Comparison of Fatality Incident Rates

0

10

20

30

40

50

60

70

1995 1996 1997 1998 1999

Year

Fatalities/100,000 Workers

All Underground Mining Ground Falls

All US Manufacturing All US Construction

Figure 1. Fatality rates in mining and other U.S. industrial

sectors.

Overview of Ground Control Research for Underground Coal Mines in The

United States

C. Mark

National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, Pittsburgh, PA, USA

ABSTRACT: Underground coal mining continues to evolve in the U.S., and more reserves are being mined under

deeper cover, with worse roof, or with interactions from previous workings. At the same time, the mining

community is responding to higher safety standards and intense competitive pressures. The need for effective

ground control design has never been greater. Ground control safety issues that have been addressed by recent the

National Institute for Occupational Safety and Health (NIOSH) research include: Improving roof support

performance; Maintaining safe tailgate escapeways from longwalls; Optimizing pillar design for retreat mining;

Controlling multiple seam interactions; Predicting roof conditions during extended cuts, and; Preventing massive

pillar collapses. As funding from both government and the private sector has diminished, the emphasis in research

has focused on providing the mining community with practical techniques for improved ground control design.

Many projects have successfully employed empirical methods that emphasize the statistical analysis of case

histories from underground mines. Other projects have employed numerical models and large-scale laboratory

testing of roof support elements. Using these data, NIOSH has developed an entire toolbox of computer programs

that have been effectively transferred to the mining community. 

1 INTRODUCTION

Roof falls have been the single greatest hazard that

underground coal miners face in the U.S. Throughout

the 20th century, roof falls accounted for approximately

half of all deaths underground. While overall safety in

U.S. coal mines has improved dramatically in the last

50 years, fatality rates continue to exceed other major

industrial sectors (fig. 1). Fatalities due to ground falls

still make up a significant portion of this rate. 

Currently, underground coal production in the U.S.

is split almost 50-50 between large longwall mines and

smaller, room-and-pillar mines. Most longwalls

operate at depths of cover in excess of 300 m. Roomand-pillar operations are still primarily at shallow

depth, often working small, irregular deposits that were

abandoned by earlier miners. Approximately 20% of

the room-and-pillar coal is won on retreat faces (Mark

et al, 1997a).

Today's underground coal industry faces intense

competitive pressures from the $4/ton Powder River

Basin strip mine coal and from the pace-setting

million-ton-per-month longwalls. Ground failures can

hardly be afforded in this climate, yet they continue to

occur. Some examples:

Roof falls: In 1998, more than 1,800 unplanned roof

falls occurred where the roof had already been

supported. While few of these resulted in injuries,

each one represented direct threat to life and limb, and

an indirect threat to ventilation, escape, and equipment.

In each of these roof falls, the majority of which

occurred in intersections, the roof bolt system failed to

perform successfully.

Massive Collapses: In 1992, miners were splitting

pillars at a southern West Virginia mine when the

fenders in a 2.3 ha area suddenly collapsed. The miners

were knocked to the floor by the resulting air blast, and

103 ventilation stoppings were destroyed. At least 12

similar events have occurred in recent years,
0

5

10

15

20

25

No. of Observations

0 - 45

(Weak)

46 -65

(Moderate)

66 -100

(Strong)

Coal Mine Roof Rating (CMRR)

Northern

Appalachia

Southern

Appalachia

Western

N = 90

Figure 2. The Coal Mine Roof Rating observed in various

U.S. coalfields

miraculously without a fatality (Mark et al., 1997b).

Pillar Squeezes: At a Kentucky coal mine, pillars

were being extracted in the main entries under 270 m

of cover. The pillars began to crush in response to the

vertical load, resulting in a roof fall that killed two

miners. This incident is an extreme example of

hazardous conditions that can be associated with slow

pillar failure. Research has identified at least 45 recent

instances of pillar squeezes in room-and-pillar mines

(Mark and Chase, 1997).

Longwall Tailgate Blockages: In 1984, 26 miners at

the Wilberg Mine in Utah could not escape a deadly

fire because of a tailgate roof fall. Similar blockages

were common in the 1980's, and 50 cases have been

documented (Mark, 1992). 

Multiple Seam Interactions: Studies indicate that the

majority of remaining room-and-pillar reserves, and

33% of longwalls, will be subject to multiple seam

interactions. At one West Virginia mine where four

seams had previously been extracted, a fatality

occurred when the roof collapsed without warning

beneath a barrier pillar.

