BNUS ANNUAL REPORT-2014

BANGLADESH
NETWORK OFFICE FORURBAN SAFETY

BUET, DHAKA, BANGLADESH
Prepared By:

Mehedi Ahmed Ansary

1CONTENTS
PART-I: ASSESSMENT OF UNDERLYING CAUSES OF FIRE RISK IN
OLD DHAKA: A CASE STUDY OF ISLAMBAG AREA OF WARD NO.
65 OF DHAKA SOUTH CITY CORPORATION ····································· 1
PART-II: MEASUREMENT OF VIBRATION ON PLOON TEXTILEBUILDING DUE TO FREQUENT MOVEMENT OF RAILS······················· 19
PART-III: FOUR RECENT FIRE INCIDENCES IN AND AROUND DHAKACITY ·························································································· 39
PART-IV: DISASTER MANAGEMENT SYSTEM OF DHAKA IN
COMBATING MAN-MADE DISASTER IN THE LIGHT OF RECENTFIRES AND BUILDING COLLAPSES ················································· 45
PART-V: RESCUE OPERATION OF A 4-YEAR CHILD, JIHAD FROM AN
ABANDONED DEEP TUBEWELL ····················································· 61
PART-VI: GPR TESTING ON BALL MILL FOUNDATION ······················ 73
PART-VII: EARTHQUAKE RISK ASSESSMENT AND PLANNING FOR
MANAGEMENT IN MYMENSINGH MUNICIPALITY, BANGLADESH ······ 77
PART-VIII: EVALUATION OF LOAD CARRYING CAPACITY OF
PRECAST CONCRETE PILES BASED ON CPT ····································· 101
PART-IX: MEASUREMENT OF VIBRATION ON UHA
TRADE CENTER ··········································································· 127
PART-X: COMPARISON BETWEEN SMA AND MICROTREMOR
MEASUREMENT AT JAMUNA BRIDGE SITES ···································· 143
PART-XI: MEASUREMENT OF SHEAR-WAVE VELOCITY
AT DIFFERENT LOCATIONS OF DHAKA CITY USING SEISMICREFRACTION ·············································································· 171
PART-XII: MEASUREMENT OF ELECTRICAL RESISTIVITY AT
DIFFERENT LOCATIONS OF DHAKA CITY ······································· 191

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PART-I
ASSESSMENT OF UNDERLYING CAUSES OF FIRERISK IN OLD DHAKA: A CASE STUDY OF
ISLAMBAG AREA OF WARD NO. 65 OF DHAKA
SOUTH CITY CORPORATIONBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Uttama Barua
Mehedi Ahmed Ansary3March 2015

1. Introduction
Incident of fire is hazardous when it results in loss of human life and economy. In urban areas theeffect of fire hazard is much more in comparison to other areas because of the development pattern
and land use. In Dhaka, the capital city of Bangladesh, fire hazards cause huge life and economic loss
every year (BSFCD). The causes behind such large scale fire hazards in the city are: violation ofbuilding codes and non-compliance with the Firefighting and Extinguishing Law, dense building
concentrations, lack of safety measures, narrow roads, flammable building materials and electricalsystem as well as the lack of resources to raise awareness and response skills (BFSCD, 2003).
Particularly in Old Dhaka, incidents of fire hazards are more frequent than any other part of the city.
In this area, most of the buildings are of mixed use, where the ground floor and/or the first floor areused for small factories like chemical, plastic, rubber etc., mechanical shop, welding shops, warehouseand food shops, etc. Rests of the floors of the buildings are used for residential purpose mainly for theworkers of the factories and shops. Thus, fire hazard vulnerability of Old Dhaka is very high.
In case of fire incidents in Dhaka city, firefighting is a very important job, but fire prevention is morecrucial to prevent an actual fire accident from happening. In general, fire protection equipments andthe use of fire fighting tools are given more emphasis, neglecting the importance of practicing fire
preventive measures. The purpose of fire prevention plan is to eliminate the causes of fire and toprevent loss of life and property by fire (OSHCON, 2006), for which a clear understanding ofunderlying cause of fire are required to be identified to take initiatives thereby. Bangladesh, as adeveloping country, cannot afford the huge amount of loss caused by fire accidents every year in Dhaka
city, particularly in Old Dhaka. So, this study aims at assessment of the reasons of fire risk in Old
Dhaka to pave the way for the preparation of a fire prevention plan for Old Dhaka. In this study,
Islambag area of Ward No. 65 (Figure 1) of Old Dhaka was selected for the assessment. The causes
are that, fire incidents are very common phenomenon in this area and this area is one of most vulnerable
areas to fire hazard because of its traditional land use and population density. Thus in this study,
assessment of fire risk was done to find out potential underlying causes behind fire hazard in Islambag
area of Ward 65 of Old Dhaka.

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Figure 1: Study Area (Ward No. 65 of Dhaka city) (Source: Dhaka City Corporation)

2. Background of The Study
2.1 Reasons of Fire Hazard
The main reasons for any fire hazard are the sources of fire hazard and other factors accelerating theincident. So, for the assessment of the reasons of fire hazard, firstly it is required to understand its
sources. Fires require fuel, an adequate oxygen supply, and an ignition source, i.e., the Fire Triangle,
which when brought together, cause fires (Figure 2). Fire prevention can be accomplished bymaintaining control over one or more of these three required elements (UoC, 2005).

Figure 2: Fire triangle (Source: UoC, 2005)

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2.1.1. Ignition Sources or Sources of Heat:
An ignition source is something that can cause an accelerant or flammable material to ignite, e. g.
unsafe electrical conditions, machines and equipments, hot work, careless smoking etc (Margentino,& Malinowski, 1992). The ignition sources can pose a fire hazard if they are placed near the
combustible materials (EHSS, 2011).


Unsafe Electrical Conditions: The unsafe electrical conditions, e.g. damaged electricalconductors, overloaded sockets, extension cords, multiple plug adapters, faulty wirings,
defective switches and outlets, blown fuses, low quality electrical equipment, malfunction ofelectrical devices, loose electrical connections etc, can all lead to electrical fires (OSHCON,
2006; EHSS, 2011). Use of unapproved electric cords or equipment in wet or damp locations
may result in a short circuit (EHSS, 2011).



Machines and equipment: Machines that are not lubricated properly can overheat and start afire (EHSS, 2011).



Hot work: Any operation involving open flames can present a fire hazard, e.g. welding (EHSS,2011).



Careless Smoking: Discarded smoking materials carelessly tossed can easily start a fire.
(EHSS, 2011)

2.1.2. Sources of Fuel:
Anything that can burn is potential fuel for a fire or, in some cases, an explosion (Margentino, &Malinowski, 1992). Certain types of substances can ignite at relatively low temperatures or pose a riskof catastrophic explosion if ignited (OSHCON, 2006)


Combustible Materials: Ordinary combustible materials, like paper, cardboard, wood, andproducts made from these materials can present a fire hazard when they are allowed toaccumulate or are stored improperly (OSHCON, 2006; EHSS, 2011). Foam or plastic cups,
utensils, materials close to heat sources burn rapidly and give off dense, toxic, black smoke(EHSS, 2011). Oily rags or other materials soaked in oil can spontaneously combust if placedin areas where the air does not circulate (EHSS, 2011).



Flammable Materials: Some flammable liquids, such as xylene, toluene, benzene, andgasoline have a tendency to accumulate a static electric charge, which can release a spark that
ignites the liquid (OSHCON, 2006; EHSS, 2011). The unsafe use, storage, dispensing, ordisposal of flammable materials can be a prime source of fires and explosions (OSHCON,
2006; EHSS, 2011). Accumulation of vapors inside of storage areas of flammable liquids may
also cause fire (EHSS, 2011).
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ICUS Report 76Accelerants: Accelerants are substances that increase the speed at which a fire spreads, e.g.
gasoline, kerosene, oil, aerosol cans etc, which must be stored in approved containers andproperly labeled (Margentino, & Malinowski, 1992). All accelerants are highly flammable or
combustible, but not all highly flammable or combustible materials are accelerants(Margentino, & Malinowski, 1992).

2.1.3. Sources of Oxygen:
The main source of oxygen for a fire or explosion is in the general body of air. There are also othersources of oxygen, such as bottled oxygen, compressed air distribution systems and chemicals that
release oxygen when heated (oxidizing agents) such as hydrogen peroxide etc (HSE, 2012).
2.1.4. Other Factors
Beyond the main sources of fire, there are other factors which are not responsible for ignition of a fire,
but fire protection and ease of fire fighting to reduce loss depend on these factors.
2.1.4.1 Structural Condition:
Spreading of fire and success of fire rescue and firefighting operation largely depend on structural
condition. The structural conditions includes, i.e. building material, condition of wall and roof,
condition of exit door, condition of stair, etc.
2.1.4.2 Safety Measures:
Safety measures include, width of access road for the access of fire fighting vehicle, availability of firefighting system and water source etc. Lack of safety measures prevent fire fighting and rescue
operation resulting in increased life and property loss.
2.2 Applicability of Thermal Image in Identification of Fire Ignition Source
In this study, thermal image captured by thermal imaging camera has been used for identification ofignition sources of fire in the factories located in the study area. So it is required to understand its
applicability in the study for the designated purpose.

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2.2.1 The Thermal Imaging Camera and How It Works
A thermal imaging camera is a unique and non-contact tool utilizing infrared thermography which isthe art of transforming an infrared image into a radiometric one allowing temperature values to be readfrom the image. Infrared radiation lies between the visible and microwave portions of theelectromagnetic spectrum where heat or thermal radiation is its primary source. Thus the tool produces
thermal image indicating the exact location of energy losses through scanning and visualizing thetemperature distribution of entire surfaces quickly and accurately providing precise and convincing
argumentation (FLIR, 2011a & 2011b).
2.2.2 Use of Thermal Images in Identification of Fire Ignition Source
From the literature review it could have been understood that, the main ignition sources of fire areunsafe electrical condition and overheated mechanical installations. Thermal imaging cameras are
powerful and non invasive tools for monitoring and diagnosing these conditions, identifying problems
early, allowing them to be documented and corrected before becoming more serious and more costly
to repair (FLIR, 2011a).
2.2.2.1 Electrical Fault Detection through Thermal Image
Electrical devices are usually rated in power indicating the maximum amount of energy the device canconsume without being damaged (Taib, Jadin, & Kabir, 2012). If an electrical equipment is operated
above its specifications, this results in lower efficiency of the device, causing the energy to be spent ingenerating heat (FLIR, 2011b, Haidar, Asiegbu, Hawari, & Ibrahimm, 2012, and Taib, Jadin, & Kabir,2012). Faulty connections and wiring indicate a loose, over tightened or corroded connection withincreased resistance and faulty fuses indicate its saturated capacity, which thus become warm (FLIR,
2011b). If the faulty electrical equipments are left unchecked, heat can rise to the point whereconnections start to melt resulting in sparks to start a fire (FLIR, 2011a & 2011b).
The radiated heat from an electrical device can be measured on the infrared spectral band of theelectromagnetic spectrum using thermal imaging (FLIR, 2011b, Haidar, Asiegbu, Hawari, & Ibrahimm,2012). If the difference in temperature between similar components under similar loads exceeds 15 °C(~25 °F), it indicates requirement of immediate repairs (FLIR, 2011b).Thus, any of the electricalproblems can be avoided with the use of a thermal imaging camera, helping to detect anomalies thatwould normally be invisible to the naked eye and to solve problems before production goes down or afire occurs (FLIR, 2011b).

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Figure 3: Use of thermal image in detecting faulty electrical instruments(Source: FLIR, 2011a & 2011b)
2.2.2.2 Overheated Mechanical Installations
Mechanical systems heat up if there is a misalignment at some point in the system, or when mechanicalcomponents become worn and less efficient. Again, increased surface temperatures can be the resultof internal faults. Excessive heat can also be generated by friction in faulty bearings due to wear,
misalignment or inadequate lubrication. When these overheated machines come to contact withelectrical equipments or any combustible or flammable materials, this results in fire to ignite. Thermal
images help to inspect overheated mechanical installations in the factories. Interpretation of results
should be based on comparison between components operating in similar conditions under similarloads (Source: FLIR, 2011b).

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3. METHODOLOGY OF THE STUDY
The research has been conducted with the following methodology:
3.1 Study Design
In Old Dhaka fire incidents are very common, but for lack of knowledge about the reasons behind such
frequent fire incidents proper initiatives for the fire prevention cannot be taken for the area. Thereby,
objective of the study was defined to find out the causes of fire incidents in Old Dhaka. Thenmethodology of the study was defined based on literature review.

Islambag

Figure 4: Fire risk zone in Ward 65
3.2 Study Area Selection
The Islambag area of Ward No. 65 of Old Dhaka is selected as the study area. The total area of Ward
No. 65 is 118.1668 acres (0.478 Square Kilometer). Ward No. 65 is divided into three risk zones
including high risk zone, moderate risk zone and low risk zone according to their land use from expert
opinion (Figure 4). High risk zone is 52.84 acres (44.72%) where dominant land use are plastic
processing industries; moderate risk zone is 30.89 acres (26.14%) where dominant land use areprocessing factory and different warehouse (plastic warehouse, cattle food storage etc), and low riskzone is 27.95 acres (23.65%) where dominant land use are residential use with commercial facilities(retail shop, office, bank and storage) (calculated from GIS). Islambag area lies in the high risk area as
the livelihoods of the inhabitants of this area are primarily based on plastic processing industries like
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plastic manufacturing, recycling and processing factories. This area also displays a high building
density with multi-storey buildings and very few urban public spaces left. So, this area is selected as
the study area.
3.3 Preparation of Questionnaire
For achieving the objectives, depending on the literature review a questionnaire for the study has been
designed which has been modified on the basis of findings from pilot survey. The questionnaire isgiven in Appendix-A.
3.4 Sampling
In Islambag area twenty factories were selected as sample for the analysis through random selection.
3.5 Data Collection
3.5.1 Base Map Collection
A base map of the study area was collected from Dhaka City Corporation (DCC) office to become
familiar with the environment of the study area.
3.5.2 Primary Data Collection
Field survey of the buildings was conducted on the basis of the DCC base map. The survey was
conducted in the study area to find out the causes of fire incidents in the study area involving visualassessment and questionnaire survey.
3.6 Data Processing and Analysis
Information collected from the survey, have been inputted in MS Excel and then converted to SPSS
12 for processing and analysis.
3.7 Finding out Reasons behind Fire Hazard in the Study Area
The reasons behind fire hazard in the study area was assessed by identification and observation of thesources of fire hazard, i.e. ignition sources, sources of ignition, fuel and oxygen, assessment ofstructural condition, and identification and observation of availability of safety measures. Considering
these factors, the methodology for fire hazard assessment was developed, which involves bothquestionnaire survey and visual assessment. According to the reasons, the assessment process has been
divided into five segments:
Assessment of the Ignition Sources: Through visual assessment and questionnaire survey,
electrical conditions, condition of mechanical equipments, hot works and smoking condition
were assessed. To detect unsafe electrical and mechanical conditions thermal images were used,which detect faults through thermal radiation, i.e. temperature difference.



Assessment of the Fuel Sources: Through visual assessment and questionnaire survey,
condition and storage of combustible materials, flammable materials and accelerants wereassessed.
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Assessment of the Oxygen Sources: Through visual assessment and questionnaire survey,
condition of ventilation and air circular system were for the oxygen source.

Assessment of Structural Condition: Through visual assessment and questionnaire survey, thestructural conditions, i.e. building material, condition of wall and roof, condition of exit door,
condition of stair, etc were assessed.

Assessment of Safety Measures: Through visual assessment and questionnaire survey, safetymeasures, i.e. width of access road for the access of fire fighting vehicle, availability of firefighting system and water source etc were assessed.

3.8 Preparation of Final Report
All information and finding were gathered and presented by tables, graphs and maps to prepare thefinal report. Some recommendations based on the findings are provided to improve the overall
conditions of Old Dhaka in the report.
4. Reasons of Fire Hazard in the Study Area
Fire hazards are mainly initiated in the factories or small scale industrial buildings in the study area.
In this study, 20 number of buildings have been surveyed which are mainly factories or small scaleindustrial buildings. In the following section of the report, detailed findings from the survey have been
described.
4.1 General Condition of the Buildings in the Study Area
Number of storey of the surveyed buildings ranged from one to seven. Table 1 shows the frequency ofbuildings surveyed with respect to occupancy and number of storey. Most of the surveyed buildings
are plastic factory all of which are one storied. The buildings with greater than one floor are mainly of
mixed use.

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Table 1: Frequency of the building surveyed with respect to building occupancy and number offloorsNo. of floors

No. of floors
1 Floor

2 Floors

Greater than 2
floors

Total

Welding Shop

1

0

0

1

Plastic Factory

7

0

0

7

Plastic Storage

1

0

0

1

Machine Shop

1

0

0

1

Welding shop and plastic storage

0

1

0

1

Welding shop and residential use

0

1

1

2

Machine shop and residential use

0

0

2

2

Plastic storage and residential use

0

0

1

1

Plastic factory and residential

0

0

1

1

Plastic shoe factory

1

0

0

1

Machine shop and plastic storage

0

1

0

1

Plastic shoe factory and residential

0

0

1

1

11

3

6

20

Building
occupancy

Total

4.2 Ignition Sources or Sources of Heat in the Study Area:
Figure 5 shows ignition sources of fire in the surveyed buildings with respect to number of buildings
containing the source. The main ignition sources in the surveyed buildings are the unsafe electricalconditions. In the study area, the overhead electric supply pole and wires are arranged in muchdisorganized way, which may cause rapid spread of fire in the area. Almost all the surveyed buildingspose similar electrical unsafe conditions which include: improper wiring system, defective switches
and outlets, defective fuses, cable conduit on wall not clipped properly and low quality electricalequipments, among which use of low quality equipments, defective wiring system, and defective
cutouts and fuses are most common (Figure 5).
Among the surveyed buildings, plastic factories and machine shops contain machines and equipments.
Most of the machines are not lubricated properly causing overheat. Thus, nine buildings among twenty
have the problem of overheated machine (Figure 5). Moreover, for lack of proper maintenance, themachines and equipments used in the factories have layer of oil cover which accelerates the possibilityof ignition of fire. In these factories, the electric equipments and machines are observed in close
proximity, which increase the risk of fire hazard.
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Careless smoking
Hotwork

Unsafe electrical condition

Overheated machine
Low quality equipment
Defective cutout or fuse
Cable conduit on wall not clipped properly
Defective wiring system
Overloaded outlets
Defective switches and outlets
0

5

10
15
No. of buildings

20

25

Figure 5: Fire ignition sources in the study area
In the welding shops, the operations involve hot works which produce open flame. In all the surveyedbuildings, careless smoking is very common according to the workers. Other significant ignition sourcethat was observed in one of the plastic storage is the use of candle light at the time of load shedding.
Close proximity of the stored plastic materials and candle light may also cause a fire to initiate. Oneof these factors may contribute to ignition of fire in the buildings and the study area.
4.3 Sources of Fuel in the Study Area:
Figure 6 shows sources of fuel of fire in the surveyed buildings with respect to number of buildings
containing the source. Most common combustible materials used, produced and preserved in thesurveyed buildings are plastic products and materials soaked in oil (Figure 6). Others include oily rags
or other materials soaked in oil. In plastic and shoe factories, flammable materials are used for plastic
productions which are stored in an unsafe manner. In storages no flammable materials are required,
but the plastics itself are combustible which are stored in the storages in an unsafe manner. Other
accelerants used in the surveyed buildings include oil. In mechanical shops oil is used for proper
functioning of the machines. Again close proximity of ignition sources and fuel sources increase therisk of fire hazard in the area.

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18
16
No. of buildings

14
12
10
8
6
4
2
0
Plastic
products

Materials
soaked in oil

Raw materialsof polyethene
production

Utensils

Oily rags

Oil

Sources of fuelFigure 6: Sources of fuel of fire in the study area
4.4 Sources of Oxygen in the Study Area:
For assessment of sources of oxygen in the study area, the air circulation systems in the buildings wereassessed. In plastic factories and storages, smoke and heat vents are installed, whereas in machine shop
and welding shops there are no sufficient ventilation systems. Thus among twenty surveyed buildings
thirteen buildings have smoke and heat vents, among which seven have sufficient ventilation. In
storages of plastic materials, heat vents are mainly located in the walls which are mostly small in size,
very few in numbers and are placed in distant locations. In plastic factories, heat vents are mainly
located in the ceilings which are mostly large in size as the plastic production activity creates greater
heat and smoke. In all the cases, smoke and heat vents are kept open. Thus among thirteen buildings,
Thus, most of the buildings lack proper air circulation system, which may result in rapid spread of firein the area.
4.5 Structural Condition in the Study Area:
Spreading of fire and success of fire rescue and firefighting operation largely depend on structural
condition. The structural conditions includes, i.e. building material, condition of wall and roof,
condition of exit door, condition of stair, etc. Figure 7 shows components of building structures in thesurveyed buildings according to building material with respect to number of buildings. The structures
made of brick have heat resistance time of three hours and concrete have heat resistance time of threehours (Brick Industry Association, 2008 and Beall, 1994). Thus the buildings with components madeof brick are safe for fire hazard. The buildings of single storey are constructed with tin roof which are
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25

No. of buildings

20
15

Brick

10

Concrete
Wood

5

Tin

0
Exterior wall

Interior wall
Component of structure

Roof

Figure 7: Component of structure with respect to material in the surveyed buildings
The minimum safe dimension of exit doors is minimum two feet width and minimum seven feet height,
which is required for safe evacuation. In all of the factories, the exit doors are steel shutter, which arewide enough. Thus, sixteen out of twenty buildings have safe exits which are suitable for evacuation.
Figure 8 shows condition of stairs in the surveyed buildings with respect to number of buildings.
Among twenty surveyed buildings nine have stairs, among which seven buildings have concrete stair
and two have steel stairs. Steel stairs are highly vulnerable to fire hazard due to its heat capacity. Stairs
are the weakest part of a construction, whereas in the surveyed buildings the stairs are in deteriorated
condition. Among nine buildings with stair, four do not have landing ventilation, three have obstruction
in stairway and four have handrails. Thus, only two are suitable with respect to general condition ofstair and seven are suitable with respect to dimension. So, conditions of the stairs are required to be
improved. Thus, structurally the surveyed buildings are highly risky to fire hazard.
4.6 Availability of Safety Measures in the Study Area:
In most of the cases, width of access roads is on an average 15 ft. Thus, in case of any fire incident,
fire vehicles will be able to enter the area through the adjacent roads, though they will have to continue
the fire fighting operation on feet within the narrow access roads. Among twenty surveyed buildings,
only two have fire fighting operation system. Again only six buildings among twenty have water source
through underground and overhead tank due to their mixed use with residential use. Moreover,capacities of these water sources are not sufficient. According to Bangladesh National Building Code,buildings should have underground reservoir of 50000 liters and overhead reservoir of 25000 liters(BNBC, 2006). Thus, safety measures are not sufficient in the buildings.
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Figure 8: Condition of stair in the surveyed buildings
5. Prevention Strategy
Based on the findings of the study, fire prevention plan can be developed for the small scale industrial
buildings of Old Dhaka to avoid any fire or explosion risks by eliminating either the potential ignition
sources or potential fuel sources, or both (HSE, 2012). However, it is not possible to eliminate all thesources, so strategies can be developed to reduce fuel loads, eliminate ignition sources or prevent thefuel/ignition interaction by keeping potential ignition sources apart from potential fuel, then fire loss
and human death and injury can be reduced (HSE, 2012). Particular strategies to prevent fire hazard
in Old Dhaka are described below:


Faulty electrical issues should be taken care of. The relevant strategies should include:
correction and improvement of wiring system, replacement of damaged wiring, fuses, switches
and plugs, avoid use of extension cords and ensure proper covering of all outlets, junction
boxes and electrical panels.



Machines and equipments should not be used by overloading their capacities to prevent
overheating. Other measures should include: cleaning of all work areas of oil to prevent buildup
and all power equipments should be turned off or unplugged after use.



Hot works, i.e. welding or working with an open flame or other ignition sources, should bedone in controlled and well-ventilated areas.

Smoking should be strongly prohibited in the work place.

Combustible or flammable materials should be kept in safe distance from the potential ignition
sources and should be stored in safer places.

Well ventilation in workplace should be ensured.
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Regular inspection in the factories should be ensured to keep the work place free of dust. The
equipments should be kept in good working order, i.e., inspect electrical wiring and appliances
regularly and keep motors and machine tools free of dust and grease. Electrical equipments
should be turned off when not in use.



Minimum fire protection instruments should be stored in the factories. Based on the type ofsource of a fire hazard, different fire protection instruments should be used, as some fire may
be sensitive to certain types of fire extinguishers. Based on source of fire, fire incidents may
be classified into five classes, for which certain extinguishing media may be required, which isshown in table 2.
Table 2: Classification of fire with respect to source and required extinguishing media

Classof fireA

B

C

Materials causing thefire
Ordinary combustible
material: wood, paper,rags, rubbish, rubber
and plastic.
Flammable or
combustible gases andliquids: gasoline,
kerosene, thinners,
paints, grease andsimilar materials.
Electric equipments

D

Extinguishing media required
and their characteristics
Water and dry chemicals:
Douse flames quickly andprevent spreading of fire.

Extinguisher thatshould not be used

Carbon dioxide, dry
chemicals, foam andhalogenated hydrocarbons:
Limit supply of air.
Water spray: to cool thecontainers which are likely tocatch fire.
Carbon dioxide or dry
powders: Non-conducting
materials.

Water: Use of water
may spread the fire.

Metals: MagnesiumSpecial extinguishing agents.
sodium, titanium,
potassium, zirconium.
Source: Adopted from AmeriCares, n.d.

Water and foam: They
may cause shortcircuiting, electric
shock and damage tothe equipment.
Normal extinguishing
agents: Increase
intensity of fire.

6. Conclusion
After an in depth assessment of the buildings with commercial and industrial use in Old Dhaka, it canbe said that the buildings are vulnerable to fire hazard and the overall condition of buildings are notsuitable for fire fighting. Although this study was not conducted on a large number of building samples,
it represents the miserable condition of the buildings in Old Dhaka increasing the risk of fire hazards
in the area. It is not possible to eliminate all the sources of fire hazard in the area, but at least some
initiatives can be taken to minimize the loss. Thus, for improving the condition some fire prevention
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strategies have been suggested in this study. For further development in the area, all buildings should
follow the provision provided by Bangladesh National Building Code and Bangladesh Fire Service
and Civil Defense during construction. To prevent violation of regulation strict inspection and actions
are required from corresponding authority. The good practices of fire hazard prevention in the building
codes of other countries need to be studied and adopted according to Bangladesh’s context. In addition,
to create public awareness, workshops and seminars may be arranged. Electronic and printing media
can play an important role for increasing awareness. A pragmatic fire safety plan may be developed
for all the buildings with the help of Bangladesh Fire Service department.
References
Bangladesh Fire Service and Civil Defense (BFSCD). (2003). Fire Fighting & Extinguishing Law.
Bangladesh National Building Code (BNBC). (2006). Published by HBRI-BIDS.
AmeriCares. (n.d.).Fire Prevention and Fire Safety: Health Worker Safety Training Module 5.
Retrieved October 11, 2014, from:http://www.americares.org/assets/downloads/pdf/modules/hws/HWS-5-fire-safety.pdf
OSHCON. (2006). Sample Written Program for Fire Prevention Plan. Occupational Safety and
Health Consultation Program (OSHCON), Texas Department of Insurance, Division of Workers’
Compensation, Publication No. HS03-013A (1-06). Retrieved October 11, 2014, from:http://www.tdi.texas.gov/pubs/videoresource/ofirepreventio.doc
EHSS. (2011). Fire Prevention Planning. Environmental, Health and Safety Services (EHSS),
Virginia Polytechnic Institute and State University. Retrieved October 11, 2014, from:http://www.ehss.vt.edu/uploaded_docs/200802261709470.Fire%20Prevention%20Planning.ppt
UoC. (2005). Basic Fire Prevention Measures. Environmental Health and Safety, Division ofAgriculture and Natural Resources, University of California, Safety Note #72. Retrieved October
11, 2014, from:http://safety.ucanr.org/files/1468.pdf
Margentino, M. R., & Malinowski, K. (1992). Fire prevention and safety measures around the Farm.
Rutgers Cooperative Extension, University of New Jersey: document FS608. Retrieved October
11, 2014, from:http://nasdonline.org/static_content/documents/1048/d000843.pdf
HSE. (2012). Guidance on the prevention and control of fire and explosion at mines used for storageand other purposes. Great Britain: Health and Safety Executive (HSE). Retrieved October 11,
2014, from:http://www.hse.gov.uk/mining/festorage.pdf
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March 2015

Beall, C. (1994). Calculating Masonry's Fire Resistance. Mag. Masonry Constr., 7(8), 372-391.
Retrieved 24 November, 2014 from:http://www.masonryconstruction.com/Images/Calculating%20Masonry%27s%20Fire%20Resista
nce_tcm68-1375295.pdf
Brick Industry Association. (2008). Technical Note 16: Fire Resistance of Brick Masonry. Brick
Industry Association, Reston, Virginia. Retrieved 24 November, 2014 from:http://www.gobrick.com/portals/25/docs/technical%20notes/tn16.pdf
FLIR. (2011a). Thermal Imaging Guidebook for Building and Renewable Energy Applications.
FLIR Systems AB.
FLIR. (2011b). Thermal Imaging Guidebook for Industrial Applications. FLIR Systems AB.
Haidar, A., Asiegbu, G. O., Hawari, K., & Ibrahim, F. A. (2012). Electrical defect detection inthermal image. Advanced Materials Research, 433, 3366-3370. Retrieved 24 November, 2014
from:http://ro.uow.edu.au/infopapers/2315/
Taib, S., Jadin, M., S., & Kabir, S. (2012). Thermal Imaging for Enhancing Inspection Reliability:
Detection and Characterization. In Prakash R., V. (Ed.). Infrared Thermography. InTech, ISBN:
978-953-51-0242-7. Retrieved 24 November, 2014 from:http://www.intechopen.com/books/infrared-thermography/thermal-imaging-forenhancinginspection-reliability-detection-and-characterization

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BNUS Annual Report-2014

PART-II
MEASUREMENT OF VIBRATION ON PLOONTEXTILE BUILDING DUE TO FREQUENTMOVEMENT OF RAILSBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Mehedi Ahmed Ansary21March 2015

1.

INTRODUCTIONManaging Director of Ploon Textiles Limited requested us for measurement of vibration on theirfactory building due to frequent train movement. This report presents the findings of the vibration test
carried out at the site on April 18, 2014. Figure 1 shows the location of the surveyed building withsensor locations and Figure 2 show measurement of building vibration using Microtremor observation
system.

Figure 1: Location of Surveyed Building with Sensor Locations

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Figure 2 Measurement of building vibration using Microtremor observation system
2.

ACCEPTABLE VIBRATION LEVELS

Humans are very sensitive vertical vibration sensors, especially in environments like quiet buildings.
An example of human comfort limit is the restriction on the acceleration - human begins to feel
uncomfortable when the acceleration reaches about 0.02g:

Corresponding velocity at 16 Hz frequency is 1.96 mm/s.
According to [1], the allowable level of vibration acceleration at 16 Hz frequency is 28.0 mm/s2, while
the allowable level of vibration velocity at the same frequency is 0.28 mm/s. The allowable levels ofvibration for public buildings according to [1] are shown in Table 1.
Table 1: Allowable levels of vibration for public buildings

Figure 3 shows general limits of displacement amplitude for human beings, machine foundations, andbuildings according to Winterkorn and Fang [2].
2321March 2015

Figure 3 General limits of displacement amplitude for a particular frequency of vibration

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3.

