journal of Mining & Safety Engineering, Volume 25,
No. 4, pp.430-434.
Zhang, D.S., Wu, X., Zhang, W. and Fan, G.W.
(2013). Stability analysis on support in large inclined
coalface during special mining period. Journal of
Mining & Safety Engineering. Volume 30, No. 3, pp.
331-336.
Zhang, Z.Y. (2011). Dynamic analysis on stabilityof hydraulic powered support in deep inclined fullymechanized wall and prevention slips measures. Journalof China Coal Society, Volume 30, No.7, pp. 705-709.

REFERENCE

Buzilo V., Serdyuk, V. and Yavorsky. (2010). A
Research of influence of support resistance of the stopein the immediate roof condition In: New Techniques andTechnologies in Mining - Proceedings of the School ofUnderground Mining. pp. 127-130
Huang, Z.Z., Ren, Y.F. and Zhang H.J. (2010),
Study on key technology of fully mechanized top coalcaving in extra-thick soft coal seam with great dip angle.
Journal of China Coal Society, Volume 35 No. 11, pp.
1878-1882.
Liu, C.Q. (2014), The Movement Law of the RoofRock and the Stability of the Support in the Big Dip
Thick Coal Seam Large Mining Height Working Face in
Quandian Coal Mine. China University of Mining andTechnology, Xuzhou, 67p.

676

ISMS 2016

Paper No. 106

Theoretical research on roof damage of the fully mechanized top-caving
mining coal seam with deep dip angle
ZHANG Ying-hua, LUO Qiang, HUANG Zhi-an*, GAO Yu-kun
State Key Laboratory of High-Efficient Mining and Safety of Metal Mines (University of Science and Technology Beijing),
Ministry of Education, Beijing 100083, China

ABSTRACT
In order to study the roof pressure of steep coal seams, it is necessary to establish a related mechanical model toanalyze the roof breaking law. Based on a working face of SDIC Nileke Mine, a mechanical model of roof facture ofdeep dip angle coal seam for roof pressure and periodic roof pressure was built in the study. The model was
analyzed in dip direction and along the advancing direction of the working face. Based on the stress analysis of themodel, the formula for the distance of roof breakage was given. The stress, deformation, and failure discipline ofcomplicated full mechanized top-caving coal seam with deep dip angle were studied, which also enriched the theoryof roof damage. The research findings provide a theoretical basis for coal mine safety support, and it can be used asa reference for other similar research on the roof failure discipline of full mechanized top-caving coal seams withsteep dip angle.
Keywords: steep coal seam; roof failure; model research

1. INTRODUCTION
The mechanical model was established based on
the SDIC Nileke Mine N11 first mining face in the
study, and the working face diagram is shown in
Figure 1. Assume the roof material is homogeneous,continuous, and isotropic. According to production
practice and related research (ZHANG, L. L. et al.,2012), the force of the working face’s hydraulicsupport is much less than the weight of overburden,
and only a part of the stratum will have a significant
impact on the working face pressure which
contributes to the roof deformation and fracture. It
will form a pressure equalization arch when the faceroof is broken, and the height of the arch is usually 4
to 8 times the mining height (GUO, S. et al., 2013).
The roof load of mechanical model was 8 times themining height of rock weight above the hydraulicsupport (LIU, J. Y. et al., 2010).

2. MECHANICAL MODEL OF THE FIRSTROOF LOADING
Roof before first pressure can be treated as afour-side-fixed inclined plate (WANG, J. A. et al.,2010). The simplified model is shown in Figure 2. Inorder to calculate the stress distribution under theuniform load of the plate, the calculation was divided
into two steps, which were analyzed in dip direction
and along the advancing direction of the working
face.

Figure 2: Model of four-side-fixed inclined plate.

Figure 1: The working face schematic diagram.

*Corresponding author – email: huang_za@qq.com

2.1 Mechanical model along the direction of faceadvance
According to structural mechanics, the directionof face advance model was simplified and can betreated as girder with uniform load whose ends areboth fixed (ZHANG, W. et al., 2006), as shown in
Figure 3(a). Its bending moment is shown in Figure2(b).

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 20163

𝑙1 = �

(a)4𝑏ℎ2 𝜎𝑡𝛾𝐻(5)According to the SDIC Nileke Mine field data,
γ=25 kN/m3, H=32 m, b=1 m, h=8 m, σt=8 MPa, thenl1=13.7 m.
According to the results, when the face advanced
to about 13.7 m, around 6.8 m the top plate in thegoaf will fracture.
2.2 Mechanical model along the dip direction of face(b)
Figure 3: Bending moment distribution of fixed girder
under uniform load in the advancing direction.

Fixed end bending moment (Timoshenko andGoodier,1951):
𝑞𝑙 2(1)
𝑀1 = −𝑀2 = −12
End reaction of the girder ends: R1 = R 2 = ql/2
Then:
𝑞𝑥 2
𝑀(𝑥) = −+ 𝑅1 𝑥 + 𝑀12(2)𝑞
𝑙 2 𝑞𝑙 2= − �𝑥 − � +2224
In the above formula: q is uniformly distributedload, l is the beam length.
When working face along the advancing
direction’s mining distance is l, the uniformly
distributed load of girder is(3)
𝑞 = 𝛾𝐻𝑙q is the uniformly distributed load of the girder
along the dip direction of the face, γ is the density ofoverburden, H is the overburden thickness, l is thelength of the girder.
When the stress of the rock σ reaches the tensile
strength of the rock, roof fracture will occur, then:
𝑞𝑙 2
𝑀𝑚𝑎𝑥
𝑀𝑚𝑎𝑥
(4)
𝜎=−
=−
= − 242 = 𝜎𝑡
𝑏ℎ2
𝑏ℎ
𝜔
6
6
In the above formula: ω is the beam bending
section coefficient, b is the width of the beam, and his the ply. When combining equation (3), the lengthof roof breakage formula is:

Figure 4: Force distribution of the girder along the dip
direction of face.

The uniformly distributed load was decomposed
into two mutually perpendicular loads one of whichis perpendicular to the axis of the girder and the otheralong the axis. First, calculate the tensile stressgenerated by the load which is perpendicular to theaxis of the girder; then calculate the tensile stressgenerated by the axial load; the total tensile stress isthe sum of the two.
(1) Perpendicular to the axis of the girder

Figure 5: Force diagram of a section perpendicular to theaxis of the girder.

Based on the analysis, the bending moment
perpendicular to the axis of the girder is (WANG, J.
A. et al., 2010):

678

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016𝑞𝑙2
(6)
𝑀(𝑥) = − 𝑐𝑜𝑠 𝛼 (𝑥 2 − 𝑙𝑥 + )2
6
M is the girder’s axial moment, q is the uniform
load, α is the angle of the girder, l is the length of thegirder.
(2) Along the girder axis
Stress at both ends along the girder axis:𝑞𝑙(7)
𝑅1′ = 𝑅2′ = sin 𝛼2advancing of the working face, while the roof, which
is about 20.5 m to 87 m apart from the bottom, will
break in the dip direction.

