BNUS ANNUAL REPORT-2013

BANGLADESH
NETWORK OFFICE

FOR

URBAN
SAFETY
BUET, DHAKA, BANGLADESH
Prepared By:

Mehedi Ahmed Ansary

CONTENTS
PART-I: THE BRAHMANBARIA TORNADO, 2013································ 1
PART-II: EARTHQUAKE VULNERABILITY ASSESSMENT IN SCHOOLSAND COLLEGES OF TANGAIL MUNICIPALITY ·································· 11
PART-III: NON-DESTRUCTIVE TESTING (NDT) IN A RESIDENTIAL
BUILDING LOCATED AT GULSHAN················································· 23
PART-IV: SAVAR BUILDING TRAGEDY IN BANGLADESH: WAY
FORWARD ·················································································· 39
PART-V: SEISMIC RISK ASSESSMENT OF SOME HISTORICAL
MOSQUE OF DHAKA USING NON-DESTRUCTIVE TESTINGMETHODS··················································································· 49
PART-VI: APPLICABILITY OF PS SUSPENSION LOGGINGDOWNHOLE SEISMIC METHOD FOR INVESTIGATION OF
DYNAMIC SOIL PROPERTIES OF BANGLADESH ······························· 59
PART-VII: ENGINEERING CHARACTERISTICS OF GROUNDMOTIONS RECORDED BY NORTHEAST INDIAN STRONG
MOTION INSTRUMENTATION NETWORK FROM 2005 TO 2013············· 69
PART-VIII: STRUCTURAL QUALITY ASSESSMENT OF PADMAPICTURE LTD. MALIBAG, DHAKA ················································· 81
PART-IX: APPLICABILITY OF EXISTING CPT, SPT AND SOIL
PARAMETER CORRELATIONS FOR BANGLADESH ···························· 91
PART-X: SLOPE STABILITY ANALYSIS OF AN EMBANKMENT AT
JAMUNA RIVER ··········································································· 103
PART-XI: LIQUEFGACTION ESTIMATION USING CPT························ 115
PART-XII: BURIED GAS PIPELINE DAMAGE ANALYSIS ····················· 133
PART-XIII: STRUCTURAL ASSESSMENT OF LIBRARY BUILDING,
BUET, DHAKA ············································································· 149
PART-XIV: NON-DESTRUCTIVE TESTING AT FACTORY BUILDING
OF V GARMENTS LIMITED ···························································· 155
PART-XV: MULTIHAZARD VULNERABILITY ASSESSMENT OF
WARD 29 IN DHAKA CITY ····························································· 169
PART-XVI: STANDARD GARMENTS FIRE: AN INTRIGUE AGAINSTRMG SECTOR OF BANGLADESH ···················································· 207
PART-XVII: GROUND PENETRATING RADAR TESTING AT THE
PROPOSED UNDERGROUND LPG STORAGE TANK AT
SOUTHERN AUTOGAS STATION, TEJGAON ····································· 211
2

PART-I
THE BRAHMANBARIA TORNADO, 2013

BANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: KM Khaleduzzaman
Mehedi Ahmed Ansary3May 2014

A deadly tornado occurred in March 22, 2013 at around 5:30 PM in the southeastern district ofBrahmanbaria in Bangladesh. It travelled at a speed of 70 kilometer per hour and lasted for 15
minutes leaving an eight-kilometre trail of destruction in its path. It struck 20 villages with along an
8 kilometres (5.0 mi) of Ramrail, Basudeb, Chinair, Sultanpur union of Sadar Upazila, Bijoynagar
Upazila and North Akhaura union of Akhaura upazila in Brahmanbaria district. The worst damage
occurred in the Bijoynagar and Akhaura Upazila.

Figure 1: Affected srea of the tornado
Thousands of trees and utility poles were toppled and thousands of peoples were left homeless. The
tornado disrupted both train and road communication, which interrupted rescue operations. Part ofjail house of this district was collapsed, resulting in the death of seven jail keepers. Many crops,

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mostly consisting of rice, were damaged as well. Both Prime minister Sheikh Hasina and opposition
leader Khaleda Zia visited the impacted areas to meet the affected people and distribute relief.