The National Institute for Occupational Safety and

Health (NIOSH) has the primary responsibility for

conducting research to reduce mining hazards in the

U.S. NIOSH continues the tradition of the U.S. Bureau

of Mines, which was closed in 1995. Mining research

is conducted at two Research Laboratories, one in

Spokane and the other in Pittsburgh.

The past 20 years has seen a steady decline in the

resources devoted to ground control research. The

labor- and instrumentation-intensive field studies of

past years are rarely feasible today. As a result, NIOSH

scientists have had to develop new approaches to

conducting ground control research. 

2 THE COAL MINE ROOF RATING (CMRR)

One approach that has proven exceptionally successful

for solving complex problems is the empirical, or

statistical, approach. It relies on the scientific

interpretation of actual mining experience represented

as case histories. For example, hundreds of longwall

and room-and-pillar panels are mined each year, and

each one is a full-scale test of a pillar design. Once

data has been collected on enough of these case

histories, statistical techniques can be used to

determine those combinations of factors most likely to

result in pillar failure. A key advantage is that critical

variables may be included even if they are difficult to

measure directly, through the use of rating scales. A

significant breakthrough was the development of a

rock mass classification system specifically applicable

to coal mine roof.

Coal Mine Roof Rating (CMRR) was proposed

because neither traditional geologic reports nor

laboratory strength tests on small rock samples

adequately described the structural competence of mine

roof. The CMRR combined 20 years of research on

geologic hazards in mining with worldwide experience

with rock mass classification systems (Molinda and

Mark, 1994). Field data was collected from nearly 100

mines in every major U.S. coalfield (figure 2). 

The CMRR weighs the geotechnical factors that

determine roof competence, and combines them into a

single rating on a scale from 0 to 100. The underlying

philosophy of the CMRR is that it is not the strength of

the intact rock that determines the stability of a mine

roof, but rather the defects or discontinuities which

weaken or destroy the roof beam.

The CMRR makes four significant contributions:

• Focuses on the characteristics of bedding planes,

slickensides, and other discontinuities that

weaken the fabric of coal measure rock;

• Applies to all U.S. coalfields, and allows

meaningful comparison even where lithologies

are quite different;

• Concentrates on the ability of the immediate roof

to form a stable structure, focusing on the

characteristics of the strongest bed within the

bolted interval, and;

• Provides a methodology for geotechnical data

collection.

Originally, the data for the CMRR was collected at

underground exposures like roof falls and overcasts. To

make it more generally useful, procedures were

developed for determining the CMRR from drill core

(Mark and Molinda, 1996). The drill core procedures

employ the Point Load Test to estimate the uniaxial

compressive rock strength and the rock strength

parallel to bedding. A new conversion factor from

point load index of strength (Is(50)) to uniaxial

compressive strength (UCS) has been determined from
Figure 3. Plan view of a typical U.S. longwall mine.

Figure 4. ALPS case history data base and design guidelines.

a large data base provided by a large U.S. coal

company (Rusnak and Mark, 2000). 

The CMRR has found many applications in ground

control research and mining practice, as described in

many of the examples below. It has also been

successfully applied in Australia and South Africa

(Colwell et al., 1999; Mark, 1998; Mark, 1999). A

computer software package has recently been

developed that makes the CMRR easier to use and to

integrate into exploratory drilling programs. 

3 DESIGN OF LONGWALL GATE ENTRY

SYSTEMS

In the fifteen years after 1972 the number of U.S.

longwall faces grew from 32 to 118 (Barczak, 1992).

The new technology created a host of operational and

safety problems, including the maintenance of stable

travelways on the tailgate side (figure 3). Researchers

initially viewed gate entry ground control primarily as

a pillar design issue. The clear correlation between

larger pillars and improved conditions that had been

established by trial-and-error at many mines supported

this approach.

In comparing longwall pillars to traditional coal

pillars, the most obvious difference is the loading.

Longwall pillars are subjected to complex and severe

abutment loads arising from the retreat mining process.

The loads are also changing throughout the pillar's

service lives. The major contribution of the original

Analysis of Longwall Pillar Stability (ALPS) was a

formula for estimating the longwall pillar load, based

on numerous underground measurements (Mark,

1990).

It became clear, however, that tailgate stability

required more than good pillar design. Other factors,

such as roof quality and artificial support, must be

important. Data were collected from approximately

55% of all U.S. longwall mines, selected to represent

a geographic and geologic cross-section of the U.S.

longwall experience. A total of 64 case histories were

classified as "satisfactory" or "unsatisfactory."