3. MECHANICAL MODEL OF THE
PERIODIC ROOF PRESSURE
Roof periodic pressure can be treated as a threeside-fixed inclined plate. A simplified model isshown in Figure 7. After first roof pressure, thecalculation method of inclined plate’s stress
distribution under uniform load is the same as firstroof pressure’s when along the working faceadvancing distance to L1.

Figure 6: the axial stress of the girder along the dip
direction.

𝑞(8)
sin 𝛼 (𝑙 − 2𝑥)2
N is the axial tension of the girder, q is theuniform load, α is the angle of the girder, l is thelength of the girder.
The stress distribution of the girder along the dip
direction:
𝑀(𝑥) 𝑁(𝑥)(9)σ(𝑥) = −+𝜔𝐴
2And ω = 𝑏ℎ /6, 𝐴 = 𝑏ℎ.
Then:
3𝑞 cos 𝛼 2𝑙2
𝜎(𝑥) =
(𝑥
−
𝑙𝑥
+
)
𝑏ℎ2
6
(10)
𝑞 sin 𝛼+(𝑙 − 2𝑥)2𝑏ℎ
σ is the stress of the girder, q is the uniform load,
α for the inclination of the girder, l is the length, b is
the width, h is the thickness of the girder.
Assuming:
3𝑞 cos 𝛼 2𝑙2
𝜎(𝑥) =
(𝑥
−
𝑙𝑥
+
)
𝑏ℎ2
6
(11)
𝑞 sin 𝛼+(𝑙 − 2𝑥) ≤ 𝜎𝑡2𝑏ℎ
According to the SDIC Nileke Mine field data,
γ=25 kN/m3, H=32 m, b=1 m, h=8 m, L=15 m, σt=8MPa, α=45°, then x1=20.5 m, x2=87 m.
According to the results of the analysis above,the middle of the roof in the advancing direction will
break when the exposure length is 13.7 m along the𝑁(𝑥) = 𝑅1′ − 𝑞𝑥 sin 𝛼 =Figure 7: Model of three-side-fixed inclined plate.

3.1 Mechanical model along the face advancedirection
A free-body diagram of the hanging stick along
the face advance direction when the roof exposure
length is l is shown in Figure 8.

Figure 8: Free-body diagram of the cantilever along theface advance direction.

The formula of uniform load (q) is as shown inequation (3).
The bending moment of the cantilever:
𝑞𝑥 2
(12)
𝑀(𝑥) =
2
Then:

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

𝑞𝑙 2
𝑀𝑚𝑎𝑥
𝑀𝑚𝑎𝑥
𝜎𝑚𝑖𝑛 = −=−= − 2 2 = 𝜎𝑡
𝑏ℎ2
𝑏ℎ
𝜔
6
6

(13)

In the above formula: σ is the stress of the beam,σt is the tensile strength of rock, ω is the beam
bending section coefficient, b is the width of thebeam, h is the ply, and l is the length of thecantilever. Combined with equation (3), the distanceof roof breakage formula is:3

𝑙=�𝑏ℎ2 𝜎𝑡3𝛾𝐻(14)According to the SDIC Nileke Mine field data,
γ=25 kN/m3, H=32 m, b=1 m, h=8 m, σt=8 MPa, andl=5.97 m.
According to the results, around 2.99 m of the
top plate in the goaf will fracture when the faceadvances to about 5.97 m after first roof pressure.
3.2 Mechanical model along the dip direction of face
The mechanical model of the girder along the dip
direction of the face is the same as Figure 4, and theway of analysis is also the same as first roof pressure
in section 2.2.
We can get an inequality using equation (11).
According to the SDIC Nileke Mine field data,
γ=25 kN/m3, H=32 m, b=1 m, h=8 m, L=15 m, σt=8MPa, α=45°, then x1=21.9 m, x2=88.9 m.
According to the results of the analysis above,the middle of the roof in the advancing direction will
break when the exposure length is 5.97 m along theadvancing of the working face, while the roof, which
is about 21.9 m to 88.9 m apart from the bottom, will
break in the dip direction.

51474017) and Natural Science Foundation of
Xinjiang Uygur Autonomous Region of China(2014211B013).
6.

REFERENCES

GUO, S., KONG, X. F, KANG, T. H. and
WANG, C. H. (2013). Support Load Analysis of
Fully-mechanized Mining Face in Close Distance
Coal Seam Under Goaf. Safety in Coal Mines,
Volume 44, No. 5, pp. 214-217
LIU, J. Y., LIAN, X. G. and HUANG, X. D.
(2010). Experimental study on physical-mechanicalproperties of rock in Wangjialing Mine. Mineral
Engineeering Reseach, Volume 25, No. 2, pp. 17-19
Timoshenko S, Goodier J N. (1951). The Theory
of Elasticity.
WANG, J. A., LI, D. Z. and MA, H. T. (2010).
Study of rheological mechanical model of pillar-roof
system in mined-out area. Chinese Journal of RockMechanics and Engineering, Volume 29, No. 3, pp.
577-582
ZHANG, L. L., WU, Q. L. and LI, A. M. (2012).
Research on the overlying strata movement rule ofhard and super high seam with the propelling
progress of working face. Coal, Volume 21, No. 2,
pp. 6–8
ZHANG, W., SU, M. L., YU, H. L., JIAO, Z.,
ZHANG, J. H. and YANG, H. J. (2006). The Elastic
Mechanics Solution of Statically Indeterminate
Beams Fixed at Two Sides under the Action ofConcentrated Load. Journal of North China Instituteof Water Conservancy and Hydroelectric Power,
Volume 27, No. 4, pp. 40-42

4. CONCLUSIONS
The mechanical model of roof damage when firstroof pressure and periodic roof pressure was built inthis study based on the beam bending theory ofelastic mechanics. The model was analysed in the dip
direction and along the advancing direction of theworking face. Based on the stress analysis of themodel, the formula for the distance of roof breakage
was given. Combined with field data, the range of theworking face roof fracture was calculated.
The results of the study provide a reasonablehydraulic support scheme for the mine, and provide atheoretical basis for mine safety support.