Figure 2: Elephant trunk like tornado

Figure 3: Damaged house

Many tin- and mud-built houses and standing crops on a huge swathe of land were badly
damaged by the tornado. The storm uprooted scores of trees and electric poles as it swept
through Urshiura and its surrounding villages of the Sadar Upazila at around 5:30 PM. Local
hospitals were crowded with injured villagers and it was difficult to move from one place to anotheras many of the roads were blocked by fallen trees. Thousands of people were rendered homeless, andpower was out across a wide area. Crops, mostly rice, were damaged across a vast swath of land.

Figure 4: Affected people

Figure 5: Dead livestock

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Figure 6: Affected trees

Figure 7: Damage structure

Figure 8: Dropped electric pole

Figure 9: Dropped trees on rail track

Prime Minister Sheikh Hasina went to Brahmanbaria on the 25 March 2013 to visit the areas hit hardby the tornado. Prime Minister Sheikh Hasina addresses a rally on Chinair Bangabandhu Degree
College premises in Brahmanbaria Sadar upazila on Monday. Prime Minister Sheikh Hasina has
assured the tornado affected people in Brahmanbaria of government support. She earlier visited threevillages in the upazila.

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Figure 10: Prime Minister met affected people

Figure 11: Opposition Party chief met affected
peopleBNP Chairperson Khaleda Zia visited Brahmanbaria on March 30, a week after the tornado. During
the visit, she met the affected people and distributed relief to them. Some senior party leaders
including Sadeque Hossain Khoka accompanied the BNP chief during her visit.
Damage
The tornado devastated a vast area of Brahmanbaria District. Total 3 upazilas are affected including
6 unions. Number of fully and partially affected families are 1326 and 402 respectively where as
fully and partially affected people are 6630 and 1985 respectively. The tornado also destructed anumber of houses where 2635 houses are affected fully and 752 are affected partially. Around 173
acres of agricultural crops are fully affected where as 1112 acres crops are partially affected.
Table 1: Damage statistics of the tornado
AffectedUpazila(No.)
3

Affected
Union
(No.)
6

Affected
Families (No.)
FullPartial1326
402

Affected People
(No.)
Full
Partial6630
1985

Affected
Households (No.)
FullPartial2635
752

Affected Crop
(Acre)
Full
Partial173
1112

Number of death toll due to tornado is 32 where as 388 people are injured severely. Livestock andpoultry are also affected greatly as 299 numbers of cows, cattle and goats died in this devastating
disaster. About 910 numbers of cock, hen and duck died.
The tornado destroyed about 2.25 kilometer road. It also affected a school fully, 5 educational
institution partially and 5 religious institution.

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Table 2: Damage statistics of the tornado
Death
(No.)

Injured
(No.)

32

388

Livestock
Death
(No.)
299

Poultry
Death
(No.)
910

Affected
Educational
Institution (No.)
FullPartial1
5Affected
Affected
Religious
Road
Institution (No.) (km)5
2.25

Others Damage
200ft boundary wall and 420ft security wall of district prison collapsed. Road communication
disrupted due to tumbled trees. Electric lines and poles are affected. Women word kitchen, security
wall and partition including main gate of prison collapsed.

Immediate Action Taken


Rescue operation has been carried with the help of Police, BGB, Fire Service, Roads andHighway, PWD and local leaders.



10ft height CI sheet partition in district prison has been constructed.

Electricity system is up now inside district prison by generator.

Electric lines and poles repaired immediately.



Two medical teams from Comilla cantonment are engaged for rendering medical services tothe victims.



Injured people are admitted in Brahmanbaria general hospital and other hospitals/clinics.
Very seriously injured 15 persons are sent to Comilla Cantonment and some other persons aresent to Dhaka Medical College Hospital as well.

Fire Service, BGB, Police, RHD have managed to restart road communication by removing
fallen trees.

Almost all affected families are getting cook food twice daily from the Government
Administration.



Dry food distribution among affected people is arranged by UP chairman, public
representatives and other organizations.