Unsatisfactory conditions almost always caused the

mine to adjust their design in future panels.

Satisfactory designs were used for at least three

successive panels without significant ground control

delays.

Each case history was described by several

descriptive variables, including the ALPS stability

factor (SF), the CMRR, entry width, and primary

support rating. Multi-variate statistical analysis showed

that when the roof is strong, smaller pillars can safely

be used (Mark et al., 1994). For example, when the

CMRR is 75, the an ALPS stability factor (SF) of 0.7

is adequate. When the CMRR drops to 35, the ALPS

SF must be increased to 1.3 (figure 4). Significant

correlations were also found between the CMRR and

both entry width and the level of primary support.

Since 1987, ALPS has become the most widely-used

pillar design method in the U.S. The ALPS-CMRR

method directly addresses gate entry performance, and

makes U.S. longwall experience available to mine

planners in a practical form. Tailgate blockages are far

less common today than they were 10 years ago, and

ALPS can surely claim some of the credit. 

4 PILLAR DESIGN FOR RETREAT MINING

The classical empirical pillar strength formulas were

all developed for room and pillar mining. However,

none ever attempted to consider the abutment loads

that occur during pillar recovery operations. The

abutment load formulas used in ALPS provided a

means to rectify that shortcoming. 

The Analysis of Retreat Mining Pillar Stability

(ARMPS) employs the same basic constructs as ALPS,
Figure 5. Model of a room-and-pillar mining section used by

the ARMPS program

0

0.5

1

1.5

2

2.5

3

0 100 200 300 400 500 600

Depth of Cover (m)

ARMPS SF

Satisfactory

Unsatisfactory

Figure 6. The ARMPS case history data base.

0

0.5

1

1.5

2

2.5

0.00 1.00 2.00 3.00 4.00 5.00

Width-To-Height Ratio

ARMPS SF

Collapse

Squeeze

Success

Figure 7. Pillar collapse case histories in the U.S

adapted to more complex and varied mining

geometries (Mark and Chase, 1997). The abutment

load formulas have been adapted to three dimensions,

to account for the presence of barrier pillars and

previously-extracted panels. Features such as varied

entry spacings, angled crosscuts, and slab cuts in the

barrier can all be modeled (figure 5).

To evaluate the validity of ARMPS, more than 200

retreat mining case histories were obtained from field

visits throughout the U.S. When the entire data set was

evaluated, it was found that 77% of the outcomes could

be correctly predicted simply by setting the ARMPS

SF to 1.46 (figure 6). When the data set was limited to

cases where the depth of cover (H) was less than

200 m, the accuracy improved to 83%. The conclusion

seems to be that ARMPS works quite well at shallow

depth and moderate width-to-height (w/h) ratios (Mark,

1999). Research is currently underway to determine

what other factors need to be included when designing

squat pillars at great depth.

The study also answered some ancient questions

regarding the value of laboratory tests to determine the

UCS of coal specimens. The analyses clearly showed

that UCS was of no value whatever in predicting the

strength of coal pillars, thus confirming the results of

an earlier study (Mark and Barton, 1996). It also found

that the best results are achieved with ARMPS when

the in situ coal strength is assumed to be 6.2 Mpa. The

study concluded that while the in situ strength of U.S.

coal seams is probably not uniform, laboratory tests do

not measure the geologic features (like bedding planes

and rock partings) which are most likely responsible

for variations in seam strength.

5 MASSIVE PILLAR COLLAPSES

Most of the pillar failures included in the ARMPS data

base are “squeezes” in which the section converged

over hours, days or even weeks. Another important

subset are 15 massive pillar collapses (Mark et al.,

1997b). These occurred when undersized pillars failed

and rapidly shed their load to adjacent pillars, which in

turn failed. The consequences of such chain reactionlike failures typically include a powerful, destructive,

and hazardous airblast.

Data collected at 12 massive collapse sites revealed

that the ARMPS SF was less that 1.5 in every case, and

was less that 1.2 in 81% of the cases. What really

distinguished the sudden collapses from the slow

squeezes, however, was the pillar’s w/h ratio (figure 7).

Every massive pillar collapse involved slender pillars

whose w/h was less than 3. Laboratory tests have

shown that slender pillars typically have little residual

strength, which means that they shed almost their entire

load when they fail. As the specimens become more

squat, their residual strength increases, reducing the

potential for a rapid domino failure. The mechanism of

massive collapses has been replicated in a numerical

model (Zipf, 1996).