5. ACKNOWLEDGEMENT
It is with great pleasure that we acknowledge thegenerous financial support of National Natural
Science Foundation of China (project number:

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Paper No. 231

ISMS 2016

Characteristics of acoustic wave velocity variation in the process ofdeformation and failure of loading coal
LI Xiangchun a,b,*, NIE Baisheng a,b, YANG Chunli c, CUI Zhe a,b, MAO Yanjun a,baSchool of Resource and Safety Engineering, China University of Mining & Technology(Beijing), Beijing, China, 100083
State Key Lab of Coal Resources and Safe Mining, Beijing, China, 100083
cSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, China, 100083b

ABSTRACTFor studying characteristics of acoustic wave velocity change during the deformation and fracture of loaded coal,using self-made acoustic parameter test system the characteristics of acoustic wave velocity change in deformationand fracture of loaded coal, the mechanism of stress influencing acoustic wave velocity change, the relation between
stress and longitudinal wave velocity and the impossibility of longitudinal wave velocity forecasting coal structure isstudied. The research results show that during the deformation and fracture of loaded coal the longitudinal wave andshear wave velocity increases firstly. When the coal is damaged the longitudinal wave velocity decreases and theshear wave disappears. The stress-strain change of coal is similar to the stress-wave velocity change highly. Basedon coal structure the formula of stress and longitudinal wave velocity is established and the longitudinal wave
velocity can be predicted well under different stress by the formula of stress and longitudinal wave velocity. The
mechanism of stress influencing acoustic wave velocity change is coal structure change mainly.
KEYWORDS: coal body; loading; stress; deformation and failure; wave velocity

1. INTRODUCTION
Coal and rock dynamic disaster is a sudden
dynamic appearance caused by the dynamic
evolutions of coal body deformation and rupture. Asa geophysical method, acoustic detection technology(Liu and Cheng., 1999) has been used in theprediction of coal and rock dynamic disasters. Due tothe complexity of coal and rock dynamic disasters, if
we want to truly achieve accurate prediction andforecast, the further research on the transmission
mechanism of acoustic wave in the coal body, thespatial distribution of the acoustic wave and thespace-time distribution of the acoustic wave areneeded to be done. Therefore, it is necessary toresearch on the characteristics of acoustic wave
propagation in the whole process of deformation andfailure.
At home and abroad, a lot of work has been done
to study the relationship between stress and wave
velocity. In the condition of hydrostatic pressure, thevelocity law of metamorphic variation rocks wasstudied by Christensen (1965). The results show thatthe rock wave velocity changes with pressure andpore arrangement in rock mass are related to thefracture morphology. Freund (1992) try to researchon the variation of the longitudinal and shear velocityof the arenaceous rocks under the multi-parametercondition of the presence of clay content, porosityand confining pressure. Under the pressure of loading
conditions, the existence state and closure state of*Corresponding author – email : chinalixc123@163.com

rock micro fissures and cracks were studied by Kinget al. (1995). It is concluded that there is a correlation
between them and the velocity in the loading process
and the shear velocity is related to the micro fracture
and the crack closure which is perpendicular to thedirection of propagation. Based on the analysis of thecompaction effect of the 45 samples by Shi et al.
(2004), the acoustic velocity of rock is related to therock porosity, the pore fluid, the structure of theskeleton and the effective pressure on the rock. Basedon case of the colliery No.3 of Huainan coalfield in
Anhui Province, Peng et al. (2005) researched on therelations of acoustic velocity and mechanicalcharacteristics of the lithofacies transition rock massby the physical modeling study and numericalsimulation technique. The results show that acoustic
velocity increases with the stress increasing. In low
stress conditions, the acoustic velocity increases
obviously with the stress increasing and becomessteady with the stress increasing. The relationshipbetween coal rock physics parameters and acoustic
wave velocity was studied by (Meng and Zhang,2006; Meng et al., 2008), which shows that thedifference between the acoustic wave velocities ofdifferent lithology is relatively large, the acoustic
wave velocities of rock are the main factors in
addition to the composition and structure, mainly
rock density and stress and groundwater factor. The
granite, gneiss and marble and sandstone loading by
Zheng et al. (2009), explore rock wave velocity with

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

the response characteristics of changes. Experimentresults show that the granite and gneiss during thelinear elastic loading phase, velocity-stress rises
linearly, velocity-stress is quadratic nonlinear change.
The damage characteristics of salt rock under
uniaxial loading are studied by using acoustic wave
technique by Jiang et al. (2009). Along with theincrease of the axial stress, the lateral wave velocity
is smaller, and the wave velocity decreases rapidly
after reaching the ultimate strength. Acoustic test to
study the impact trend coal seam by Gong et al.
(2012). The experiment was conducted under thecondition of uniaxial stress loading path. The results
show that with the increase of tress, the changes oflongitudinal wave velocity of rock samples fasterthan the changes of longitudinal wave velocity ofcoal samples; in the elastic deformation stage of coalsample loading, the impact tendency of the coal rockis greatly increased, with the increase of stress, thedeformation enters into the plastic stage, and the
speed change area is gentle. It shows that there is a
power exponent function relation between the stresschange and the change of the wave velocity.
From these studies, it can be seen that the studies
on the characteristics of acoustic wave change in theprocess of loading and failure of coal are less. Somestudies are only preliminary studies. The change law
and response mechanism of acoustic wave in
different stage of coal deformation and failure need
to be further analyzed. That the characteristics ofacoustic wave variation in the process of coal loading
and failure and analyses mechanism of stressinfluencing on the change of acoustic wave velocity
were studied. The relationship between longitudinal
wave velocity and stress is also discussed, and thepossibility of predicting the structure of pore andfracture in coal body is discussed in order to provide
theoretical basis for prediction of coal and rockdynamic disaster.

2. EXPERIMENT
2.1 Experiment System
The system includes coal sample clamping
system, stress loading system, acoustic excitation
system and wave receiving and acquisition system.
The system structure of the system is shown in Fig.1.
Coal sample holding system can be put into thestandard sample of Φ25mm×50mm standard coalsample, through the interface to connect stressloading system, which is connected to an acoustic
wave excitation system and acoustic wave receiving
system through an end head with sound wave
transducer. Force loading system for manual
hydraulic loading system, which can achieve, twodifferent loading and triaxial loading process,uniaxial loading and triaxial loading, axial pressure
and confining pressure of different loading modes
were achieved: constant pressure loading, step
loading and cyclic loading, wave velocity variation
under different loading modes and loading conditions
were studied. At the two ends of the coal sample has
two detachable ends, the first coal sample is put inthe experiment, one end of the end is fixed, and theother end of the end head can be moved under theaction of hydraulic pressure to achieve the loading ofcoal samples. Acoustic wave excitation system wasdeveloped by the State Key Laboratory of Southwest
Petroleum University. For the sound wave pinger andacoustic probe (sound wave energy converter) its
longitudinal wave frequency is 500 kHz and the shear
wave frequency is 200 kHz. When system isconnected to the digital oscilloscope, sound wave
energy converter emitting end of the shear andlongitudinal waves are in turn connected to the soundwave pinger of shear and longitudinal waves on theinterface connecting lines, the digital oscilloscopeexternal input terminals and EXT connection head ofsound wave pinger are respectively connected with amoderate length of double shielded wire, and the twoconnecting head of the other sound wave energy
converter are respectively connected to two CH1 andCH2 terminal on the digital oscilloscope. The
acoustic wave receiving and acquisition system use
the DSO7012B model of the dual channel
oscilloscope, which can be used to measure the timedifference between the longitudinal wave and theshear wave passing through the coal sample at thesame time.