MEASUREMENT OF VIBRATIONThe BUET team conducted vibration test for the Pantaloon Textile building with and without rail
movement. The measurement is conducted simultaneously at the ground near the rail line (sensor 4),
at the building’s ground floor (sensor 1), first floor (sensors 2 and 3) and at the top floor (sensor 5) of
the building. In this report, the vibration data for the building which is located around 75 ft from therail line is presented.
Location: 1X
Measurement Mode
Ambient noiseTime History

Maximum
Velocity (µm/s)
19.2

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

34.0

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
15 compartment train

0

10

20

Time (s)

30

40

45

41.4
60

Velocity (m/s)

40
20
0
-20
-40
-60

0

10

20

Time (s)

30

40

45

25
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March 2015

Location: 1Y
Measurement Mode
Ambient noiseTime History

Maximum
Velocity (µm/s)
19.2

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
8 compartment train

0

5

10

15

20

25

Time
p (s)

30

35

40

45

53.4

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
15 compartment train

0

5

10

15

20

25

Time(s)
p

30

35

40

45

49.3

60

Velocity (m/s)

40
20
0
-20
-40
-60

24

0

5

10

15

20

25

Time (S)

30

35

40

45

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Location: 1Z
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
22.7

500
400

Velocity (m/s)

300
200
100
0
-100
-200
-300
-400
-500

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

409.4

500
400

Velocity (m/s)

300
200
100
0
-100
-200
-300
-400
-500

With noise
15 compartment train

0

10

20

Time (s)

30

40

45

354.4

500
400

Velocity (m/s)

300
200
100
0
-100
-200
-300
-400
-500

0

10

20

Time (s)

30

40

45

27
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Location: 2X
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
37.6

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

61.3

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
15 compartment train

0

10

20

Time(s)

30

40

45

62.9

60

Velocity (m/s)

40
20
0
-20
-40
-60

26

0

10

20

Time (s)

30

40

45

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Location: 2Y
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
53.0

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
8 compartment train

0

10

20

Time (s)

30

40

45
5

60

f2

51.7

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
15 compartment train

0

10

20

Time (s)

30

40

45

55.4

60

Velocity (m/s)

40
20
0
-20
-40
-60

0

10

20

Time (s)

30

40

45
f

29
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March 2015

Location: 2Z
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
20.3

500
400

Velocity (m/s)

300
200
100
0
-100
-200
-300
-400
-500

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

374.6

500
400

Velocity (m/s)

300
200
100
0
-100
-200
-300
-400
-500

10

20

Time (s)

30

40

45

382.7

400
300

Velocity (m/s)

With noise
15 compartment train

0

500

200
100
0
-100
-200
-300
-400
-500

28

0

10

20

Time(S)

30

40

45

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Location: 3X
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
25.9

2000

Velocity(m/s)

1500
1000
500
0
-500
-1000
-1500
-2000

With noise
8 compartment train

0

10

20

Time(s)

30

40

45

1159.2

2000
1500

Velocity (m/s)

1000
500
0
-500
-1000
-1500
-2000

With noise
15 compartment train

0

10

20

Time(s)

30

40

45

1871.32000
1500

Velocity(m/s)

1000
500
0
-500
-1000
-1500
-2000

0

10

20

Time(S)

30

40

45

31
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March 2015

Location: 3Y
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
12.0

2000

Velocity (m/s)

1500
1000
500
0
-500
-1000
-1500
-2000

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

1207.72000
1500

Velocity (m/s)

1000
500
0
-500
-1000
-1500
-2000

With noise
15 compartment train

0

10

20

Time (s)

30

40

45

1980.62000
1500

Velocity (m/s)

1000
500
0
-500
-1000
-1500
-2000

30

0

10

20

Time (s)

30

40

45

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Location: 3Z
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
30.8

1500

Velocity (m/s)

1000
500
0
-500
-1000
-1500

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

937.1

1500

Velocity (m/s)

1000
500
0
-500
-1000
-1500

With noise
15 compartment train

0

10

20

Time (s)

30

40

45

1437.31500

Velocity (m/s)

1000
500
0
-500
-1000
-1500

0

10

20

Time (s)

30

40

33
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March 2015

Location: 4X
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
47.7

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

64.8

60

Velocity (m/s)

40
20
0
-20
-40
-60

With noise
15 compartment train

0

10

20

Time
p (s)

30

40

45

62.5

60

Velocity (m/s)

40
20
0
-20
-40
-60

32

0

10

20

Time (s)

30

40

45

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BNUS Annual Report-2014

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Location: 4Y
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
47.8

80

Velocity (m/s)

60
40
20
0
-20
-40
-60
-80

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

61.3

80
60

Velocity (m/s)

40
20
0
-20
-40
-60
-80

With noise
15 compartment train

0

10

20

Time (s)

30

40

45

66.0

80
60

Velocity(m/s)

40
20
0
-20
-40
-60
-80

0

10

20

Time(S)

30

40

45

35
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March 2015

Location: 4Z
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
33.3

600

Velocity (m/s)

400
200
0
-200
-400
-600

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

427.7

600

Velocity (m/s)

400
200
0
-200
-400
-600

10

20

Time (s)

30

40

45

502.0

600
400

Velocity (m/s)

With noise
15 compartment train

0

200
0
-200
-400
-600

34

0

10

20

Time (s)

30

40

45

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BNUS Annual Report-2014

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Location: 5X
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
18.0

600

Velocity (m/s)

400
200
0
-200
-400
-600

With noise
8 compartment train

0

10

20

Time (s)

30

40

45

20.5

600

Velocity (m/s)

400
200
0
-200
-400
-600

With noise
15 compartment train

0

10

20

Time(s)

30

40

45

502

600

Velocity (m/s)

400
200
0
-200
-400
-600

0

10

20

Time( s)

30

40

37
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March 2015

Location: 5Y
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
18.9

without noise
400

Velocity (m/s)

200

0

-200

-400

0

10

20

Time(s)30

40

45
14.grf1

With noise
8 compartment train

With Noise

8 compartments

303.3

400

Velocity (m/s)

200

0

-200

-400

0

10

20

Time (s)3040ch-14.grf

With noise
15 compartment train

With Noise

15 Compartments

318.0

400

Velocity (m/s)

200

0

-200

-400

0

10

20

Time(S)

30

40
14.grf

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Location: 5Z
Measurement Mode
Ambient noiseTime History

Maximum Velocity(µm/s)
20.1

400

Velocity (m/s)

200

0

-200

-400

With noise
8 compartment train

0

10

20

Time(s)
p

30

40

45

192.7

Velocity (m/s)

400

200

0

-200

-400

With noise
15 compartment train

0

10

20

Time(s)

30

40

45

339.5

400

Velocity (m/s)

200

0

-200

-400

0

10

20

Time (s)

30

40

39
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March 2015

4. 4. REMARKSREMARKSMeasured
Measuredvaluevalueof buildingof building
velocity
velocity(mm/s)(mm/s) Allowable
Comment
AllowablelevelslevelsVelocity
Velocity
at which
at whichCommentof vibration
for for vibration
vibration
is is
NS NSEW EWUD UD Maximum
Maximum
Corresponding
Correspondingof vibration
publicbuildings
buildings dangerous
dangerous
to tofrequency
frequency(Hz) (Hz)public
fromfrom
TableTable
1 1 buildings
buildings(mm/s),(mm/s),
fromfrom
FigureFigure3 3Ambient
Ambient
noisenoise
0.05 0.05
0.05 0.050.03 0.03 0.05 0.05
3.0 3.0
0.65 0.65
No No
problemto toproblembuildings
buildings
WithWithnoise:noise:
8 81.16 1.16
1.21 1.210.94 0.94 1.21 1.21
3-15 3-15
0.28-0.65
0.28-0.65
75 75
May Maycausecause
problemcompartmentcompartment
problemto tobuildings
train train
buildings
WithWithnoise:15
noise:15
1.87 1.87
1.98 1.980.38 0.38 1.98 1.98
6-15 6-15
0.28-0.35
0.28-0.35
75 75
May Maycausecause
problemcompartmentcompartment
problemto tobuildings
train train
buildings
Condition
Condition

References
References
1. Federal
1. Federal
Sanitary
SanitaryNorm
Normof Russianof RussianFederation
Federation(1996).
(1996).
“SN2.2.4/2.1.8.566-96“SN2.2.4/2.1.8.566-96
– The
– The
sanitary
sanitary
norms
norms
of industrialof industrial
vibration,
vibration,
vibration
vibrationof residentialof residential
and andpublicpublicbuildings,
buildings,
1996”.
1996”.
2. Winterkorn,
2. Winterkorn,
H. F.
H. andF. and
Fang,
Fang,
H. Y.
H. (1975).
Y. (1975).
Foundation
Foundation
Engineering
Engineering
Handbook
Handbook
publisher:
publisher:
VanVan
Nostrand
NostrandReinhold.
Reinhold.

38

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BNUS Annual Report-2014

PART-III
FOUR RECENT FIRE INCIDENCES IN AND
AROUND DHAKA CITYBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Uttama Barua
Mehedi Ahmed Ansary41March 2015
1. Blaze at a Chemical Shop in a Residential Building

A fire spread out at the hardware store named Mahfuz Sewing and Electric, a shop that sells
accessories for garment factories in East Tejturi Bazar near Farmgate beside Tejgaon Women’sCollege on April 10, 2014.
The fire, started at 2:45 PM at the ground floor of a 4 storied residential building seemed to becaused by exploding of a paint thinner drum. Flame spread in the whole shop and burnt thestore owner and employees. The fire spread to the front of the store. Most of the victims werepedestrians and at least six of the injured are fighting for life with over 30 percent of theirbodies burnt. Two university students and a minor boy are among the injured. Out of 11 victims
4 victims died of their injuries after being taken to Dhaka Medical College. On information,
three fire fighting units rushed to the spot and doused the flame around 3:30pm.

Figure 1: Position of Shop

Figure 2: After doused fire

Figure 3: Victims at Hospital

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2. Plastic Factory FireAt the night of April 11, 2014 a fire attacks in a three-storey plastic factory building. The
factory is situated at Rahmatganj in Old Dhaka's Lalbagh area.
The fire originated at the plastic factory housed in a three-storey tin-shed building near
Rahmatganj Playground. Seven units of fire-fighters rushed to the spot and were trying to douse
the blaze. As the factory was located at a congested area, that made it difficult for the firefighters to reach the spot and douse it. The fire that began around 8:00pm on the ground floorof factory building brought under control around 9:20pm. Several adjoining houses were also
damaged in the fire.

Figure 4: Fire Blaze

Figure 5: Fire fighters put out flames in theplastic factory at Lalbagh in Dhaka

3. OTOBI Furniture Factory FireA huge fire broke out at the OTOBI furniture factory at Birulia Union’s Khagan area in Savaron the outskirts of the capital city Dhaka on 22nd April night. The fire broke out around 9:45pm
and was brought under control around 3am. Ten units of Fire Service from Savar, Ashulia,
Tongi, EPZ, Dhamrai and Dhaka Central stations rushed to the spot and brought the fire undercontrol after five hours of frantic efforts.
At least thirty workers were injured when they were getting out of the factory while therearound 400 workers was on duty in evening shift. No death was reported. The fire had guttedthe entire factory, which was set up over 10 acres of land with corrugated tin roof over walls.
It is assumed that an electrical short-circuit caused the fire. The fire spread quickly because of
the stored furnitures and chemicals inside. Chemical-filled drums exploded frequently with

43

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March 2015

loud noise. The fire-fighting capacity inside the factory was inadequate and the fire service
faced difficulty as it had to haul in water from outside.

Figure 6: Position of factory in Google Earth

Figure 7: Burning tin shades

4. Fire hazard at a blanket factory in Bakshibazar area

A devastating fire broke out at around 4:20 pm at a one storey tin-shed blanket factory ‘Kajal
Woolen Mills Limited’, located beside the gate number-3 of Dhaka Central Jail at Bakshibazarin the capital on Friday, 7th November 2014, gutting the entire factory including themachineries. More than 150 workers were busy making blankets when the fire broke out. They
were working to deliver an order of 2,214,000 blankets to the Disaster Management and Relief
Ministry and 20,000 blankets for the jail authorities ahead of winter. In addition there weremany blankets and raw materials stocked in the warehouse.
Soon after the fire incident, security in and around the central jail was beefed up. Around threeplatoons of police have been deployed around the jail to thwart any unpleasant incident. On
information, eight firefighter units from fire service headquarters, Lalbagh and Polashi stations
rushed to the spot and worked hard to douse the blaze. The fire was brought under control at
about 6:00pm, but complete dousing of fire took two or three more hours.
However, none was injured in the incident and the fire did not affect the Dhaka Central Jail,because the main boundary wall was high enough to prevent fire entering the compound. The
goods worth around 22 crore BDT has been burnt in the incident. More than two lakh and 21
thousand pieces of blankets were in the store in the factory.

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The fire might have originated from an explosion of an electric bulb in the one-storied woolen
mill. According to Md Maznu Mia, who was working in the cutting section of the factory,
sparks from a machine lit the blankets on fire. The flames spread quickly due to the woolenmaterials.

Figure 8: Fire blaze

Figure 9: Fire fighting operation by local people

Figure 10: Fire fighting operation by fire fighting team45

43

PART-IV
DISASTER MANAGEMENT SYSTEM OFDHAKA IN COMBATING MAN-MADE
DISASTER
IN THE LIGHT OF RECENT FIRES AND
BUILDING COLLAPSESBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Uttama Barua

46

March 2015

1. Background of the Study
Disasters occur when hazards meet vulnerability. Man-made disasters stem from man-madehazards, which cause due to human intent, negligence, or error; or involving a failure of a manmade system. In urban areas the effect of manmade hazards, especially fire hazard and building
collapse, is much more in comparison to other areas because of the development pattern andland use. The development trend of Dhaka, the capital city of Bangladesh took place in ahaphazard and unplanned manner with little or no attention to the issue of land use andstructural planning. High-rise buildings are now being constructed in different parts of the cityand most of them are without the provision of adequate safety. Thus, in the city, manmadehazards cause huge life and economic loss every year. The causes behind such hazards in thecity are: violation of building codes and non-compliance with the legislations, dense building
concentrations, incompatible landuse, narrow roads, flammable building materials andstructural weakness of buildings, electrical system, lack of safety measures, institutional
inefficiency, insufficient equipment support and lack of public awareness as well as the lack ofresources to raise awareness and response skills. This study aims to explain the weakness ofpresent disaster management system of Dhaka in combating man-made disaster in the light ofrecent fires in high rise buildings and collapse of buildings.
2. Recent Significant Fire Incidents in Dhaka
2.1 BSEC fire, 26 February and 24 December, 2007, and 31 October, 2014
A devastating fire broke out in the 11-storey building Bangladesh Steel and Engineering
Corporation (BSEC) Bhaban at Karwan Bazaar in the capital at about 10.15 am on 26 February
2007. The building houses private satellite television channels NTV and RTV, and Bangla
daily Amar Desh. Within minutes the fire engulfed the entire floor and gradually started tospread to the upper floors, trapping hundreds of people inside. It originated from a storehouseon the top floor as a result of electric short circuit. In BSEC building there were fire
extinguishers, but people had no knowledge about how to use them. For not having fire lift oralternate stair, people rushed to the central stair case resulting in more disastrous situation. The
first batch of fire-fighters came in BSEC from the Tejgaon fire station after half an hour ofignition. Twenty-five fire-fighting units from different fire stations arrived at the spot andworked frantically for more than six hours to bring the fire under control. Acute shortage ofwater and inadequate equipment hampered the rescue operation. The firemen had to bring inwater from the nearby WASA Bhaban and the Sonargaon Hotel. Massive rescue efforts,
including the first-ever airborne operation, were carried out when over 1,000 people were
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evacuated from the building. Three persons were killed and more than 100 injured in thisincidence. Ntv, Rtv and Amar Desh offices totally burnt and went off air.
On December 24 of the same year, another fire broke out in a room on the ground floor of thebuilding. Even after the fire incidents on 2007 in BSED, no preventative or mitigation measures
were taken in the building, causing fire for the third time in 2014 for the same reason, i.e.
electric short circuit at storeroom of papers. The building caught fire for the third time at about
11:48 am on 31 October, 2014, which originated from a storehouse on the top floor. Twenty
one fire-fighting units doused the flames after over two hours of frantic efforts, which included
100 fire fighters along with volunteers. The firemen had to bring in additional water-carrier
trucks, for shortage of water in the spot. They used two long ladders to reach for the top floorsof the building. Ambulances were stationed nearby along with additional water-carrier trucks.
No casualties have been reported from the fire.
2.2 Bashundhara City Complex fire, 13 March, 2009
On 13th March 2009, Friday at around 1:45 pm, a hell fire engulfed the upper levels of 20
storey office cum shopping centre known as Bashundhara City Complex at Panthopath, Dhaka.
The fire originated from the 17th floor, due to electric short circuit. Though Bashundhara City
Complex had fire fighters, they had little training. Again, the building was equipped with
sufficient fire detecting, suppressing, and evacuating systems but they were inactive during thefire. The fire alarm was defective which used to give false alarm, so the fighters of the building
didn't care about those warnings. Thus, the fire fighters of the complex could do nothing. At
Bashundhara City only one stairs leading to basement parking which act as fire exit, but thisremains locked all the time and the escape route is occupied by trash, resulting in chaotic
situation (Tabassum, Ahmed, & Romeo, 2014).
All fire fighting units of the capital and from its surroundings along with military, police and
RAB personnel, took about six hours to tame the massive blaze that raged through the Tower.
The hydrants were useless on the event as there was no water in the tank of the complex.
Initially water was pumped from nearby Unique Trade Centre. The fire brigade brought a fireengine, but did not have enough hoses or water sources to tame the fire. Fire fighters claimed
that the blaze was brought under control at about 7:00pm. Black plumes of smoke from thehigh rise spiraled upward, while blazing windowpanes, furniture, and other objects rained downon the pavement causing another fire in adjacent one storey furniture shop. The incident killed
7 and injured 20 people. The top six floors were totally gutted.
2.3 Nimtoli fire, 3 June, 2010

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In 3rd June 2010, a devastating fire broke out in the densely-populated part of Old Dhaka called
Nimtoli, which gutted eight buildings and over twenty shops. Initially it was thought that
explosion of two transformers at Nimtoli started the fire but later it has been known the fire
originated from an oil stove in five storey mixed use building with chemical warehouse. The
fire spread very quickly because the chemicals exploded and flew all over. Fire killed at least
117 people and caused injury to a hundred people. Most of the affected peoples were womenand children.
3. Recent Significant Incidences of Building Collapse in Dhaka
3.1 Phoenix, 25 February, 2006
On 25 February 2006, a five storied building undergoing remodeling construction for floors
space-use collapsed without warning at the Tejgaon industrial area of Dhaka city. Initially thebuilding was used as warehouse for factory machines and equipments of Phoenix Fabrics ayear ago. It was being converted into a 500 bed specialized hospital in joint collaboration with
Mount Elizabeth Hospital, Singapore. There were also showrooms of Phoenix Fabrics andPhoenix Electronics on the ground and first floors and a number of tin‐shed rooms on therooftop. Experts blamed faulty and unplanned construction, and increased concentrated verticalload for the collapse. Soldiers, police, fire officials and hundreds of volunteers rushed to thescene to pull out victims trapped under the caved-in Phoenix Building in the city’s congested
industrial area. Cleaning of the concrete debris and rescue operation took a few days for lackof proper logistics. As consequence of the incident, 20 people died and 40 were injured.
3.2 Begunbari, 1 June, 2006
A five‐storey building toppled onto three tin‐shed houses at Begunbari area in the Tejgaon areaof the city at 11 pm on 1 June. From the way the five-storied structure fell down, it appears
there was no proper plan for the building, nor was any rule or code followed during its
construction. The building was built on land filled with garbage instead of soil. Some heavy
construction materials were stored in the top floor of the building. Moreover the foundation
was not design properly. And it is also patently clear that the workmanship and engineering aswell as the materials that went into the making of that house were also of very poor quality.
FSCD, Police, AFD, BDRCS, Ansar, community volunteers all were involved in the searchand rescue operations, but still the collapsed building could not be removed. Narrow Accessroute made the response work difficult. This incident resulted death to 23 people.
3.3 Rana Plaza, 24 April, 2013

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ICUS Report 76“Rana Plaza” is located at Dhaka-Aricha highway near Savar bus stand, collapsed on 24 April,2013 at around 9:30 am. The building housed five garment factories (New Wave Button, New
Wave Styles, Ethar Tex, Phantom Apparels and Phantom Tex) employing around 5,000 people,
300+ shops, and a bank. Rana Plaza was a 9-storied industrial building with a single basement.
Instead of Rajuk, local municipality (Savar) gave the owner permission to construct a five
storey commercial building with one basement in 2005 and later allowed the owner to extend
it up to nine storey, without considering the structural design, though the foundation of thebuilding was of 5 storey (Odhikar, 2013; Osman, Khan, Hossain, & Khan, 2013; Rahman, &Ansary, 2013). Moreover, the building was converted from commercial to industrial use andPower Generators were placed at the higher floors (Rahman, & Ansary, 2013).
A day prior to the fateful day, on 23 April 2013, cracks developed on some pillars and a few
floors of the building following a jolt. After inspection of industrial police, they requested thebuilding authorities to close the building and to suspend operations of the factories. However,the building owner and top-management of the garment factories ignored the warning andforced the workers to work in the morning of 24th April. An official statement of the
Bangladesh Garment Manufacturers and Exporters Association cited 3,122 workers to be in
the building at the time of the collapse. This resulted in the high death toll of 1,127 at the endof the rescue operation on 14 May 2013, one of the world’s deadliest industrial disasters(Osman, Khan, Hossain, & Khan, 2013). Right after the collapse, members of the Bangladesh
Army, Fire Service and Civil Defence, Police, BGB, pedestrians and also members of various
social welfare organizations had begun rescue operations. Armed Forces Division (AFD) of
Bangladesh coordinated the search and rescue operation. Thus around 2438 could be rescued,
however badly injured (Odhikar, 2013).
4. Recent Acts and Policies Regarding Urban Development in Bangladesh
4.1 Building Construction Act 1952
The Act provided regulations regarding setbacks, building heights etc. in urban areas andprovided prevention of haphazard construction of buildings.
4.2 The Town Improvement Act (TI), 1953
It is the first statute which recognized the need for planning approach and created a special
agency for development such as preparation of master plans, improvement schemes, and theirimplementations.
4.3 Building Construction Rules, 2008

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These rules seek to control development plot‐by‐plot and case‐by‐case by imposing conditions
on setbacks, site coverage, Floor Area Ratio (FAR), construction of garages, access to plot,
provision of lift, land use of that particular plot and height of building. It helps to control thedensity of an area and manage the growth providing rules of building coverage area, allowablefloor space and relation among building height ‐ road width and plot size. The Rule provided

more authority to RAJUK for responsibility to monitor the development of the city, spread out
the responsibilities to various actors, and spell out responsibilities of building designers,
structural engineers, site supervisors and their penalties etc.
4.4 Bangladesh National Building Code (BNBC), 2014
The purpose of the Code is to establish minimum standards for design, construction, quality ofmaterials, use and occupancy, location and maintenance of buildings within Bangladesh inorder to safeguard, within achievable limits, life, limb, health, property and public welfare.
4.5 Land Development Rules for Private Housing, 2004
This is a legal instrument for controlling land development in private sector housing. It provides

procedures and guidelines for land development protecting the environment, spelling out landfor community facilities, amount of land to be sold out, school sites, road hierarchy andimportantly planning standards.
5. Recent Acts and Policies Regarding Disaster in Bangladesh
5.1 Disaster Management Act, 2012
The Act is enacted to create the legislative tool and legal basis for disaster risk and emergency
management, along with mandatory obligations and responsibilities on Ministries, committees
and appointments. The main aims of the Act include development of mitigation, response andrecovery strategies, and establishment of institutional framework for disaster management. The
Act addressed manmade disasters in some activities.
5.2 Disaster Management Bureau Strategic Plan, 2005-2006
The purpose of the Plan is to provide a statement of key strategies for the provision of Disaster
Management Policy and Plan. It provided seven strategic goals for the purpose.
5.3 National Disaster Management Policy, 2008
The Policy is formulated to define the national perspective on disaster risk reduction andemergency management, and to describe the strategic framework and national principles ofdisaster management in Bangladesh. The policy proposed some actions based on sevenstrategic goals.
5.4 National Plan for Disaster Management, 2010-2015
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The Plan which aims to give direction, vision and goal for the disaster management initiatives
along with implementation including all stakeholders and considering all hazards under sevenstrategic goals. It provides the overall guideline for the relevant sectors and the disastermanagement committees at all levels to prepare and implement their area specific plans. It
addresses fire and infrastructure collapse as hazard for Bangladesh.
5.5 Standing Orders on Disaster, 2006
The SOD has been prepared to make the concerned persons understand their duties andresponsibilities regarding disaster management at all levels, and accomplishing them,describing the detailed roles and responsibilities of committees, Ministries and otherorganizations in disaster risk reduction and emergency management, and establishes thenecessary actions required in implementing Bangladesh’s Disaster Management Model. All
Ministries, Divisions/Departments and Agencies shall prepare their own Action Plans in
respect of their responsibilities under the Standing Orders for efficient implementation. The
National Disaster Management Council (NDMC) and Inter-Ministerial Disaster Management
Coordination Committee (IMDMCC) will ensure coordination of disaster related activities at
the National level. Coordination at District, Thana and Union levels will be done by therespective District, Thana and Union Disaster Management Committees. The Disaster
Management Bureau will render all assistance to them by facilitating the process.
5.6 Fire Prevention and Extinction Act, 2003 and Rules, 2014
The Act and Rules include provision for preparedness and responsibilities of fire brigade,license, clearance and occupancy, and general arrangement for fire fighting with respect tooccupancy.
6. Bangladesh Fire service and Civil Defence
BFSCDA is the legitimate authority responsible for managing fire along with other disasters in
Bangladesh. The present Fire Service and Civil Defense has been established in 1980 with
amalgamation of the then Fire Service Directorate, Civil Defense Directorate and The Rescue
Department of Roads and Highway. At present the department is running under the Ministryof Home Affairs. In Dhaka city there are total 79 fire stations, and a training complex, which
is located in Mirpur-10, where mock drills and training programs are organized by cocoordinating, the officers, trained volunteers, government and NGOs, to response properly aftera disaster. Table 1 shows class wise number of fire stations in Dhaka city, table 2 shows classwise manpower of the fire stations, and table 3 shows equipments available in the fire stations
according to class. Other fire fighting equipments include: special water truck (with capacity
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8000/ 11000 liters), foam tender, chemical tender, cold cut, foam making generator, water mist,
and ground monitor. Equipments for rescue includes: emergency tender, smoke ejector, lifting
air bag, hydraulic cutter, hydraulic speeder, breathing apparatus, air line breathing apparatus,
chopping hammer, door opener, pipe squeezer, chains, and reciprocating. These numbers arevery insignificant with respect to the population of Dhaka city. Thus, the institution ischaracterized by weak equipment, poor technology, and inadequate manpower.
Table 1: Fire stations in Dhaka
Fire station typeClass AClass BClass CRiver fire station
Total

No. of fire station
21
30
23
5
79

Table 2: Manpower in fire stations
Designation
Senior station
officer
Station officer
Sub-station
officer
LeaderDriverFireman
Other staff
Total

Fire station
Class AClass BClass CRiver firestation

1

0

0

0

1

1

1

1

0

1

0

0

3
5
22
3
35

2
4
16
3
27

1
2
10
2
16

1
3
8
0
13

Table 3: Equipments in fire stations
Equipment
Water truck
Pump truck
Helping truck
Potable pump
Ambulance
Fire float
Speed boat

Fire station
Class AClass BClass C

1
1
1
3
1
0
0

1
1
0
2
0
0
0

1
0
0
1
0
0
0

River firestation
0
0
0
1
0
1
1

Despite their limited resources and capacity, the BFSCD has taken various steps to reduce lossof lives and properties at the time of disasters, especially fire. The main activity of BFSCD is
to keep themselves standby as first responder for fire fighting, fire prevention, search & rescue,
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to render first aid, to send the serious casualties to hospital, to provide fire safety for the VIP's,and issue silence fire safety. BFSCD is also responsible to take necessary initiatives for raisingawareness among people. Mass communication through poster, leaflet, speech, seminar,
workshop etc, and training and drill programs in institutional, residential, and commercial
buildings, on fire fighting rescue operation, first aid, send the serious casualties to hospital,
safe escape from building through escape route, response according to plan etc, are some of theinitiatives to raise awareness among people as well as to make them resilient and prepared forany kind of disaster. In some case, people or institutions can apply to BFSCD to organize ortake part in the training program accordingly. Moreover, the total manpower of the agency is
not adequate in respect to necessity, and community people are the first responder for any kindof disaster. Realizing the fact, CDMP has initiated volunteer training program which aims tostrengthen the capacity of the city dwellers to face, manage and operate the plan effectively atthe event of any disaster through BFSCD. For this purpose, CDMP has procured lightequipments for search and rescue operations and ICT devices. Training to the community
volunteers enables them to render their service more efficiently in the mitigation of earthquake
disaster especially for collapsed structure search and rescue, fire fighting and first aid before
and after the arrival of professionals. Thus, Fire Service and Civil Defence has aimed to train
62,000 Urban Community Volunteer. Already 19,500 volunteers have been trained by this time.
On the other hand, for disaster resilience in slum areas, BFSCD provides training to the slum
dwellers, where 600 volunteers have already been trained.
7. Strengths and Weaknesses of Present Disaster Management System of Dhaka in
Combating Man-Made Disaster7.1 Prevention and Mitigation Measures
The Acts and Policies regarding urban development are the means to control development,
which are meant to ensure safety from manmade hazards, i.e. fire hazard and infrastructure
collapse. Even though, haphazard and unplanned development violating the regulations aregoing on, which result is devastating disasters. From the case studies, it could be observed thatin all of the cases of building collapse, the buildings were constructed violating the rules of
setback, FAR, building material, structural fitness, etc and most importantly they wereconstructed without permission from concerning authority. Even after taking clearance, they
did not build the building according to the approved design. Even use of some buildings arechange which result in increased vertical load. This was evident in the cases of Phoenix
building collapse, 2006 and Rana Plaza collapse, 2013. Internal roads in most of the areas are54