Two alternative strategies were proposed to prevent

massive pillar collapses. Prevention requires increasing

either the SF of the pillars, or their w/h ratio.
Figure 8. Stress analysis of multiple seam interaction using

LAMODEL.

A. Single-Seam Stress

B. Multiple-Seam Stress

C. Additional Stress from Upper Seam

Legend (MPa)

-7 3 -2 8 13 18

Gob

Gob

Legend (MPa)

6 12 18 24 30 36

Gob

Gob

Containment is used if barrier pillars are used to

separate compartments in which high extraction is

practiced. The small pillars may collapse within a

compartment, but because the compartment size is

limited, the consequences are not great. Design charts

have been developed for each approach, considering

the width of the panel, the seam thickness, and the

depth of cover (Mark et al., 1997b).

6 LAMODEL: A NUMERICAL MODEL FOR

MULTIPLE SEAM DESIGN

Multiple seam situations and other complex mining

geometries do not lend themselves readily to simplistic

empirical models like ALPS and ARMPS. Numerical

methods are the alternative approach, but to be useful

they must realistically portray the behavior of large

volumes of rock. In addition, they must not require

rock material properties that cannot be easily

determined.

To address these concerns, NIOSH has developed

the displacement-discontinuity model LAMODEL

(Heasley and Salamon, 1996a). LAMODEL simulates

the overburden as a stack of homogeneous isotropic

layers, with frictionless interfaces and with each layer

having the identical elastic modulus, Poisson’s ratio,

and thickness. This “homogeneous stratification”

formulation does not require specific material

properties for each individual layer, and yet it still

provides a realistic suppleness to the overburden that

is not possible with the homogeneous overburden

(Salamon, 1989; Heasley and Salamon, 1986b). 

For practical pillar design using a DD model, the

input coal strength is generally derived from empirical

pillar strength formulas which are solidly based on

observed pillar behavior, as opposed to laboratory tests

(Mark and Barton, 1996). Similarly, the gob and

overburden properties in the DD model are calibrated

so that the resultant gob and abutment stresses closely

match field measurements/observations such as the

abutment load formulas in ALPS or ARMPS. This

technique of combining empirical pillar strength and

abutment load formulas with the analytical mechanics

of a displacement-discontinuity model capitalizes on

the strengths of both the empirical and analytical

approaches to pillar design. Using this technique, a

displacement-discontinuity model can be the most

practical approach for stress analysis and pillar design

in complex mining situations such as; multiple seams,

random pillar layouts and/or variable topography

(figure 8). 

7 GUIDELINES FOR ROOF BOLT SELECTION

Despite more than half a century of experience with

roof bolting, no design method has received wide

acceptance. To begin to improve this situation, NIOSH

evaluated the performance of roof bolt systems at

37 mines (Molinda et al., 2000). Success was measured

in terms of the number of roof falls that occurred per

3,000 m of drivage with a particular roof bolt design

when other geotechnical variables were held constant.

A variety of statistical techniques were used to explore

trends in the data.
L 0.12(I )log (3.25H)

100 CMRR

100 B s 10 =  − 









Figure 9. Roof bolt performance case histories.

Shallow Cover

25.00

35.00

45.00

55.00

65.00

75.00

85.00

2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00

PRSUP

CMRR

Design 

Equation

No Roof Falls

Few Roof Falls

Many Roof Falls

PRSUP L N C

14.5 W

B B

B e

= (S )

Deeper Cover

25.00

35.00

45.00

55.00

65.00

75.00

85.00

2.00 4.00 6.00 8.00 10.00 12.00 14.00

PRSUP

CMRR

Design

Equation

No Roof Falls

Few Roof Falls

Many Roof Falls

Figure 10. Design equations for roof bolts.

The study evaluated five different roof bolt

variables, including length, tension, grout length,

capacity, and pattern. Roof spans and the CMRR were

also measured. Stress levels could not be measured

directly, but the depth of cover was used as a surrogate.

As expected, the competence of the roof rock,

represented by the CMRR, was the single best

predictor of the roof fall rate. More surprising was the

importance of depth. The higher horizontal stresses

encountered in deeper mines apparently require greater

levels of roof support (figure 9). Important findings

were also made regarding bolt length and intersection

span. Unfortunately, the data was too sparse and too

scattered to allow conclusions to be made regarding

tension and other roof bolt variables.