Axial Confining
Pressure Pressure

Manualpump1

Manualpump2

Experimental Cavity

Oscilloscope Sonic Transmitter

Figure 1: Schematic diagram of acoustic wave parameter
test system in coal and rock

2.2 Coal Sample
The coal sampling of this experiment is comefrom Shanxi Guandi Coal Mine and Malan Mine2#,
which is made to the standard of Φ25mm×50mm,
coal sample section of flatness error is less than
0.02mm, the preparation of coal samples werevacuum drying (12 hours), and placed in dry bottles
stored for a long time. Industrial analysis data of coalsample is shown in Table.1.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Guandi

0.82

13.28

11.03

75.48

2.3 Experimental Programs
In this experiment, the variation of longitudinaland shear velocity of loading coal in uniaxial loading
is studied. During the loading process, the test
direction of wave velocity is the same as the directionof axial load of the axial load when the coal sample
that the axial load of coal is loaded is destroyed.
Limited by the design of the experimental instrument,
the deformation of coal sample can only be measured
in axial deformation.
2.4 Experimental ProceduresFirstly, coal sample is placed in a coal sample
holding system, stress loading system, acoustic
excitation system and the sound receiver acquisition
system were connected, then the experiment starts,
the acoustic velocity of coal samples was measured
in the no pressure condition, and in accordance withthe pre-set pressure of axial compression loading stepby step, sample acoustic velocities of each stage on aloading pressure condition were measured, theexperiment ends until the coal is destroyed.

3. EXPERIMENTAL RESULTS
3.1 Measure Principles
The usual method of measuring acoustic velocity
is that measuring the ratio that sound wave
transmission medium of unit length per unit time.
The calculation formula is as follows.

V=

L
T

(1)

Where L the coal sample length, m; T the
propagation time of acoustic wave in the medium, s;
V the coal and rock mass acoustic wave velocity,m/s.
3.2 Experimental Results
The experiment selected three groups of coalsamples, Guandi mine, Malan mine 2#, the change
trend of the experimental results is similar, therefore,
the typical of a group selected of experimental data isanalyzed. Fig.2 shows that the experimental results ofthe damage process for the Malan mine 2# coal andGuandi coal. The experimental results show that thevelocity of longitudinal wave velocity of coal androck mass increases until the rupture velocity of coal

body decreases, and the shear wave velocity
increases firstly, but when the coal body breaks
down, the shear wave disappears signally. This ismainly due to the coal and rock mass under loading,the deformation can be divided into two stages: (1)the elastic-plastic deformation stage, namely understress, voids and fissures inside coal and rock tends to
be closed; (2) deformation and failure stages, with theexternal load stress increasing, beyond the limits ofcoal and rock mass stress, coal body structure
occurred deformation damage, pore fissure structure
secondary development. The characteristics of theelastic and plastic deformation stage of the specimen
and the change of the wave velocity in the
deformation and failure stage. In the elastic plastic
deformation stage, with the rapid closing of the porecrack, the acoustic wave velocity increases gradually,
and the change of the longitudinal wave velocity ismore obvious than that of the shear wave. In
deformation and failure stages, after the uniaxial
stress loading is beyond the limit of stress, and its
internal structure began to damage, micro cracks andmicro cracks begin develop to the coal rock breaked
and fractured (Fig.3). In the coal and rock massfragmentation fracture moment, its shape variableoccurs suddenly Corresponding sample in loading
process of stress-strain of the force velocity law also
appeared mutation, in specimen loading moment of
failure, acoustic velocity decreased suddenly. The
shear wave velocity attenuation is much larger than
the attenuation of the longitudinal wave velocity, sothat the acoustic wave receiving probe is difficult toreceive its attenuation signal.
In addition, Fig.2 shows samples stress-strain
curves and stress-wave velocity curve have a highdegree of consistency. It is also indicated that the
acoustic wave velocity can be used as an indicator,
which can reflect the stress state and the deformationof the internal structure in coal and rock mass,
especially, the change of longitudinal wave velocity
can be used as a good indicator that evaluates thestress state and the deformation of the internal
structure in coal and rock mass.

2800

longtinal wave

shear wave

250

strain2500
wave velocity（m/s）

Table 1: Industrial analysis of the coal samples
coal mine moisture Air dry base Dry basis Fixed
content（ volatile（% ash（%） carbon（%））%）
Malan 2# 0.48
24.55
5.69
69.29

200

2200
150
1900
100
1600
50

1300
1000

0
0

2

4

6
8
uniaxial pressure（MPa）

10

12

Malan 2# coal683

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

wave velocity（m/s）

longtinal wave

shear wave

strain

3000

300

2500

250

2000

200

1500

150

1000

100

500

50

0

0
0

1

2

3

4

5

6

7

8

9

10

uniaxial pressure（MPa）

Guandi coal
Figure 2: Wave velocity changes with increasing pressure
under uniaxial loading

Malan 2# coal

Guandi coal

Figure 3: Fracture map of coal sample under uniaxial
loading

4. THE RELATIONSHIP BETWEEN AND
LONGITUDINAL WAVE VELOCITY
In a sense, the wave velocity of coal and rockmass mainly depends on the degree of porosity andfracture, namely porosity (Xu et al., 2015). Generally
speaking, with the porosity increasing, the wave
velocity decreases sharply. The experimental results
show that the wave attenuation is very large, so it isdifficult to receive the signal when the coal bodybreaks down. Therefore, it is more significant tostudy the longitudinal wave in the study of coal androck deformation and rupture, it is necessary toanalyze the relationship between the wave velocity
and stress change.
Many scholars have done a lot of work toresearch on the relationship between wave velocity
and stress. These relations include mainly two kindsof fitting formula and theoretical formula. For
example, Wang and Xian (1988) for the rock underelastic stress, it is considered that the relationshipbetween stress and elastic wave velocity can be
expressed in a linear dependence coefficient. Nur(1997) considered that the stress and the wave
velocity are in accordance with the two function
relation. Huang (1991) established the relationshipbetween wave velocity and stress by multiple
regression analysis. Zhao and Wu (1999) based onlinear elastic fracture mechanics and the assumptionthat the shape of the crack in the rock is ellipsoid, therelationship between wave velocity and stress isestablished. Gong et al. (2012) establish a powerfunction relationship between force and velocity byfitting. Chen et al. (2010) believe that there is atransition point in the change of the velocity of rockduring the loading and failure process. Below thetransition point, the relationship between stress andwave velocity is in the form of power function. And
above the transition point, the relationship between
stress and wave velocity is in accordance with thetwo functions. One of the characteristics of theseformulas is that the mathematical relation between
stress and wave velocity is mainly considered, andthe characteristic of wave equation can be known thatthe elastic wave velocity is related to the structure of
the elastic body. They are related to the porosity of
the rock, the degree of fracture development, or the
degree of closure of the hole under a stress state (Din,
1997). Therefore, it is more scientific and reasonable
to establish the relationship between the structurechange of the hole and the change of the wave
velocity through the stress action. Previous studies
have showed that there is a mathematical relationshipbetween the longitudinal wave velocity and theporosity (Luan and Hu, 1985).