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narrow which do not comply with the legislations, especially in old part of Dhaka. Thus, themain problems regarding these acts and policies are that, these are not exercised properly, forlack of manpower regular monitoring cannot be ensured, and the concerning authorities alsolack modern technology for data management. The existing manpower of RAJUK is not
sufficient to monitor and enforce the building code properly.
The Disaster Management Act, 2012 enacted arrangement of instruments regarding fire
prevention and mitigation according to risk of different occupancy buildings, along withrestriction on preservation and use of combustible and flammable materials without proper
safety measures in residential area, but the act lacks specific provision prevention andmitigation measures. National Disaster Management Policy, 2008 proposes development of astandard guideline, preparation, and implementation of hazard specific risk reduction plan formanmade hazards under fifth strategic goal, i.e. expanding risk reduction programming acrosshazards and sectors. On the other hand the National Plan for Disaster Management, 2010-2015
does not include risk reduction plan for manmade hazards. The plan addresses strategies tostrengthen national capability to reduce the risks of manmade hazards (including infrastructure
collapse and fire) under the fifth strategic goal. The strategies include: reduction of theincidence of disasters in the manufacturing industry by developing guidelines and risk
reduction plans for chemical and technological hazards and increasing awareness ofcommunity, and strengthen Bangladesh Fire Service and Civil Defence providing better
equipped with latest fire fighting technology including training. Guidelines and risk reductionplans for chemical and technological hazards have not been prepared yet. Again, awarenessactivities are very inefficient because of lack of integration at the community level. In most of
the cases, people are not aware of the manmade hazards, though they know about theconsequences. The incident of the collapse of Rana Plaza caused due to negligence and lack ofawareness of the respective authorities, for which they did not take the warning seriously.
To prevent and mitigate fire incident, Fire Prevention and Extinction Act, 2003 and Rules,
2014, and Bangladesh National Building Code (BNBC), 2014 have enforced legislation forlicense, clearance and occupancy certificate to ensure fire safety, indicating the provision forpunishment for any discrepancy by BFSCD. In Bangladesh National Building Code (BNBC),
2014, fire zones have been defined with respect to occupancy class. In most of the cases,
different activities are carried out without license, clearance and occupancy certificate, or
violating the permitted license, clearance and occupancy certificate. Most of the buildings do
not comply with the building code, i.e. use of low quality electric equipments, unsafe electric
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wiring system and unsafe storage of flammable and combustible materials. Thus, most of thefire incidents are ignited from electric short circuit, and spread by flammable and combustible
materials and chemicals. The evidence of such incidence can be observed in case of BSEC fire(2007 and 2014). Even after the fire incidents on 2007 in BSED, no preventative or mitigation
measures were taken in the building, causing fire for the third time in 2014 for the same reason,
i.e. electric short circuit at storeroom of papers. For limitation of manpower in BFSCD, regularmonitoring and inspection cannot be done.
7.2 Preparedness Measures
In the Disaster Management Act, 2012 responsibilities of different committees, groups andcouncils at different levels, and Disaster Management Bureau for preparedness purpose havebeen specified. Moreover the act addressed establishment of National Disaster Volunteer
Committee, and National Disaster Management Research and Training Institute for proper
preparedness. The Act entitled establishment of fund for arrangement of different instruments
to ensure proper preparedness. The Act enacted arrangement of instruments necessary for
preparedness for fire hazard and building collapse, and safe escape along with proper marking,according to risk and occupancy load of different occupancy buildings. The Act skipped
community level preparedness issues and most importantly the awareness initiatives which arevery important for fire hazard and building collapse. Again, most of the stakeholders areunaware of their responsibility stated in the act, plan or SOD. For financial preparedness,formation of three funds has been stated in National Disaster Management Policy, 2008
including, National Risk Reduction Fund, National Disaster Response and Recovery Fund, andDisaster Management Fund, but details about the funds arrangement and allocation are absent.
The National Plan for Disaster Management, 2010-2015 does not include plan for manmadehazards specifying preparedness strategies.
To ensure proper preparedness, Fire Prevention and Extinction Act, 2003 and Rules, 2014 havedefined the responsibilities and activities of brigade including response activities, awarenessactivities for officer, government and mass people, training programs for officials, volunteers
and general people, arrangement and preservation of necessary equipments. In reality, therespective authorities do not have sufficient manpower, equipments and vehicles to carry on
the rescue operation (Osman, Khan, Hossain, & Khan, 2013). Fire service authority can provide
equipment support for firefighting up to 10th floor, but there are high rise buildings beyond
this height in Dhaka city (Islam, & Adri, 2008).
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Moreover, in these rules and acts along with Bangladesh National Building Code (BNBC),
2014, fire fighting floor plan has been made mandatory for different occupancy class buildings,
which should include, permanent and potable fire fighting system, emergency and alternative
stair, lift and fire lift, smoke and heat detection system, alarm system, emergency light, exit
sign, fire command station, transformer and generator room, fire fighting and pump house, riser
point and hoes cabinet, sprinkler head, water spray projector head, safety lobby, means ofescape, water source and reservoir, minimum width of road, etc. In reality, people are not awareof the facts and thus the plans are not prepared thereby. The buildings do not have stair withproper sign. Moreover, the exits remains locked all the time and the escape route is occupied
by trash. This incident was evident in case of Bashundhara City Complex fire, 2009. From thecase studies it could be observed that fire extinguishers are not preserved in the buildings. Even
though some buildings are equipped with sufficient fire detecting, suppressing, and evacuating
systems, people have no knowledge about how to use them, and they also remain deactivateand defective , i.e. Bashundhara City Complex fire, 2009; BSEC fire incident, 2007. People ofthe city also do not have any training and not even the minimum perception about how to
respond or cope with the fire when an accident occurs. General people are not trained for
response to and rescue from the incidents. Again, regular training for volunteers is absent(Osman, Khan, Hossain, & Khan, 2013). Even though some buildings have fire fighters, theylack proper and regular training, i.e. Bashundhara City Complex fire, 2009.
7.3 Response Measures
In the Disaster Management Act, 2012 responsibilities of different committees, groups andcouncils at different levels, and Disaster Management Bureau for preparedness purpose havebeen specified. Moreover the act addressed establishment of National and Local Level Disaster
Response Coordinator Group integrating different stakeholders in the committee for proper
response during and after a disaster at different level. The Act specified activities immediately
after a disaster including declaration of disaster affected area and activities of different
stakeholders, ensuring uninterrupted movement of fire fighting and rescue team. The Act
enacted arrangement of instruments regarding search and rescue according to risk of different
occupancy buildings. Thus the act could properly address the response issues properly. The
National Plan for Disaster Management, 2010-2015 defines responsibility of different
stakeholders to prepare plan at different levels including response activities, but it does notinclude plan for manmade hazards specifying response strategies.
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The buildings do not have stair with proper sign, and the exits remains locked all the time andthe escape route is occupied by trash, which worsen the scenario. This incident was evident incase of Bashundhara City Complex fire, 2009. For not having fire lift or alternate stair, peoplerush to the central stair case resulting in more disastrous situation. This happened in BSEC fire(2007), where people rushed to central staircase to go out off the building. Though in somebuildings fire extinguishers are preserved, but for lack of knowledge and training people cannot
use those at the time of necessity. This situation was observed in BSEC fire (2007).
Various fire fighting equipments are sometimes provided at the individual building but they
are inferior in number, and in many cases located in theisolated places andpeopledo

not know how to use these equipments. As a result, theequipment does not provide

anybenefit at the time of emergency.
The prime challenges that the authority usually face after a fire call is to reach the sp
ot rapidly considering the low mobility in the road way and to manage water for fire fi
ghting. To ensure proper response, Fire Prevention and Extinction Act, 2003 and Rules, 2014
have ruled to keep the roads clear for easy movement of fire fighting vehicles, but it is notfollowed properly. Narrow access roads hamper the movement of fire vehicles and make theresponse work difficult, especially in Old Dhaka. The crowd of curious people is also anotherproblem that is usually had to face by the fire fighters during their work. Sometimes the crowd
becomes

too large that they even clog the movementof fire fighting

vehiclestowards

the target location. The crowd and road blockage results in delay of fire fighting vehicles toreach at the spot. According to the rules and acts, the brigade will be responsible for firefighting, rescue, first aid and transfer the injured to hospital through ambulance service. Thereis no provision of water for emergency situation, which result in delay in the fire fighting
operation, i.e. Bashundhara City Complex fire, 2009; BSEC fire, 2007 and 2014. For lack ofsufficient equipments, rescue operations are delayed (From case studies). Since Fire Service
and Civil Defence's only aerial ladder cannot gain access beyond 13th floor, six floors of the
20-storey mall-cum-office tower remained out of the fire fighters' reach to be left in ruins, inBashundhara City Complex fire incident in 2009.
Moreover, in the rules and acts along with BNBC, 2014, provision for trained fire safety
officers has been enforced for buildings to ensure immediate response. In case of Rana Plaza
collapse in 2013, the rescue operation was hampered for absence of training and guidance,
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weak chain of command, and lack of coordination (Osman, Khan, Hossain, & Khan, 2013).
Even though some buildings have fire fighters as provision, they cannot response to thesituation properly for lack proper and regular training, i.e. Bashundhara City Complex, 2009.
In any incident, general people play the role of first responder, though they do not have therequired knowledge, training or experience, i.e. Phoenix building collapse, 2006, Rana Plaza
collapse, 2013. After the incident of Rana Plaza collapse in 2013, fifty percent of the volunteers
were general and untrained people. They also helped the injured to various hospitals, delivered
dead bodies to the relatives, arranged for the burial of unidentified bodies and financiallyhelped the affected (Odhikar, 2013).
7.4 Relief and Recovery Measures
The Disaster Management Act, 2012 entitled establishment of fund for ensuring relief after
occurrence of a disaster and arrangement of instruments regarding first aid according to risk ofdifferent occupancy buildings, which is not done in reality. The National Plan for Disaster
Management, 2010-2015 defines responsibility of different stakeholders to prepare plan at
different levels including relief and recovery activities, but it does not include plan formanmade hazards. Management system for relief has not been stated in any of the acts or rules.
In case of Rana Plaza collapse in 2013, aids were raised from government, foreignorganizations along with aids from general people. For lack of proper management many ofthe victims either did not get the defined amount of aid or did not get it at all. Rather someother people received aid instead with fake ID (Moazzem, Afros, & Sehrin, 2014). Again, Fire
Prevention and Extinction Act, 2003 and Rules, 2014 have ruled to investigate the causes andresults of any fire incident afterwards, for taking necessary actions accordingly. Whenever afire occurs or building collapse, the authorities are usually asked to investigate the fire, pay
exemplary compensation to the survivors as well as to the families of those that died, take
immediate steps to improve health and safety in the industry, as well as take legal action against
those found responsible for criminal negligence in allowing the existence of such unsafe
conditions. This activity is done efficiently after every incident because of the involvement ofmass media.
8. Conclusion
The real city is a safe city that ensures the security of living and livelihood of its citizens. Safetyissues should be given high priority in the urban areas because of the involvement of huge
population in a limited geographical space. Dhaka is growing in an unplanned manner and
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unfortunately the authorities have very limited control over the development trend. The safetyissues in the large urban areas, like Dhaka are not highly emphasized from the city planningperspective in Bangladesh. In most cases, immediately after any large scale fire and building
collapse, the issue of urban safety is highly discussed by local newspapers but with the progressof time, the issue ultimately fades away from people’s memory. As a result, the governmentshows an attitude of reluctance in taking further. At present, the authority of this metropolitan
city has no contingency plan and sufficient preparation to avoid manmade hazards. The city
authority has no proper equipment and adequate trained manpower to combat fire. Again, atpresent BFSCDA is working as the emergency service providing organization and the authority
has very limited involvement to the planning decision. The city authorities like RAJUK, City
Corporation etc. are also characterized by weak institutional capacity. The existing legal
provisions are also limited and needed to be modified for proper enforcement. To overcome
the situation, these short comings should be minimized and safety issues should be addressedfrom the individual building premises to the city planning level.
References
Alam, N. (2010). Collapse of 4 storied building in Begunbari‐‐‐A pictorial case study.
BFSCD. (n.d.). Bangladesh Fire Service and Civil Defence (BFSCD). Retrieved on 27
December, 2014, from: http://www.fireservice.gov.bd/
Islam M. M., & Adri N. (2008). Fire Hazard Management of Dhaka City: Addressing Issues
Relating to Institutional Capacity and Public Perception. Jahangirnagar Planning
Review, 6:57–67.
Moazzem, K. G., Afros, A. & Sehrin, F. (2014). Post-Rana Plaza Developments: Rana Plaza
Tragedy and Beyond: A Follow Up on Commitments and Delivery: Monitoring Report on
Rana Plaza Tragedy. Center for Policy Dialogue (CPD) in collaboration with Canada
Fund for Local Initiative (CFLI).
Odhikar. (2013). Broken Dreams: A Report on the Rana Plaza Collapse. Fact finding report,
Odhikar.
Osman, M. S., Khan, M. A. A. M., Hossain, M. A. & Khan, A. I. (2013). Search and Rescue
Roles of Fire Service and Civil Defence and Urban Community Volunteers in Rana
Plaza: A Rapid Assessment. CDMP, Ministry of Disaster Management and Relief.
Rahman, N. & Ansary, A. A. (2013). Savar Building Tragedy in Bangladesh: Way Forward.
Presented at USMCA conference.

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Tabassum, S., Ahmed, S., & Romeo, T. M. (2014). An Investigation on Fire Safety of Airconditioned Shopping Centers at Dhaka City. Asian Journal of Applied Science andEngineering, 3(2), 20-34.

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PART-VRESCUE OPERATION OF A 4-YEAR CHILD,JIHAD FROM AN ABANDONED DEEP
TUBEWELLBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Uttama Barua
Mehedi Ahmed Ansary62March 2015

The Incident
On Friday evening, 26 December, 2014, Jihad was playing with two of his playmates in aplayground at the Shahjahanpur Railway Colony. At one moment of playing, Jihad fell into apipe adjacent to the playground at about 4 pm. He did not see the pipe as its mouth was covered
only with an empty jute sack, which was just wide enough to fit the boy and too narrow for an
adult to pass through. Seeing the incident, his playmates informed the local people and his
family about the incident. Several women had heard Jihad scream from down the pipe. Jihad’sfather Nasiruddin works as a security guard at the Motijheel School and College. Jihad is the
youngest among his parents' three children. They live in the same colony. Residents said the
deep tubewell was declared abandoned when it stopped delivering water. A new deep tubewelland pump were being installed near it by the Bangladesh Railway. Locals said another childnearly had a similar accident on the previous day in the same pipe where Jihad fell. One of his
legs went inside the pipe accidentally, but the locals saved him. From the surface, the pipe is
17 inches wide for around 300 feet underground. It is followed by a 'submersible pump' andfilter. After that, the pipe is three inches wide and has gone over 300 feet underground. Jihad
was sitting on the pump at about 300 feet depth.
Response to Rescue Jihad
Getting the news, three units of firefighters arrived at the scene around 4 pm and started therescue efforts, and were assisted by Dhaka WASA, railway, RAB, police and other volunteer
agencies. Jihad, kept responding for six hours since the launch of the rescue operation. Rescuers
said they spoke to the boy several times and provided him with some food, juice, bottled milk
and fresh oxygen. They also sent a torch down the pipe as the evening fell. But Jihad got weakerafter spending long hours in the cold, dark and damp underground.
The fire brigade personnel employed various techniques one after another. Between 4pm and7:30pm, the firefighters repeatedly tried to bring up the child by using the rope line, but failed
every time as he could not hold on to the rope for long enough. Firstly the rescuers tried to pullup the boy with thin nylon rope, but the rope got lighter after pulling up around 10 feet.
Afterwards, they dropped a thick rope with a torch and the boy had held it but released aftersome time. Thus the fire-fighters made five abortive attempts to bring the boy, 'Jihad', up usingrope. After 7:30pm, the fire-fighters sent down a sack and asked Jihad to sit on it. That planalso failed as the child fell again after being pulled up for a while.

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Figure: Initiation of rescue operation

Figure: Rescue effort using rope

Figure: Rescue effort using sack
Their attempts to save the boy were facing obstruction as the hole was not that wide and had
another three inches wide pipe inside the first one. At about 8.20 pm the fire service brought
their crane in the spot to uproot the inner pipe. Then after 11 pm, the rescue team was able topull up the 350 feet long pipe, three inches in diameter that went inside the first one using thecrane to create more space.

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Figure: Uprooting of internal pipe
Rescuers then planned to send one of their men down the pipe with a camera and light. A man
named Bashir Uddin Ahmed volunteered to go down into the well at around 11:30pm to bringout the child. He took all the preparations to follow through with the plan, but ultimately he
was not allowed to go down considering safety issues because the experts wanted to observe
the situation down the well through the camera first.
Soon after that, a team from BUET's mechanical engineering department arrived at the scene
with an alternative plan to save the boy. After consulting them, Fire Service and Civil Defence
Director tried the BUET team's plan. One of the team members, BUET student Tanvir Arafat
Dhrubo said they planned to use another pipe, smaller in diameter, which would have a 'catcher'at the end. After it reaches Jihad, the mouth of the 'catcher' would open up and get a hold ofboy and bring him up, he said. The work to build the 'catcher' started near the scene. Meanwhile,the Directorate General of Health Services kept a medical team standby from Dhaka Medical
College and Hospital with a fully equipped ambulance at the spot to meet Jihad's emergency
needs once he is rescued.
Nine hours after Jihad fell; Dhaka WASA sent a waterproof camera to get visual inside thepipe. The rescuers lowered the borehole camera down the pipe and searched for an hour without
success. In the first attempt, the borehole camera identified a piece of cloth, sandals, pieces ofcork sheet, a common lizard and pieces of paper around 250 meter down. The camera
completed its slide into the hole around 2:00am but there was no sign of the boy. After that,
Jihad's existence down the pit was denied by professionals known for their skills. Abu SayeedRaihan, joint director of National Security Intelligence, termed the news of Jihad’s falling inthe shaft as “rumor” after seeing images sent by Dhaka WASA camera. Confusions grew when
the State Minister for Home Affairs Asaduzzaman Khan Kamal, at about 2:45am Saturday

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declared that there was no boy trapped in the well and the entire episode might be a ‘rumor’saying, "...I'm sure there's nobody down there".
Shahjahanpur police picked up Jihad's father Nasir Uddin moments after the announcement.
Police picked him up around 3am on Saturday saying journalists would pester him if he wereat the scene. But at the police station, he was told that his son was not spotted by a camera sent
down the pipe. The law keepers suspected Jihad had been hidden somewhere else. They
questioned Jihad's father suspecting the whole thing was staged. He was threatened and tortured
in the name of RAB to tell the 'truth'. Police confined Nasir for 12 hours.
At this stage, rescuers doubted same but did not give up. DG Khan said they would continue
their search until they were absolutely sure. “Though we can’t see any human being there, we
are not wrapping up our operation. We will remove the debris to be certain,” he said. But
optimism slowly gave way to frustration and outrage. They decided to send the camera again,
after clearing the debris. Thus, in a second attempt, non-government experts sent anothercamera around 4:00am. It got obstructed again after reaching 240 feet. After that the rescue
operation slowed down.
In the morning, the rescuers tried to send the catcher they prepared to the bottom of the well ina bid to pull out the boy allegedly trapped inside the well shaft. A camera has also been attachedwith the case made with iron rods. Despite their renewed efforts since 9:30am, the fire fighters,
who have been conducting rescue operation since yesterday, failed to send the “catcher” at thebottom till 11:00am.
The Fire Service closed the rescue operation at 2:30pm on Saturday; 23 hours after the rescue
operation had started. Fire Service DG Brigadier General Ali Ahmed Khan made theannouncement at 2:40pm after the rescuers failed to detect any human body inside the tubewell, using high-tech camera and catcher. He said: "We have tried several times, but could notdetect the location of the boy. Experts from different organizations also could not find any
specific evidence in this regard. However, we continued the rescue efforts as the parents
requested us. We are now handing over the operation to railway engineers. They will takefurther step in this regard and the fire fighters will help them if necessary. We are thanking all
for their efforts and expressing our sorrow and shock for the family members of the ill-fated
boy”.

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Rescue of the Child by Locals
When sophisticated instruments failed to even locate Jihad, ten volunteers eventually
succeeded to bring him out using a simple handmade tool. The volunteers were unknown toeach other before the operations and had been with the rescue team since Thursday night. They
also volunteered during last year’s Rana Plaza tragedy in Savar. Three of the volunteers leadthe rescue operation and planned to make a metal-rod cage seeing the rescue method of fireservice. They are Shafiqul Islam Faruq, Shah Muhammad Abdullah Al-Moon and Sujon Das
Rahul. Faruq, who financed and led the drive, is a businessman while Moon, a diploma
engineer, is working for a private firm and Rahul is studying at a private polytechnic institute.
They made the instrument with a net, a close circuit camera, a torch, a tri-stand and a cleat tied
to a 600-feet-long rope. They attached the manual cable TV camera binding it with an ironrope. The device was named ‘mechanical capsule’. The volunteers claimed that it was possible
to rescue the boy on Friday night, but they were not allowed to do that. They had the chance to
use it only after the fire service declared postponement of the operation.

Figure: Mechanical capsule

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At 2.30 pm on Saturday, 27 December 2014, the volunteers started their rescue operation by
slowly lowering the cage into the pipe. After sliding down around 100 feet it got stuck into
something. Later, they pulled the cage around ten feet up and then dropped it again. This time,
it started going down fast. They started releasing the rope slowly. He said the cage was stuckagain at the spot where Jihad’s body was found. At one stage about 250 feet down the pipe, thecamera captured the boy’s image, spurring the private rescuers on. They could see on thecamera that the head of the boy was upward and an arm was on his forehead. The rescuers thenpulled the body up, which was tied up with wires. Water was traced 235-240 feet down thehole. Jihad was found 5-7 feet down from there. Thus the volunteers rescued the kid at 3:00pm
by their brave effort within half an hour. They however, gave some credit to the fire service
personnel for extending help to them. Many of the fire service officers stood by them when
they were conducting the operation, and they used the crane of fire service. The recovery ended
the story with an unsettling combination of human ingenuity and neglect. DG Khan was quick
to take credit saying Jihad was rescued with everyone's help. But the ‘success’ turned out to bean embarrassment for the Fire Service.

Figure: Rescue operation by volunteers

Figure: Jihad after rescue

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Figure: Overall 23 hours rescue effort of Jihad
Declaration of Death of Jihad
After pulling out Jihad, he was taken to Dhaka Medical College and Hospital where doctors
announced him dead. Doctors said the boy had died several hours before he was brought there.
Jihad's body bore bruise marks apparently from the fall; Dr Riaz Morshed said adding there
were evidences of him falling into water as well. Later, the body was sent to the college morgue
for an autopsy. The autopsy was performed by Habibuzzaman Chowdhury along with Forensic
Department Assitant Professor AKM Shafiuzzaman Khair and lecturer Pradip Kumar Biswas.
After post-mortem of the four-year-old child, Dhaka Medical College and Hospital's Forensic
Department chief Habibuzzaman Chowdhury said that internal and external injury marks were
found on the boy's head, which were caused during his fall into the abandoned deep tube-well.
Rust particles were found under Jihad's fingernails, proving that the boy desperately tried tohold on to the wall of steel pipe, used to reinforce the shaft, during the plunge. "The presenceof water inside the boy's stomach, respiratory system and lungs indicates that his death was
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caused by drowning. We have come to the conclusion that the child drowned in the water within
two hours of his fall inside the pipe. Even if there were no water, the [head] injury itself could
prove fatal for him.” said Habibuzzaman Chowdhury.
Shahjahanpur Police Sub-Inspector Abu Jafar said the body has been handed over to the familyaround 9:45am Sunday at the end of the post-mortem. The child was buried his ancestral village
of Nagerpara in Shariatpur's Gosairhat upazila and buried there. Several thousand people
attended his janaza before the burial.
Aftermath of the Incident
At the time of rescue operation in Friday, 26 December, 2014 at night, Jahangir Alam, who
was in charge of the project, was suspended following the incident, while the project contractor
firm, SR House, which was installing a new deep tube-well at the site, was blacklisted.
Nasir Fakir, the father of Jihad was released on Saturday afternoon after his son's body wasrecovered from the pit. The state minister and the police chief claimed law enforcers picked up
him with a good intent to inquire about the lost kid. But they could not explain why the man
was held in police station for so long.
The locals and volunteers marched in processions at Shajahanpur and in front of DMCH
demanding immediate withdrawal of the junior minister for his ‘irresponsible’ remarks about
the incident. Angry over the authorities' slow move to rescue Jihad, locals demonstrated against
State Minister and officials of the Fire Service. They also expressed anger citing that the rescue
operation has been delayed as different government bodies gave contradictory opinions andsuggestions over the issue. By then, agitated locals vandalized shops around the accident spot
and WASA's temporary establishments. Later, police tried to calm the situation, but agitatedmob threw brick chips at police. To maintain law and order, police charged batons anddispersed the protesters. After Jihad's rescue, authorities welded the pipe's entrance with aniron plate.

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Figure: Sealed pipe’s entrance after rescue operation
Nasir filed a case against Abdus Salam, owner of the construction company responsible forsetting the pipe, and Jahangir Alam, Railway senior sub-assistant engineer around Saturday
midnight bringing charges of negligence. Two writs were filed with the High Court seeking a
number of directives, including asking the government to give adequate compensation to
Jihad's family and take actions against officials who failed to rescue the boy.
Comments on the Incident and the Rescue Operation
The accident was the result of negligence on the part of the contractor and the railway that were
supposed to keep the abandoned well sealed but they left it open. Open manholes on various
city roads have become virtual death traps for the commuters, but the civic bodies are hardly
taking any notice of this, alleged city dwellers. More than 100 manholes remain open on
various roads in the capital for years, posing serious threat to public particularly for pedestrians.
Careful strategy and prompt action are the two things required, which only well-trained
professionals can undertake. There was veritable lack of discipline and coordination among the

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civil defence people at the site with apparently no chain of command. The confusion at thescene over how best to deal with the situation, whether or not there was, in fact, a child stuckin the hole at all, and even the depth of the hole with estimates ranging from 400 to 700 feet,demonstrates how unprepared we are when it comes to handling emergencies. While rescue
operations started within half an hour of the accident, the next several hours were wasted overmany short-sighted attempts to recover the child. Even though the expectation of the rescue
team to drag a frightened four-year-old boy up 600 feet using a rope was unrealistic, they
repeatedly pursued the same method after the first failed attempt.
To say the least, the rescue effort was unplanned and disorganized, with no control over thelarge number of onlookers. Police were having trouble with the large number of onlookers
gathered there at the time of rescue operation. Shahjahanpur Police Station OC Mehedi Hasan
said the huge gathering of onlookers was hindering the rescue. Moreover, State Minister for
Home Affairs Asaduzzaman Khan Kamal, WASA Director General Engineer Taksim A Khan,DMP Commissioner Benazir Ahmed, BNP Standing Committee member Mirza Abbas andDhaka University Vice-Chancellor AAMS Arefin Siddique visited the scene at the time ofrescue operation in Friday, 26 December, 2014, which added more chaos in the scene. It is hightime that the government seriously considers a thorough reworking of its rescue preparedness
and take full-scale measures to guarantee a systematic and effective response to emergencies
in the future.
Moreover the deceit resorted to and the hint of conspiracy that the authority ‘discovered’ in thematter was uncalled for. The callous and insensitive behavior of the government agencies
involved in the rescue effort worsened and slowed down the rescue operation. Not only theFire Brigade failed to handle the situation, the behavior and utterances of persons in positionsof responsibility, including the state minister for home also confounded the situation. And how
does the government explain the extremely cruel treatment meted out by the police to a father
who was not sure at that time what his son's fate would be? One wonders what his fate would
have been had Jihad's body not been recovered. To keep him in custody for 12 hours without
food is cruel and betrays a government that is prone to see conspiracy in every event.

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PART-VI
GPR TESTING ON BALL MILL FOUNDATIONBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA
Prepared By: Mehedi Ahmed Ansary73March 2015

1.0 Introduction
The General Manager of a cement company has approached us for undertaking non-destructive
testing on existing Ball Mill foundation at their cement plant site at Meghnaghat, Sonargaon,
Narayanganj. It has been agreed that the terms of reference of the work would be limited to
non-destructive testing of Ball Mill foundation using Ground Penetrating Radar (GPR). Testingat the plant site was carried out on August 30 and September 2, 2014. The report indicated theprobability of void and possible location void. The cement company injected ConbextraEP10(M) by high pressure pumping through drilled holes. 2nd time GPR test at the plant was doneon December 10, 2014 after the first grouting. Significant improvement by grouting wasobserved in the 2nd time GPR Test. However, still there were small voids indicated near the
first grouting points. The cement company again injected ConbextraEP10 (M) by high pressure
pumping through drilled holes. 3rd time GPR test was performed at the site on December 19,
2014 after second grouting. This report is the outcome of the 3rd GPR tests after second time
grouting.
2.0 NDT Using Ground Penetrating Radar (GPR)
Ground Penetrating Radar (GPR) is a near-surface geophysical technique that can provide highresolution scan of the dielectric properties of the earth. GPR works by sending a tiny pulse ofenergy (Electromagnetic Energy) into a material and recording the strength and the timerequired for the return of any reflected signal. A series of pulses over a single area make up
what is called a scan. Reflections are produced whenever the energy pulse enters into a material
with different electrical conduction properties or dielectric permittivity from the material it left.
The strength, or amplitude, of the reflection is determined by the contrast in the dielectric
constants and conductivities of the two materials.
Signal of 400 MHz has been used to investigate the machine foundation. All data were collectedin simple line and point scan format. The direction of arrow in site plan and data collection
grids indicates the starting and ending point GPR scan. The attached pictures and drawings
show the results of those investigations.
3.0 Data Collection
GPR data were collected using 400 MHz with a GSSI SIR-3000 control unit. Data werecollected in simple line scan format. Figure 1 shows the schematic diagram of the ball millfoundation plan. Figure 2 shows the GPR scan lines with scan ID. The direction of arrow insite plan and data collection grids is indicating the starting point of GPR scan.

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Figure 1: Ball mill foundation plan (note: drawing is not in scale)Figure 2: Data collection grid lines (note: drawing is not in scale)75

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4.0 Data Processing
The collected data sets were processed by specialized software program RADAN. Three basic
kind of processing tools were used in order to calculate accurate depth, to remove noise and to
improve display for documentation purpose.
Time-Zero Correction: A corrected Time-Zero provides a more accurate depth calculation
because it sets the top of the scan to a close approximation of the ground surface. Timezero
corrections also remove the section of data that occurs before direct wave.
Infinite Impulse Response (IIR): Often used to remove noise.
Finite Impulse Response (FIR): Background noise, often seen as horizontal banding, may beremoved using the FIR Filter.
5.0 Findings of Ground Penetrating RADAR (GPR) after First Grouting
The results of 400 MHz GPR data are presented below. These scan data don’t show any clear
contrast within the foundation area except scan ID 05 and 06. Figure 3 shows the comparisonof reflectogram at the same line before and after grouting. After second time grouting, 3rd GPR
test data clearly shows the absence of any void or crack in the foundation.

Figure 3: Comparison of reflectogram before and after grouting

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PART-VII
EARTHQUAKE RISK ASSESSMENT AND
PLANNING FOR MANAGEMENT IN
MYMENSINGH MUNICIPALITY,BANGLADESHBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Uttama Barua
Mehedi Ahmed Ansary77March 2015

1. Introduction
Earthquake is one of the most destructive natural hazards. It can occur at any time without any
warning and can destroy buildings, infrastructure and above all lead to human loss and tragedy.
Again urban earthquake risk is rapidly increasing, particularly in developing countries, becauseof high rate of urbanization, faulty land-use planning and construction, inadequate
infrastructure and services, and environmental degradation (Erdik, 2006). There are three basicstages to reduce urban earthquake risk: evaluation (understanding the underlying problem andits magnitude), planning (taking actions to solve it), and implementation (realizing the
proposed actions) (Villacis, 2000). Earthquake risk evaluation is the first step for quantificationof the effects of the earthquake on the physical and social environment (Guragain, Jimee, &Dixit, 2008; Erdik, 2006).
Total elimination of risks may be difficult and impractical, so disaster management throughproper hazard assessment is very essential to reduce loss of lives and sufferings of people.
Realizing the importance of damage estimation, different studies have been undertaken for
hazard specific damage estimation, i.e. flood (Smith, 1994; Herath, Dutta, & Musiake, 1999;
Renyi, & Nan, 2002; Dutta, Herath, & Musiake, 2003; Kang, Su, & Chang, 2005; Koshimura
et al, 2009; Middelmann‐Fernandes, 2010; Pistrika, 2010; Poser, & Dransch, 2010), earthquake(Park, Ang, & Wen, 1985; Cret et al, 1993; Kanamori, Hauksson, & Heaton, 1997; Kircher etal, 1997a; Kircher et al, 1997b; Eguchi et al, 1997; Whitman et al, 1997; Rojahn et al, 1997;
Yamazaki, Noda, & Meguro, 1998; Dolce et al, 2003; Spence et al, 2003; Aleskerov et al, 2005;
Bird et al, 2006; Miura et al, 2008; Brunner, Lemoine, & Bruzzone, 2010), hurricane (Pinelli
et al, 2004; Watson Jr, & Johnson, 2004; Ginger et al, 2007), landslide (Alexander, 1986;
Petrucci, Pasqua, & Gullà, 2010), etc.
Different studies related to earthquake damage estimation have been carried out covering
different aspects. Park, Ang, & Wen (1985) proposed a method for evaluating structural
damage of reinforced concrete buildings under random earthquake excitations. Yamazaki,
Noda, & Meguro (1998) studied early earthquake damage assessment systems in Japan toprovide future direction in the process. Cret et al (1993) presented earthquake damage
estimation and decision analysis for emergency shut-off of city gas networks using fuzzy set
theory. Whitman et al (1997) summarizes the development of a Geographic Information
System (GIS) based regional earthquake loss estimation methodology for the United States
funded as part of a four‐and‐one‐half year project by the Federal Emergency Management
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Agency (FEMA) through the National Institute of Building Sciences (NIBS). Kircher et al(1997a & 1997b) described building damage functions that were developed for the
FEMA/NIBS earthquake loss estimation methodology. Rojahn et al (1997) developed and/or
updated methodology for estimation of damage due to ground shaking, estimation of damage
due to collateral loss causes such as fault rupture, ground failure, inundation, and fire following
earthquake, estimation of time to restore damaged facilities to pre‐earthquake usability, andestimation of deaths and injuries, for implementation in a geographic information system (GIS)
application, or in a non‐GIS software application, such as a relational database management
system or spreadsheet for Salt Lake County, Utah (ATC‐36). Eguchi et al (1997) described thedevelopment, operation and application of the first real‐time loss estimation system to be
utilized by an emergency services organization. Kanamori, Hauksson, & Heaton (1997) studied
the then real-time seismology and earthquake hazard mitigation. Spence et al (2003) comparedestimated loss from two different approaches (using predicted macro-seismic intensity, and thespectral displacement) with actual observed losses in the Kocaeli event at two different
locations for estimating future losses. Dolce et al (2003) presented damage scenarios relevantto the building stock of the town of Potenza, Southern Italy. Bird et al (2006) presented aframework for resolving issues that, the assessment of building damage caused by liquefactioninduced ground deformations requires the definition of building capacity and vulnerability as
a function of the demand, as well as damage scales to describe the state of the damagedbuilding; within the context of earthquake loss estimations, where large variations in building
stock and ground conditions must be considered. Brunner, Lemoine, & Bruzzone (2010)
presented a novel method that detects buildings destroyed in an earthquake using pre-event
VHR optical and post-event detected VHR SAR imagery at individual building level.
The earthquake records of Bangladesh suggest that the country is prone to massive earthquakein near future (The Daily Star, 2008). The active faults are gaining energy, which can beindicated by the occurrences of historical earthquakes in and around the country and long-termsilences of happening potential earthquake (seismic-gap) across the region (The Daily Star,
2008). The country is divided into three earthquake zones and Mymensingh municipality liesin the northeastern zone which is designated as the most earthquake prone area of Bangladesh(Sarker, Ansary, Rahman, & Safiullah, 2010 and Ali, 1998). So, earthquake preparedness in
Mymensingh Municipality has become necessary for which, earthquake damage estimation is