Response
Government of Bangladesh

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Department of Disaster Management (DDM) has sent 753 tents to build temporary shelter.
Meanwhile, with the help of Bangladesh Army, 453 tents have been pegged. Remaining 300 tents arein the process. DDM has sent 1200 bundle of C.I Sheets (500 from DDM and 700 from Dutch
Bangla Bank Ltd). District administration has also mobilized another 176 bundles of C.I sheets fromits previous stock. So far, 673 bundles have been distributed. In addition, Tk.15,00,000 (fifteen lac)against 500 bundles has been allocated to distribute as Tk.3,000.00/bundle among CI sheet receivers
to build their houses. DDM has allocated 200MT of GR Rice to distribute for affected families.
DDM has allotted Tk.25,60,000 (Twenty Five Lac Sixty Thousand) to distribute at Tk. 20,000.00 forfamilies of each dead people and Tk.5000.00 for each injured people. So far distributed amount is
Tk.5,80,000 among family of 29 dead people and Tk.19,40,000.00 among 388 injured family. Also,
48.93MT out of 261.58MT allocated GR Rice is distributed among 1631 families at 30 kg for eachfamily. DDM has deployed two officers along with other three officers (PIO) from adjacent Upazilas
to make list of affected people and to help distribute relief materials. Besides, DDM has sent two
emergency pick-up vans to DRRO to expedite the response activities. District Administration has
engaged four Additional District Commissioners and two Upazila Nirbahi Officers (UNO) at
Distribution Point to monitor post-disaster relief and rehabilitation activities.
Furthermore, the government is providing corrugated galvanised iron (CGI) sheets and cash grant
BDT 6,000 (approximately CHF 73) to those with damaged house. Government has distributed 40
million tones (mts) of rice from its allocated 100 mts of rice from its gracious relief (GR) fund.
In addition, response from Dutch Bangla Bank Ltd (DBBL) -Tk. 1,050,000 and 700 tents has beenreallocated among affected Upazilas.
Bangladesh Red Crescent Society (BDRCS)
Immediately after the tornado, BDRCS and the International Federation of Red Cross and Red
Crescent Societies (IFRC) have been closely monitoring the situation. BDRCS Response department
and its Unit Office have promptly assessed the situation in Brahmanbaria district. Volunteers of
BDRCS Brahmanbaria district unit conducted search and rescue soon after the disaster struck.
Within hours after the disaster, BDRCS deployed its National Disaster Response Team (NDRT) toassess the damages on people and their properties. Jointly, BDRCS national headquarters (NHQ) and
IFRC jointly dispatched non-food items (NFIs) for 600 families for immediate distribution from its
existing disaster preparedness (DP) stock. Each NFI included one tarpaulin, two water jerry cans andone family kit for each family.

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Figure 12: BDRCS volunteers helping theaffected people

Figure 13: NFIs distribution by BDRCS
district unit to provide relief to theaffected people

From BDRCS NHQ, a medical team has been deployed hours after the disaster to Brahmanbaria tohelp the injured, while 70 unit volunteers were providing first aid in the Brahmanbaria Sadar hospital.
On 23 March, the medical team adapted its service to mobile unit and provided furthermedical
assistance to the tornado affected villages: (I) Dubla, (2) Jarultala, (3) Bashudevpur, (4) Chandanpurand (5) Chinnai. A total of 62 patients were treated, largely for sharp cuts, laceration, bruises, scalp
injury and fractured bones. The serious fracture cases were referred to B.Baria general hospital.
Fortunately, most of the injuries of the patients were minor in nature.

Figure 14: BDRCS youth volunteers offering
first aid to the affected people.

Figure 15: BDRCS mobile unit attending
to the affected people in one of the villages

World Food Programme (WFP)
In order to complement Government efforts to support the victims of the Tornado, WFP has
allocated 12.333 MT of fortified biscuits for distribution to 1631 affected households. WFP is
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distributing 7.5 kilogrammes (kg) of high energy biscuits to each of the affected families to meettheir nutritional need for at least five days. Provision of safe drinking water and household sanitationneeds are yet to be sufficiently addressed. The Water, Sanitation and Hygiene (WASH) cluster isreviewing the situation and mobilizing resources to address these needs. All the development
partners would continue to fill up the existing gaps with the resources that are available.
Other Supports
Concern worldwide has started psychosocial support to the affected people using their trained
personnel; while Muslim Aid has a medical team in the affected area. Apart from these twoorganizations, CARE, Islamic Relief are conducting assessment. From the donor community, theEuropean commission humanitarian aid (DG-ECHO) has dispatched a team to the affected area toassess the situation. The Humanitarian Country Task Team (HCTT) met on 25 March 2013 to takestock of the situation. The meeting concluded that no Joint Needs Assessment (JNA) will belaunched. A total of 1,350 families have been provided with emergency shelter by Government and
BDRCS. If there are more of shelter needs, the shelter cluster and relevant partners are to review andcontribute towards meeting those needs. Government also reported that cooked food has been
provided to the affected people. In order to meet the provision of cooked rice for families, morecooking pots need to be provided immediately.