φ = beaV p(2)

Where φ the porosity, %; a, b the constant; VP
the longitudinal wave velocity, km/s.
Before and after the destruction of coal, porosity
changed greatly. It is difficult to use a unified
formula to show the porosity change before and after
the destruction of coal, so it is difficult to establish a
uniform stress effect on the wave velocity change
formula. Based on this, the main consideration is toestablish the formula of the velocity change of thestress before the failure.
This is the relationship (Tao et al., 2010)
between porosity and stress before failure:

φ =1−(1 − φ0 )exp(− K yσ )(3)Where φ the initial porosity, %; σ the stress,
MPa; Ky the volumetric compression coefficient,MPa-1.
The formula (3) taken into the formula (2) can
get the relationship between stress and longitudinal
wave velocity:(1 − φ0 ) 1−
exp(− K yσ ) 
1 
V p = ln

a 
b





(4)

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

According to the parameters measured in thelaboratory, as Table.2 shown, a and b can be obtainedby using the formula (4) to fit.
Table 2: a, b constant
Ky /MP
φ0 /
coal
a-1
%
Guand 10.1
1.7×10-4iMalan 5.4
6.2×10-4
2#

a

b

r

4.21×10-5
2.3×10-0.1112490.08752
2

0.959
6
0.995
6

4

The Table 2 shows that the longitudinal wave
velocity fitted by the formula has a high correlation
with stress, which can be used to predict thelongitudinal wave velocity of coal under different
stress.

5. MECHANISM ANALYSIS OF STRESSINFLUENCING ACOUSTIC WAVEVELOCITY CHANGE OF COAL
SAMPLES
Coal and rock mass, as a non elastic medium, its
wave velocity is highly influenced by thedevelopment degree of the internal pore and fissure.
When the coal body is subjected to stress, the partial
primary fracture and pore are closed, with the stressincreasing, the primary coal, the external cracks andpores are formed, developed and expanded
constantly, and finally broke down. Because of thepore in the structure of the coal body, the crack andthe new crack have a great influence on the velocity
propagation of coal，the characteristics of coal poreand fracture structure are based on analyzing the lawof acoustic wave velocity variation under the loading
condition of coal body. As shown in Fig.4 The
internal structure of coal was studied by scanningelectron microscope. From the SEM pictures, it
intuitively shows that there is a small amount of
micro pores development on Malan 2# coal samples,of which layered structure can be seen obviously;
structure of Guandi Coal Samples is relatively entire,and only trace amounts of cement debris existed.

Malan 2# coal

Guandi coal

Figure 4: SEM scanning under the magnifying
multiple of 7k

The experimental results show that thelongitudinal wave velocity and shear wave velocityof Malan 2# coal and Guandi coal are increasing withthe stress increasing. This is mainly because theporosity decreases with the stress increasing, andcausing the elastic deformation of the particles, theincrease of the contact area between particles and thewave velocity of the particles. But at the same time,
due to the coal and rock mass consisted of a numberof different structures mutual cementation, andstructural surface was formed in the interface ofstructure, which cause wave velocity decayed in thecoal. Under the action of stress, these structuralmorphology and structural plane will be deformed
and damaged, which will change the direction of
acoustic wave propagation and increase the acoustic
attenuation characteristics. And when the soundwaves propagate in the coal and rock mass andencounters a structural morphology or structuralplane, for example, the crack and crack developmentof the place, due to the presence of a certain
reflectivity difference between the interface and theair, the sound wave in the transmission occurs at thesame time, there will be some reflection andrefraction. If the size of the pore is similar to thewavelength of the sound wave, or the difference isvery large, the acoustic diffraction phenomenon will
occur. And when the fissure is filled with the otherphases of matter, the transmitted wave will occur todifferent degree of attenuation of energy. But before
the destruction of coal, the increase of the velocity islarger than the decrease of the wave velocity.
Therefore, the increase of the wave velocity is shownon the macroscopic. When the coal body stressreaches the peak value, the fracture in the coal seamis rapidly diffused, with the porosity increasing, thewave velocity decreased greatly.

6. CONCLUSIONS(1) In the course of full stress and strain of coalloading, the longitudinal wave velocity increases
firstly, and then decreases when the coal body broke,
and the shear wave velocity also increases firstly, butwhen the coal body breaks, the shear wave signal
disappears.
(2) Stress-strain curves of samples have an highconsistency on the stress-wave velocity curve, whichsuggests that the wave velocity can be as the index ofreflecting longitudinal wave velocity variations ofcoal and rock mass stress and the deformation of theinternal structure, specially, velocity variations of
longitudinal wave can be as a good evolution index
of reflecting stress state of the deformation of internal
structure.

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3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

(3) The relationship between the stress and thelongitudinal wave velocity of coal is based on thechange of the pore structure of the coal body, which
can predict the longitudinal wave velocity of coal
body under different stress states.
(4) With stress changed, the variation of acoustic
velocity is increased mainly because that the effect of
the wave velocity increasing is larger than the effectof the wave velocity decreasing before thedestruction of coal, but the large increase of poreclosure caused the wave velocity decreased largely
after stress peak of coal body up to its peak.

7. ACKNOWLEDGEMENTS
This research is supported by National Natural
Science Funds of China (51304212), Fundamental
Research Funds for the Central Universities(2009QZ09). The authors would like to express their
gratitude to the foundation.

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scientiarum naturalium niversitatis pekinensis,
Volume 40, No. 2, pp. 177-183
Tao Y. Q., Xu J., Peng S. J. (2010). Yuan M.
Experimental study of influencing factor of porosityand effective stress of gas-filled coal, Rock and Soil
Mechanics, Volume 31, No. 11, pp. 3417-3422
Wang H. T. and Xian X. F. (1988). The study on
characteristics of elastic wave propagation in rocks
under complicated stress states, journal of Chongqing
university, No. 5, pp. 104-112
Xu X. L, Zhang R., Dai F. (2015). Effect of coaland rock characteristics on ultrasonic velocity,
Journal of China Coal Society, Volume 40, No 4, pp.
793-800
Zhao M. J. and Wu D. L. (1999). Ultrasonicvelocity and attenuation of rock under uniaxial
loading, Chinese Journal of Rock Mechanics andEngineering, Volume 18, No. 1, pp. 50-54
Zheng G. P., Zhao X. D., Liu J. P. (2009).
Experimental Study on Change in Acoustic Wave
Velocity When Rock Is Loading, Journal ofNortheastern University(Natural Science), Volume
30, No. 8, pp. 1197-1200

686

ISMS 2016

Paper No. 159

Numerical Simulation Technique for Gateroad Stability Analysis under
Fractured Ground Condition
Lishuai Jiang a,b,*, Atsushi Sainoki b, Hani S.Mitri b,c, Nianjie Ma aa