The study’s findings were used to develop

guidelines for designing roof bolt systems (Mark,

2000). Building upon an equation initially proposed by

Unal (1984), a formula for selecting bolt length was

proposed:

Where: LB = Bolt Length (m)

 IS = Intersection span (average of the sumof-the-diagonals, m)

 H = Depth of Cover (m)

Once the bolt length has been determined, the bolt

pattern and capacity is determined using the following

equation:

Where: NB=Number of bolts per row

C=Capacity (kN)

SB=Spacing between rows of bolts (m)

We=Entry width (m)

The suggested value of PRSUP depends on the

CMRR and the depth of cover, as expressed in the

following equations: 

PRSUP = 15.5 - 0.23 CMRR (low cover)

PRSUP = 17.8 - 0.23 CMRR (high & moderate cover)

Figure 10 shows these equations together with the

field data from which they were derived. The design

equations are slightly more conservative than the

discriminate equations that they are based on. The

guidelines are currently being implemented into a

computer program called Analysis of Roof Bolt

Systems (ARBS).

8 SUPPORT TECHNOLOGY OPTIMIZATION

PROGRAM

The 1990’s saw an unprecedented development of

innovative supplemental roof support technologies for

underground coal mines. Compared with the

traditional wood posts and cribs, the new supports

provide better roof control and material handling

advantages. The new supports include both engineered

wood products and novel concrete designs.

As new support systems are developed, they should

be tested to determine their performance

characteristics. NIOSH operates a world-class facility

called the Safety Structures Testing Laboratory

(Barczak, 2000a). During the past seven years, over
Figure 11. Typical Windows screen from the STOP program.

1,000 tests have been conducted on various support

systems. As a result of this effort, 18 new support

systems have been introduced to the mining

community.

To facilitate the use of these new supports, NIOSH

developed the Support Technology Optimization

Program (STOP). STOP includes a complete database

of the support characteristics and loading profiles

obtained from the testing (Barczak 2000b). Using

criteria introduced by the user, STOP can determine

the support pattern that will carry the required load and

provide convergence control. Comparisons among the

various support technologies are easily made. STOP

can also estimate material handling requirements and

installation costs. Figure 11 shows a typical screen

from the STOP program.

9 CONCLUSIONS

The NIOSH ground control program has focused on

providing the mining community with practical tools

for improving the safety of U.S. underground coal

miners. Using these techniques, mine planners can

optimize pillar design and support selection for a

variety of mining techniques.

Transferring these tools to the industry is an integral

part of the program. Traditional techniques, such as

conference presentations and NIOSH publications, are

employed extensively. But innovative methods are also

employed to bring the research results directly to the

end users. Open Industry Briefings are regularly held in

numerous coalfield locations, to allow researchers

direct access to their customers. Software packages are

made available free of charge, and hundreds are

distributed at meetings or in response to requests. Most

recently, all the ground control software has been

posted on the NIOSH mining website for easy access.

The technology transfer efforts have paid off in

many ways. Large segments of the mining community

uses NIOSH software routinely for many aspects of

mine design. Mine operators and safety regulators both

consider NIOSH as the central source for information

ground control. While it is hard to measure directly,

there is every reason to believe that our efforts have

helped make underground coal mines safer places to

work.

10 REFERENCES

Barczak, T. M. The History and Future of Longwall Mining in the

United States. BuMines IC 9316, 1992, 26 pp. 

Barczak, T. M. NIOSH Safety Performance Protocols for

Standing Roof Supports and Longwall Shields. Proceedings:

New Technology for Coal Mine Roof Support, NIOSH IC

9453, 2000a, pp. 207-222. 

Barczak, T. M. Optimizing Secondary Support with the NIOSH

Support Technology Optimization Program (STOP).

Proceedings: New Technology for Coal Mine Roof Support,

NIOSH IC 9453, 2000b, pp. 151-164.

Colwell, M., Frith, R. and Mark, C. Calibration of the Analysis of

Longwall Pillar Stability (ALPS) for Australian Conditions.

Paper in the Proceedings of the 18th International Conference

on Ground Control in Mining, Morgantown, WV, 1999, pp.

282-290.

Heasley, Keith A., and Miklos D. G. Salamon, 1996a, A New

Laminated Displacement-Discontinuity Program, Proceedings

of the Second North American Rock Mechanics Symposium,

Montreal, Quebec, Canada, June 19-21, p. 1879-1886.