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PART-II
EARTHQUAKE VULNERABILITY ASSESSMENT INSCHOOLS AND COLLEGES OF TANGAILMUNICIPALITYBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Md. Rajib Hossain, Md. Sirajul Islam,
Mehedi Ahmed Ansary, Lutfun Naher Banna andTanmoy Roy Tusher

12May 2014

Abstract
Assessing school and college vulnerability to earthquakes can be regarded as an ill-structured
problem i.e. a problem for which there is no unique, identifiable and objectively optimal solution.
The study was conducted to assess the earthquake vulnerability of the schools and colleges in
Tangail municipality. The study investigated the present condition of the buildings or infrastructuresof the schools and colleges where some buildings or infrastructures were highly vulnerable due toold age and the rest were vulnerable due to their plan or vertical irregularity. The study showed that58.82% infrastructures made by concrete were non-engineered and the old concrete-frame buildings
were vulnerable to earthquake. If they collapse due to any seismic event, they will be comparatively
more lethal and will take higher percentage of lives than the masonry structures. The study
demonstrated that 15.69% school buildings were older than 30 years, 21.57% was vertically irregularand 31.37% infrastructures showed plan irregularity. By analyzing the above circumstances, 64.71%
school buildings/ infrastructures are needed to detailed evaluation as early as possible to safe
children and people from earthquake hazards.
Key words: Earthquake, Vulnerability, Plan irregularity, Vertical irregularity.
Introduction
Bangladesh is the most vulnerable to several natural disasters due to its geographical location, andevery year natural calamities upset people’s lives in some parts of the country. The destructive
disasters concerned here are the occurrences of earthquake, flood, cyclone and storm surge, flash
flood, drought, tornado, riverbank erosion and land slide (UNEP, 2001). Earthquake, the tremblingor shaking movement of the earth is the most discussed topic among them. It is a form of energy ofwave motion, which originates in a limited region and then spreads out in all directions from thesource of disturbance (Banglapedia, 2008). The 1897 Great Indian earthquake with a magnitude of
8.7 affected almost whole of the Bangladesh. Damages were very severe particularly in Sylhet,
Rangpur and Mymensingh. In the city of Dhaka, most of the brick masonry buildings either
collapsed or were severely damaged (Oldham, 1899).
Bangladesh is surrounded by the regions of high seismicity which include the Himalayan Arc andShillong Plateau the north, the Burmese Arc, Arakan Yoma anticlinorium’s in the east and complex
Naga-Disang-Jaflong thrust zones in the northeast. It is also the site of the Dauki Fault system alongwith numerous subsurface active faults and a flexure zone called Hinge Zone (SAARC, 2011). These
weak regions are believed to provide the necessary zones for movements within the basin area.
According to Sharfuddin (2001), both the seismic hazard analysis and the establishment of seismic
maps were made difficult in Bangladesh due to the lack of homogenous, accurate and complete data.
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The 1993 Bangladesh national building code has adopted a seismic zoning map consisting of three
seismic zones, with zone coefficients of 0.25 (Zone 3 in the north and north-east), 0.15 (Zone 2 in the
middle, north-west and south-east) and 0.075 (Zone 1 in the south west). This zoning map is basedon peak ground accelerations estimated by Hattori (1979) for a return period of 200 years, where
Modhupur fault is situated in Zone 2 which is not so far from the Tangail municipality (Ali and
Choudhury, 1994). It is about only 40 km away from the fault, so it can be said that the infrastructureof Tangail municipality is highly vulnerable to earthquake.
There are three government colleges, seven non-government colleges, three government high school,
thirty non-government high schools, one hundred and sixteen government primary schools, thirty
five non-government primary schools, twelve madrasa in Tangail municipality but majority of themare very old (Banglapedia, 2008). Most of the existing schools and colleges’ buildings are 2 or 3
storied reinforced concrete frame buildings with infill brick walls and 1 storied brick masonrybuilding with reinforced concrete roofs and uses cement mortar in most of the cases. For this reason,a moderate level earthquake may create a huge damage to property and valuable lives. That is why
this earthquake risk assessment was done to evaluate the existing condition of the schools andcolleges in this region. School safety was given a major focus by the United Nations International
Strategy on Disaster Reduction (UNISDR) when the 2006-2007 World Disaster Reduction
Campaign was devoted to the theme Disaster Reduction Begins at School. This theme was chosen by
United Nations International Strategy on Disaster Reduction (UNISDR) because (a) it is in line with
the Priority 3 of the Hyogo Framework for Action 2005-2015: "Use knowledge, innovation andeducation to build a culture of safety and resilience at all levels, and (b) schools are the best venues
for forging durable collective values; and therefore suitable for building a culture of prevention anddisaster resilience (UNISDR, 2009).
From Bangladesh's perspective, school infrastructures are the most vulnerable during disasters due topoor construction, lack of proper maintenance and many other issues related to the schools andcolleges. Moreover, as a result of the rapid urbanization and over population in urban areas, schools
and colleges are growing in an unplanned way to accommodate students in the education system. As
a result, vulnerability is increasing in education sector and safety of the students is becoming
questionable day by day. Considering all these, school safety has become an issue of major priorities
to make schools safer for the well being of our next generation. In the study, the earthquake
vulnerability of schools and colleges in this region was identified to evaluate the existing conditionof the schools and colleges.