Faculty of Resources & Safety Engineering ,China University of Mining & Technology, Beijing, China 100083
Department of Mining and Materials Engineering, McGill University, Montreal, Canada H3A 2A7cSchool of Civil Engineering, Henan Polytechnic University, Jiaozuo, China 454000b

ABSTRACTThe ground stability of gateroads is a major concern in underground coal mines, especially where the surrounding
strata are weak and fractured. This paper presents a novel numerical modelling technique for gateroad stability
analysis based on a case study conducted in Zhaogu No.2 mine, China. Considering the occurrence of fractures andits weakening effect on the stiffness of rock mass, a tension-weakening model is implemented into FLAC3D,
whereby the stiffness of rock mass is progressively decreased according to failure state. A relationship between theintensity of fractures and the residual properties is built. A parametric study of the tension-weakening model withrespect to weakening parameter is carried out, and the results are compared to perfect elasto-plastic model andstrain-softening model. The comparison shows that the tension-weakening model exhibits a noticeable effect on
ground deformation and rock support loading, and can simulate more realistic behavior of a gateroad. The proposedmodel provides a rigorous approach for gateroad stability analysis and can be utilized for rock reinforcement design
under similar geotechnical circumstances.
KEYWORDS: numerical simulation; ground stability; coal mine gateroad; tensile failure; fractures

1. INTRODUCTION
The stability of roadways is a long-standing
issue in underground coal mines, especially forgateroads that serve and ensure the safety production
for longwall panels. Ground stability and failure
mechanisms of roadways vary depending on stress,
geological and geotechnical conditions. However, as
distinct from drifts and other roadways, thedifficulties of maintaining gateroad stability aremainly due to weak surrounding rock mass andcontinuous geotechnical disturbance.
A large number of researchers analyzed gateroad
stability with numerical modelling methods for the
past few years. Among these studies, the mostcommonly used constitutive models are perfectelasto-plastic and strain-softening models using
Mohr-Coulomb failure criterion (Shen, 2014; Zhang
et al., 2015; Li et al., 2015).
Due to the sedimentary effect of coal-forming
process, the surrounding rock mass of undergroundcoal mines exhibit a geologically stratified structure.
Under this geologic feature, tensile failure plays thedominate role when the surrounding rock is not
subjected to high horizontal stress (Vaziri, 2001;
Bakun-Mazor, 2009). This rock failure characteristicof underground coal mining activities is also
demonstrated with field investigation (Hebblewhite
and
Lu,
2004)
and
numerical
analysis(Shabanimashcool and Li, 2012). Since joints and*Corresponding author – email: jlsh1989@126.com

other fractures in rock can offer little or no resistanceto tensile stresses, fractures will take place anddevelop in a brittle manner when rock mass issubjected to tensile stress. Previous studies (Cai et al.,
2001; Mitri et al., 1995; Hoek et al., 2002) elaborateon the relation between the modulus of elasticity ofrock mass and the occurrence of cracks and fractures,and corresponding formulas are proposed. In light ofthe previous studies examining the post-peak
behavior of surrounding rock, it is therefore
reasonable to take the variation of elastic modulus
induced by tensile failure into consideration forstability analysis of openings in underground coalmines.
In the present study, tension-weakening model,
which allows for the reduction in the stiffness of rockmass due to fracture generation, is developed with
FISH (a programming language embedded within
FLAC3D) and implemented into FLAC3D - a three
dimensional explicit finite-difference program, inorder to simulate the gateroad stability based on acase study in Zhaogu No.2 mine. In the numericalmodel, the failure state of rock mass is continuously
monitored during analysis, and the properties are
weakened according to different failure states tosimulate the post-failure behavior. Numericalsimulations with perfect elasto-plastic model, strainsoftening model and tension-weakening model are
conducted for comparison analysis to the field3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

measurement. In addition, a model parametrical studyof the tension-weakening model is carried out toexamine the effect of tension-weakening and provide
basis for gateroad stability investigation and rock
support design.

The tailgate of panel 11050 is numericallymodelled to investigate its ground stability using
finite-difference software FLAC3D.

2. CASE STUDY
2.1 Geology and geotechnical overview of Zhaogu
No.2 mine
Zhaogu No.2 mine is located in Xinxiang City,
Henan Province, China. All panels in this mine areusing retreat longwall method to extract coal seams.
The coal seam is nearly horizontal with a mean
thickness of 6.12m.
The target gateroad for this case study is thetailgate of panel 11050 at a depth of 600 m. The
panel is approximately 180m wide along the dip and2000 m long along the strike as illustrated in Fig. 1.
The roof strata of this panel are mainly composed of
mudstone, sandy mudstone and sandstone. The
immediate roof is a layer of less than 2 m thickmudstone, which would cave and fall into the goaf,
following the advance of coal extraction and shield
support.
The tailgate of panel 11050 is 3.3 m high and 4.8
m wide. The gateroad is driven along the roof line of
the thick coal seam, which leaves the ribs andimmediate floor consisting of coal. Cable bolt
support is employed as primary support, and wire
mesh is utilized to prevent rock falling.

(a)

(b)

Figure 2: Field observations of severely deformed andfractured area (a) Roof (b) Rib-595m
Monitoring area

Tailgate of 11050

Panel of 11050-610m

Planned panel of 11030
-625m

-640m

Goaf of 11010

Figure 1: Plan view of local panel layout

2.2 Field monitoring of ground stability
As can be seen from field, as shown in Figure 2,
the surrounding rocks are severely fractured into
small and loose fragments after the gateroad
excavation has advanced, which also is accompanied
by significant rib convergence.

3. NUMERICAL SIMULATION WITHTENSION-WEAKENING MODEL
3.1 Local model based on case study

Figure 3: Isometric view of local model

Considering the symmetry of the panel withrespect to its centerline, a 3D numerical model
encompassing the tailgate of panel 11050 isgenerated, as shown in Figure 3. The dimensions of
the model are 155 m wide, 140 m long and 100 m
high, which are determined based on model
sensitivity analysis with regard to size and meshdensity. A vertical stress of 15 MPa is applied at the
top model boundary to simulate overburden pressure.
The horizontal-to-vertical stress ratio is set to 0.8 and
1.2 in the x- and y-directions, respectively (Yan et al.,688

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 20162013). No horizontal displacement is allowed at sideboundaries, and no vertical displacement is allowed
at the bottom boundary of the model. Rock massproperties for the numerical simulation, as listed inTable 1, are estimated from the intact rock properties
and by using the generalized Hoek-Brown failure

criterion (Hoek et al., 2002). Values of softening
parameters, εp and cr are assumed according to theliterature on strain-softening behavior in gateroad
stability analysis using numerical simulation (Shen,
2014; Zhang et al., 2015; Li et al., 2015;
Shabanimashcool and Li, 2012).