Heasley, Keith A., and Miklos D. G. Salamon, 1996b, A New

Laminated Displacement-Discontinuity Program: Fundamental

Behavior, Proceedings of the Fifteenth International

Conference on Ground Control in Mining, August 13-15. p.

111-125. 

Mark, C. Analysis of Longwall Pillar Stability: An Update. Paper

in the Proceedings of the Workshop on Coal Pillar Mechanics

and Design. USBM IC 9315, 1992, pp. 238-249.

Mark, C. Pillar Design Methods for Longwall Mining. USBM IC

9247, 1990, 53 pp.

Mark, C. Design of Roof Bolt Systems. Paper in Proceedings of

the New Technology in Roof Support, NIOSH IC 9453, 2000,

pp. 111-132.

Mark, C. Empirical methods for coal pillar design. Paper in

Proceedings of the Second International Conference on Coal

Pillar Mechanics and Design, Vail, CO, NIOSH IC 9448, pp.

145-154. 

Mark C. Comparison of Ground Conditions and Ground Control

Practices in the USA and Australia. Proceedings, 17th

International Conference on Ground Control in Mining.

Morgantown, WV, 1998, pp.

Mark C. Comparison of Ground Conditions and Ground Control

Practices in the USA and South Africa. Proceedings, 18th

International Conference on Ground Control in Mining.

Morgantown, WV, 1999, pp. 63-71.

Mark C, and T. M. Barton. The Uniaxial Compressive Strength of

Coal: Should it be Used to Design Pillars? Proceedings, 15th

International Conference on Ground Control in Mining.

Golden, CO, August 13-15, 1996.

Mark C, and T. M. Barton. The Uniaxial Compressive Strength of

Coal: Should it be Used to Design Pillars? Proceedings, 15th

International Conference on Ground Control in Mining.

Golden, CO, August 13-15, 1996.

Mark, C., and F. Chase. Analysis of Retreat Mining Pillar

Stability. Paper in New Technology for Ground Control in

Retreat Mining, NIOSH IC 9446, 1997, pp. 17-34.

Mark, C., F. E. McCall, and D. M. Pappas. A Statistical Overview

of Retreat Mining of Coal Pillars in the United States. Paper in
New Technology for Ground Control in Retreat Mining,

NIOSH IC 9446, 1997a, pp. 2-16.

Mark, C., F. Chase, and R. K. Zipf, Jr. Preventing Massive Pillar

Collapses in Coal Mines. Paper in New Technology for

Ground Control in Retreat Mining, NIOSH IC 9446, 1997b,

pp. 35-48.

Mark, C., F. E. Chase, and G. M. Molinda. Design of Longwall

Gate Entry Systems Using Roof Classification. Paper in New

Technology for Longwall Ground Control: Proceedings of the

USBM Technology Transfer Seminar, USBM SP 94-01, 1994,

pp. 5-18.

Mark, C. and G. M. Molinda. Rating Coal Mine Roof Strength

from Exploratory Drill Core. Proceedings, 15th International

Conference on Ground Control in Mining. Golden, CO,

August 13-15, 1996, pp. 415-428. 

Molinda, G. M., C. Mark, and D. R. Dolinar. Assessing coal mine

roof stability through roof fall analysis. Proceedings: New

Technology for Coal Mine Roof Support, NIOSH IC 9453,

2000, pp. 53-72.

Molinda, G. and C. Mark. The Coal Mine Roof Rating (CMRR)--

A Practical Rock Mass Classification for Coal Mines. USBM

IC 9387, 1994, 83 pp.

Rusnak J., and Mark, C. Using the Point Load Test to Determine

the Uniaxial Compressive Strength of Coal Measure Rock. In

Peng SS, Mark C, eds. Proceedings of the 19th International

Conference on Ground Control in Mining, Morgantown, WV,

2000, pp. 362-371.

Salamon, M. D. G. 1989b. Some Applications of the Frictionless

Laminated Model. Paper in Proceedings of the 30th U.S.

Symposium of Rock Mechanics. A. A. Balkema, Rotterdam.

1989, pp. 891-898. 

Unal, E. Empirical approach to calculate rock loads in coal mine

roadways. Proc. 5th Intl. Conf. On Ground Control in Mining,

Morgantown, WV, 1986, pp. 232-246.

Zipf, R. K. Jr. Simulation of cascading pillar failure in room-andpillar mines using the boundary element method. Paper in

Proceedings of the 2nd North American Rock Mechanics

Symposium, Balkema, 1996, pp. 1887-1892.