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a must. This study aims at estimation of earthquake damage in Mymensing municipality andpreparation of risk management plan on its basis.
2. Study Area Profile: Mymensingh Municipality
Mymensingh Municipality is located in the district headquarters of Mymensingh District of
Dhaka division and is situated on the right bank of the old river Brahmaputra (Mymensingh
Municipality, 2012), which is shown in Figure 1. The municipality lies in the northeastern zone
of Bangladesh which is designated as the most earthquake prone area of Bangladesh (Sarker,
Ansary, Rahman, & Safiullah, 2010 and Ali, 1998). For this reason, this municipality was
selected as the study area of this study. It is one of the oldest towns established in 1869 having
an area of 21.73 sq km. The municipality is divided into 21 wards and 85 mahallahs (BBS,
2001a,b). Mymensingh is one of the rapidly growing and densely populated secondary townsof Bangladesh, with an estimated present population (night time) of 0.414 million in themunicipal area (Mymensingh Municipality, 2012). Number of buildings in this municipality
is 46,055 and average family size is 5.6 (Mymensingh Municipality, 2012). About 60.4 percent
population of the Pourashava is literate, of which 66.4 percent are male and 53.4 percent arefemale (BBS, 2001a,b). The principle occupations of the adult males in the Pourashava are in
the business and service areas.
3. GIS based RADIUS Methodology for Earthquake Damage Estimation in Mymensingh
Municipality
For the efficient seismic risk management and for the establishment of efficient and effective
mitigation schemes; advanced, multidisciplinary and integrated methodological tools are
required to estimate the likely emergency response resource needs and socioeconomic impactsof large earthquakes in urban areas (Pitilakis, & Kalliopi, 2011). For the purpose, different
methods and tools have been developed from different perspectives, some of which integrate
information from existing building inventory and site seismicity (Alam, Tesfamariam, & Alam,2012). These methods can be broadly grouped into: probabilistic methods based on secondary
information and deterministic methods with detailed quantitative analysis (Guragain, Jimee, &Dixit, 2008). Bayraktarli, Yazgan, Dazio, & Faber (2006) utilized Bayesian Probabilistic
Networks (BPN’s) for earthquake risk management on the basis of a generic and indicator
based risk assessment framework. Korkmaz (2009) introduced a probabilistic-based
methodology for earthquake disaster risk assessment and evaluation for Turkey. Lang, MolinaPalacios, & Lindholm (2008) utilized CSM-Based Tool SELENA for damage estimation which
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takes into account epistemic uncertainties in all types of input data by a logic-tree computation
scheme. Sarris, Loupasakis, Soupios, Trigkas, & Vallianatos (2010) developed a GIS based
application for the purpose considering a localized model. Rashed, & Weeks (2003) developed
GIS methodology for same through a spatial analytical procedure combining elements fromthe techniques of spatial multicriteria analysis and fuzzy logic. In U.S., several methodologies
and standards have been developed, such as Hazard- United States (HAZUS) and Applied
Technology Council (ATC), which provide comprehensive earthquake loss estimation
methodology for post-earthquake assessment (Korkmaz, 2009). In Nepal six different
methodologies have been used for evaluation of earthquake risk: KVERMP (Kathmandu
Valley Earthquake Risk Management Program) methodology, RADIUS (Risk Assessment
Tools for Diagnosis of Urban Areas against Seismic Disasters) methodology, GIS (Geographic
Information System) in Grid, SLARIM (Strengthening Local Authorities in Risk Management)
methodology (GIS based), community watching (Community Based Disaster Risk
Management Program) and HAZUS (Hazards-United States) methodology (Guragain, Jimee,& Dixit, 2008). The overall comparison of various loss estimation processes is summarized intable 1.
Among these processes RADIUS is more convenient to use for its simple methodology and it
does not require detail technical knowledge on earthquake engineering (Guragain, Jimee, &Dixit, 2008). But, the process has become more and more complex in terms of handling a large
amount of spatial data with subsequent analysis (Guragain, Jimee, & Dixit, 2008). So, GIS
based RADIUS (GBR) has been developed integrating RADIUS with GIS to simplify theprocess (RADIUS, 2000). RADIUS initiative was launched in 1996 by the secretariat of theInternational Decade for Natural Disaster Reduction (IDNDR 1990-2000) of the United
Nations to develop seismic risk assessment and management tools to reduce the effects ofseismic disasters in urban areas, particularly in developing countries (RADIUS, 2000 and
Villacis, 2000). Under RADIUS initiative, a methodology was developed by GeoHazards
lnternational for implementation of case studies in nine cities around the world. Based on ninecase studies, OYO Group, Japan (OYO Corporation and OYO International and coded by
Geosoft Technical Support Singapore and Risk Management Software India) developed acomputer program in excel, for earthquake damage estimation, providing a basis for similar
efforts as a first step of earthquake risk management for other cities in developing countries tounderstand the seismic vulnerability of cities, to raise awareness and encourage the start ofdisaster prevention programmes (GHI, 2004 and RADIUS, 2000). Figure 2 shows general flow
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of GIS based RADIUS methodology along with required inputs and generated output. It
requires input of a simple data set which is organized in GIS. After analyzing in RADIUS, theresults can be represented in GIS maps to show the spatial distributions of the seismic damage
states (Alam, Tesfamariam, & Alam, 2012). So, in this study GIS based RADIUS methodology
was followed for earthquake damage estimation in Mymensingh Municipality. This study was
conducted in November, 2013.
Damage estimation in GIS based RADIUS is generally carried out by subdividing the study
area (Alam, Tesfamariam, & Alam, 2012). So, firstly the area of Mymensingh municipality is
divided into equal-sized square grids in GIS, where the grid size is defined 1 sq.km. Then the
input values are assigned to each of the grids to obtain spatially distributed outputs in RADIUS.
RADIUS tool only requires total night-time population of the study area from which day-time
population and population distribution in each mesh is calculated by predefined factors in thetool. In RADIUS methodology, building inventory is required in different format. In
Mymensingh municipality, data on total number of buildings, grid by grid number of buildings
and grid by grid percentage of buildings of each class are collected and calculated in GIS andthen inputted in RADIUS. In table 2 classifications of building types used in RADIUS andbuilding stock in Mymensingh Municipality in terms of percentage are described. Weight ofeach mesh is defined based on relative building density and population density in each meshunit. Categories of mesh weight in RADIUS are: 0 (none), 1 (low), 2 (average), 3 (high) and 4(very high).
For hazard assessment, five ground classifications have been adopted in the RADIUS tool,
based on the surface soil. They are: hard rock, soft rock, medium soil, soft soil and unknown
soil (for the convenience of the users). It is used to evaluate the site amplification ratio inearthquake scenario study. Again, different seismic scenarios for the municipality are
determined on the basis of past earthquake history of the study area. Tectonically, Bangladesh
lies in the north eastern Indian plate and at the junction of three tectonic plates–the Indian plate,the Eurasian plate and the Burmese microplate (Akhter, 2010). OYO International Corporation(OIC) proposed four earthquake scenarios for Bangladesh, where each scenario was set as a
maximum possible earthquake occurring within each of the five major fault zones (CDMP,
2009b). The history of severe earthquake in Mymensingh municipality is described in table 3.
A powerful earthquake needs at least 100-150 years to be originated for a particular region(CDMP, 2009b) and it is overdue for Mymensingh municipality, as 129 years and 117 years
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have passed by since earthquake from Madhupur Fault and Dauki fault hit the region
respectively (Table 3). So, scenarios of earthquakes generated from these two faults are
considered as scenario earthquakes for damage estimation in Mymensingh municipality (Table
4).
The time of occurrence for the scenario earthquake are specified 2 am and 2 pm, because thecasualty count depends on whether the earthquake occurs during night or day (Alam,
Tesfamariam, & Alam, 2012). In RADIUS tool, two seismic intensity scales are adopted:
Modified Mercalli Intensity (MMI) peak ground acceleration (PGA), where PGA is calculated
by one of three of the most popular attenuation formulas and converted to MMI using theempirical formula of Trifunac and Brady (1975) (Table 5). Average MMI for Dauki and
Madhupur earthquake scenarios in Mymensingh municipality are 5.95 and 6.35 respectively.
So, earthquake from Madhupur fault will have greater impact on the area. For Dauki and
Madhupur earthquake scenarios, the north-eastern and south-western part of the area will havegreater probable intensity respectively.
The tool gives vulnerability curves for each of the building categories, which show the
relationship between the mean damage rate and seismic hazard (MMI or PGA). Combining all
the factors with the calculated seismic intensity distribution, building damage of Mymensinghmunicipality is estimated. Casualties (injury and death) are calculated in RADIUS from thenumber of damaged buildings. It varies with the time of earthquake occurrence: the day (6 am– 6pm) and night (6pm – 6am) as, the number of inhabitants residing inside buildings during
the earthquake are normally not the same during day and night time (Alam, Tesfamariam, &Alam, 2012). Thus earthquake damage estimation was done in RADIUS tool.
4. Results and Discussion
4.1 Estimated Damage in Mymensingh Municipality
Total number of damaged building for Dauki and Madhupur earthquake scenarios are 1174 and2023 respectively. So, building damage is greater for Madhupur earthquake scenario. Figure 3
shows mesh-by-mesh damaged building count in Mymensingh municipality for two scenario
earthquakes. For Dauki earthquake scenario, most of the meshes contain 35 to 55 damagedbuilding each, where building damage ratio is between 2.00 and 2.80, and for Madhupur
earthquake scenario, most of the meshes contain 60 to 100 damaged building each, wherebuilding damage ratio is between 3.14 and 4.97. Though impact from Madhupur earthquake
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scenario is greater; higher damaged building count and damage ratio can be observed in almost
same areas for two scenario earthquake events. Again, for both scenario earthquakes casualty
is greater for earthquake event occurrence at night and it is higher for Madhupur earthquake
scenario. Figure 4, 5, and 6 represent mesh-by-mesh death count, severe injury count, andmoderate injury count in Mymensingh municipality for two earthquake scenarios occurring at
day or night. Though casualty from Madhupur earthquake scenario (night-time occurrence) isgreater; higher casualty (death and injury) can be observed in almost same areas for two
scenario earthquake events and two occurrence times.
4.2 Use of the Estimated Damage: Earthquake Risk Management Planning
Earthquake risk can be reduced by coordinating and focusing on risk management activities tomaintain community safety, to reduce physical damage and socio-economic disruption and; toreduce potential impact of large earthquakes on urban societies by timely and correct action
after a disastrous earthquake (Pitilakis, & Kalliopi, 2011). Chile's earthquake (2010) was larger
but less destructive than Haiti's (2012) which represent the importance of disaster preparedness
in preventing possible disastrous events or at least minimizing their impacts on the society(Wayman, 2010 and Bapat, 2010). The preparation of earthquake preparedness plans based on
the assessment of the impact of earthquakes and the minimization of their consequences are
the most important tasks of civil protection (Pitilakis, & Kalliopi, 2011).
The results of GIS based RADIUS analysis emphasize the importance of earthquake risk
reduction in Mymensingh municipality. So, the estimated damage can be regarded as apreliminary estimation for earthquake risk management in the municipality. The results givethe spatial idea about the potential losses, which can be integrated mainly in preparedness,
response and recovery steps of earthquake disaster management. From the damage maps,
potential risky areas in the municipality can be found out to take mitigation steps respectively.
It will guide to improve the seismic performance of existing structures, improve safety inschool buildings, and help the decision makers to integrate seismic resistance into new
construction processes. From the damaged buildings count in the municipality, distribution ofinternal displaced people can be estimated, which will further guide to take preparedness
through earthquake shelter planning. Casualties (death and injury) caused by the seismic events
are the main social damage parameters (Alam, Tesfamariam, & Alam, 2012). Overall damage
scenario will help to increase awareness among the local people of the municipality about theearthquake risk, to increase preparedness for earthquake, to take part in the preparation ofearthquake preparedness plan, and most importantly to improve emergency response planning
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and capability. The results also provide a preliminary estimation of severe and moderate injury
for the decision makers to plan and to be prepared for taking actions according to therequirement and guide the first responders for quick response during a disaster, e.g. first aid,
hospital requirement, emergency treatment requirement etc. It will also help the authority to
immediately take decision to repair or retrofit vulnerable buildings and to take preparation for
long-term community recovery after an earthquake. Thus, the estimated earthquake damage of
Mymensingh municipality will help to guide the future development activities of themunicipality.
5. Conclusion
GIS based RADIUS methodology is very useful for quick earthquake damage estimation totake immediate steps for earthquake disaster risk management, though it has some limitations.
For its simple methodology, its function and accuracy is limited (GISdevelopment, n.d.), where
quantification of this uncertainty in the results is not addressed within the framework (Alam,
Tesfamariam, & Alam, 2012). To simplify the methodology, fragility functions generalize both
reinforced concrete (RC) and masonry buildings, which does not match with the real-lifescenario (different damage pattern for a particular seismic activity) and thus develops someuncertainty and similar uncertainty can be observed for building occupancy classes (Alam,
Tesfamariam, & Alam, 2012). Another fact is that earthquakes and their impacts differ widely,which is not considered in the methodology. So the results cannot be used for detailed analysis:exact engineering analysis, site specific earthquake analysis etc and for exact engineering
decision making (GISdevelopment, n.d.). So, the tool should be used for only preliminary
estimation, where further validation and more detailed studies should be done (RADIUS, 2000).
It is hoped that the results of the earthquake risk assessment in Mymensingh municipality willassist the decision makers to understand the risk of the municipality to earthquake, to takeinitiatives for earthquake risk management in the municipality, to promote awareness among
the local people to contribute in the management process and most importantly to assist starting
preparedness programmes for future earthquake disasters in Mymensingh municipality.

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60. Watson Jr, C.C., & Johnson, M.E. (2004). Hurricane loss estimation models: Opportunities
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62. Whitman, R.V., Anagnos, T., Kircher, C.A., Lagorio, H.J., Lawson, R.S., & Schneider, P.
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http://ares.tu.chiba-u.jp/~papers/paper/ICOSSAR/ICOSSAR1997-1Early.pdf

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Figure 1: Location Map of Mymensingh Sadar Upazila in Mymensingh District (Source:
LGED, 2012 and Muhit, Roy, Rahman, and Ahamed, 2011)93

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Figure 2: Process of earthquake damage estimation in GIS based RADIUS methodology

Figure 3: Mesh-by-mesh damaged building count in Mymensingh municipality for two
scenario earthquakes (Dauki and Madhupur)

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Figure 4: Mesh-by-mesh death count in Mymensingh municipality for two scenario
earthquakes (Dauki and Madhupur) at two occurrence times (2am and 2pm)

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Figure 5: Mesh-by-mesh severe injury count in Mymensingh municipality for two scenario
earthquakes (Dauki and Madhupur) at two occurrence times (2am and 2pm)

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Figure 6: Mesh-by-mesh moderate injury count in Mymensingh municipality for two scenario
earthquakes (Dauki and Madhupur) at two occurrence times (2am and 2pm)

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Table 1: Comparison of earthquake loss estimation methodologies (Source: Guragain, Jimee,& Dixit, 2008)
Stakeholders involvement
Possibili
Motivati
Resour ty of use
AccuraMethodolo
on to
ce
in
cy
Profession Authoriti Commungycommunirequire developi
als
es
ity
ty
d
ng
countries
CommunityLowMedium
High
High
Low
Low
Yes
Watching
HAZUS
High
Low
Low
Low
High
High
Yes
Mediu
RADIUS
MediumHigh
Medium
High
Low
Yes
m
GIS based
Mediu
High
Low
Low
Low
High
Yes
RADIUSm–highTable 2: Classifications of building types used in RADIUS and percentage in Mymensingh
Municipality (Source: adopted from RADIUS, 2000)
Buildingclass in
RADIUS
Residential 1

Residential 2

Residential 3

98

Type

Definition

DefinedheightInformal construction

Mainly slums and row housing
made from unfired bricks, mudmortar, loosely tied walls androofs

Building stockin
Mymensingh
Municipality
(%)

n.d.

29.14

Substandard construction, notcomplying with thelocal building code provisions

up to 3stories

42.05

4–6 stories

1.27

n.d.

9.94

up to 2stories

1.89

higher than
2 stories

0.27

Low- tomedium-rise

0.19

High-rise

0.0

n.d.
n.d.

12.53
2.72

Unreinforced masonry(URM)-reinforced
concrete composite
construction
URM-reinforced
concrete composite
construction

Residential 4

Engineered reinforced
concrete construction

Educational 1

School buildings

Educational 2

School buildings

Medical 1

Hospitals

Medical 2

Hospitals

Commercial
Industrial

Shopping centers
Industrial facilities

Old, deteriorated construction,
not complying with the latest
building code provisions
Newly constructed multistory
buildings for residential andcommercial purposes
Generally, the percentage ofthis type of building should bevery low
Generally, the percentage ofthis type of building should bevery low
Generally, the percentage ofthis type of building should bevery low
Generally, the percentage ofthis type of building should bevery low
n.d.
n.d.

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Table 3: History of earthquake in Mymensingh municipality (Source: Akhter, 2010 and The
Daily Star, 2008)
Name ofYear
Magnitude
OriginComment
earthquake
1822 Kishoreganj
7.1
Kishoreganj
Caused severe damage
1846 Mymensingh
Mymensingh
Three foreshocks occurred
6.4
Many structures were damaged
1885 Bengal
Madhupurone of the most severe earthquakes
7.0
Fault
eleven aftershocks occurred1897 Great Indian
Dauki Fault
one of the most powerful and8.7
destructive earthquakes in recorded
history
1923 Meghalaya
7.1
Meghalaya
Hundreds of aftershocks occurred2008 Mymensingh
Madhupur
Caused heavy damage
5.1
Fault
Table 4: Earthquake scenarios for Mymensingh municipality
Dauki earthquake
Madhupur earthquake
Scenario
scenario
scenario
Occurrence time
2am and 2pm
2am and 2pm
Earthquake Magnitude (Mw)
8.0
7.5
Depth to top
3
10
of fault (km)Earthquake direction relative from
North-east
South-westreference mesh
Earthquake distance (km) to reference
87.9
58.3
mesh
Table 5: Attenuation equations and empirical formula adopted in RADIUS (Source:
RADIUS, 2000)
Equation Source
Attenuation Equation
Joyner & ��� = ���(�.�����)����(�)�(�.�������)��.��]
1
Boore
�
� = �(�� � �. �� )(1981)
Campbell ��� = �. ���� � ���(�. �� � �) � ���.��
2(1981)
� = � � ��. ��� � ���(�. ��� � �)]
Fukushim(�.����) ��a& ��� = ����(�.����)� ����� �� � �.������
� �. ���� � (�3Tanaka� �. ��)] � ���(1990)Or, ��� =Trifunac & Brady ���(��� � ���) = (�. � � ���) � �. ��� ,���(�������)(1975)
� �. ���
�.�
E = Epicentral distance, R = Hypocentral distance, M = Earthquake magnitude, PGA unit ‘g’9999PART-VIII
EVALUATION OF LOAD CARRYINGCAPACITY OF PRECAST CONCRETE PILESBASED ON CPTBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA
Prepared By: Mominur Rahman
Mehedi Ahmed Ansary100March 2015

1

GENERAL

The study location is at a site in Siddhirganj. In this site seven CPT and twelve SPT have been
carried out. In this chapter pile capacity has been estimated from CPT and SPT methods
discussed in chapter 2.
2

GEOLOGY OF THE PROJECT

According to geological map of Bangladesh published in 1990 geological characterictics of
Siddhirganj is described. Geology of this location is alluvial silt – light to medium grey, finesandy to clayey silt. Commonly poorly stratified; average grain size decreases away from main
channels. Chiefly deposited in flood basins and interstream areas. Unit includes small
backswamp deposits and varying amounts of thin, interstratified sand, deposited during
episodic or unusually large floods. Illite is the most abundant clay mineral. Most areas areflooded annually. Included in this unit are thin veneers of sand spread by episodic large floods
over flood-plain silts. Historic pottery, artefacts, and charcoal ( radiocarbon dated 500-6000
yrs. B.P.) found in upper 4 m.
3

SUBSOIL INVESTIGATION BASED ON SPT

Figure 1 represents the site plan showing the five sections of soil profiles, location of twelve
bore holes for SPT values and location of seven CPT points. Figures 2-6 describe the five soil
profile sections having twelve bore holes which exhibit SPT values with depth, visual soil
classification and thickness of soil layers. RL of the site is not the same. RL is 5.7m for bore
hole no. 02, 03,04, 05, 06, 07, 08, 09, 10, 11 and RL is 4.0m and 5.3m for bore hole no. 12 and
01 respectively.
The soil of the site is very erratic in nature. The predominant soil of the whole site is clay andthe thickness of the clay layers varies drastically among the bore holes. The maximum andminimum thickness of clay layers is 26m and 12m respectively when total depth of all bore
holes is 26m. For bore hole no. 05 and 06, soil of 26m depth is clay; for bore hole no. 3, 8, 9,
11and 12 the maximum 6m top soil is either fine sand or nonplastic silt when the soil of theremaining depth is clay; for bore hole no. 1, 7 and 10 the maximum 16m top soil is clay when
the soil of the remaining depth is nonplastic silt and clay; for bore hole no. 4, the 8m top soil
102

101

BNUS Annual Report-2014

ICUS Report 76

is fine sand, clay and nonplastic silt when the soil of the remaining depth is clay; for bore holeno. 2, the 2m top soil is nonplastic silt,then 18m depth is clay, then 2m depth is nonplastic silt
and the remaining depth is clay.
4

SUBSOIL INVESTIGATION BASED ON CPT

Figure 7-13 presents cone tip resistance, shaft friction, friction ratio and soil classification forseven different locations. The total depth of the soil profile tested for CPT data is variable andthe maximum total depth is 22m. From seven CPT points it is seen that the soil of the whole
site is erratic and the predominant soil of the site is cohesive soil. For soil profiles as shown in
Figures 7, 10 and 12, the plus and minus 18m top soil is cohesive soil (clay, silty clay) and theremaining soil of the profiles is cohesionless soil ( nonplastic silt, silty sand). For soil profiles
as shown in Figures 8, 9 and 13, the 2m top soil is fine sand and the remaining soil of the
profiles is cohesive soil ( clay, silty clay) except 1m nonplastic silt existing in the soil profileas shown in Figure 13. For soil profile as shown in Figure 11, the 2m top soil is fine sand, thebottom soil below 19.5m depth is nonplastic silt and the remaining 17.5m middle soil of the
profile is cohesive soil ( clay, silty clay).
5

INTERPRETATION OF SOIL PROFILE FROM CPT

In this report, soil classification chart by Robertson and Campanella as presented in Article
2.5 is used to identify the soil layers. This method is selected since it is simple and provides
output that can be easily understood. Douglas and Olsen chart shows the soil classification
change (diagonally) from SP to SM to ML to CL to CH as the cone tip resistance decreases
and friction ratio increases. Douglas and Olsen (1981) method demonstrates that the CPT
classification charts cannot provide an accurate prediction of soil type based on soil
composition, but rather serve as a guide to soil behavior type. Figures 7-13 present CPT as well
as soil classification after Robertson and Campanella.

102

103

B

E

A

C

104
B

E

A

103

Figure 1. Layout of bore holes and sections

C

D

D

March 2015

BNUS Annual Report-2014

104
3

2

12

14

Depth(m)
26

24

22

20

18

4

4

5

16

15

Clay

3

12

Clay

26

32

24

26

31

20

21

Nonplastic Silt

5

Clay

N-values
16 24

Nonplastic Silt

24

22

20

18

16

3

2

5

10

14

8

4

2

2

8

6

4

2

0

0

8

6

4

2

0

26

24

22

20

18

16

14

12

10

Depth(m)

16

4

3

3

5

5

4

Nonplastic Silt

N-values
8
16

10

8

6

4

2

0

0

RL=5.70 m

0

2

2

1

4

Clay

6

6

4

3

4

5

24

23

21

N-values
16
24

Fine Sand

8

27.7

25.7

23.7

21.7

19.7

17.7

15.7

13.7

11.7

9.7

7.7

5.7

3.7

1.7

0

8

7

5

4

3

3

2

8

RL=4.0 m
N-values
24
32

16

14

16

14

12

Clay

Nonplastic Silt

Rubbish

16

40

50

48

ICUS Report 76

BORE HOLE 12

Depth(m)BORE HOLE 11

BORE HOLE 10

Depth(m)BORE HOLE 09

Figure 2. Geotechnical Characterization, Section-AA

105

106
12.4

10.4

8.4

6.4

4.4

2.4

0.4

105
Depth(m)

26.4

24.4

22.4

20.4

18.4

16.4

14.4

0

1

5

13

10

8

21

Clay
24

28

Clay

N-values
16
24
32

Nonplastic Silt

4

2

8

RL=5.3 m

31

36

40

50

48

2

1

1

26

24

22

24

N-values
16

8

13

12

Clay

22

22

20

17

32

40

30

36

31

Clay

Nonplastic Silt

8

Nonplastic Silt

20

18

16

14

12

10

8

6

4

2

0

0

RL= 5.7 m

6

8

5

26

24

22

20

18

16

14

12

10

8

12

13

10

8

6

11

10

3

2

4

Nonplastic Silt

6

4

N-values
8

Fine Sand

Clay

2

0

0

Clay

26

24

22

20

18

16

14

12

10

8

6

4

2

0

8

4

2

2

3

5

5

4

4

5

5

4

2

Fine Sand

N-values
08March 2015
BORE HOLE 08

Depth(m)BORE HOLE 04

Depth(m)BORE HOLE 02

Depth(m)BORE HOLE 01

Figure 3. Geotechnical Characterization, Section-BB

BNUS Annual Report-2014

12

10

8

6

4

2

0

106
Depth(m)
26

24

22

20

18

3

2

5

5

5

3

3

2

10

20

18

17

14

Clay

Nonplastic Silt

N-values
8
16

6

8

5
Clay

Fine Sand

N-values
8

26

24

22

20

18

Clay

16

14

12

10

8

12

13

10

8

6

11

10

3

2

4

Nonplastic Silt

6

4

2

0

0

26

24

22

20

18

16

14

12

10

8

6

4

2

0

0

1

4

3

1

8

10

9

20

17

15

28

25

40

34

38

32

Clay

Clay

24

N-values
16

N-values
8
16

26

24

22

20

18

16

14

2

4

4

5

4

3

12

3

5

5

4

3

8

6

4

2

16

15

Clay

Nonplastic Silt

0

0

10

Depth(m)

16

14

0

RL=5.70 m

3
12

Clay

Nonplastic Silt

5

Clay

26

32

24

26

31

20

21

N-values
16 24

Nonplastic Silt

24

22

20

18

16

3

2

5

10

14

8

4

2

2

8

6

4

2

0

0

ICUS Report 76

BORE HOLE 10

Depth(m)BORE HOLE 09

BORE HOLE 05

Depth(m)BORE HOLE 04

Depth(m)BORE HOLE 03

Figure 4. Geotechnical Characterization, Section-CC

107

108

107

8

13

12

26

24

22

Clay

22

22

20

17

Clay

Nonplastic Silt

20

40

30

36

31

32

26

24

22

20

18

16

14

12

10

8

6

4

2

0

Depth(m)

18

2

1

1

24

N-values

16

Nonplastic Silt

8

8

16

N-values

3

2

5

5

5

3

3

2

10

20

18

17

14

Clay

Nonplastic Silt

0

26

24

22

20

18

16

14

3

2

2

2

10

12

2

4

3

2

8

24

18

16

14

12

11

Clay

16

N-values

8

6

4

2

0

0

26

24

22

20

18

16

14

3

2

2

2

10

12

2

4

3

2

16

24

18

16

14

12

11

Clay

8

N-values

8

6

4

2

0

0

RL=5.70 m

8

6

4

2

0

12

10

26

24

22

20

18

16

14

Depth(m)

16

14

12

10

8

6

4

2

0

0

RL=5.70 m

0

2

8

7

5

6

6

11

Clay

N-values
16 24 32

Clay

26

26

22

Nonplastic Silt

4

8

37

34

40

26

24

22

20

18

16

14

12

10

8

6

4

2

8

4

2

2

3

5

5

4

Clay

4

5

5

4

2

Fine Sand0

N-values
08March 2015
BORE HOLE 08

Depth(m)BORE HOLE 07

BORE HOLE 06

Depth(m)Figure 5. Geotechnical Characterization, Section-DD

BORE HOLE 06

Depth(m)BORE HOLE 03

BORE HOLE 02

Depth(m)Figure 6. Geotechnical Characterization, Section-EE

BNUS Annual Report-2014

ICUS Report 76

Shaft friction,f s (KPa)

Cone resistance, qc (MPa)
0

2

4

6

8

10

12

0

0

50

100

Friction ratio, %

150

200

0 2 4 6 8 10 120Cone resistance, qc (MPa)

2
0

2

4

6

8

10

0

Shaft friction,f s (KPa)

2
12

0

50

100

150

2 Friction ratio, %
200

Clay

0 2 4 6 8 10 12

0

4

4

2

2

6

6

4

4

8

8

6

6

6

10

10

10

8

8

8

12

12

12

10

10

10

14

14

14

12

12

12

16

16

16

14

14

14

18

18

18

16

16

16

20

20

20

18

18

18

22

22

22

20

20

20

24

24

24

22

22

22

Depth (m)Depth (m)Figure 7 Cone Tip Resistance, Shaft Friction and Friction Ratio with
Depth

0

0
4
2
6
4
8

Figure 7 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth
24

Clay

24

24

Silty Clay

Silty Clay

Nonplastic
Silt

Nonplastic
Silt

Soil Classification basedon CPT (after Robertsonand Campanella)
Soil Classification basedon CPT (after Robertsonand Campanella)

108
108

109

March 2015

0

Shaft friction,f s (KPa)
Hundreds
0.25 0.5 0.75
10Shaft friction,f s (KPa)
Hundreds
0.25 0.5 0.75
1Cone resistance, qc (MPa)
0

1

2

3

4

0

0

Fine Sand
Friction ratio, %0 2 4 6 8 10 120

Fine Sand
Cone resistance, qc (MPa)
0
02

1

2

3

4
02

Friction ratio, %0 2 4 6 8 10 12

Clay

02

24

24

24

46

46

46

68

68

68

8
10

8
10

8
10

Depth (m)Depth (m)Figure 8 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth

Clay

Silty Clay

10
12

10
12

10
12

Silty Clay

12
14

12
14

12
14

14
16

14
16

14
16

16
18

16
18

16
18

Figure 8 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth
18

18

Soil Classification
based on CPT (after
Robertson andCampanella)
Soil Classification basedon CPT (after Robertsonand Campanella)

18

109

BNUS Annual Report-2014

110
109

ICUS Report 76

Fine Sand0

Cone resistance, qc (MPa)

Shaft friction, f s (KPa)

1

0

2

3

4

25

50

Friction ratio, %

75

100

0

0

0

2

4

6

8 10 120Fine Sand
Cone resistance, qc (MPa)
0

1

2

3

Shaft friction, f s (KPa)
0

4

25

50

75

Friction ratio, %
100

0

0

2

2

0

2

4

6

8 10 12

Clay

0

2

Clay
2

4

4

4

4

4

6

6

Depth (m)

6

6

6

6

8

8

Depth (m)Figure 9 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth

2

2

4

8

8

8

8

10

10

10

10

10

10

12

12

12

14

14

14

14

14

14

16

16

16

Soil Classification basedon CPT (after Robertsonand Campanella)
Soil Classification basedon CPT (after Robertsonand Campanella)

Figure 9 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth
16

Silty
Clay

12

12

12

Silty
Clay

16

16

110

111
110

March 2015

0

2

4

6

8

10

12

14

16

0

0

0

2

2

4

50

100

150

200

0

250

2

4

6

8

10

12

14

0
0

2

2

2

3

4

50

100

150

200

Silty
Clay

Friction ratio, %Shaft resistance,fs(KPa)
16

1

Silty
Clay

0

0

Cone resistance, qc (MPa)0Friction ratio, %Shaft resistance,fs(KPa)

Cone resistance, qc (MPa)

0

250
0

4

2

2

1

2

3

4

4

4

6

4

6

4

6

Clay

8

8

Depth (m)

6

10

6

8

8

6

10

8

8

10

Depth (m)Figure 10 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth

Clay

10

12

14

16

18

12

14

16

18

20

10

12

14

16

18

12

10

14

12

16

14

18

16

20

18

12

14

16

18

20

Figure 10 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth
20

Silty
Clay

Silty
Clay

Silty
Sand

Silty
Sand
Soil Classification
based
on CPT (after Robertsonand Campanella)
Soil Classification basedon CPT (after Robertsonand Campanella)

20

20

111

BNUS Annual Report-2014

112
111

ICUS Report 76

Shaft friction,fs (KPa)

Cone resistance,qc ( MPa)
0

2

4

0

6

30

60

90

120

0

0

0

2

4

2

4

6

8

10

0

Shaft friction,fs (KPa)

Cone resistance,qc ( MPa)
0

Fine
Sand

Friction ratio, %

0

6

30

60

90

Friction ratio, %
120

0

2 0

2 0

4 2

4 2

4 2

4

6

8

10

Fine
Sand
Clay

Clay
6 4

6 4

6 4

8 6

8 6

8 6

10 8

10 8

10 8

Depth (m)

Silty
Clay

12 10

12 10

12 10

14 12

14 12

14 12

16 14

16 14

16 14

18 16

18 16

18 16

20 18

20 18

20 18

Depth (m)Figure11 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth

2 0

2

Silty
Clay

Nonplastic
Silt

Nonplastic
Silt
22 20

22 20

22 20

24 22

24 22

24 22

24

24

24

Figure 11 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth

Soil Classification basedon CPT (after Robertsonand Campanella)
Soil Classification basedon CPT (after Robertsonand Campanella)

112

113
112

March 2015

Shaft resistance,fs (KPa)

Cone resistance,qc (MPa)
0

2

4

6

8

10

12

14

0

0

50

100

150

Friction ratio, %
200

0

2

4

6

8

10

12

14

2

4

6

8

10

0

Shaft resistance,fs (KPa)

Cone resistance,qc (MPa)
0

0

0

50

100

150

Friction ratio, %
200

0

0
2

0
2

2
4

2
4

2
4

4
6

4
6

4
6

6
8

6
8

6
8

8
10

8
10

8
10

10
12

10
12

10
12

12
14

12
14

12
14

14
16

14
16

14
16

16
18

16
18

16
18

18
20

18
20

18
20

2

4

6

8

10

Silty Clay

Depth (m) Depth (m)Figure 12 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth

02Silty Clay

Silty Sand

20
22

20
22

20
22

22
24

22
24

22
24

24

24

24

Figure 12 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth

Silty Sand
Nonplastic
Silt

Nonplastic
Silt

Soil Classification basedon CPT (after Robertsonand Campanella)
Soil Classification basedon CPT (after Robertsonand Campanella)

113

BNUS Annual Report-2014

114
113

ICUS Report 76

Cone resistance, qc(MPa)
0

1

2

3

4

5

0

0

2

2
4

4
6

6
8

Depth (m) Depth (m)Figure 13 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth

0

8

10

10
12

12
14

14
16

16
18

18
20

1

2

3

4

40

60

80

100

4

6

8

10

12

10

12

Friction ratio, %Shaft resistance, fs (KPa)
5

2

0

0

20

40

60

80

100

0

120

0

0

2

2

2

2

4

4

4

4

6

6

6

6

8

8

8

8

10

10

2

4

6

8

Fine Sand
Clay

Clay

Silty
Clay

Silty

Clay
Nonplastic
Silt

Nonplastic
10

10

12

12

12

12

14

14

14

14

16

16

16

16

18

18

18

18

20

20

Figure 13 Cone Tip Resistance, Shaft Friction and Friction Ratio with Depth
20

0

120

0

Cone resistance, qc(MPa)020Fine Sand

Friction ratio, %Shaft resistance, fs (KPa)

20

20

Silt

Silty
Clay

Silty
Clay

Soil Classification basedon CPT (after Robertsonand Campanella)
Soil Classification basedon CPT (after Robertsonand Campanella)

114

115
114

March 2015

3.6

CHARACTERIZATION OF THE INVESTIGATED PILES

Seven square precast RC concrete piles depending on depth and soil characteristics are
considered in the current study. A summary of the characteristics of the investigated piles ispresented in Table 1. The piles are categorized based on the predominant soil type, pile type
and pile splicing..
Table 1: Seven precast piles investigated based on pile type, soil type, and pile splicing
355mm
Pile Type
SquareEndPrecast Pile Friction
bearing
Length
21m
1
1
15m
1
0
14m
1
0
20.5m
0
1
22m
1
0
20m
1
0
17m
1
0
Note: 1 = Yes, 0=No

3.7

Predominant Soil Type

Splicing of Pile

Cohesive

Cohesionless

Both

Yes

No

1
1
1
0
1
1
1

0
0
0
0
0
0
0

0
0
0
1
0
0
0

1
0
0
1
1
1
0

0
1
1
0
0
0
1

PREDICTED PILE CAPACITY USING SPT AND CPT DATA

Only seven piles depending on depth and soil characteristics are used in the analyses and mostof the piles are identified as friction piles. To predict the ultimate axial load capacity of thepiles, the methods used are the Schmertmann, de Ruiter and Beringen, Bustamante andGianeselli, Tumay and Fakhroo, Aoki and De Alencar, Price and Wardle, Philipponnat, andPenpile method. The ultimate load capacity for each pile is also predicted from the soil
properties (soil boring close to the pile) using the SPT data. The ultimate load carrying capacity
predicted by these methods (Qp) using the CPT data is compared to the pile capacity (Qm)obtained from the SPT data. Table 2 summarizes the results of the analyses conducted on theinvestigated piles. Among the data presented in Table 2 are: the pile size, type, length, thepredicted ultimate load carrying capacity from CPT, the predicted ultimate load carrying
capacity from SPT, average ultimate pile capacity for each pile and standard deviation for eachpile.
The predicted ultimate load carrying capacity (Qp) consists of pile tip capacity (Qt) and pile
shaft resistance (Qs). Comparison between the pile capacities Qt, Qs, and Qp predicted by the
116

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CPT methods and the pile capacities Qt, Qs, and Qm predicted by the SPT method. The resultsof five friction piles, one friction and end-bearing pile and one end-bearing pile are shown inthese figures. Inspection of these figures shows that the ratio Qt/Qp for the 5 piles is relatively
small, which is consistent with the previous classification of these piles as friction piles (pilecapacity is derived mainly from the shaft resistance). On the other hand, the ratio Qt/Qp for 1
pile is relatively large and hence this pile is considered as end bearing pile (pile capacity isderived mainly from the pile tip capacity).
The ratio Qt/Qp for 1 pile is almost one and hence this pile is considered as friction and end
bearing pile (pile capacity is derived mainly from the shaft resistance and pile tip capacity).
These figures also find out the method giving the maximum/minimum ultimate end bearing
capacity, the maximum/minimum ultimate shaft friction capacity, and the maximum /minimum
total ultimate pile capacity for seven piles.