Table 1: Rock mass mechanical propertiesa
φKGc(deg.)
(GPa)
(GPa)
(MPa)
45

cr
(MPa)
0.39

εp
(%)
0.01

3.2

40

0.32

0.01

1.1

2.1

35

0.21

0.01

0.6

1.4

31

0.14

0.01

StrataLithology

9.1

5.9

3.9

Roof

Sandstone
Sandy
mudstone
Mudstone

5.2

3.1

2.4

Coal

1.3

Coal
seam

Sandy
7.2
4.0
3.4
37
0.34
0.01
mudstone
Siltstone
9.6
6.5
4.2
47
0.42
0.01
a
K is bulk modulus, G is shear modulus, c is cohesion, φ is friction angle, cr is residual cohesion, εp is plastic strain parameter at
the residual strength
Floor

3.2 Model description of tension-weakening model
As indicated in Section 1, perfect elasto-plastic
and strain-softening models are most widely utilized
in numerical studies of ground stability ofunderground coal mines.
When perfect elasto-plastic behavior is assumed,
the mechanical properties remain constant after thematerial yields and fails, which obviously is not inaccordance with the true characteristic of mostgeological material (Cui et al., 2006). While, for thestrain-softening model, the strength parameters are
decreased with the increase in εp until reaching theirresidual values ultimately. However, for both of theconstitutive models, elastic modulus remains
constant, irrespective of the occurrence of failure.
The difficulty and feature of gateroad support lie
with the ground stability that must be maintained not
only during a gateroad driven period, but also when
the panel is mined in retreat. According to the casestudy and numerical simulation, it is evident that thesurrounding rocks are heavily fractured after thegateroad is driven. As the modulus of elasticity ofrock mass is directly related to the occurrence of
cracks and fractures (Cai et al., 2001; Mitri et al.,
1995; Hoek et al., 2002), the variation of elastic
modulus of the fractured area induced by tensile
failure should be taken into consideration in order tosimulate and analyze the gateroad stability properly,
especially under mining influence. Otherwise, thestability analysis assuming constant elastic modulus
may underestimate the ground deformation and fail topredict the stability condition.
For the purpose of simulating the variation ofelastic modulus due to the tension-induced fractures,a novel numerical simulation technique, hereinreferred to as tension-weakening model, is developedwith FISH language and implemented into FLAC3D.
The tension-weakening model is developed on thebasis of the strain-softening model, whereby it
overcomes the limitation of the conventional
simulation techniques (Shen, 2014; Zhang et al.,2015; Li et al., 2015; Shabanimashcool and Li,2012), that is, elastic modulus is kept constantregardless of rock mass failure and fracture
propagation. Considering the observed brittle failuremanner of the rock sample in laboratory experiments,
both tension-weakening and strain-softening model
employ an instantaneous decrease in strengthparameters to the residual values and express thesame post-peak behavior of rock. After the strength
reduction, the parameters are kept at the residual
values.
In order to take into account the variation ofelastic modulus, a brittle tension-weakening
parameter A is given as(1)
Er= A ⋅ Em
where Er is the residual elastic modulus of rock mass
after tensile failure takes place and Em is the elastic
modulus of rock mass estimated from experimentdata. When tensile failure occurs, the elastic modulus
decreases to the residual elastic modulus Er in abrittle manner.
In order to characterize the post-peak behavior of
fractured rock mass and estimate the residual elastic
modulus, the Geological Strength Index (GSI) system
is utilized to study the effect of different Er on groundstability.
Although the GSI system developed by Hoek et
al is generally used to determine the rock mass689

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

deformability and strength on the basis of intact rockproperties and geological structures, it is reasonable
to assume that this index can be applicable toevaluating the intensity of fractures induced bytensile failure, such as blocky rock mass withtension-induced fractures shown in Fig. 4. In thisstudy, GSI for rock mass with tension-induced
fractures is defined as GSIt. The implication is that
GSI varies with the occurrence of tensile failurecaused by the gateroad excavation.
For rock with σc < 100 MPa, the elastic modulusof rock mass Em is estimated with GSI system fromthe following equation (Hoek et al., 2002):
GSI t −10
(
)
σm
(2)
=
Er
⋅ 10 40100
where σm is the uniaxial compressive strength of rockmass. Assuming GSIt =90 implies that no tensile
failure occurs or no fractures and joints are induced
by tensile failure, namely
90 −10
(
)
σm
(3)
=
Em
⋅ 10 40
100
By dividing Equation (2) by Equation (3), theweakening parameter A can be expressed as
GSI t −90
(
)
Er
=
A =
10 40
Em

(4)

In order to comprehensively investigate theweakening behavior after tensile failure, aparametrical study of the tension-weakening model iscarried out with 4 different values of GSIt (10, 30, 50,70), and the obtained results are compared with thosesimulated with the perfect elasto-plastic and strainsoftening models

gateroad undergoes significant ground destabilizationand deformation.
As shown in Figure 4, the ground deformation
simulated with the strain-softening and tensionweakening models is remarkably larger than thatsimulated with the elastic-perfectly plastic model.
This large difference is ascribed to the strength
reduction and corresponding stress re-distribution
during the post-peak behavior.
Also, the magnitude of deformation simulatedwith the tension-weakening model shows a negative
correlation with GISt. This is due to the fact that highfracture intensity leads to low modulus of elasticity,
ultimately resulting in severe deformation andinstability. The maximum difference in deformation
between the strain-softening and tension-weakening
models during the gateroad driven period and themining period is 25.1 mm and 49.7 mm for roof sag,
31.0 mm and 74.3 mm for floor heave, 51.9 mm and99.8 mm for rib convergence. The large deformationinduced by tension weakening is reasonable because,
although the surrounding rocks almost stop
deforming under the effect of ground self-stability
and rock support, rocks that undergo tensile failure
are weakened as a result of fractures development
during the process of mining-induced stressreadjustment, causing large deformation andinstability.

4. RESULTS OF PAREMETRIC STUDYRoof sag deformation is a major issue in groundcontrol of gateroads. Failure or instability of the roof
may cause not only economic loss, but more
importantly also fatalities and injuries.
Figure 4 shows the evolution of roof sag for thedifferent models during both the gateroad driven andretreat mining periods. As can be seen, for all thecases, large ground deformation takes place
immediately after the gateroad is driven, and theincrease rate of ground deformation becomesmoderate or quite small after the distance between
the monitoring station and the advancing driven facebecomes greater than 15m. The surrounding rock
begins to deform when the mining operation starts,
however this increasing deformation is not noticeable
until the mining face reaches a distance of 20 m fromthe monitoring station, and this effect is generally
referred to as mining influence. As a result of theintensive mining influence ahead of mining face, the

(a)

(b)

690

3rd International Symposium on Mine Safety Science and Engineering, Montreal, August 13-19, 2016

Figure 4: Evolution of roof sag (a) gateroad driven period;(b) retreat mining period