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Materials and Methods
The study was conducted to know the earthquake vulnerability assessment of schools and colleges at
Tangail municipality in Tangail district, Bangladesh. Tangail municipality is the central part and themost crowded area of Tangail district. For completing the study, 51 educational institutions including
20 primary schools, 17 high schools, 2 madrasa and 12 colleges in Tangail municipality was selected
because most of the schools and colleges are situated in urban areas where population density is sohigh. These infrastructures are vulnerable to earthquake due to rapid urbanization and also as theeducational institutions are not following the building code and many of them are more than 100
years old. Moreover, the institutions are just 40 km away from the Modhupur fault which is an active
fault.
The research work was done on the basis of Rapid Visual Screening (RVS) of Buildings for Potential
Seismic Hazards (PSH) method. To perform with this method, at first a data collection form wasselected which known as FEMA-154 data collection form (Fig. 1). The data collection form wascompleted for each building screened through execution of the following steps: a) verifying andupdating the building identification information, b) walking around the building to identify its sizeand shape, and sketching a plan and elevation view on the data collection form, c) determining anddocumenting occupancy, d) determining soil type, e) identifying the seismic lateral-load resisting
system (entering the building, if possible, to facilitate this process) and circling the related Basic
Structural Hazard Score on the data collection form, f) Seismic Performance Attribute Score
Modifiers (e.g., number of storeys, design date, and soil type on the data collection form), g)
determining the final score, S (by adjusting the basic structural hazard score with the score modifiers
identified in step g) and deciding if a detailed evaluation is required, and h) photographing thebuilding and attaching the photo to, or indicating a photo reference number on, the form. The
masonry building structures have more than seven storeys, and those schools that have no permanenteducational building were excluded from the present assessment.

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Fig. 1. FEMA-154 data collection form used in the study (FEMA, 2002).
Results and Discussions
Types of Infrastructures
In the study, three types of infrastructures were found: wooden, concrete and masonry. Among them
23.52, 58.82 and 17.65% were wooden, concrete and masonry, respectively. The percentages goeshigher towards the concrete building because people thought that it is more reliable against various
types of disasters and has a sustainable utilization, but it is also found that low quality or old
construction may also be great deadly for school student (Fig. 2). According to OECD (2004), a
primary school in San Giuliano, Italy, collapsed during Earthquake, killing 29 children and one
teacher in 2002. It is observed from the study that numbers of wooden buildings are not modest
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amount in this area which is comparatively safer than old concrete and masonry construction. Thus,
strong infrastructure plays important role as an earthquake resistor and reduce damage during
earthquake.
120
Total Number

Percent (%)

100

Percent (%)

100

80
58.82

60
40
20
0

23.53

30
17.65
9

12
Wooden51

Concrete

Masonry

Total

Infrastructure types
Fig. 2. Types of infrastructures of schools and colleges in Tangail municipality.
Epoch (age) of Infrastructures
Most of the school buildings of the study area were very old. Many of them, e.g. Santosh Zanbhi
High School, were built in British Period. From the study, 7 (13.73%) buildings were less than 10
years old, 19 (37.25%) buildings were less than 20 years old, 17 (33.33%) buildings were less than
30 years old and 8 (15.69) buildings were found more than 30 years old. Hays et al. (1998) foundthat with the passage of time buildings loss their lateral resistance and turn into more vulnerable toan earthquake. It is revealed from the study that 15.69% visited educational institutions were built
about more than 30 years ago that have followed low construction standards (Fig. 3). They arevulnerable to earthquake and age related decay compel then to fall a victim to seismic vibration.
Many of older buildings also showed vertical and plan irregularity whereas some of the newbuildings and infrastructures have also not been sited, designed, and constructed with adequate
enforcement of modern, state-of-the-art building regulations, lifeline standards, and land use
ordinances.