116

117

118
117

117

Qs: Pile shaft capacity (friction), Qt : Pile tip capacity (end-bearing), Qu: Total ultimate capacity(Qs+Qt)

onon
squarereinforced
concretepilespiles
at a atsitea in
Table 3.2:
3.2: Results
Resultsof
ofthe
theanalyses
analysesconductedconducted
squarereinforced
concretesiteSiddhirganj.
in Siddhirganj.
Increaseor decrease
Pile
TP1,
355mm
SquarePrecastRC RC TP2,TP2,
355mm
SquarePrecastRC RC
Increaseor decrease
PileID
ID
TP1,
355mm
SquarePrecast
355mm
SquarePrecastofpilecapacity
Concrete
Pile(Spliced)
ConcretePileof pile capacity
Concrete Pile (Spliced)
Concrete Pile
comparedwith with
Pile
and
Soil
Pile
15 15
21 21
comparedPile and Soil
PileLength(m)Length(m)arithmetic
mean (in%) (in %)Identification
Embedded
15 15
21 21
arithmetic
mean
Identification
EmbeddedLength(m)Length(m)Pile
Friction
Friction
andandendendbearing
PileClassification
Classification
Friction
Frictionbearing
Predominant Soil
Cohesive
Cohesive
Predominant Soil
Cohesive
Cohesive
Qu
Qu
Qs
Qt
Qs
Qt
Predicted Ultimate
TP1
TP2
Qu
Qu
Qs
Qt
Qs
Qt
Predicted Ultimate
TP1
TP2
Load (KN)
Load (KN)
Schmertmann
453
450
240
94
2
-25
903
334
Methods ofSchmertmann
453
450
240
94
2
-25
903
334
Methodsofde Ruiter & Beringen
478
450
394
56
5
1
928
450
Predicting Pilede Ruiter & Beringen 905
478
5 64
1
Predicting
Pile LCPC
221450673 394 62 56281126928735 450
Capacity
by Cone
LCPC& Fakhroo
905
28 82
64
1126
Capacity
by TestCone Tumay
1028
417221
722 673 93 62
64
1445
815 735
Penetration
Tumay & Fakhroo
1028 303417
82
257
261 722 54 93-37 64 -30
5601445315 815
Penetration(CPT) Test Aoki & De Alencar
Aoki&&Wardle
De Alencar
257
Price
263
157303
129 261 33 54-52 -37 -64 -30
420560162 315(CPT)
Price & Wardle
263-64
Philipponnat
528
210157397 129 50 33-16 -52 0738420447 162
Philipponnat
5280
Penpile280
56210
142 397 23 50-62 -16 -63
336738165 447
Penpile
280
56
142
23
-62
-63
336
165
Pile Capacity by
847
630
540
61
67
34
1477
601
SPTCapacity by
Pile
847
630
540
61
67
34
1477
601
SPT
881
447
Arithmetic Mean
881
447
Arithmetic Mean
390
219
Standard Deviation
Qs: Pile shaft
capacity (friction), Qt : Pile tip capacity (end-bearing),
390Qu: Total ultimate capacity(Qs+Qt) 219
Standard
Deviation

March 2015

BNUS Annual Report-2014

749

722

722

554

1303

697

976

976

479

1176

461

119
118

118

Qs: Pile shaft capacity (friction), Qt : Pile tip capacity (end-bearing), Qu: Total ultimate capacity(Qs+Qt)

347
351
Standard Deviation
Qs: Pile shaft
capacity (friction), Qt : Pile tip capacity (end-bearing),
Qu: Total ultimate capacity(Q347351Standard
Deviations+Qt)Arithmetic Mean

Arithmetic Mean

SPT

Pile
PileID
ID

275

490

275

490

20

481

80

20

-2

TP5,
355mm
SquareTP6,
355mm
Square355mm
Squareor decrease
TP5,
355mm
SquareTP6,
355mm
Square TP7,TP7,
355mm
Square Increase
Increaseor decrease
PrecastRC
Concrete
Pile
PrecastRC
Concrete
Pile
PrecastRC
Concrete
Pile
of
pile
capacity
Precast RC Concrete Pile Precast RC Concrete Pile Precast RC Concrete Pile of pile capacity
comparedwith with
Pile and
Length(m)
20 20
17 17
22 22
compared
Pile
and Soil
Soil Pile
Pile Length(m)arithmetic
mean (inIdentification
Embedded
Length(m)201722arithmetic
mean (inIdentification
Embedded Length(m)
20
17
22
%) %)
Pile
Classification
Friction
Friction
Friction
Pile Classification
Friction
Friction
Friction
Predominant Soil
Cohesive
Cohesive
Cohesive
Predominant Soil
Cohesive
Cohesive
Cohesive
Qu
Qu
Q
Qs
Qt
Qs
Qt
Qs
Qt
Predicted Ultimate
TP5 TP6 TP7
Qu
Qu
Qs
Qt
Qs
Qt
Qs
Qt u Qu
Predicted Ultimate
TP5 TP6 TP7Load (KN)
Load (KN)
Schmertmann
333
321
497
434
318
98
-10
-5
-15
654
931
416
Methods ofSchmertmann
333
321
497
434
318
98
-10
-5
-15
654
931
416
MethodsofRuiter & Beringen
435
321
663
434
508
59
5
12
15
756
1097
567
Predicting Pile dede Ruiter & Beringen 738
435 164321 902756 1239663 272 434 15111097 667 508 42 59 709 56725
555
12
15
Predicting
Pile LCPC
44
Capacity
by ConeLCPC & Fakhroo
738 310164 1219
1239 406 272 145115111036 667 90 421126 70969 2555
44
902 1045
Capacity
by TestCone Tumay
909
49
129
Penetration
Tumay&
Fakhroo
909
310
1045
406
1036
90
69
49
129
1219
1451
1126
316
183
381
248
260
56
-31
-36
-36
499
629
316
Penetration(CPT) Test Aoki & De Alencar
Aoki
&
De
Alencar
316
183
381
248
260
56
-31
-36
-36
499
629
316
Price & Wardle
189
112
389
152
142
34
-58
-45
-64
301
541
176
(CPT)
Price & Wardle
189 148112 618301 673389 278 152 951 541 380 142 44 34 424 176-15 -58-45-64
Philipponnat
470
-3
-14
Philipponnat
470
148
673
278
380
44
-15
-3
-14
Penpile
206
40
108
24
-49
-59
246618 387
495 951 175
199 424-66
Penpile
206
40
387
108
175
24
-66
-49
-59
246
495
199
Pile Capacity by
749
554
697
479
461
20
80
20
-2
1303
1176
481
SPTCapacity by
Pile

Table 3.2: Resultsononsquarereinforced
concretepilespiles
at a atsitea incontinued
Table
Resultsof
ofthe
theanalyses
analysesconductedconducted
squarereinforced
concretesiteSiddhirganj,in Siddhirganj,
continued

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March 2015

3.8 APPLICABILITY OF THE VARIOUS METHODS USED FOR PREDICTING
PILE CAPACITY
Evaluating the performance of different pile capacity prediction methods is not an easy task. In thisstudy, an evaluation scheme using only analytical criteria is considered in order to observe theperformance of different CPT methods for predicting the ultimate axial capacity of piles. The
arithmetic mean and standard deviation of piles at seven locations( such as TP1, TP2, TP3, TP4, TP5,TP6 and TP7) for each method are calculated. The best applied method among nine methods is the one
which is closer to the mean of nine methods.
Ultimate pile capacities of piles at six locations calculated by Schmertmann method and de Ruiter andBeringen method are closer to mean of nine methods than any other methods except Philipponnat
method. All the values at six locations determined by these two methods are lying within plus andminus of one standard deviation.
Ultimate pile capacities for piles at five locations calculated by Schmertmann method tend tounderpredict the ultimate pile capacity by not more than 25% in comparison with the mean of nine
methods. This method uses sleeve friction,fs to calculate ultimate friction capacity of pile and sleeve
friction is lower in clayey soil which is predominant as shown in Figure 3.8. Ultimate pile capacities
for piles at two locations calculated by this method tend to overpredict the ultimate pile capacity.
According to CPT values as shown in Figure 3.10, this method exhibits 35% higher pile capacity thanthe mean of nine methods. In Figure 3.10 the bearing stratum of the pile is dense silty sand where highcone tip resistance exists. The ultimate end bearing capacity estimated by this method shows the largest
value because of not applying any reduction factor to cone tip resistance like only Tumay and Fakhroo
method. Besides this, ultimate shaft friction capacity by this method is lower, because cone shaft
friction exhibits lower value in predominant clayey soil. Philipponnat method estimates better resultsfor piles at all locations of this site fortunately, though it does not consider the consistency of cohesive
soil (soft or hard) to determine the ultimate shaft friction capacity,Qs of pile and assumes the same
empirical factor for all types of clay.
de Ruiter and Beringen method also exhibits relatively better performance. Ultimate pile capacities ofpiles at six locations calculated by this method are closer to mean of nine methods. Ultimate pile
capacity at CPT4 location is 46% higher than the mean of nine methods. In this method no reduction
factor is imposed in sandy soil to calculate ultimate end-bearing capacity like Schmertmann method.
This method assumes the larger empirical factor for soft clay and the lower empirical factor for stiff
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clay to calculate the ultimate shaft capacity of pile. Ultimate pile capacities for piles at seven locations
calculated by de Ruiter and Beringen method tend to overpredict the pile capacity. The maximum
value has been observed at CPT4 location as shown in Figure 3.10.
The performance of Bustamante and Gianeselli method (LCPC/LCP method) is not satisfactory at thisstudy. This method overpredicts the pile capacity by 24%-64% and the values at three locations arelying beyond one standard deviation. This method for the French Highway Department is based on
the analysis of 197 pile load tests with a variety of pile types and soil conditions. It utilizes cone tip
resistance,qc instead of shaft friction,fs to determine the ultimate shaft friction capacity,Qs. To
calculate shaft friction capacity it shows much larger value in clayey soil which is predominant at allseven CPT locations.
Tumay and Fakhroo method overpredicts the pile capacity excessively and pile capacities for piles at
six locations are beyond one standard deviation. In this method no reduction factor is assumed for cone
tip resistance,qc to calculate the ultimate end bearing capacity. Same adhesion factor is used both forcohesive and cohesionless soil to calculate the ultimate shaft friction capacity of pile and this factor
becomes very high when sleeve friction is very low.
Aoki and De Alencar method underpredicts the pile capacity and the results show the moderate
performance. This method assumes the identical empirical factor for both clayey and sandy soil to findout the ultimate end bearing capacity of pile. It does not consider the consistency of cohesive soil (softor hard) to determine the ultimate shaft friction capacity,Qs of pile and assumes the same empiricalfactor for all types of clay.
Both Price and Wardle method and Penpile method tend to underpredict the pile capacity seriously
and show the values beyond one standard deviation. Those are very conservative to calculate the pile
capacity. Penpile method uses empirical factor 0.25 for clay and 0.125 for sand to calculate the end
bearing capacity of pile when Price and Wardle method utilizes 0.35 for both types of soil. Bothmethod uses sleeve friction,fs to determine the shaft friction capacity.
The results of pile capacity have been estimated for different depths at seven locations using SPT
values. Arithmetic mean and standard deviation at different depths for those seven locations have also
been estimated. Ultimate pile capacities based on SPT values show the wide variation. Pile capacities
at five locations overpredict or underpredict the pile capacity satisfactorily. The rest of the piles at two
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March 2015

locations overpredict the pile capacity beyond one standard deviation. The soil of this site is very
erratic and the thickness of soil layers varies drastically throughout the soil layer. SPT is not reliablefor cohesive soil which is predominant for the whole site.
3.9

CONCLUDING REMARKSIn this chapter five soil profile sections having twelve bore holes describe SPT values with depth,
visual soil classification and thickness of soil layers. Cone tip resistance, sleeve friction, friction ratio
and soil classification at seven different locations are presented graphically. The results of the analyses
based on SPT and CPT data are conducted on square reinforced concrete piles at a site in Siddhirganj.
Applicability of eight CPT methods are focused to predict the ultimate axial compression load carrying
capacity of piles. The static analysis using the SPT method is applied to evaluate the load carrying
capacity for seven locations of the site. Ultimate pile capacity predicted by various methods of CPT
are compared graphically with the one predicted by SPT data. The pile size, type, length, the predicted
ultimate load carrying capacity from CPT, the predicted ultimate load carrying capacity from SPT,
average ultimate pile capacity, and standard deviation are presented in tabular form. The arithmetic
mean and standard deviation are calculated in order to observe the performance of different CPT
methods for predicting the ultimate axial capacity of piles. The four CPT methods, which are de Ruiterand Beringen method, Philipponnat method, Schmertmann method and Aoki and De Alencar method
show better performance than the currently used method based on SPT.

REFERENCES
Abedin, M. Z. et al. ( 1998). “ Ultimate Capacity of a Low Cost Pile Foundation in Soft Ground” ,Proceedings of Conference on Low and Low Medium Cost Housing Development, 9-10 July, 1998,
Kuching, Sarawak, Malaysia.
Ansary, M. A. et al. ( 1999). “ Status of Static Pile Lload Tests in Bangladesh” , Proceedings of theEleventh Asian Regional Conference on Soil Mechanics and Geotechnical Engineering, Seoul, Korea.
Aoki, N. and de Alencar, D.(1975). “An Approximate Method to Estimate the Bearing Capacity of
Piles”, Proceedings of the 5th

Pan-American Conference of Soil Mechanics and Foundation

Engineering, Buenos Aires, Vl. 1, pp. 367-376.
Bandini, P. and Salgado, R. (1998). "Methods of Pile Design Based on CPT and SPT results",
Proceedings of 1st International Conference on Site Characterization (P. Robertson and P. Mayne ed.),Balkema, Rotterdam, pp. 967 - 976.
Bowles, J.E.(1982). “Foundation Analysis and Design”, McGraw-Hill, Inc., New York, p.816.
Briaud, J-L and, Tucker, L.M.(1988). “Measured and Predicted Axial Response of 98 Piles”,
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Journal of Geotechnical Engineering, ASCE, Vol. 114, No. 8, pp. 984-1001.
Briaud, J-L et al. (1986). “H.M. Development of An improved Design Procedure for Single Piles inClays and Sands”, Report No. MSHDRD-86-050-1, Mississippi State Highway Department, Jackson,
MS, p. 192.
Bullock, P.J. et al.(2005). Side shear set-up I; Test piles driven in Florida. ASCE Journal of
Geotechnical and Environmental Engineering. 131 (3) 292-300
Bustamante, M., and L. Gianeeselli(1982). “Pile Bearing Capacity Predictions by Means of Static
Penetrometer CPT”, Proceedings of the 2nd European Symposium on Penetration Testing, ESOPT-II,
Amsterdam, Vol. 2, pp. 493-500.
Clisby, M.B. et al.(1978). “An Evaluation of Pile Bearing Capacities”, Volume I, Final Report,
Mississippi State Highway Department.Campanella, R.G., et al. (1989). "Use of In Situ Tests in Pile
Design", Proceedings of International Conference on Soil Mechanics and Foundation Engineering, pp.
199 - 203.
de Ruiter, J., and F.L. Beringen.(1979). “Pile Foundations for Large North Sea Structures”, Marine
Geotechnology, Vol. 3, No. 3, pp. 267-314.
Douglas, J.B. and Olsen, R.S.(1981). “Soil Classification Using Electric Cone Penetrometer,
Symposium on Cone Penetration Testing and Experience”, Geotechnical Engineering
Division, ASCE, St. Louis, pp. 209-227.
El-Sakhawy N.R. et al. (2008),” Prediction of the Axial Bearing Capacity of Piles by Five -Cone
Penetration Test Based Design Methods” ,(IAMAG),India.
Eslami, A., and Fellenius, B.H.(1997). “Pile Capacity by Direct CPT and CPTU Methods Applied to
102 Case Histories”, Canadian Geotechnical Journal, Vol. 34, pp. 886-904.
FDOT. (2010). Standard specifications for road and bridge construction 2010. Section 455-2.2.1.
Florida Department of Transportation, Tallahassee, Florida.
Fellenius, B. H., and Eslami, A. (2002). “Soil Profile Interpreted from CPT Data”, GeotechnicalEngineering Conference. Asian Institute of Technology. Bangkok. Thailand.18 p.
Fellenius, B. H., (1991). Summary of pile capacity predictions and comparison with observed behavior.
American Society of Civil Engineers, ASCE, Journal of Geotechnical Engineering, Vol. 117, No. 1,
pp. 192 - 195.
Fellenius B.H. (2008). Effective Stress Analysis and Set-up Capacity of Piles in clay. Geotechnical
Special Publication No. 180.ASCE
Hu, Z. (2007). Updating Florida Department of Transportation’s (FDOT) pile/shaft design procedures
based on CPT & DTP data. Ph.D. dissertation, University of Florida, Gainesville, Florida.
Lambe, W.T. and Whitman, R.V. (1986). Soil Mechanics, SI Version, John Wiley and Sons, Korea.
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Lehane, B.M. et al.( 2005). CPT based design of driven piles in sand for offshore structures. UWA
Report, GEO: 05345.
Long, J.H. and Wysockey, M.H.(1999). “Accuracy of Methods for Predicting Axial Capacity of Deep
Foundations”, ASCE Geotechnical Special Publication GSP 88, OTRC ’99 Conference, Analysis,
Design, Construction, and Testing of Deep Foundations, Austin, TX,
pp. 180-195.
Lunne, T. et al. (1997). “Cone Penetration Testing in Geotechnical Practice”, Blackie Academic andProfessional, London.
Meyerhof, G. G. (1956). "Penetration Tests and Bearing Capacity of Cohesionless Soils",
Journal of Geotechnical Engineering, ASCE, 82(1), 1- 19.
Paikowsky, G.S. (2004). Load and resistance factor design (LRFD) for deep foundations. NCHRP
Report 507.
Philipponnat, G.(1980). “Methode Pratique de Calcul d’un Pieu Isole a l’aide du Penetrometre
Statique”, Revue Francaise de Geotechnique, 10, pp. 55-64.
Price, G. and Wardle, I.F.(1982). “A Comparison Between Cone Penetration Test Results and the
Performance of Small Diameter Instrumented Piles in Stiff Clay”, Proceedings of the 2nd European
Symposium on Penetration Testing, Amsterdam, Vol. 2, pp. 775-780.
Robertson, P.K. and Campanella, R.G.(1984). “Guidelines for Use and Interpretation of theElectric Cone Penetration Test”, Hogentogler & Company, Inc., Gaithersburg, MD, Second
Edition, p. 175.
Robertson, P.K. (1990). Soil classification using the cone penetration test. Canadian Geotechnical
Journal 27(1): 151-158.
Robertson, P. K., and Campanella, R. G., (1989). Guidelines for use, interpretation, and application of
CPT and CPTU. Soil Mechanics Series, No. 105, UBC, Dept. of Civil Engineering.
Schmertmann, J.H.(1978). “Guidelines for Cone Penetration Test, Performance and Design”, U.S.
Department of Transportation, Report No. FHWA-TS-78-209, Washington, D.C., p.145.
Skempton, A.W.(1951). “The Bearing Capacity of Clays”, Proceedings Building Research
Congress, Vol. 1, pp. 180-189.
Sumanta H. and Sivakumar B.(2008),”Reliability measures for pile foundations based on CPT testdata”,NRC Canada.
Terzaghi, K. and Peck, R. B. (1948). Soil Mechanics in Engineering Practice, John Wiely
and Sons Inc., New York, N.Y.
Terzaghi, K. and Peck, R. B. (1967). Soil Mechanics in Engineering Practice, 2nd
Edition, John Wiely and Sons Inc., New York, N.Y.
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Togliani G.( 2008). “Pile Capacity Prediction for in Situ Tests”, Proceedings ISC-3. Taiwan, 11871192. Taylor & Francis Group, London, UK.
Tomlinson, M. J. (1971). Some effects of pile driving on skin friction, Proceedings of the Conference
on the Behavior of Piles, Institution of Civil Engineers, London, 107-14.
Tomlinson, M. J. (2001). Foundation Design and Construction. 7th ed., Pearson Education Ltd, Essex,
99 - 154.
Tumay, M.T.(1994). “Implementation of Louisiana Electric Cone Penetrometer System (LECOPS) for
Design of Transportation Facilities”, Executive Summary, Report No.
FHWA/LA-94/280 A&B. LTRC, Baton Rouge, LA.
Tumay, M.T., and Fakhroo, M.(1982). “Friction Pile Capacity Prediction in Cohesive Soils Using
Electric Quasi-Static Penetration Tests”, Interim Research Report No. 1, Louisiana
Department of Transportation and Development, Research and Development Section,
Baton Rouge, LA, 275 p.
Zhang, Z. and M.T. Tumay (2003). “Nontraditional Approaches in Soil Classification Derived fromthe Cone Penetration Test,” ASCE Special Publication No. 121 on Probabilistic Site Characterization
at the National Geotechnical Experimentation Sites, ISBN 0-7844-06693, pp. 101-149.
Zhou, J. et al. (1982). " Prediction of Limit Load of Driven Pile by CPT,” Penetration Testing, Proc.
2nd European Symp. Penetration Testing, ESOPT II, Amsterdam,Vol. 2, pp. 957-961.

124
125

PART-IX
MEASUREMENT OF VIBRATION ON UHA
TRADE CENTERBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Mehedi Ahmed Ansary126March 2015

1.

INTRODUCTION

Landlord of Uha Trade Center, Tejgaon requested us for measurement of vibration on theirbuilding due to a roller movement in a nearby road construction project at Hatirjheel.
This report presents the findings of the vibration test. Figure 1 shows the location of thesurveyed building with sensor locations and Figure 2 shows the measured building, the roller
and the measurement of building vibration using Microtremor observation system.

Figure 1: Location of Surveyed Building with Sensor Locations

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Figure 2 Measurement of building vibration using Microtremor observation system

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March 2015

2.

ACCEPTABLE VIBRATION LEVELS

Humans are very sensitive vertical vibration sensors, especially in environments like quiet
buildings. An example of human comfort limit is the restriction on the acceleration - human
begins to feel uncomfortable when the acceleration reaches about 0.02g:

Corresponding velocity at 16 Hz frequency is 1.96 mm/s.
According to [1], the allowable level of vibration acceleration at 16 Hz frequency is
28.0 mm/s2, while the allowable level of vibration velocity at the same frequency is
0.28 mm/s. The allowable levels of vibration for public buildings according to [1] are shownin Table 1.
Table 1: Allowable levels of vibration for public buildings

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3.

MEASUREMENT OF BUILDING VIBRATIONThe BUET team conducted vibration test for the BRAC Bank located at Usha Trade Center atambient state, with generator and with roller movement. The measurement is conductedsimultaneously at the ground (sensor 5), at the building’s 2nd floor (sensor 4), 3rd floor(sensor 3), 5th floor (sensor 2) and at the roof (sensor 5) of the building. The Fourier Spectraof the measured vibrations and corresponding predominant frequencies are shown in the next
few pages.
In the following table, the amplitude of vibration at different vibration state for the building
which is located around 400 ft from Hatirjheel area where a 5 ton roller is working, ispresented.
Condition

Ambient
noise

0.08

0.11

0.25

0.25

7-11

Allowablelevels ofvibration
for publicbuildings
fromTable 10.28-0.32

With
Generator
running inthebasement
With
Generator
running inthebasement
and a 5 ton
Rollerworking
about 400 ft
away

0.11

0.09

0.35

0.35

7-12

0.28-0.32

0.14

0.15

0.90

0.90

11

0.28

X

Measured value of building velocity (mm/s)
Y
Z
Maximum Corresponding
frequency (Hz)130

CommentNo
problemto thebuilding
May causeslightproblemto thebuilding
May cause
problemto thebuilding

131

March 2015

Location: 1X (Roof)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency
3

tes20150204_1158.xls
tes20150204_11585
Predominant Frequency = 3.0 Hz

Amplitude for ch-01

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT

With Generator runningin the basement

tes20150204_1237.xls
tes20150204_1237

35
Predominant Frequency = 3.0 Hz

Amplitude for ch-01

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT3

With Generator runningin the basement and a 5
ton Roller working
about 400 ft away

tes20150204_1451.xls
tes20150204_1451

11.1

5
Predominant Frequency = 11.1 Hz

Amplitude for ch-01

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT6

132

131

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Location: 1Y (Roof)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency
2

tes20150204_1158.xls
tes20150204_115810
Predominant Frequency = 2.0 Hz

Amplitude for ch-02

9
8
7
6
5
4
3
2
1
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT1

With Generator runningin the basement

tes20150204_1237.xls

2

tes20150204_123710
Predominant Frequency = 2.0 Hz

Amplitude for CH-02

9
8
7
6
5
4
3
2
1
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT4

With Generator runningin the basement and a 5
ton Roller working
about 400 ft away

tes20150204_1451.xls

11.1

tes20150204_145110
Predominant Frequency = 11.1 Hz

Amplitude for CH-02

9
8
7
6
5
4
3
2
1
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT7

132

133

March 2015

Location: 1Z (Roof)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency
7 & 10.5

tes20150204_1158.xls
tes20150204_11585
Predominant Frequency = 10.5 Hz

Amplitude for CH-03

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT2

With Generator runningin the basement

tes20150204_1237.xls
tes20150204_1237

7 & 10.65Predominant Frequency = 10.6 Hz

Amplitude for ch-03

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

12

14

16

18

20
FFT5

With Generator running White noisein the basement and a 5
ton Roller working
about 400 ft away

134

10

Frequency, Hertz

133-

BNUS Annual Report-2014

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Location: 2X (5th floor)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency

tes20150204_1158.xls
tes20150204_11585
Predominant Frequency = 3 Hz

Amplitude for CH-04

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT

With Generator runningin the basement

tes20150204_1237.xls
tes20150204_1237

5

Amplitude for CH-04

4.5

Predominant Frequency = 3 Hz

4
3.5
3
2.5
2
1.5
1
0.5
0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT3

tes20150204_1451.xls
tes20150204_1451

5
Predominant Frequency = 3 & 11.1 Hz

4.5

Amplitude for CH-04

With Generator runningin the basement and a 5
ton Roller working
about 400 ft away

0

4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT6

134

135

March 2015

Location: 2Y (5th floor)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency

tes20150204_1158.xls
tes20150204_11585
Predominant Frequency = 2 Hz

Amplitude for CH-05

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT1

With Generator runningin the basement

tes20150204_1237.xls
tes20150204_12375
Predominant Frequency = 2 Hz

Amplitude for CH-05

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT4

tes20150204_1451.xls
tes20150204_1451

5
Predominant Frequency = 2 & 11.1 Hz

4.5

Amplitude for CH-05

With Generator runningin the basement and a 5
ton Roller working
about 400 ft away

0

4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT7

136

135

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Location: 2Z (5th floor)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency

tes20150204_1158.xls
tes20150204_11585
Predominant Frequency = 10.6 Hz

Amplitude for CH-06

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT2

With Generator runningin the basement

tes20150204_1237.xls
tes20150204_12375
Predominant Frequency = 10.6 Hz

Amplitude for CH-06

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT5

tes20150204_1451.xls
tes20150204_1451

35
32.5

Predominant Frequency = 11.1 Hz

30

Amplitude for CH-06

With Generator runningin the basement and a 5
ton Roller working
about 400 ft away

0

27.5
25
22.5
20
17.5
15
12.5
10
7.5
5
2.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT8

136

137

March 2015

Location: 3X (4th floor)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency

tes20150204_1158.xls
tes20150204_11585
Predominant Frequency = 3 Hz

Amplitude for CH-07

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT

With Generator runningin the basement

tes20150204_1237.xls
tes20150204_1237

5

Amplitude for CH-07

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT4

tes20150204_1451.xls
tes20150204_1451

5
4.5

Amplitude for CH-07

With Generator runningin the basement and a 5
ton Roller working
about 400 ft away

0

4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT7

138

137

BNUS Annual Report-2014

ICUS Report 76

Location: 3Y (4th floor)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency

tes20150204_1158.xls
tes20150204_11585
Predominant Frequency = 2 Hz

Amplitude for CH-08

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT1

With Generator runningin the basement

tes20150204_1237.xls
tes20150204_1237

5

Amplitude for CH-08

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT5

tes20150204_1451.xls
tes20150204_1451

5
4.5

Amplitude for CH-08

With Generator runningin the basement and a 5
ton Roller working
about 400 ft away

0

4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT8

138

139

March 2015

Location: 3Z (4th floor)
Measurement Mode
Ambient noise

Fourier Spectrum

Predominant Frquency

tes20150204_1158.xls
tes20150204_11585
Predominant Frequency = 10.5 Hz

Amplitude for CH-09

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT3

With Generator runningin the basement

tes20150204_1237.xls
tes20150204_1237

5

Amplitude for CH-09

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT6

tes20150204_1451.xls
tes20150204_1451

30
27

Amplitude for CH-09

With Generator runningin the basement and a 5
ton Roller working
about 400 ft away

0

24
21
18
15
12
9
6
3
0

0

2

4

6

8

10

12

14

Frequency, Hertz

16

18

20
FFT9

4.
MEASUREMENT OF GROUND VIBRATION
The ground vibration is also measured and computed predominant frequency is presented in thefollowing figure.
Location: Ground
Measurement Mode

H/V Ratio

140

139

PredominantFrequency
BNUS Annual Report-2014

ICUS Report 76

Ambient noise

1.5 Hz

20
10
7
5

HVR

3
2
1
0.7
0.5
0.3
0.2
0.1
0.1

5.