5. CONCLUSION
A case study on gateroad stability at the Zhaogu
No.2 coal mine in China is carried out. According tofield observations and monitoring results, severe
fractures and significant deformation severely
destabilize the surrounding rock, which leads topotentially high risk to personnel safety.
Based on the geotechnical characteristics of thegateroad, a tension-weakening model allowing for the
stiffness weakening of rock mass due to tensile
fracture generation is proposed and implemented into
FLA3D to analyze the gateroad stability under
severely fractured ground conditions. Taking into
account the weakening effect of tensile fractures, abrittle tension-weakening parameter A is introduced
to establish the relationship between the intensity offractures induced by tensile failure and the residual
property.
A model parametric study with respect to theweakening parameter is conducted, and the obtained
results are compared to those simulated with theconventional elastic-perfectly plastic and strainsoftening models. It is demonstrated that the effect oftension-weakening on the deformational behavior of
the gateroad is significant during not only the gateroad driven period but also the retreat mining period.
Considering the intensity of fractures induced bytensile failure and its weakening effect on rock mass,
the tension-weakening model provides a rigorous
simulation approach to studying the gateroad stability
under fractured ground conditions. This model can beutilized for ground stability investigation, pillar
design and rock reinforcement design (both primaryand secondary support) under similar geotechnicalcircumstances.

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6. REFERENCES
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691

AUTHOR INDEX
Last Name
Abdellah
Abdelrahman
Abou-Jaoude
Abouelkair
Ahmed
Aitao
AkhtarAl Heib
AndersonAndersson
Ang
Antunes
Aziz
BaptistaBarańskiBasahel
Belem
Benton
Boltz
Cai
Cai
Cain
Cao
Cao
Cao
Cao
Chang
Charette
Che
Chen
Chen
Chen
Chen
Chen

First Name
Wael
M.Z.
Elie
M.M.
Samar
Zhou
Saad
MarwanRyan
H.
Liu
Maria M.
Naj
Adelina L.F.
Adam
HassanTikou
DonovanShawn
Jiawen
Ming
Peter
Chen
Jie
Qinggui
Yang
De-qiang
Francois
De-fu
Li
Shaojie
Wenxue
Xuexi
Peng

Pages
84
140
387
140
640
564, 585
605
78, 640
611
24
564
398
432, 557
381
1
127102, 419
71
71
552
12
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18
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335
591
204
60
199
442
581
208, 471, 557
199, 520
520
692

Cheng

Li Zhen

419

Cong
Coulibaly
Coulombe
Cui
Cui
Dai
De Souza
De Werk
De WitDeadman
Debia
Dehua
Dejun
Demir
Deng
Descamps
Ding
Ding
Diogo
Domingues
Dongwei
Duo
DurkinDuzgun
Ekman
Esterhuizen
Fan
Fan
Feng
Feng
Fujii
FukudaGalera
Gao
Gao

Xiang
Yaya
Hugo
Xuefeng
Zhe
Linchao
Euler
Marco
Ben
AllisonMaximilien
Chang
Miao
Serenay
Qigen
Fanny
Cui
Shiwei
Miguel TatoMaria S.Q.
Tan
Yingquan
StevenH. Sebnem
Jonas
GabrielLin-yuPenghong
CaiyunJunfa
YoshiakiDaisukeJose-Miguel
Na
Xiang

536
419
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487,
681
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494

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Yu-kunGao
Gardhouse
Ge
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Gunzburger
Guo
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Han
HansenHe
Henning
Henschel
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Jiao
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JohnsonKai
Kang

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Wang
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442,
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Kang

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351

King
KodamaKomljenovic
Konicek
Kou
KumralKurniaLachapelle
Lan
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Lawrence
Li
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Lin
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Ronald F.
Jun-ichiDraganPetr
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MustafaJundika C.
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Liu

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Lu
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Mäkitaavola
Manouchehrian
Mao
Mao
MartinMasny
MattieMazairaMbonimpa
McGillMeguidMeng
Mirzaghorbanli
Mitri

Wei Victor
WeihuaXianglong
Xiliang
Yanli
YanweiGeorges
Jiang
Yueze
Qiang
Hui
Nianjie
Yuntong
Bryce
KarolaAmin
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Yanjun
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Wojciech
Brian
Alejandro
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Hani S.

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Shengnan
Aleksandra
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276

482, 520, 595, 681

640

90,
38

181, 687

314, 634

697

Souley

Mountaka

78

Stöckel
Sun
Sun
Tan
Tang
Tang
TasorenThoeseTong
Tshibangu
Tulu
VennesVeyratWalentek
Wan
Wang
Wang
Wang
Wang
Wang
Wang
Wang
Wang
Wang
Wang
Wang
Wang
Wang
Wei
Wen
Wickramanayake
Wu
Wu
Wu
Xie

Britt-Mari
Qian
Siheng
LaizaiBaoyaoGuoshui
KorhanW.
Shu Jiao
Jean-Pierre
Ihsan Berk
Isaac
SantiagoAndrzej
Long
Bo
Dong
HaiyanHetangHui
Jianhua
Jun
Kai
Rujun
Shu
ShurenWei-xiang
Zhiliang
Shanyang
JiejieAnura
HaijunJun
ZongzhiChangzhen

133
281
231
302
453
18
114
24
296,
187
659
65
24,
54
459
514
531
302,
291
154,
459
658
514,
296,
236,
413
308,
325
647
487,
133
302
208
296,
335

477

38

574
159, 666

540
477, 527
346
314, 346, 634

494

527

698

Xu

Changfu

302, 574

Xu
Yang
Yang
Yang
Yang
Yang
Yang
Yang
Yao
Yaylaci
Yu
Yun
Yuyu
Zeng
Zhang
Zhang
Zhang
Zhang
Zhang
Zhang
Zhang
Zhang
Zhang
Zhang
Zhang

Teng
Chunli
Fei
JunzheLonglong
Shengqiang
Tao
WentaoHaifei
Evren Deniz
Hongming
Xiaoyou
Kong
Hongbiao
Haiqing
Hongwei
Hui
Kai
Lang
Lihui
Qun
Rui
Sai
Shouming
Ying-hua

Zhang
Zhang
Zhang
Zhao
Zhao
Zhao
Zheng
Zheng
Zhou

Yue
YuebingLi
Ruhui
Xinglong
Xue
JiewenZhong-ya
Peiling

616
616,
159
291
647
552
520
319
225,
368
447
453
564
447
413
18
341
319
531
291
225,
351
335,
335
159,
666,
319
325
498
658
329
231
208
574
285

681

302, 574

574
487
258, 264, 268, 276, 281, 285, 442,
672, 677

699

Zhou

Xiuhong

552

Zhou
Zhu
Zhu
Zhu
Zhu
Zhu
Zhu
Zimmerman
Zou
Zou

You
Bin
Feng
Hong-qing
Hongjie
HongminYuanyue
KarstenWeifeng
Zhengsheng

658
651
18
574
214
622
319
145
248
413

700