HVRX15
HVRY150.2 0.3

0.5 0.7 1

2Frequency

3 4 5 6 7 8 1020

REMARKSThe predominant frequency of the building in X direction (NS) is around 3 Hz and along Y
direction is around 2 Hz.



The predominant frequency of the ground is around 1.5 Hz.

Additional frequency (around 11 Hz) is generated by a 5 ton roller working in the Hatijheel
area.



The amplitude of vibration caused by the roller is greater than the allowable levels ofvibration for public buildings, but is not high enough to cause damage to the building.
References

1. Federal Sanitary Norm of Russian Federation (1996). “SN2.2.4/2.1.8.566-96 – The sanitary
norms of industrial vibration, vibration of residential and public buildings, 1996”.
2. Winterkorn, H. F. and Fang, H. Y. (1975). Foundation Engineering Handbook publisher: Van
Nostrand Reinhold.

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PART-X
COMPARISON BETWEEN SMA AND
MICROTREMOR MEASUREMENT AT JAMUNABRIDGE SITESBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Mehedi Ahmed Ansary141March 2015

1. INTRODUCTION
An agreement has been signed on July 2014 between Bangladesh Bridge Authority (BBA) and
Bureau of Research, Testing, and Consultation (BRTC), Bangladesh University of Engineering andTechnology (BUET) for Consultancy Service for the Seismic Instrumentation Monitoring of
Bangabandhu Bridge. The BUET Consultant team has visited different free-field sites of Strong
Motion Devices as listed in the Inception Report (2014) and the Bridge site between November 10
and 23, 2014 and has carried out microtremor study both array and stand alone measurements. This
report has presented the findings of those study carried out at those free-field sites tabulated in Table
1.
Table 1 Free-field Instruments
Model

Type

Location

ETNA

LGED, Bogra

ETNA

LGED, Natore

ETNA

Triaxial Accelerometer

West-End of Bridge

ETNA(NS, EW, Vertical)

East-End of Bridge

ETNA

plus Digital Recorder

Police Staff College, Mirpur

ETNA

Hazicamp, Dhaka

ETNA (Portable)

BUET

2. BACKGROUND
The geotectonic set-up of Bangladesh suggests high probabilities of damaging future earthquakes
and the possibility of rarer but extraordinarily large earthquakes that can cause damage far from theirepicenters. Thus continuous watch of earthquake motion is necessary to predict and monitor theoccurrence of earthquake disaster.
Using microtremor for site response has been widely popular among developing countries and also inlower seismic areas. Kanai and Tanaka (1954) initially studied the applicability of Microtremor andthey had some limitations regarding the analysis. Afterward, based on their studies Nogoshi and
Igarashi (1971) introduced a method of using horizontal and vertical spectral amplitude ofMicrotremor readings which was later modified and popularized by Nakamura (1989). Nakamura
customized the new technique using the horizontal-to-vertical spectral ratio which is widely known
as H/V Method. Investigations have been going in general still now and more improvements aretaking place around the world consequently.

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Microtremor is a type of short term vibration, preferably termed as “Ambient Vibration” for thisspecial phenomenon, coming from lower amplitude. Generally, the vibrations can be caused due tonatural occurrences and sometimes caused by disturbance commenced by mankind. It is renowned
for the ease of using. It can be simply used in places of low seismicity and still give a good numberof information. Moreover it is inexpensive which makes it more convenient for developing country
like ours where resources are short. It can be really useful to obtain the key parameters in the site
response studies (site period, local site effects), soil-structure interaction studies, seismic hazard
studies, site geological conditions estimation (peak period of amplification) etc.
3. OBJECTIVE OF THE STUDY
In this study, the main objective is to report the preliminary factors that can give some perception
about the site response of the ground. Moreover, knowing one or two parameters, that hold thefundamental feature of the site response, can be helpful to resolve further seismic response
characteristics of surface ground and Bridge structures.
Monitoring the variation of the frequency is an important feature to perceive. The reasons of thosevariations should be observed closely. These variations can mainly occur due to the placement of theapparatus, time of data recording, soil condition, weather conditions, surrounding environment andespecially traffic conditions. These variations, while comparing with relevant data, give a definitive
point of view of the stability of the site. It also points out the obstacles to be covered up while
examining at another sites.
So, to summarize, the overall objectives are:
 Experimental determination of predominant frequency of site Investigational assessment of soil for vulnerability
Throughout this whole report these objectives have been pursued with the help of microtremor (MT)equipment and convenient locations have been selected.
4. OUTCOME OF THE STUDY
The H/V ratio method in the microtremor analysis is widely used for microzonation study and local
effects studies. But this research mainly emphasizes on observing and analyzing site response ofsoils and structures due to ambient noise at various times of a day using H/V ratio technique.
Measurement done using this microtremor method can give valuable information about the natural
frequency, amplification factor and even weak points on all types of soil and structure.

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March 2015

In this study, H/V ratio technique for microtremor data analysis has been used to investigate
resonance criteria for ground. This approach is able to determine the weak points of ground, bridge
structure and weak points of ground and structure to estimate the real earthquake damage before an
earthquake. The results therefore, can be used for earthquake disaster mitigation. Estimation ofdamage can be done quickly and accurately. Possible types of preparatory study in highly seismic
region are very promising for disaster prevention activities in the future.
Again, the comparison studies can indicate the effects of surroundings. These results shed light on
the fact that soil and structure react differently while some factors are changed. Thus, these factors
have a great influence over the behavior of damage due to seismic hazards. So, if the nature ofchange is identified, manners of damage can be perceived too.
If weak points of ground and structures can be detected in advance by investigating the durability ofvarious structures and ground, damage can be decreased by taking appropriate countermeasures. In
addition, if seismic characteristics of ground and structures are already known, seismic intensity
distribution of the area can be precisely estimated.
Occurrence of earthquake damage depends upon strength, period and duration of seismic motions.
These parameters, of course, depend upon earthquake itself but they are also strongly influenced by
the seismic response characteristics of surface ground and structures. So, there are a lot of scopes toinvestigate using this H/V ratio method for microtremor data analysis.
5. METHODOLOGY
Spectral contents of microtremor can be normally influenced by the near-surface geologicalstructures. For example due to soft soil layer resonant amplification is produced. This phenomenon
leads to amplification at the fundamental S-wave resonance frequency of the soil layer (Nakamura,1989). Also, it should be kept in mind that, source characteristics are usually unknown inmicrotremor studies. Moreover, microtremor consists of shear, Rayleigh and Love wave. So, using
H/V ratio provides more stable measure for site related properties. Stability check of microtremor
data, effects of processing of raw data and analysis of calculated results are discussed. After
analyzing and checking the H/V curves, interpretation of the results (predominant frequency, peaktype of H/V curve) are discussed.

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One of the most widely used methods for site response estimation using ambient vibration
measurements is the so-called Nakamura’s technique (1989). This technique, initially introduced by
Nogoshi and Igarashi (1971), consists in taking the ratio between the Fourier spectra of thehorizontal and vertical components of the ambient vibrations. Many studies (Ohmachi et al. 1991,
Field and Jacob 1993b) confirmed that these ratios (H/V ratios) are very stable, and on soft soil sites
they exhibit a clear peak that is correlated with the fundamental resonant frequency. Regarding theamplitude of the peak, there are still a lot of debates. According to Konno and Ohmachi (1998) there
is a good correlation between the amplitude of the H/V peaks and the S-wave site amplification,
while other researchers (Lermo and Chavez-Garcia, 1994) suggests that there is no good correlation
between the H/V peaks and site transfer function. Lachet and Bard (1994) proposed that the good
match at the fundamental frequency is due to horizontal-vertical polarization of the Rayleigh waves,
an interpretation that is in agreement with the early Japanese studies (Kudo, 1995).
Using microtremor H/V method gives a benefit for low seismological areas for recording the dataand investigates them at ease. Taking data in different time period is the singular field activity here.
After that, only transforming those time domain data and using some software to analyze them will
give us enough outcomes to study further for assessing site effects. Due to the insufficiency ofadequate reference sites, especially in flat areas where exposed rock sites are not found, thetraditional ‫ܪ‬ௌ Ȁ‫ܪ‬ோ method cannot be used generally. Hence, approach to the microtremor H/Vmethod, which requires no reference sites, is the only convenient path. There are so many proceduresthat can be followed for this research. In this experiment, a simple and widely used method has beenused with some modifications. The following flow chart (Figure 1) shows the outline of themethodology.

145
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March 2015

Site Selection (Field Visit)

Microtremor Data
recording (x, y and z
Direction)

Selection of Microtremor
Data for Analysis

Strong Motion(earthquake) Database for
Jamuna Bridge

Selection of Earthquake
Data (x, y and z direction)
for Analysis

Fast Fourier
Transformation (FFT)
along x, y and z directions

Fast Fourier
Transformation (FFT) alongx, y and z directions

H/V Ratio (HVR) Plottingwith Frequency
H/V Ratio (HVR) plottingwith Frequency (Hz)Smoothing of HVR
Smoothing of HVR

Estimation of PredominantFrequency from HVR of
Microtremor Data

Estimation of PredominantFrequency from HVR ofStrong Motion Data
Comparison of HVRs frommicrotremor and earthquake

Predominant Frequency of a
Site

Figure 1 Flow Chart for Methodology of Microtremor and Strong Motion Data Analysis

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6. DATA COLLECTION AND EQUIPMENT USED FOR THIS STUDY
Data are collected from various field stations. They are situated in BUET, Police Staff College, Hazi
Camp, LGED of Bogra and Natore, East and West part of Jamuna Bridge as shown in Table 1. There
are some preinstalled devices in these places, where ground excitation due to earthquakes have been
already recorded. As there are memory cards so the data can be collected with two or three monthintervals. On 10 November 2014, prerecorded data from BUET, Police Staff College and Hazi Camp
have been collected. Field vibration data has also been collected from these places using microtremor
array technique. Five sensors have been used to collect field vibration data from one site.
On 20 November 2014, the BUET team has collected data from Natore and Bogra LGED. Similarly
on 21 November 2014, data has been collected from East and West side of Jamuna bridge. Groundvibration data using microtremor array technique has been collected from all those sites. Groundvibration has also been collected next to the west bridge abutment. In all sites, microtremor data has
been collected for 30 minutes. The data are collected at various time periods for specific time
duration. This is mainly done to minimize the consequence of any kind of interruption that candistort the results.
Microtremor measurement apparatus includes Geodas 15-HS equipment (data logger and laptop),
five sensors, cable, battery, and GPS. Mtobs.exe software has been used to record microtremor data.
Sensors comprise three components, which can record the horizontal motion (in Latitude andLongitude directions) and the vertical motions (up and down). Microtremor sensor sensitivity is 2,
95,900 lm/s/V. The converting speed is 50 kHz. The sampling frequency was 100-500 Hz. Velocity
time history field microtremor data have been recorded in Mtobs.exe software with suitable numberof observation channels, observation length, observation frequency, specific low or high pass filter
code, amplification ratio, observation latitude and longitude, observation time, and observation
channel mode. For each location, three sensors have been used.

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March 2015

7. DATA INTERPRETATION
7.1 BOGRA LGEDThe data are collected at various time periods for specific time duration. This is mainly done tominimize the consequence of any kind of interruption that can distort the results.
The following Figure 2 shows time history microtremor (MT) data of 80 seconds duration. These
MT data were recorded at Bogra LGED. Time history data is not suitable to estimate dynamic
properties. Movements of the Earth’s surface generated by the whole ambient seismic backgroundnoise, and their corresponding Fourier spectra for frequencies above 1 Hz, are usually recorded by
MT. Transformation of time domain data to frequency domain data is required with Fouriertransformation. Therefore FFT has been used and compared with actual earthquake data. Figure 1
shows the ground wave velocity recorded in three channels of MT. Ch1, ch2 and ch3 respectively
represent x, y and z component of ground wave velocity in µm/s. Peak velocity is recorded in ch3 or
2E+1

2E+1

1.6E+1

1.6E+1

1.2E+1

1.2E+1

8E+0

8E+0

4E+0

4E+0

CH-02

CH-01

in Z direction with a value of 20µm/s.

0
-4E+0

0
-4E+0

-8E+0

-8E+0

-1.2E+1-1.2E+1-1.6E+1-1.6E+1-2E+1

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

-2E+1

Time

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

2E+1
1.6E+1
1.2E+1

CH-03

8E+0
4E+0
0
-4E+0
-8E+0
-1.2E+1-1.6E+1-2E+1

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

Figure 2 Microtremor Time History data at Bogra, LGED
Figure 3 shows Earthquake (EQ) data recorded by triaxial accelerometer on 22june 2004. Here timeis in Second and ground acceleration is in cm/s2. The figure shows that the highest groundacceleration was in north-south (n-s) direction with a value of 20 cm/s2. The duration of the EQ was
41 seconds. The peak acceleration in east- west (e-w) and Up-down (u-d) was 16 and 4 cm/s2
respectively.
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BNUS Annual Report-2014

20

20

16

16

12

12

8

8

4

4

ns

ew

ICUS Report 76

0

0
-4

-4
-8

-8

-12

-12

-16

-16

-20

-20

0

5

10

15

20

25

30

Time

35

40

0

5

25

30

4

10

15

20

25

30

Time

35

40

45

20
16
12
8

ud

4
0
-4
-8
-12
-16
-20

0

5

10

15

20

Time

35

40

45

Figure 3 Earthquake Time History data at BOGRA (22-06-2004)
Figure 4 shows Earthquake (EQ) data recorded by triaxial accelerometer on 14Feb 2006. The Figure
shows that the highest ground acceleration was in e-w direction with a value of 2.4 cm/s2. The
duration of the shaking was 75 seconds. The peak acceleration in n-s and up-down (u-d) was 1.8

3

3

2.4

2.4

1.8

1.8

1.2

1.2

0.6

0.6

ns

ew

cm/s2 and 0.7 cm/s2 respectively.

0

-1.2

-1.2

-1.8

-1.8

-2.4

-2.4
-3

0
-0.6

-0.6

-3

0

5

10

15

20

25

30

35

40

Time

45

50

55

60

65

70

75

5

10

15

20

25

30

0

5

10

15

20

25

30

45

50

55

60

65

70

75

35

40

Time

45

50

55

60

65

70

75

3

2.4
1.8
1.2

ud

0.6
0
-0.6
-1.2
-1.8
-2.4
-3

0

35

40

Time

Figure 4 Earthquake Time History data at BOGRA (14-02-2006)
Figure 5 shows Earthquake (EQ) data recorded by triaxial accelerometer at 27 July 2008. The figure
shows that the ground acceleration in both e-w and n-s direction was equal with a value of 18 cm/s2.
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The duration of the shaking was 70 seconds. After that the vibration gradually dissipated. The peak
30

30

24

24

18

18

12

12

6

6

ns

ew

displacement in u-d was 8 cm/s2.

0

0

-6

-6

-12

-12

-18

-18

-24

-24

-30

0

10

20

30

40

50

Time

60

70

80

90

-30

100

0

10

20

30

40

70

80

90

100

27072008

50

Time

60

70

80

90

100

30
24
18
12

ud

6
0
-6
-12
-18
-24
-30

0

10

20

30

40

50

Time

60

Figure 5 Earthquake Time History data at BOGRA (27-07-2008)
Figure 6 shows comparison of horizontal to vertical ratio (HVR) of MT and EQ data. HVR of EQ
data is average of 11 different earthquakes. HVR of MT is also average of 5 data. Comparison ofearthquake and MT HVR shows similar overall trend. For both cases predominant frequency ranges
between 1 and 2 hz.
20
10
7
5

HVR

3
2
1
0.7
0.5
0.3
0.2
0.1
0.01 0.02

MTEQ
0.05 0.1

0.2 0.3 0.5

1Frequency

2 3 4 5 67 10

20

Figure 6 HVR vs Frequency plot of MT and EQ

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7.2 BUET CAMPUS
Figure 7 shows Earthquake (EQ) data recorded by triaxial accelerometer on 18 September 2005 at
BUET campus. Ground acceleration in both e-w and n-s direction was equal with a value of 1.8
cm/s2. The duration of the shaking was 40 seconds. After that the vibration gradually dissipated. The
peak acceleration in u-d direction was 8 cm/s2.
3
2.4

3

1.8

2.4
1.8

1.2

1.2
0.6

0

ns

ew

0.6

-0.6
-1.2

-1.2

-1.8

-1.8

-2.4
-3

0
-0.6

-2.4

0

5

10

15

20

25

30

time

35

40

-3

45

0

5

10

15

20

25

time

30

35

40

45

3
2.4
1.8
1.2

ud

0.6
0
-0.6
-1.2
-1.8
-2.4
-3

0

5

10

15

20

25

time

30

35

40

45

Figure 7 Earthquake Time History data at BUET (18-09-2005)
Figure 8 shows Earthquake (EQ) data recorded by triaxial accelerometer on 5 August 2005. The
figure shows that the ground displacement in n-s direction had the highest acceleration of 3.2 cm/s2
and e-w direction had an acceleration of 1.6 cm/s2. The duration of the shaking was 40 seconds. The
peak displacement in u-d was 0.8 cm/s2

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05082006
3.2

2.4

2.4

1.6

1.6

0.8

0.8

ns

4

3.2

ew

4

0

0

-0.8

-0.8

-1.6

-1.6

-2.4

-2.4

-3.2

-3.2

-4

0

5

10

15

20

25

30

time

35

40

-4

45

0

5

10

15

20

25

time

30

35

40

45

4
3.2
2.4
1.6

ud

0.8
0
-0.8
-1.6
-2.4
-3.2
-4

0

5

10

15

20

25

30

time

35

40

45

Figure 8 Earthquake Time History data at BUET (05-08-2005)
Figure 9 shows Earthquake (EQ) data recorded by triaxial accelerometer on 09 June 2011. The figure
shows that the ground acceleration in n-s direction had a value of 6 cm/s2 and e-w direction had adisplacement of 5 cm/s2. The duration of the shaking was 15 seconds. After that the vibration

6

6

5

5

4

4

3

3

2

2

1

1

ns

ew

gradually dissipated. The peak acceleration in u-d was 6 cm/s2.

0

0

-1

-1

-2

-2

-3

-3

-4

-4

-5

-5

-6

-6
0

1

2

3

4

5

6

7

8

time

9

10 11 12 13 14 15 16

0

1

2

3

4

5

6

7

8

time

9

10 11 12 13 14 15 16

6
5
4
3

ud

2
1
0
-1
-2
-3
-4
-5
-6

0

1

2

3

4

5

6

7

8

time

9

10 11 12 13 14 15 16

Figure 9 Earthquake Time History data at BUET (09-06-2011)

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Figure 10 shows Earthquake (EQ) data recorded by triaxial accelerometer on 18 March 2012. The
figure shows that the ground acceleration in both e-w and n-s direction was equal with a value of 20

20

20

16

16

12

12

8

8

4

4

ew

ns

cm/s2. The duration of the shaking was 50 seconds. The peak acceleration in u-d was 12 cm/s2.

0

0
-4

-4
-8

-8

-12

-12

-16

-16

-20

0

5

10

15

20

25

time

30

35

40

45

-20

50

0

5

10

15

20

30

35

40

45

50

25

time

30

35

40

45

50

20
16
12
8

ud

4
0
-4
-8
-12
-16
-20

0

5

10

15

20

25

time

Figure 10 Earthquake Time History data at BUET (18-03-2012)
The following Figure 11 shows time history MT data of three segments with data length of 80
seconds at BUET campus. FFT has been used and compared with actual earthquake data.It shows
ground wave velocity recorded in three channels of MT. Peak ground velocity is recorded in ch1
with a value of 120 µm/s. ch3 recorded a uniform velocity of 2µm/s.Later FFT has been used and1.5E+2

1.2E+2

1.2E+2

9E+1

9E+1

6E+1

6E+1

3E+1

3E+1

CH-02

1.5E+2

0
-3E+1
-6E+1

0
-3E+1
-6E+1

-9E+1

-9E+1

-1.2E+2-1.2E+2-1.5E+2

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90-1.5E+2Time

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

1.5E+2
1.2E+2
9E+1
6E+1

CH-03

CH-01

compared with actual earthquake data.

3E+1
0
-3E+1
-6E+1
-9E+1
-1.2E+2-1.5E+2

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

Figure 11 Microtremor Time History data at BUET campus
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Figure 12 shows comparison of horizontal to vertical ratio (HVR) of MT and EQ data recorded at
BUET campus. HVR of EQ data is average of 4 different earthquakes and HVR of MT is average of
5 data. Comparison of earthquake and MT HVR shows similar overall trend. For EQ predominantfrequency ranges between 0.7 to 1 hz. MT recorded data shows predominant frequency between 1 to
2 hz.
10
7
5
3

HVR

2
1
0.7
0.5
0.3

MT
EQ

0.2
0.1
0.01 0.02

0.05 0.1

0.2 0.3 0.5

1Frequency

2 3 4 5 67 10

20

Figure 12 HVR vs Frequency plot of MT and EQ
7.3 EAST SIDE OF JAMUNA BRIDGE
Figure 13 shows Earthquake (EQ) data recorded by triaxial accelerometer on 14 February 2006. The
figure shows that the ground acceleration in both e-w and n-s direction was equal with a value of 2.4
cm/s2. The duration of the shaking was 70 seconds. The peak acceleration in u-d was 0.6 cm/s2.
1.8

1.8

1.2

1.2

0.6

0.6

ns

3
2.4

ew

3
2.4

0

0

-0.6

-0.6

-1.2

-1.2

-1.8

-1.8

-2.4

-2.4

-3

-3
0

5

10

15

20

25

30

35

time

40

45

50

55

60

0

5

65

70

0

5

30

35

10

15

20

25

30

35

time

40

45

50

55

60

65

70

3
2.4
1.8
1.2

ud

0.6
0
-0.6
-1.2
-1.8
-2.4
-3

10

15

20

25

time

40

45

50

55

60

65

70

Figure 13 Earthquake Time History data at East Side of Jamuna Bridge (14-02-2006)

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Figure 14 shows Earthquake data recorded by triaxial accelerometer on 11 April 2006. The figure
shows that the ground acceleration in n-s direction has highest acceleration with a value of 1 cm/s2.
Acceleration in e-w direction had a value of 0.8 cm/s2.The duration of the shaking was 40 seconds.
1

1

0.8

0.8

0.6

0.6

0.4

0.4

0.2

0.2

ns

ew

The peak displacement in u-d was 0.2 cm/s2.

0

0

-0.2

-0.2

-0.4

-0.4

-0.6

-0.6

-0.8

-0.8

-1

0

5

10

15

20

25

30

time

35

40

-1

45

0

5

10

15

20

25

30

time

35

40

45

1
0.8
0.6
0.4

ud

0.2
0
-0.2
-0.4
-0.6
-0.8
-1

0

5

10

15

20

25

30

time

35

40

45

Figure 14 Earthquake Time History data at East Side of Jamuna Bridge (11-04-2006)
Figure 15 shows Earthquake data recorded by triaxial accelerometer on 05 August 2006. The figure
shows that the ground acceleration in e-w direction had highest acceleration with a value of 3.2 cm/s2.
Acceleration in e-w direction had a value of 2.4 cm/s2.The duration of the shaking was 65 seconds.
4
3.2

2.4

2.4

1.6

1.6

0.8

0.8

ns

4
3.2

0

0

-0.8

-0.8

-1.6

-1.6

-2.4

-2.4

-3.2

-3.2

-4

0

5

10

15

20

25

30

35

time

40

45

50

55

60

65

5

10

15

-4

0

5

10

15

20

25

30

35

30

35

40

45

50

55

60

65

time

40

45

50

55

60

65

4
3.2
2.4
1.6
0.8

ud

ew

The peak acceleration in u-d was 1.6 cm/s2.

0
-0.8
-1.6
-2.4
-3.2
-4

0

20

25

time

Figure 15 Earthquake Time History data at East Side of Jamuna Bridge (05-08-2006)
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Figure 16 shows time history MT data of three segments with data length of 80 seconds at East sideof Jamuna Bridge. FFT has been used and compared with actual earthquake data. It shows groundwave velocity recorded in three channels of MT. Peak ground velocity was recorded in ch3 with a
3E+1

3E+1

2.4E+12.4E+1

1.8E+1

1.8E+1

1.2E+1

1.2E+1

6E+0

6E+0

ch-01

CH-03

value of 24 µm/s. Later FFT has been used and compared with actual earthquake data.

0
-6E+0

0
-6E+0

-1.2E+1-1.2E+1-1.8E+1-1.8E+1-2.4E+1-2.4E+1

-3E+1

0

-3E+1

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

3E+1
2.4E+1
1.8E+1CH-02

1.2E+16E+0
0-6E+0-1.2E+1-1.8E+1-2.4E+1-3E+1

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

Figure 16 Microtremor Time History data at East Side of Jamuna Bridge
Figure 17 shows comparison of horizontal to vertical ratio (HVR) of MT and EQ data recorded at
East side of Jamuna bridge. HVR of EQ data is average of 3 different earthquakes and HVR of MT isaverage of 5 data. Comparison of earthquake and MT HVR shows similar overall trend with apredominant frequency in the range of 0.7 to 1 hz.
20
10
7
5

HVR

3
2
1
0.7
0.5
0.2

MT
EQ

0.1
0.01 0.02

0.05 0.1

0.3

0.2 0.3 0.5

1Frequency

2 3 4 5 67 10

20

Figure 17 HVR vs Frequency plot of MT and EQ

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7.4 WEST SIDE OF JAMUNA BRIDGE
Figure 18 shows Earthquake (EQ) data recorded by triaxial accelerometer on 14 February 2006.
Ground acceleration in both e-w and n-s direction was equal with a value of 2 cm/s2. The duration of
the shaking was 45 seconds. The peak acceleration in u-d was 1.5 cm/s2 .
2.5

2.5

2

2

1.5

1

1

0.5

0.5

ns

ew

1.5

0

0
-0.5

-0.5
-1

-1

-1.5

-1.5

-2

-2

-2.5

-2.5

0

5

10

15

20

25

Time

30

35

40

45

50

0

5

30

35

10

15

20

25

Time

30

35

40

45

50

2.5
2
1.5
1

ud

0.5
0
-0.5
-1
-1.5
-2
-2.5

0

5

10

15

20

25

Time

40

45

50

Figure 18 Earthquake Time History data at West Side of Jamuna Bridge (14-02-2006)
Figure 19 shows Earthquake (EQ) data recorded by triaxial accelerometer on 27 July 2008. The
figure shows that the ground displacement in e-w direction has the highest acceleration of 4 cm/s2
and n-s direction has a displacement of 3 cm/s2.The duration of the shaking was 60 seconds. The

60

50

50

40

40

30

30

20

20

10

10

ns

60

0

0

-10

-10

-20

-20

-30

-30

-40

-40

-50
-60

-50

0

5

10

15

20

25

30

35

Time

40

45

50

55

60

65

5

10

15

-60

0

5

10

15

20

25

30

35

40

25

30

35

40

45

50

55

60

65

Time

45

50

55

60

65

60
50
40
30
20
10

ud

ew

peak displacement in u-d was 1 cm/s2.

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

0

20

Time

Figure 19 Earthquake Time History data at West Side of Jamuna Bridge (27-07-2008)
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Figure 20 shows time history MT data of three segments with data length of 80 seconds at West sideof Jamuna Bridge. FFT has been used and compared with actual earthquake data. It shows groundwave velocity recorded in three channels of MT. Peak ground velocity was recorded in ch3 with avalue of 500 µm/s. Lowest ground velocity was recorded in ch1 with a value of 50 µm/s. Later FFT
6E+2

6E+2

5E+2

5E+2

4E+2

4E+2

3E+2

3E+2

2E+2

2E+2

1E+2

1E+2

CH-02

ch-01

has been used and compared with actual earthquake data.

0
-1E+2

0
-1E+2

-2E+2

-2E+2

-3E+2

-3E+2

-4E+2

-4E+2

-5E+2

-5E+2

-6E+2

-6E+2

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

6E+2
5E+2
4E+2
3E+2

CH-03

2E+2
1E+2
0
-1E+2
-2E+2
-3E+2
-4E+2
-5E+2
-6E+2

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

Figure 20 Microtremor Time History data at West Side of Jamuna Bridge
Figure 21 shows comparison of horizontal to vertical ratio (HVR) of MT and EQ data recorded atWest side of Jamuna bridge. HVR of EQ data is average of 2 different earthquakes and HVR of MT
is average of 5 data. Comparison of earthquake and MT HVR shows similar overall trend.
Predominant frequency of EQ is 0.7hz and MT reading shows predominant frequency of 1hz.
20
10
7
5

HVR

3
2
1
0.7
0.5
0.2

MT
EQ

0.1
0.01 0.02

0.05 0.1

0.3

0.2 0.3 0.5

1Frequency

2 3 4 5 67 10

20

Figure 21 HVR vs Frequency plot of MT and EQ
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7.5 POLICE STAFF COLLEGE
Figure 22 shows Earthquake (EQ) data recorded by triaxial accelerometer on 18 September 2011.
Ground acceleration in n-s direction had an acceleration of 6 cm/s2and e-s direction had an
acceleration of 5 cm/s2.The duration of the shaking was 40 seconds. The peak acceleration in u-d
6

6

5

5

4

4

3

3

2

2

1

1

ns

ud

was 3 cm/s2.

0

0

-1

-1

-2

-2

-3

-3

-4

-4
-5

-5
-6

0

5

10

15

20

25

Time

30

35

40

-6

4

0

5

10

15

20

25

30

35

40

4

25

Time

30

35

40

45

6
5
4
3

ew

2
1
0
-1
-2
-3
-4
-5
-6

0

5

10

15

20

time

Figure 22 Earthquake Time History data at PSC (18-09-2011)
Figure 23 shows time history MT data of three segments with data length of 80 seconds at Police
Staff College. FFT has been used and compared with actual earthquake data. It shows ground wave
velocity recorded in three channels of MT. Peak ground velocity was recorded in ch2 with a value of
24 µm/s. Later FFT has been used and compared with actual earthquake data.

159
161

4E+1

4E+1

3.2E+1

3.2E+12.4E+12.4E+1

1.6E+1

1.6E+1

8E+0

8E+0

CH-02

CH-01

March 2015

0
-8E+0

0
-8E+0

-1.6E+1-1.6E+1-2.4E+1-2.4E+1-3.2E+1-3.2E+1

-4E+1

0

-4E+1

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

4E+1
3.2E+12.4E+1CH-03

1.6E+18E+0
0-8E+0-1.6E+1-2.4E+1-3.2E+1-4E+1

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

Figure 23 Microtremor Time History data at Police Staff College
Figure 24 shows comparison of horizontal to vertical ratio (HVR) of MT and EQ data recorded at
Police Staff College. Comparison of earthquake and MT HVR shows similar overall trend.
Predominant frequency of EQ is 0.45hz and MT reading shows predominant frequency around 1 hz.
20
10
7
5

HVR

3
2
1
0.7
0.5
0.2

MT
EQ

0.1
0.01 0.02

0.05 0.1

0.3

0.2 0.3 0.5

1Frequency

2 3 4 5 67 10

20

Figure 24 HVR vs Frequency plot of MT and EQ
7.6 HAZI CAMP
Figure 25 shows Earthquake (EQ) data recorded by triaxial accelerometer on 10 September 2010.
The figure shows that the ground acceleration in e-w direction had highest acceleration value of 10
cm/s2and n-s direction had an acceleration of 6 cm/s2. The duration of the shaking was 21 seconds.
The peak displacement in u-d was 4 cm/s2 .

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12

9

9

6

6

3

3

ns

15

12

ew

15

0

0

-3

-3

-6

-6

-9

-9

-12

-12

-15

0

3

6

9

12

15

Time

18

-15

21

0

3

6

9

12

Time

15

18

21

15
12
9
6

ud

3
0
-3
-6
-9
-12
-15

0

3

6

9

12

15

Time

18

21

Figure 25 Earthquake Time History data at Hazi Camp (10-09-2010)
Figure 26 shows Earthquake (EQ) data recorded by triaxial accelerometer on 18 September 2011.
Ground acceleration in e-w direction had a value of 8 cm/s2and n-s direction had an acceleration
value of 4 cm/s2. The duration of the shaking was 35 seconds. The peak acceleration in u-d was 2
10

8

8

6

6

4

4

2

2

ns

10

0

0

-2

-2

-4

-4

-6

-6

-8

-8

-10

-10

0

5

10

15

20

25

Time

30

35

0

5

10

15

20

Time

25

30

35

10
8
6
4
2

ud

ew

cm/s2

0
-2
-4
-6
-8
-10

0

5

10

15

20

Time

25

30

35

Figure 26 Earthquake Time History data at Hazi Camp (18-09-2011)

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Figure 27 shows time history MT data of three segments with data length of 80 seconds at Hazi
Camp. FFT has been used and compared with actual earthquake data. It shows ground wave velocity
recorded in three channels of MT. Three channels had almost the same ground velocity with a peak
6E+1

6E+1

5E+1

5E+1

4E+1

4E+1

3E+1

3E+1

2E+1

2E+1

1E+1

1E+1

CH-01

CH-03

value of 30µm/s.Later FFT has been used and compared with actual earthquake data.

0
-1E+1

0
-1E+1

-2E+1

-2E+1

-3E+1

-3E+1

-4E+1

-4E+1

-5E+1

-5E+1

-6E+1

-6E+1

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

6E+1
5E+1
4E+1
3E+1
2E+1

CH-02

1E+1
0
-1E+1
-2E+1
-3E+1
-4E+1
-5E+1
-6E+1

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

Figure 27 Microtremor Time History data at Hazi Camp
Figure 28 shows comparison of horizontal to vertical ratio (HVR) of MT and EQ data recorded atWest side of Jamunabridge. HVR of EQ data is average of 2 different earthquakes and HVR of MT
is average of 5 data. Comparison of earthquake and MT HVR shows similar overall trend.
Predominant frequency of EQ is 2hz and MT reading shows predominant frequency around 1 hz.
20
10
7
5

HVR

3
2
1
0.7
0.5
0.2

MT
EQ

0.1
0.01 0.02

0.05 0.1

0.3

0.2 0.3 0.5

1Frequency

2 3 4 5 67 10

20

Figure 28 HVR vs Frequency plot of MT and EQ

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7.7 NATORE LGED
Figure 29 shows Earthquake (EQ) data recorded by triaxial accelerometer on 14 February 2005. The
figure shows that the ground acceleration in both e-w and n-s direction was equal with a value of 2.4

3

3

2.4

2.4

1.8

1.8

1.2

1.2

0.6

0.6

ud

ew

cm/s2. The duration of the shaking was 80 seconds. The peak displacement in u-d was 0.6cm/s2.

0

0

-0.6

-0.6

-1.2

-1.2

-1.8

-1.8

-2.4

-2.4

-3

0

8

16

24

32

40

48

Time

56

64

72

80

8

16

24

32

-3

0

8

16

24

32

48

56

64

72

80

40

Time

48

56

64

72

80

3
2.4
1.8
1.2

ns

0.6
0
-0.6
-1.2
-1.8
-2.4
-3

0

40

Time

Figure 29 Earthquake Time History data at Natore (14-02-2006)
Figure 30 shows Earthquake (EQ) data recorded by triaxial accelerometer on 23 February 2006.
Ground acceleration in n-s direction had a value of 1.6 cm/s2 and in e-s direction the value is 1.6
2
1.6

1.2

1.2

0.8

0.8

0.4

0.4

ns

2
1.6

0

0

-0.4

-0.4

-0.8

-0.8

-1.2

-1.2

-1.6

-1.6

-2

0

5

10

15

20

25

30

Time

35

40

-2

45

0

5

10

15

20

25

Time

30

35

40

45

2
1.6
1.2
0.8
0.4

ud

ew

cm/s2. The duration of the shaking was 45 seconds. The peak displacement in u-d was .4 cm/s2

0
-0.4
-0.8
-1.2
-1.6
-2

0

5

10

15

20

25

Time

30

35

40

45

Figure 30 Earthquake Time History data at Natore (23-02-2006)
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Figure 31 shows Earthquake (EQ) data recorded by triaxial accelerometer on 05 june 2006. Groundacceleration in both e-w and n-s direction was equal with a value of 1.6 cm/s2. Duration of the
2

2

1.6

1.6

1.2

1.2

0.8

0.8

0.4

0.4

ns

ew

shaking was 45 seconds. The peak displacement in u-d was 1.2 cm/s2.

0

0

-0.4

-0.4

-0.8

-0.8

-1.2

-1.2

-1.6
-2

-1.6
0

5

10

15

20

25

Time

30

35

40

45

-2

50

0

5

10

15

20

35

40

45

50

25

Time

30

35

40

45

50

05082006
2
1.6
1.2
0.8

ud

0.4
0
-0.4
-0.8
-1.2
-1.6
-2

0

5

10

15

20

25

Time

30

Figure 31 Earthquake Time History data at Natore (05-06-2006)
Figure 32 shows time history MT data of three segments with data length of 80 seconds at Natore
LGED. FFT has been used and compared with actual earthquake data. It shows ground wave velocity
recorded in three channels of MT. ch3 had recorded the highest ground velocity with a value of
30µm/s. Later FFT has been used and compared with actual earthquake data.

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3E+2

3E+2

2.4E+22.4E+2

1.8E+2

1.8E+2

1.2E+2

1.2E+2

6E+1

6E+1

CH-02

CH-01

ICUS Report 76

0
-6E+1

0
-6E+1

-1.2E+2-1.2E+2-1.8E+2-1.8E+2-2.4E+2-2.4E+2

-3E+2

0

-3E+2

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

3E+2
2.4E+2
1.8E+2
1.2E+2

CH-03

6E+1
0
-6E+1
-1.2E+2-1.8E+2-2.4E+2-3E+2

0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time

Figure 32 Microtremor Time History data at Natore LGED
Figure 33 shows comparison of horizontal to vertical ratio (HVR) of MT and EQ data recorded atWest side of Jamunabridge. HVR of EQ data is average of 2 different earthquakes and HVR of MT
is average of 5 data. Comparison of earthquake and MT HVR shows similar overall trend.
Predominant frequency is 0.7hz both for EQ and MT.
10
7
5
3

HVR

2
1
0.7
0.5
0.3
0.2
0.1
0.01 0.02

MTEQ
0.05 0.1

0.2 0.3 0.5

1Frequency

2 3 4 5 67 10

20

Figure 33 HVR vs Frequency plot of MT and EQ

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8. CONCLUSIONS
Microtremor measurement has been carried out in 7 locations where Earthquake data has beenrecorded for the last 10 years. The overall predominant frequency for these sites range between 0.7
Hz and 1.5 Hz. On the other hand, the overall H/V ratio for these sites range between 1.9 and 5.1.
Table 2 summarizes findings of this study. The table also shows average soil conditions of the sites
based on Vs30. All the sites fall into NEHRP D-class, which is stiff soil (180≤ Vs30≤ 360 m/s).
Table 2 Microtremor Test Location, Predominant Frequency, H/V Ratio and Vs30 for the sites
SL.
Location
Predominant
H/V Ratio,
Vs30 (m/s)
No

Frequency,
Fg (Hz)

Ag

1.5

4.6

270

BUET Campus

1.2

1.9

250

East Side of

0.9

3.7

280

1.0

2.3

280

1

5.1

280

1

Bogra LGED2
3

Jamuna Bridge
4

West Side of
Jamuna bridge

5

Police Staff
College

168

6

Hazi Camp

1

3.9

220

7

Natore LGED

0.7

4.1

210

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REFERENCESBUET (2014). Inception Report on Seismic Instrumentation Monitoring of Bangabandhu Bridge,
report submitted to JMBA.
Field, EH and Jacob, KH (1993). The theoretical response of sedimentary layers to ambient seismic
noise, Geophysical Research Letter 20:2925–2928.
Kanai, K and Tanaka, T (1954). Measurements of Micro-tremors 1. In: Bulletin Earthquake ResearchInstitute, vol 32. Tokyo University, pp 199–210.
Konno, K and Ohmachi ,T (1998). Ground motion characteristics estimated from spectral ratio
between horizontal and vertical components of microtremor. Bull Seism Soc Am 88(1):228–241.
Lermo, J and Chavez-Garcia, FJ (1994). Are Microtremors Useful in Site Response Evaluation? Bull
Seism Soc Am 84:1350–1364.
Nogoshi, M. and Igarashi, T. (1971). On the Amplitude Characteristics of Microtremor (Part 2) (inJapanese with English abstract)”, Jour. Seism. Soc. Japan, 24, 26-40.
Nakamura Y (1989). A method for dynamic characteristics of subsurface using microtremors on the
ground surface, Quick Report of Railway Technical Research Institute, vol 30, no 1, pp 25–33 (inJapanese).
Ohmachi, T, Nakamura, Y and Toshinawa T (1991). Ground motion characteristics in the San
Francisco Bay area detected by microtremor measurements. In: Proceedings 2nd International
Conference on Recent Advances in Geotech Earth Engand Soil Dyn, Saint Louis, pp 1643–1648.

167
169

PART-XI
MEASUREMENT OF SHEAR-WAVE VELOCITY AT
DIFFERENT LOCATIONS OF DHAKA CITY USINGSEISMIC REFRACTIONBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA
Prepared By: Abul Khair
Mehedi Ahmed Ansary168March 2015

1. Introduction
Seismic refraction is a commonly used geophysical technique to determine depth-to bedrock,competence of bedrock, depth to the water table, or depth to other seismic velocity Boundaries(www.nga.com,20th, April, 2009). The seismic refraction method involves the analysis of the travel
times of arrivals that travelled roughly parallel to the upper surface of a layer during theirtransmission through the subsurface. This method uses the seismic energy that returns to the surfaceof the earth after traveling along ray paths through the ground, to locate refractors that separate
layers of different seismic velocities (Keller et al, 1981).
Seismic refraction methods provide an effective and efficient means to obtain general information
about large volumes of the subsurface in the two dimensions of depth and horizontal (or slope)
distance. Information provided by seismic refraction includes compression wave (p-wave) velocities
within the investigated subsurface profile. Traditionally, these velocities are interpreted to be present
within layers or horizons whose depths are also interpreted. Newer interpretation methods aremaking it possible to interpret velocity changes as gradients as well as discrete layers. Limitations
due to subsurface geometries such as thin layers and lower velocity horizons underlying higher
velocity horizons must be understood and, if necessary, accounted for. Cross correlation with otherexploration methods such as drilling, test pits and geologic mapping, can greatly increase the valueof refraction seismic data. In return, refraction seismic data can significantly enhance the value ofother exploration data. Both basic field operations and basic interpretations of the resulting data canbe performed by properly trained and experienced geotechnical or geological engineering personnel
as well as by geophysical specialists.
Seismic refraction measurements are applicable in mapping subsurface conditions for various uses
including geological, geotechnical, hydrological, environmental, mineral and archaeologicalinvestigations. The calculated seismic wave velocity is related to the typeof rock, degree of
weathering, and rippability assessment on the basis of seismic velocity and other geologic
information.
2. Background of the study
The seismic refraction survey has application in a variety of geological exploration problems, where
information on the depth and strength of subsurface materials is required. These surveys provide
subsurface information over large areas at relatively low cost; locate critical areas for more detailed
testing by drilling and can readily eliminate less favorable alternative sites. Seismic surveys can also
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reduce the number of boreholes required to test a particular site and improve correlation between
boreholes. The following are the areas, where this method can be used to obtain informationa) Problems of engineering geologyi.

Depth to bedrock (thickness of overburden and for weathered rock).

ii.

Strength of the bedrock (looking for weak zones like fractures, shears and weatheringand for faults etc) for foundation studies.

iii.

Rippability/excavability studies for quarries and dynamic elasticity determination.

iv.

Location of sink holes and other manmade objectsv.

Correlation of geological units between boreholesvi.

Monitoring of landslides.

b) Problems in alluvial prospectingi.

Indirect search for alluvial deposits.

ii.

Location of ancient stream channels.

iii.

Location of thick gravel bedsc) Problems in hydrogeologyi.

Thickness of aquifer over lying impermeable bedrock.

ii.

Detection of water table, mainly in alluvial aquifers.

iii.

Location of leakage zones.

2.1 Advantages / Disadvantages:
 Difficulty of interpretation in areas morphologically rough or with many underground pipes Open spaces is needed for cables and electrodes array, the electrodes must be planted into theground (can also be applied in paved areas or asphalt, drilling holes).
 Good vertical and lateral stratigraphic resolution.
 For best accuracy, a calibration reference stratigraphy is needed.
 Very useful for discrimination of metal, clay / sand and aquifers
2.2 Literature review:
The refraction method consists of measuring (at known points along the surface of the ground) the
travel times of compressional waves generated by an impulsive energy source. The energy source isusually a small explosive charge and the energy is detected, amplified, and recorded by special
equipment designed for this purpose. The instant of the explosion, or "zero-time,” is recorded on therecord of arriving pulses. The raw data, therefore, consists of travel times and distances, and thistime-distance information is then manipulated to convert it into the format of velocity variations withdepth. The interpretation of this raw data will be developed as we go along. The process is170
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schematically illustrated in Fig. 1. All measurements are made at the surface of the ground, and thesubsurface structure is inferred from interpretation methods based on the laws of energy propagation.

Fig 1: Schematic of seismic refraction survey
The fundamental law that describes the refraction of light rays is Snell's Law (see Fig. 2), and this,
together with the phenomenon of “critical incidence,” is the physical foundation of seismic refraction
surveys.
A small explosive charge is detonated in a shallow hole at A and the energy is detected by a set ofdetectors laid out in a straight line along the surface. The arrival times of the impulses are plottedagainst the corresponding shot-to-detector distances as shown in Fig. 3. The first few arrival times
are those of direct arrivals through the first layer, and the slope of the line through these points,
ΔT/ΔX, is simply the reciprocal of the velocity of that layer; i.e., 1/V1. At some distance from theshot, a distance called the critical distance, it takes less time for the energy to travel down to the topof the second layer, refract along the interface at the higher velocity V2 and travel back up to thesurface, than it does for the energy to travel directly through the top layer.

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Fig 2: Snell’s law and refraction of ray transmitted across boundary between two media withdifferent velocities.
The energy that arrives at the detectors beyond the critical distance will plot along a line with a slopeof 1/V2. The line through these refracted arrivals will not pass through the origin, but rather will
project back to the time axis to intersect it at a time called the intercept time. Because both theintercept time and the critical distance are directly dependent upon the velocities of the two materials
and the thickness of the top layer, they can be used to determine the depth to the top of the second
layer.

Fig 3: Simple two-layer case with plane, parallel boundaries and corresponding time-distance curve.
The rock types can be found to know the seismic velocity transmitted to the soil. The verities ofseismic velocity of different layers indicated different types of soil. There is an approximate range toclassify rocks depending on seismic velocities (www.Geo2X,com).

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Table 1: Approximate seismic velocities for rocks
Rock type

Vp(km/sec)
Unconsolidated sedimentClay

1.0-2.5

Sand, dry

0.2-1.0

Sand, saturated

1.5-2.0
Sedimentary Rocks

anhydrite

6.0

Chalk

2.1-4.5

Coal

1.7-3.4

Dolomite

4.0-7.0

limestone

3.9-6.2Shale

2.0-5.5

Salt

4.6

sandstone

2.0-5.0
Igneous and metamorphic rocks

Basalt5.3-6.5

Granite

4.7-6.0

gabbro6.5-7.0

Slate

3.5-4.4

Ultramafic rocks

7.5-8.5
OthersAir

0.3

Natural gas

0.43

Ice

3.4

Water

1.4-1.5oil

1.3-1.4

In the following articles different methods of depth calculation are described.
2.2.1

Intercept times

Referring to Fig. 3, let us compute the arrival time of the refracted impulse at a detector. Consider
the travel path ABCD

AB  CD 
176

Z1
cos 

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Where Z1 is the thickness of the top layer, and a is the critical angle of incidence. The travel time istherefore given byAB  CD BC

V
1
2Z1
X V22 Z1 tan 
V1 cos 
V2
1
sin 
X
 2 Z1 ()V1 cos  V2 cos  V2
V  V sin X 2Z1 ( 2 1)Snell's law defines the critical angle of incidence,
V1V2 cos a, by: V2
T

(1)

V
sin   1
V2 the previous equation:and selectively substituting Eq. (1) into

And substituting V1 for V2sinα

1
 sin X
T  2 Z1V1 ( sin )V1V2 cos2
V2
1  sin X
T  2 Z1V1 ()
V1V2 sin  cos  V2
cos 2 XT
V2 sin  cos  V2

2Z cos  X
T 1V1intercept
V2 time, Ti, and we can rewrite the last expression as:
If we now let X = 0, then T becomes the

i.e.,

TV
Z1  i 1T V
Z1  2 cos i 1V
2 cos(sin 1 1 )V2(2)For the situation we have assumed in Fig. 3, everything on the right-hand side of Eq.(2) can be
determined from the time distance plot; therefore, the depth to the second layer can be computed. Avery important point to bring out at this time is that all depths determined in refraction surveys aremeasured normal to the boundary between layers and are not necessarily vertical depths beneath theground surface. The intercept-time analysis can be extended to the case of multiple layers; however,
only the resulting formulas will be given here because their derivations are redundant and may befound in a number of references. Fig. 4 schematically illustrates the multiple layer case andcorresponding time-distance plots. The intercept times and layer thicknesses have been identified bya subscript corresponding to the number of the layer:

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Fig 4: Schematic of multiple-layer case and corresponding time-distance curve.

Z1 (Ti1 )V1
2 cos(sin 1

V1
)
V2

1
 shot depth
2

(3)

V 

cos(sin 1 1 ) V3
Ti 3  Ti 2
V2
1 V1 
(4)cos(sin)V2 
Z2  
V
2 cos(sin 1 2 )
V3
V 
V

cos(sin 1 1 ) 2Z 2 cos(sin 1 2 ) 

V4V4
Ti 4  Ti 2
V3

V
V2
1 1

 (5)
cos(sin
)


V2
Z3 
V
2 cos(sin 1 3 )V4If the velocity contrasts between layers are high enough; say 2 to 1, and only approximate depths are
required, then the following formulas can be used:(6)(T2 )V2V
2 cos(sin 1 2 )V(7)(T3 )V3 3
Z3 V
2 cos(sin 1 3 )VWhereT2 and T3; are as indicated in Fig. 4. 4Equations (6) and (7) will give thicknesses that are
Z2 

greater than actual, and it is suggested that thicknesses initially be computed both ways to learn
whether the error is significant in a particular situation.

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2.2.2

Critical DistanceThe critical-distance method for determining depth will receive only brief attention here because it isanalogous to the intercept-time method, and offers no advantages significant enough to warrant
further detail. Its primary application is to compute the depth of the first layer and to estimate thelength of the seismic line required for a particular exploration task. The critical distance is the
distance from the shot point to the point at which the refracted energy arrives at the same time as theenergy traveling directly through the top layer. The critical distance (Xc) is illustrated in Fig. 3; it is
the breakpoint in the graph of arrival times.
By an approach similar to the one used in deriving the intercept-time formulas, it can be shown thatthe depth of the first layer is given by:
V1
)
Xc
V2
Z1 
V
2
cos(sin 1 1 )V2Where Xc is the critical distance.
(1 

(8)

Equation (8) can be used to construct a graph showing the length of a seismic line (relative to thedepth of the first layer) required to detect refractions from the underlying layer, as a function ofvelocity ratios. Figure 5 is a graph of Eq. (8), which can be of use in planning a seismic survey ifvelocity ratios are assumed. The graph also assists in giving a sense of perspective to the effect ofvelocity contrasts. For example, assume that there is about 15 feet of overburden with a velocity of 2,
500 feet/sec, and that it is underlain by a shale with a velocity of about 5,500 feet/sec. How longshould the seismic line be to insure adequate coverage for mapping the overburden thickness? The
velocity ratio, V2/V1, is 2.2 so that Xc/Z1 is approximately3.25, which means that the criticaldistance will be about 50 feet. The seismic spread should be at least three times this distance;
therefore, a seismic line 150 to 200 feet long would be satisfactory.
2.2.3

Dipping Layer

If the boundaries between interface are not parallel (that is, if they are dipping interfaces), the t-x
curve will give only apparent velocities for the refracting layers usage of which can give erroneous
depths. Reverse shooting field procedure can provide complete protection against above said errors.
Reverse shooting means firing a shot at both ends of the seismic line so that arrival times at eachdetector are measured from both directions. The case of a dipping boundary and its effect on traveltime plots is as shown in Fig. 4. The condition of reciprocity provides a valuable constraint. The
condition of reciprocity states that the total travel time from A to D must be equal to the total travel
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time from D to A. The gradients of the travel-time curves of reflected arrivals along the forward andreverse profile lines yield the down dip (VJ and up dip (VJ apparent velocity respectively (see Fig, 4).
From the forward direction
V1
sin(i12   )And from the reverse direction
V2 d 

V2u V1sin(i12   )Solving for i12 and θ
i12 

1  1 V1   1 V1 )  sin ( )sin (
2
V2 d  
V2u 

1

V

 

V 

  sin 1 ( 1 )  sin 1 ( 1 )
2
V
V

2d 
2u 


The perpendicular distances Z and Z’ to the interface under the two ends of the profile are obtained

from the intercept times t1 and ti’ the travel-time curves obtained in the forward and reverse direction.

Z

V11t ii
2 cos i12
12

By using the computed refractor dip e, the perpendicular depths Z and Z’ can be converted into
vertical depths h and h’ usingZ
cos' 
Z
'
h 
cos
h

2.3 Methodology

Measurement of subsurface conditions by the seismic refraction method requires a seismic energy
source, trigger cable, geophones, geophone cable, and a seismograph. The geophones and the seismic
source must be placed in firm contact with the soil or rock. The geophones are usually located in aline, sometimes referred to as a geophone spread. The seismic sources may be a sledge hammer, amechanical device that strikes the ground, or some other type of impulse source. Explosives are used
for deeper refractors or special conditions that require greater energy. Geophones convert the groundvibrations into an electrical signal. This electrical signal is recorded and processed by theseismograph. The travel time of the seismic wave (from the source to geophone) is determined fromthe seismic wave form.
2.3.1
180

Study area selection
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Over the past 45 years, Dhaka city has experienced a rapid growth of urban population and it willcontinue in the future due to several unavoidable reasons. Hence, most of the areas of Dhaka city
have already been occupied. As a result, different new areas are being reclaimed inside and near
Dhaka city by both government and private agencies. General practice for reclaiming such areas is tofill low lands (ditches, lakes etc.). In most cases, the practice for developing new areas is just to fill
low land by dredge fill materials. In most cases, the dredged material is almost silty sand with highfines content .The presence of fines in hydraulic fill means greater compressibility and greaterdifficulty in compaction of the fill. Fines also reduce permeability and hence the rate of drainage isslow. Therefore consolidation rate is also slow. Since Dhaka city exists in seismic Zone II of
Bangladesh. This silty sand layer may liquefy if an earthquake of sufficient magnitude occurs infuture. As well as, it may cause geotechnical problems.
It is clear that this very soft clay layer, in reclaimed areas demand special attention for designingfoundation system on or through it. So, it is felt necessary to carry out research to know thecharacteristics of the soft organic clay layer of such reclaimed areas.
The different location of Dhaka city is selected as the study area. The location are selected uponsome criteria such as free open space, less noisy area, dominating soil characteristics of that region,
land use characteristics etc. The table below shows the location of the study area.
Table 2: List of the study points of Dhaka city
Sl.

Date

no
01 14/11/2014

Name of the point ofstudy area

Location
Latitude

Garden in front of Civil 23o 43’ 19” N

City

Longitude
90o 23’ 48” E

Dhaka

Building at BUET
02 13/11/2014

Vatara, Gulshan

23o 47’ 39” N

90o 26’ 40” E

Dhaka

03 14/11/2014

Bashaundhara river view, 23o 39’ 45” N

90o 26’ 25” EDhaka

90o 23’ 03” E

Dhaka

Keranigong
04 14/11/2014

New Jail, Keranigong

23o 39’ 07” N

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March 2015

Fig 5: Location of study points within Dhaka city
2.3.2

Data collection and Analysis

Planning and design of a seismic refraction survey should be done with due consideration of theobjectives of the survey and the characteristics of the site. These factors determine the survey, design,
the equipment to be used, the level of effort, the interpretation method selected, and budget necessary
to achieve the desired results. Important considerations include site geology, depth of investigation,
topography and access. The presence of noise-generating activities and operational constraints
should also be considered. It is a good practice to obtain as much relevant information about the site,
prior to planning a survey and mobilization to the site.
The first important consideration in planning a field refraction survey is the spacing between thegeophones. The spacing will depend on the desired depth of exploration. Selection of detector
spacing is also determined by the required detail of the refractor geometry. This is because thesampling interval of interpretation points on the refractor is approximately equal to the detector
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spacing on the surface. Thus, the horizontal resolution of the method for subsurface targets is equal
to the detector spacing. Once the spacing between geophones is decided, the “spread” length that iscovered by one shot is fixed by the number of channels of the seismic equipment being deployed.
Usually, in detailed engineering surveys, a 5m interval between geophones is appropriate. But due tolack of energy 3m interval between geophone is selected to found better result. If the profile length
required to get the desired subsurface information is more than one “spread” length, the timedistance information should be collected by overlapping as many spreads as required. In doing so, atleast two geophones should be kept overlapping between successive spreads to tie the timings fromdifferent shots to make profile continuous. Usually, five to seven shots are required for each spread.
The data of the different locations were collected using different combination of seismic impulse
source and different spacing of geophones. Some specific softwares based on conventional method
were needed to process seismic refraction. WinSism is widely used to analyze the seismic refraction
data after collecting field data. The details of data collection and results after processing data aredescribed below:
 Seismic refraction result analysis for BUET groundThe geophone spread and impulse source is shown in Fig. 6 and Fig. 7 respectively during seismic
refraction test at BUET. Five shot points were selected during this test named middle shot, 1st offset
shot, 1st end shot, last end shots and last offset shot. The position of two offset shots 23m away from
1st and last geophone, which is half of the total spread length 46m as shown in fig 8.Sevenstrikes foreach offset shot and 5 strikes for rest three shots were taken by tripod hammer. As the noise provides
bad data, the strikes were taken when the circumstances seems to be quiet.

Fig 6: Spread of geophones duringrefraction test at BUETFig 7: Using 140lb hammer as impulse
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Fig 8: Layout of shots position during seismic refraction test at BUETThe soil profile of the seismic refraction test is shown in Fig. 9. It shows that the investigation depthof soil profile is about 30m. The seismic velocity ranges is about to 150m/s to 350m/s which range
indicates the sub soil is dry sand according to Table 1.

Fig 9: Soil profile at BUET playground using seismic refraction
 Seismic refraction result analysis for Vatara

The geophone spread and impulse source is shown in Fig. 10 and Fig. 11 respectively during seismic
refraction test at Vatara. Five shot points were selected during this test named middle shot, 1st offset
shot, 1st end shot, last end shots and last offset shot. The position of two offset shots is 30m awayfrom 1st and last geophone as shown in Fig. 12.Sevenstrikes for each offset shot and 5 strikes for rest
three shots were taken by tripod hammer. As the noise provides bad data, the strikes were taken
when the circumstances seems to be quiet.

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Fig 10: Spread of geophones during
Refraction test at Vatara

Fig 11: Using 140lb hammer as impulse
sourceFig 12: Layout of shots position during seismic refraction test Vatara
Recently this place has filled up by filling materials about 3m in depth. As the filling materials is notcompacted properly the energy of impulse source were consume by lose filling. Hence the result mayvary from actual one due to lack of energy through the subsoil .The soil profile of the seismic
refraction test is shown in Fig. 13. It shows that the investigation depth of soil profile is about 30m.
The seismic velocity range is about to 150m/s to 290m/s which range indicates the sub soil is dry
sand according to Table 1.

Fig 13: Soil profile at Vatara using seismic refraction
 Seismic refraction result analysis for Bashundhara River view:
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The geophone spread and seismic data collection is shown in Fig. 14 and Fig. 15 respectively during
seismic refraction test at Bashundhara river view. Five shot points were selected during this test
named middle shot, 1st offset shot, 1st end shot, last end shots and last offset shot. The position of
two offset shots 30m away from 1st and last geophone, which is half of the total spread length 69m
as shown in Fig. 16.Sevenstrikes for each offset shot and 5 strikes for rest three shots were taken by
tripod hammer. As the noise provides bad data, the strikes were taken when the circumstances seems
to be quiet.

Fig 14: Spread of geophones during

Fig 15: Seismic data collection equipment

refraction test at Vatara

Fig 16: Layout of shots position during seismic refraction test at Bashundhara river view
The soil profile of the seismic refraction test is shown in Fig. 17. It shows that the investigation depthof soil profile is about 35m. The velocity range is about to 50m/s to 250m/s which range indicatesthe sub soil is dry sand.

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Fig 17: Soil profile of Bashundhara river view
 Seismic refraction result analysis at Outside of New jailThe geophone spread and impulse source is shown in Fig. 18 and Fig. 19 respectively during seismic
refraction test at New Jail. Five shot points were selected during this test named middle shot, 1stoffset shot, 1st end shot, last end shots and last offset shot. The position of two offset shots 30m
away from 1st and last geophone, which is half of the total spread length 69m as shown in Fig.
20.Sevenstrikes for each offset shot and 5 strikes for rest three shots were taken by tripod hammer.
As the noise provides bad data, the strikes were taken when the circumstances seems to be quiet.

Fig 18: Spread of geophones duringrefraction test at New JailFig 19: Using 140lb hammer as impulse
sourceFig 20: Layout of shots position during seismic refraction test at New Jail184
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The soil profile of the seismic refraction test is shown in Fig 21. It shows that the investigation depthof soil profile is about 18m. The velocity range is about to 150m/s to 280m/s which range indicatesthe sub soil is dry sand.

Fig 21: Soil profile besides new jail using seismic refraction
2.3.3

Limitations

A hidden layer, or blind layer, is one that is undetectable by refraction surveying. In practice, there
are two different types of hidden layer problem. A layer may simply not give rise to first arrivals,
that is, rays traveling to deeper levels may arrive before those critically refracted at the top of thelayer in question(see Fig. 22). This may result from the thickness of the layer or from the closenessof its velocity to that of the overlying layer. In such a case, a method of survey involving recognitionof only first arrivals will fail to detect the layer. The problem may be overcome by firing a shot in a
deep hole so that arrivals from the intermediate layer are recorded at the surface. A more insidioustype of hidden layer problem is associated with a low velocity layer, as illustrated in Fig. 23. Rays
cannot be critically refracted at the top of such a layer and the layer will, therefore, not give rise tohead waves. Hence, a low velocity layer cannot be detected by refraction surveying although the topof the low velocity layer gives rise to wide angle reflections that may be detected during a refraction
survey. In the presence of a low velocity layer, the interpretation of travel-time curves leads to an
overestimation of the depth to underlying interfaces. Low velocity layers are a hazard in all types ofrefraction seismology. On a small scale, a peat layer in muds and sands above bedrock may escapedetection, leading to a false estimation of foundation conditions and rock depths beneath a
construction site.
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Fig 22: Hidden layer problem in seismic
refraction

Fig 23: Blind zone problem in seismic
refraction

Due to lack of available impulse source the seismic refraction test is difficult in maximum places. To
buy and use explosive is difficult in Bangladesh. Hence seismic refraction test is not feasible toinvestigate subsoil characteristics.
References
1. Alhassan, D. U., Dangana, L.M., Salako, K.A., Jonah, S.A. and Ofor, seismic refraction
investigation of the subsurface structure at the southern part of niger state college ofeducation, Bayero Journal of Pure and Applied Sciences, 3(2): 56 – 61
2. Geological exploration by geophysical method (seismic refraction) —code of practice,burau of indian standard, is 15681:2006 , pp.8-15

3. Keller G.R, Sinno Y.A, and Sbar M.L (1981). Seismic refraction in West and central
Arizona, journal of Geophysical Research, New York, U.S.A, Vol. 86 ,No. 36, PP5023
4. Redpath B. B., A book of “Seismic refraction exploration for Engineering site
investigations” Explosive Excavation Research Laboratory Livermore, California, May 1973

5. www.geo2X.com

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MEASUREMENT OF ELECTRICAL RESISTIVITY
AT DIFFERENT LOCATIONS OF DHAKA CITYBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA
Prepared By: B.S. Pushpendue Biswas
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1.

Introduction:

Ground Resistivity survey methods have been widely used in order to solve engineering, archeology,
environmental and geological problems in the last decades. Subsurface resistivity distributions aremeasured by applying electrical current into the ground by using two current electrodes. The
potential differences caused by the flow of current between any two points in linear line with thecurrent electrodes are then measured by a pair of potential electrodes. From the measured voltage (V)and current (I) values, the resistance at the specified point in the subsurface can be determined. In
homogeneous ground, penetration depth is directly proportional to electrodes spacing, and changing
the electrode’s separation gives information on sub surface’s stratification [1-2].
For 2D resistivity imaging, it is important to have a large set of data recorded along a survey line toeffectively map the complex resistivity distribution of subsurface structure. The most practical way
to acquire such large amount of data is by using automated multi-electrode data acquisition system.In
the interpretation of ground resistivity survey, it is important to differentiate between apparent
resistivity and true resistivity. Apparent resistivity can be defined as the volumetric average of aheterogeneous half-space, except that the averaging is not done arithmetically but by a complex
weighing function dependent on electrode’s configurations [3].
In resistivity survey, true resistivity can only be measured in ideal condition where the ground ishomogenous, which is almost never is the case. Advancement in computer forward modelingsoftware (e.g. Res2DINV, Resix) have made it possible to calculate numerous amount of dataobtained from 2D resistivity survey in a short amount of time, and minimized the different between
true and apparent resistivity for subsurface earth material by subdividing the subsurface into small
rectangular cells where each cell has resistivity value close to the true resistivity of subsurface
material. The principle is in determining the cell resistivity that provides a model response that fits
well with the measured data [4].
However, this assumption is only true theoretically. Uncertainty still remains in the final obtained
image even if the inversion is a quasi-automatic process. In practice, there are a lot of factors that canaffect resistivity pseudo section imaging. Apparent resistivity is measured instead of trueresistivity
due to unknown near surface strata with different resistivity. This affects the conduction of current
through earth material and thus affects the resistivity measurement.Most of field resistivity surveys
conducted by geophysicist are not always validated by laboratory measurement. The difficulty inobtaining the core sample, where the drillingworks should be preceded by resistivity survey has
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made it difficult for geophysicist to analyze samples in laboratory [5]. Figure 1 shows the points (redstar marked) of the study area of Dhaka city.

Figure 1: Study Area
2.

Background of the study

In the seismic and GPR methods, signals from the source pass through the medium and return to asensor. They are more ‘direct’ methods, changes in the travel time and characteristics of the signal
due to passage through the anomaly give information about it.The electrical method is an ‘indirect’
method;it directly measures the current that passes through the anomaly but it measure distortions in
the electrical potential on the ground surface due to changes in the current flow causes by theanomaly. This sometimes makes the interpretation of electrical data more difficult.

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Fields of application:
Geology: lithological discontinuities and voids, tectonic lines localization, deposits of gravel•and sand, mining plans etc.
•

Hydrogeology: aquifers surveys, interface freshwater/salt detection etc.

•

Environmental studies: presence of pollutants in the soil, filling areas, leakage fromlandfills, trace contaminants in leachate and groundwater
Archaeology: surveys of large buried structures.

•

Advantages / Disadvantages:•

Difficulty of interpretation in areas morphologically rough or with many underground pipes.

•

Open spaces is needed for cables and electrodes array, the electrodes must be planted into theground (can also be applied in paved areas or asphalt, drilling holes).
•Good vertical and lateral stratigraphic resolution.

•

For best accuracy, a calibration reference stratigraphy is needed.

•

Very useful for discrimination of metal, clay / sand and aquifers

The electrical resistivity method allows the calculation of the resistivity present in soil. The
calculation of resistivity makes it possible to obtain information about the subsoil nature andstructure. Applying a potential difference (V) to the two poles of a conductor, in it will pass acurrent of intensity (I) which is related to the potential difference from Ohm's law:R = V/I
Where,
R= electrical resistance that depends on the nature and geometric characteristics of the conductor.
ΔV = difference of potential measured between M and N [V]
I = current injected into soil [A]For each acquisition performed in the selected spreading, the following formula is generally applied:
ρ=(

��
I

). K

Where,
ρ = apparent resistivity [Ω m]
ΔV = difference of potential measured between M and N [V]
I = current injected into soil [A]K = geometric coefficient related to the sounding being usedρ (spell it ‘rho’) is known as resistivity, is measured in Ω*m and provides useful elements for
identifying the nature of the rock types investigated.The value of this parameter depends on the
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mineralogical composition of soils, the presence of fluid saturation, temperature, porosity and degreeof cementation.
Electrical properties of sediments and sedimentary rocks

The resistivity of sedimentary rocks and sediments/soils depend mainly on the porosity, fluid content
and clay content. Most resistivity values range from 10 to 1000 ohm*m. Resistivity decreases withincreasing clay content. Most clay has resistivity of 1to 10 ohm*m. For rocks and sediments withlow clay content, the electrical conduction is mainly through the fluids filling the pores of therock.The relationship between resistivity and porosity is given by Archie's Law:
ρr = a ρw φ-m(a ≈ 1, m ≈ 2, ρr = rock resistivity, ρw = fluid resistivity, φ = fraction of the rock filled with fluid).The
resistivity of ground water varies from 10 to 100 Ω*m, depending on the concentration of dissolved
salts. The resistivity of sea water is about 0.2 Ω*m due to the relatively high salt content.
Electrical properties of metamorphic and igneous rocks

Igneous and metamorphic rocks typically have high resistivity values of over 1000 Ω*m. The
resistivity of these rocks is greatly dependent on the degree of fracturing, and the percentage of thefractures filled with ground water. A given rock type can have a large range of resistivity, from about1000 to 10 million Ω*m, depending on whether it is wet or dry. This characteristic is useful in thedetection of fracture zones and other weathering features, such as in engineering and groundwater
surveys.
Electrical properties of mineral ores

Metals, such as iron, have extremely low resistivity values. Metallic sulfides (such as pyrrhotite,
galena and pyrite) have typically low resistivity values of less than 1 Ω*m. The resistivity value of aparticular ore body can differ greatly from the resistivity of the individual crystals. Other factors,
such as the nature of the ore body (massive or disseminated) have a significant effect. Graphitic slate
has a low resistivity value, similar to the metallic sulfides, which can give rise to problems in mineralsurveys. Most oxides, such as hematite, do not have a significantly low resistivity value. One
exception is magnetite.
Electrode array

Common array types are

Wenner arrayWenner-Schlumberger array

Dipole-dipole arrayPole-dipoleMultiple gradient array
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Wenner array:The Wenner array is an attractive choice for a survey carried out in a noisy area (dueto its high signal strength) and also if good vertical resolution is required.
Wenner-Schlumberger array:The Wenner-Schlumberger array (with overlapping data levels) is areasonable all-round alternative if both good horizontal and vertical resolutions are needed,
particularly if good signal strength is also required. This is a combination of the Wenner and
Schlumberger arrays. The “n” factor for this array is the ratio of the distance between the C1-P1 (orP2-C2) electrodes to the spacing (“a”) between the P1-P2 potential pair.The geometric factor is
proportional to n2. Figure 2 given below shows the Wenner- Schlumberger array.

Figure 2: Wenner- Schlumberger array (source: PASI-2010) [17]Dipole-dipole array: The dipole-dipole array might be a more suitable choice if good horizontal

resolution and data coverage is important (assuming your resistivity meter is sufficiently sensitive
and there is good ground contact).To use this array, the resistivity meter should have comparatively
high sensitivity and very good noise filtering circuitry, and there should be good contact between theelectrodes and the ground. A high current output is also desirable. This array has been successfully
used in many areas to detect structures such as cavities where the good horizontal resolution of thisarray is a major advantage. Figure 3 shows the Dipole-dipole array.

Figure 3: Dipole-dipole arry(source: PASI –2010) [17]196192BNUS Annual Report-2014

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Pole-dipole array: If the system is limited with a limited number of electrodes and limited survey

line length, the pole-dipole array with measurements in both the forward and reverse directions
might be a suitable choice. It is an alternative to the dipole-dipole for IP surveys.Unlike the otherarrays, the pole-dipole array is an asymmetrical array.
The pole-dipole array requires a remote electrode, the C2 electrode, which must be placed
sufficiently far from the survey line (at least 5 times the maximum C1-P1 distance used).Over
symmetrical structures the apparent resistivity anomalies in the pseudo section are asymmetrical. In
some situations, the asymmetry in the measured apparent resistivity values could influence the modelobtained after inversion. Figure 4(a) and 4(b) shows the Pole-dipole array and Reverse pole-dipole
array respectively.

Figure 4: a) Pole-dipole array b) Reverse pole-dipole array (source: PASI – 2010) [17]One method to eliminate the effect of the asymmetry of this array is to repeat the measurements withthe electrodes arranged in the reverse manner. By combining the measurements with the “forward”
and “reverse” pole-dipole arrays, any bias in the model due to the asymmetrical nature of this array
would be removed. However these procedures will double the number of data points andconsequently the survey time.
Multiple gradient array: This is a relatively new array developed primary for multi-channel

resistivity meter systems. In the multiple gradient arrays, different sets of measurements are madewith the potential electrodes at different locations for the same current electrodes. As an example, fora system with 32 electrodes, one set of measurements can be made with the current electrodes at
nodes 1 and 32. Next, another series of measurements are made with the current electrodes at nodes
1 and 16, as well as another with the current electrodes at 16 and 32. A similar set of measurements
can be made with the C1-C2 electrodes at 1-8, 8-16, 16-24 and 2-32. This can be repeated using
smaller distances between the current electrodes. Figure 5 shows the Multiple Gradient array.

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Figure 5: Multiple Gradient array (source: PASI –2010) [17]Wenner configuration is, on equal terms, the most robust since it allows a greater ΔV signal andtherefore less sensitive to environmental noise.This is due to the geometrical factor K, for Wenner isthe smallest possible.
Among the characteristics of an array that should be considered are:

the depth of investigationthe sensitivity of the array to vertical and horizontal changes in the subsurface resistivitythe horizontal data coveragethe signal strength

The Figure 6 below shows the electrode arrays of different methods-

Figure 6: Electrode arrays of different methods (source: PASI – 2010) [17]

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The signal strength is an important factor in noisy areas, or when large electrode spacing’s are usedor for surveys with conductive material. The signal strength is inversely proportional to thegeometric factor, so it can be easily estimated. The Wenner (alpha) array has the smallest geometricfactor, and thus the highest signal strength. This means surveys with the Wenner alpha array are
generally less noisy.The pole-pole array has the same geometric factor but it has higher telluric noisedue to the large distance between the potential electrodes.The geometric factor for the dipole-dipole
array is proportional to n3, thus dipole-dipole surveys tend to have the noisiest data. As a general rule,the maximum ‘n’ value should not exceed 6.The geometric factors for pole-dipole and WennerSchlumberger arrays are proportional to n2, thus the signal strength is stronger than the dipole-dipole
but weaker than the Wenner.The signal strength for the gradient array is between that of the
Schlumberger and pole-dipole arrays.


Depth of investigation - different arrays

The "median depth of investigation", ze, can be easily calculated for different arrays, and the results
are listed in the table below. The depths are given as the ratio to the ‘a’ spacing or the total length ‘L’of the array. To calculate the actual depth of investigation, just multiply this ratio by the ‘a’ spacingor ‘L’ length used in the field survey.Table 1shows the combination of depth for different arraysTable 1: Combination of depth for different arrays (source: PASI –2010) [17]The Wenner alpha array is about half the ‘a’ spacing between the electrodes. The pole-pole array has
the deepest depth of investigation. The ‘median depth of investigation’ for the dipole-dipole array isprobably an underestimate, due to the extreme form of the shape of the sensitivity function.
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

Types of surveys and models

In geophysical inversion, the finding is a model that gives a response that is similar to the actual
measured data. The model is an idealized mathematical representation of a section of the earth(which is always 3-D). The models used can be classified as 1-D, 2-D and 3-D.
The Figure 7 below illustrates the models-

Figure 7: Different resistivity models (source: PASI –2010) [17]1-D electrical imaging survey: Resistivity only changes in the vertical direction (with depth). 1-D

surveys are the simplest to carry out, but interpretation model is too simplistic and not sufficiently
accurate in many cases. Traditional 1-D models are probably too inaccurate for most surveys where
there are significant lateral variations. Lateral changes might be mistaken for vertical changes in theresistivity.
2-D electrical imaging survey: A 2-D imaging survey is usually carried out with a computer

controlled resistivity meter system connected to a multi-electrode cable system. The control software
automatically selects the appropriate four electrodes for each measurement to give 2-D coverage ofthe subsurface. A large variety of arrays and survey arrangements can be used with such a system.
Resistivity changes in the vertical direction and one horizontal direction (the x-direction). Assume
resistivity does not change in y-direction. 2-D surveys and models are potentially the most accurate,
but requires involves higher surveys costs and greater computational resources.
To plot the data from a 2-D imaging survey, the pseudo-section contouring method is normally used.
The horizontal location of the point is placed at the mid-point of the set of electrodes used to makethat measurement. The vertical location of the plotting point is placed at a distance that is
proportional to the separation between the electrodes. For example, the data point measured byelectrodes 1, 2, 3 and 4 are plotted at the mid-point between electrodes 2 and 3 in the diagram
below.Figure 8 shows an example of the electrodes arrangement and measurement sequence that canbe used for a 2-D electrical imaging survey.
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Figure 8 below shows the Sequence of measurements to build up a pseudo-section using a computer
controlled multi-electrode survey setup

Figure 8: Sequence of measurements to build up a pseudo-section using a computer controlled multielectrode survey setup(source: PASI –2014) [17]A 2-D model is used to interpret the data from a 2-D imaging survey. The model usually consists of alarge number of rectangular cells. The size and position of each cell is fixed. An inversion program isused to determine the resistivity of the cells from the measured apparent resistivity values.Figure 9shows the arrangement of model blocks and apparent resistivity datum points197
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Figure9:

Arrangement

of

model

blocks&apparent

resistivity

datum

points(source:

www.geoelectrical.com, 2010) [18]3-D electrical imaging survey: Resistivity can change in all directions. Probably the bestcompromise in many situations, particularly over elongated geological structures.For more complex
situations, a 2-D (or even a 3-D) survey and interpretation model is required.


The software RES2DINVRES2DINV is a computer program that will automatically determine a two-dimensional (2-D)
resistivity model for the subsurface for the data obtained from electrical imaging surveys (Griffiths
and Barker 1993) [7]. This program is designed to invert large data sets (with about 200 to 21000
data points) collected with a system with a large number of electrodes (about 25 to 16000 electrodes).
The 2-D model used by the inversion program, which consists of a number of rectangular blocks, isshown in Figure 9.
The arrangement of the blocks is loosely tied to the distribution of the data points in the pseudosection. The distribution and size of the blocks is automatically generated by the program using the
distribution of the data points as a rough guide. The depth of the bottom row of blocks is set to beapproximately equal to the equivalent depth of investigation of the data points with the largest
electrode spacing(Edwards 1977) [8]. The survey is usually carried out with a system where the

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electrodes are arranged along a line with a constant spacing between adjacent electrodes. However,the program can also handle data sets with non-uniform electrode spacing.
A forward modeling subroutine is used to calculate the apparent resistivity values, and a non-linear
least-squares optimization technique is used for the inversion routine (deGroot-Hedlin and Constable
1990, Loke and Barker 1996a) [9-10]. The program supports both the finite-difference and finiteelement forward modeling techniques. This program can be used for surveys using the Wenner, polepole, dipole-dipole, pole-dipole, Wenner-Schlumberger and equatorial dipole-dipole (rectangular)
arrays. In addition to these common arrays, the program even supports non-conventional arrays withan almost unlimited number of possible electrode configurations. Besides normal surveys carried out
with the electrodes on the ground surface, the program also supports underwater and cross-borehole
surveys.
The inversion routine used by the program is based on the smoothness-constrained least-squares
method (deGroot-Hedlin and Constable 1990, Sasaki 1992) [9, 11].The smoothness-constrained
least-squares method is based on the following equation(JTJ + uF)d = JTg

Where F=fxfxT+ fzfZT
fX=horizontal flatness filter
fZ= vertical flatness filter
J = matrix of partial derivatives
u = damping factor
d = model perturbation vector
g = discrepancy vector
One advantage of this method is that the damping factor and flatness filters can be adjusted to suitdifferent types of data. The program supports a new implementation of the least-squares method
based on a quasi-Newton optimization technique (Loke and Barker 1996a). This technique issignificantly faster than the conventional least-squares method for large data sets and requires lessmemory.
3.

Literature review

Electrical resistivity is known to be highly variable among other physical properties of rock. In somecases, different in extreme values of a single rock type can differ by a factor approaching several
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orders of magnitude.Wide range of rock’s resistivity parameter has always been the reason thatmakes it difficult to distinguish subsurface rock type if no information on the geologicalsurroundings of field survey is available. Electrical current flows through the earth material undersubsurface through two methods, which are electrolytic and electronic conduction [12].
Electronic conduction, which is conduction through the rock’s mineral compositions, occurs mainly
through metallic ore minerals, providing that these minerals exist in dense enough concentration.
However, most conducting minerals rarely exist in sufficient quantity in a rock composition,
especially granite, to have considerable effect on the electrical properties of host rock. This
conduction is controlled by matrix properties (semi conduction, lattice defects, and conductive
accessories) which often resulted in very high resistivity values [13].
Thus, for dry rock, it is common to find the resistivity values to be higher than 104 Ω.m. For mostsubsurface rock, electrical conduction occurs mainly through groundwater that exists in pores andcracks of the rocks. The flow of current in electrolyte conduction through rock is largely influenced
by the porosity of the rock. Generally, for rocks that are still in their original conditions (in situ
condition), rock with higher porosity have lower resistivity. Under any normal condition, the porous
structure of rock is partly or completely filled with underground water, which usually carries salt
solution and thus increasing the moisture content of the rock. It is not unusual for igneous rock tohave moisture content less than 1%. However, even that small percentage of water is enough toaffect the rock’s resistivity considerably [14].
Electrical geophysical methods have proven to be fairly effective in delineating inorganic
contaminants in the subsurface. The mechanism and responses are fairly well understood. Theirapplication for mapping organic contaminants in the subsurface, in particular non-aqueous phaseliquids is not as well accepted nor the mechanisms as well understood. Various surveys havereported results conducted over subsurface organic contamination; however the actual anomaly
associated with the organic contamination has been difficult to ascertain over other factors caused byvariations in the porosity, degree of saturation, mineralogy, and structure [15]. For this reason, anumber of laboratory studies and controlled spill experiments have been conducted over the past few
years in order to evaluate the changes in the physical properties of the geological formations and theassociated geophysical responses due the presence of the organic contamination [16].

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4.

Methodology of the study

The research has been conducted with the following methodology:
4.1Study design

Over the past 45 years, Dhaka city has experienced a rapid growth of urban population and it willcontinue in the future due to several unavoidable reasons. Hence, most of the areas of Dhaka city
have already been occupied. As a result, different new areas are being reclaimed inside and near
Dhaka city by both government and private agencies. General practice for reclaiming such areas is tofill low lands (ditches, lakes etc.). In most cases, the practice for developing new areas is just to fill
low land by dredge fill materials. Different filling procedures are in practice to develop such land.
One of them is to carry soil by vehicles from remote sources and manually dumped at the filling site.
Due to huge traffic congestion, most widely used method is hydraulic filling procedure. In mostcases, the dredged material is almost silty sand with high fines content .The presence of fines inhydraulic fill means greater compressibility and greater difficulty in compaction of the fill. Fines also
reduce permeability and hence the rate of drainage is slow. Therefore consolidation rate is also slow.
Since Dhaka city exists in seismic Zone 2 of Bangladesh. This silty sand layer may liquefy if anearthquake of sufficient magnitude occurs in future. As well as, it may cause geotechnical problems.
It is clear that this very soft clay layer, in reclaimed areas demand special attention for designingfoundation system on or through it. So, it is felt necessary to carry out research to know thecharacteristics of the soft organic clay layer of such reclaimed areas. Thereby, objectives of the study
were defined to characterize the sub-surface soil profile of Dhaka city. Then methodology of thestudy was defined based on literature review.
4.2

Study area selection

Four different points of Dhaka city is selected as the study area. The points are selected upon somecriteria such as free open space for electrical resistivity test, dominating soil characteristics of that
region, land use characteristics etc.The list below shows the points of the study area. Table 2 shows
the Geological and Geomorphological classification of the study area.

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Table 2: Geological and Geomorphological classification of the study area
Sl. noDateName of the point ofLocationstudy area

City

LatitudeLongitude

01

13/10/2014

Kamrangir Char23o 42’ 34” N

90o 22’ 04” E

Dhaka

02

16/11/2014

Bosila23o 44’ 32” N

90o 21’ 10” E

Dhaka

03

17/11/2014

AftabNagor

23o 45’ 38” N

90o 27’ 02” E

Dhaka

04

18/11/2014

BUET Play Ground23o 43’ 19” N

90o 23’ 48” E

Dhaka

4.3

Data collection

The Electrical Resistivity Tomography consists of the experimental determination of the apparent
resistivity ρ of a given material, through joint measurements of electric current intensity and voltage
introduced into the subsoil through electrodes, driven in the ground surface. By deploying a linear
array and recording the electrical signals for an acquisition time, it is possible to back-figure a 2D
pseudo-section, which can be subsequently turned into an actual resistivity section, with aninvestigated depth of the order of one sixth of the array length; of course, the longer the array, thehigher the depth, but increasing the electrode spacing the resolution decreases.
The Electrical Resistivity Tomography data have been gathered through electrodes of length equal to
50 cm, partially driven into the ground. The electrodes were then connected through multichannel
cables, adopting the Wenner-Schlumberger array configuration.This type of arrangement is hybrid
between the Wenner and Schlumberger arrays: during the acquisition, the wiring is continuously
changed so that the spacing a between the ‘potential electrodes’ remains constant, while that between
the ‘current electrodes’ increases as a multiple n of a.
The data of the four points were collected using different electrode and spacing combination as thegeology and the available free spaces of the points were different. The details of the data collectionof the points are given below:
I.

Kamrangir Char

Low land area which is situated at a distance of about 500m-600m from the Buriganga River.

Number of Electrodes used = 32Electrodespacing = 1m

Three data acquisitions were made, two parallel acquisitions @ 5m apart and one cross acquisition

across the center of the parallel acquisitions.

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Figure 10 and Figure 11 given below illustrates the data acquisition setup in the field and spread ofelectrodes and ERT arrangement during resistivity test respectively.

Figure 10: Data acquisition setup in the field

Figure 11: Spread of electrodes and ERT arrangement during resistivity test
II.

Bosila

Number of electrodes used = 32



Two data acquisitions were made, one parallel acquisition and one cross acquisition across thecenter of the parallel acquisition.
Spacing between electrodes of parallel acquisition is 2m and spacing between electrodes of crossacquisition is 1.5m

Figure 12 and Figure 13 given below illustrates the data acquisition setup in the field and spread ofelectrodes and ERT arrangement during resistivity test respectively.

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Figure 12: Data acquisition setup in the field

Figure 13: Spread of electrodes and ERT arrangement during resistivity test
III.

AftabNagor

Semi-submerged land during rainy season

Number of electrodes used = 31

Electrode spacing = 3m



Two data acquisitions were made, one parallel acquisition and one cross acquisition across thecenter of the parallel acquisition.

Figure 14 and Figure 15 given below illustrates the data acquisition setup in the field and spread ofelectrodes and ERT arrangement during resistivity test respectively.

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Figure 14: Data acquisition setup in the field

Figure 15: Spread of electrodes and ERT arrangement during resistivity test
IV.

BUET Play Ground

Number of electrodes used = 32Electrode spacing = 3m

Four data acquisitions were made, two parallel acquisitions @ 5m apart and two cross acquisitions@ 5m apart across the center of the parallel acquisition.

Figure 16 and Figure 17 given below illustrates the data acquisition setup in the field and spread ofelectrodes and ERT arrangement during resistivity test respectively.

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Figure 16: Data acquisition setup in the field

Figure 17: Spread of electrodes and ERT arrangement during resistivity test
4.4

Data processing and analysis

The data collected from the survey have been analyzed with the software RES2DINV. RES2DINV isa computer program that automatically determined a two-dimensional (2-D) resistivity model for the
subsurface for the data obtained from electrical imaging surveys.
4.5

Preparation of Final Report

All information and findings were gathered and presented by tables and maps to prepare the final
report.
5.

Data processing and analysis

Sub-soil analysis is necessary for the dynamic characteristics of soil. The Electrical Resistivity
Tomography (ERT) method was under-taken with several different electrode spacing. Wenner–
Schlumberger array was used as electrode arrays. Measuring was performed with electrodes
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positioned on the surface. Primary data were processed through a 2-D inverse method, using the
program Res2DInv. The presented figures are the results of smoothness-constrained inversion; these
outputs best fit the situation observed in the sites. The validity of these results is supported by the
low RMS error. Sounding was performed with various electrode spacing and configurations
according to the purpose and position of the particular site. Data from these profiles were also
processed through a 2-D inverse method in the program Res2DInv. Table 3 shows the reference
resistivity values table of various materials.
Table 3: Reference resistivity values table of various materialsi.

Kamrangir CharThe electrode spacing was 1 m. Resistivity tomography’s for Kamrangir Char was measured with
Wenner–Schlumberger array. The validity of Wenner–Schlumberger ERT section of KamrangirChar is supported by good low RMS error of 5.6% for the 11th iteration for parallel acquisition and of
4.4% for the 20th iteration for cross acquisition. The depth of the investigation was found of about
5.73 m. The resistivity’s along the profile span a range of 1.55-7526 Ω m for parallel acquisition and8.29-6671 Ω m for cross acquisition. The soil profile of the Kamrangir Char is shown in the Table 4.
The analysis for soil profile is made by combining both the parallel and cross acquisition. This
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profile exists three soil layers. The top layer exist clayey filling sand from 0 to 2.62 m. The second
layer exist organic clay from 2.62 to 4.99 m and the third layer exist clay from 4.99 to 5.76 m.
Figure 18 and Figure 19 shows the model resistivity of ERT at Kamrangir Char of parallelacquisition and cross acquisition respectively.

Figure 18: Model resistivity of ERT at Kamrangir Char, parallel acquisition

Figure 19: Model resistivity of ERT at Kamrangir Char, cross acquisition
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Table 4 given below shows the Electrical Resistivity Tomography (ERT) result at Kamrangir CharTable 4: Electrical Resistivity Tomography (ERT) result at Kamrangir Char
Depth (meter)

Soil Description

Resistivity ranges (Ω m)

0 to 2.62

Filling Sand

200-666

2.62 to 4.99

Clay and Sand mixture

10-2004.99 to 5.76

Sand

198-2239

Kamrangir Char is situated in latitude 23o 42’ 34” N and longitude 90o 22’ 04” E. The upper 2.62 m
is filling sand. For better resolution and model images salted water was used outside the periphery of
the inserted electrodes to increase the conductivity of electricity as the soil surface was in very dry
condition. In the model resistivity of ERT there are some high local resistivity’s which isinsignificant with respect to local soil profile.
ii.

BosilaThe electrode spacing was 2 m and 1.5 m for parallel and cross acquisition respectively. Resistivity
tomography’s for Bosila was measured with Wenner–Schlumberger array. The validity of Wenner–
Schlumberger ERT section of Bosila is supported by good low RMS error of 10.2% for the 22th
iteration for cross acquisition and of 33.8% for the 25th iteration for parallel acquisition. The depth of
the investigation was found of about 8.00 m. The resistivity’s along the profile span a range of 0.047507 Ω m for cross acquisition and 1.88-1872 Ω m for parallel acquisition. The soil profile of the
Bosila is shown in the Table 5. The analysis for soil profile is made by combining both the parallel
and cross acquisition. This profile exists four soil layers. The top layer exist filling sand from 0 to 2
m. The second layer exist organic clay from 2 to 4.88 m. The third layer exit clay from 4.88 to 6.75
m and the fourth layer exist sand from 6.75 to 10.5 m. Figure 20 and Figure 21 shows the model
resistivity of ERT at Bosila of parallel acquisition and cross acquisition respectively.

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Figure 20: Model resistivity of ERT at Bosila, Parallel acquisition

Figure21: Model resistivity of ERT at Bosila, Cross acquisition
Table 5 given below shows the Electrical Resistivity Tomography (ERT) result at BosilaTable 5: Electrical Resistivity Tomography (ERT) result at Bosila
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Depth (meter)

Soil Description

Resistivity ranges (Ω m)

0 to 2Filling Sand

68.9-223

2 to 4.88

Clay

1-68.94.88 to 6.75

Clay and Sand mixture

68.9-273

6.75 to 10.5

Sand273-723

Bosila is situated in latitude 23o 44’ 32” N and longitude 90o 21’ 10” E. The upper 2 m is filling sand.
For better resolution and model images salted water was used outside the periphery of the inserted
electrodes to increase the conductivity of electricity as the soil surface was in very dry condition. In
the model resistivity of ERT there are some high local resistivity’s which is insignificant with respect
to local soil profile. In the graph of model resistivity of Bosila, the left side is showing very highresistivity because that side is very adjacent of Bosila High School building. The foundation of thebuilding is very nearby. From this illustration it is clear that the ERT machine is also useful for theinvestigation of the building foundation and their corresponding depth.
iii.

Aftabnagar

The electrode spacing was 3 m for both parallel and cross acquisition. Resistivity tomography’s for
Aftabnagar was measured with Wenner–Schlumberger array. The validity of Wenner–Schlumberger
ERT section of Aftabnagar is supported by good low RMS error of 15.1% for the 18th iteration forparallel acquisition and of 13.0% for the 12th iteration for cross acquisition. The depth of theinvestigation was found of about 20.4 m. The resistivity’s along the profile span a range of 0.434922 Ω m for parallel acquisition and0.315-855 Ω m for cross acquisition. The soil profile of the
Aftabnagar is shown in the Table 6. The analysis for soil profile is made by combining both theparallel and cross acquisition. This profile exists four soil layers. The top layer exist clayey fillingsand from 0 to 2.98 m. The second layer exist sand from 2.98 to 7.28 m. The third layer exist clay
from 7.28 to 10.1 m and the fourth layer exit sand from 10.1 to 20.4 m. Figure 22 and Figure 23
shows the model resistivity of ERT at Aftabnagar of parallel acquisition and cross acquisition
respectively.

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Figure 22: Model resistivity of ERT at Aftabnagar, Parallel acquisition

Figure 23: Model resistivity of ERT at Aftabnagar, Cross acquisition

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Table 6 given below shows the Electrical Resistivity Tomography (ERT) result at Aftabnagar
Table 6: Electrical Resistivity Tomography (ERT) result at Aftabnagar
Depth (meter)

Soil Description

Resistivity ranges (Ω m)

0 to 2.98

Filling Sand

100-309

2.98 to 7.28

Clay

10-70

7.28 to 10.1

Clay and Sand mixture

10-30910.1 to 20.4

Sand

309-922

Aftabnagar is situated in latitude 23o 45’ 38” N and longitude 90o 27’ 02” E. The upper 2.98 m isfilling sand. For better resolution and model images salted water was used outside the periphery of
the inserted electrodes to increase the conductivity of electricity as the soil surface was in very dry
condition. In the model resistivity of ERT there are some high local resistivity’s which isinsignificant with respect to local soil profile.
iv.

BUET Play GroundThe electrode spacing was 3 m for both parallel and cross acquisitions. Resistivity tomography’s for
BUET Play Ground was measured with Wenner–Schlumberger array. The validity of Wenner–
Schlumberger ERT section of BUET Play Ground is supported by good low RMS error of 15.4% for
the 3rditeration for parallel acquisition and of 14.2% for the 8th iteration for cross acquisition. The
depth of the investigation was found of about 19.7 m. The resistivity’s along the profile span a rangeof 2.98-2938 Ω m for parallel acquisition and03-874 Ω m for cross acquisition. The soil profile of
the BUET Play Ground is shown in the Table 7. The analysis for soil profile is made by combining
both the parallel and cross acquisition. This profile exists four soil layers. The top layer exist clayeysilt from 0 to 5.18 m. The second layer exist clay from 5.18 to 7.85 m. The third layer exist clay andsand mix from 7.85 to 15.8 m and the fourth layer exit sand from 15.8 to 19.7 m. Figure 24 andFigure 25 shows the model resistivity of ERT at BUET Play Ground of parallel acquisition and crossacquisition respectively.

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Figure 24: Model resistivity of ERT at BUET Play Ground, Parallel acquisition

Figure 25: Model resistivity of ERT at BUET Play Ground, cross acquisition

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Table 7 given below shows the Electrical Resistivity Tomography (ERT) result at BUET Play
Ground.
Table 7: Electrical Resistivity Tomography (ERT) result at BUET Play Ground
Depth (meter)

Soil Description

Resistivity ranges (Ω m)

0 to 5.18

Clayey silt

3-74

5.18 to 7.85

Clay34.2-76.8

7.85 to 15.8

Clay and Sand mixture

76.8-389

15.8 to 19.7

Sand389-1097

BUET Play Ground is situated in latitude 23o 43’ 19” N and longitude 90o 23’ 48” E. In the model
resistivity of ERT there are some high local resistivity’s which is insignificant with respect to local
soil profile.
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Pitchford, A.M., A.T. Mazzella, and K.R. Scarbrough, 1989, “Soil-Gas and GeophysicalTechniques for Detection of Subsurface Organic Contamination,” Final Report, Air ForceEngineering and Services Center Report, ESL-TR-87-67, 172 p.
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Greenhouse, John, Brewster, M., Schneider, G., Redman, D., Annan, P.,Olhoeft, G., Lucius,J., Sander, K., Mazzella, A., 1993, Geophysics and Solvents: The Borden Experiment, The Leading
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