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Less than 10 years
Less than 30 years
15.69%

33.33%

Less than 20 years
More than 30 years
13.73%

37.25%

Fig. 3. Epoch (age) of the infrastructures of schools and colleges in Tangail municipality.
Number of Storeys of the Infrastructures
Height of the building is important as it is directly related to the weight of the structures andtheir response to ground motion. The natural frequency of building is low for tall buildings andhigh for short buildings. From the study it is revealed that 37.25, 23.53, 21.57 and 11.76%
infrastructures were 1, 2, 3 and 4 and above 4 stored, respectively (Fig. 4). Short buildings tend
to collapse or experience damage when amplification is higher in high frequency domain andtall buildings experience damage when amplification is higher in low frequency domain that means
the safety of building depends on its resonance. According to BIS (2002), one and two storeys
buildings have physical frequency of 10 and 5, respectively, whereas 3 to 5 storeys buildings havefrequency of 2.

Fig. 4. Storeys of the infrastructures of schools and colleges in Tangail municipality.
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Plan Irregularity
The buildings appearing to be E, L, T, U, or + shaped show plan irregularity, whereas square shapedbuilding has no plan irregularity for what they are more strong in structure. From the study it was
found that 31.37% of the infrastructures had plan irregularity which may fall in as victim toearthquake and other 68.63% had no plan irregularity (Fig. 5). Plan irregularity often results in shapeirregularity. It is an unfavorable feature of buildings. The shapes determine the probability of damage
in specific parts or storeys of a building which may even cause collapse. According to Herrera andSoberón (2008), it is observed from seismic events during 1980 to 2008 that the building damaged
causes due to plan irregularities. McCrum (2012) found that the effect of strength eccentricity on theseismic response of plan irregular structures needs further investigation and increasing the strengthof a lateral force resisting element in the infrastructure.
Vertical Irregularity
Structures having significant physical discontinuities in vertical configuration or in their lateral force
resisting systems are termed as vertically irregular structure. Vertical irregularity plays an importantrole in the earthquake vulnerability detection of the buildings. FEMA (2012) showed that verticalirregularity includes buildings with setbacks, hillside buildings, and buildings with soft storeys. The
observed 21.57% infrastructures have vertical irregularity that results from the uneven distribution ofmass, strength or stiffness along the elevation of a building structure and other 78.43%
infrastructures have no vertical irregularity (Fig. 6). Mass irregularity results from a sudden change
in mass between adjacent floors, such as mechanical plant on the roof of a structure, where stiffness
irregularity results from a sudden change in stiffness between adjacent floors, such as setbacks in theelevation of a building. SAARC report (2011) explained that vertical irregularity particularly is
considered a serious weakness and the corresponding score modifier is negative for all building types
with a recommendation for detailed evaluation.

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Fig. 5. Plan irregularity of the infrastructures of schools and colleges (left) and the verticalirregularity of the studied infrastructures (right).
Detailed Evaluation
On the basis of the final score, S, it is measured that detailed evaluation of the infrastructure isneeded or not. If the value is 2 or more than 2 then no need to detailed evaluation. But if the value isless than 2, then the infrastructure should be detailed evaluated (the value vary from country tocountry). According to Wang and Goettel (2007), a final score, S, of 2.0 means that the calculated
probability of building collapsed at the maximum considered earthquake is 10−2 or 0.01 i.e., 1%
chance of collapse, where a building with a final score of 3.0 has a factor of 10 times lower
probability of collapse than does a building with a final score of 2.0. Similarly, a building with afinal score of 1.0 is 10 times more likely to collapse than a building with a final score of 2.0. Fromthe study, 33 out of 51 infrastructures (64.71%) were needed detailed evaluation due to low finalscore of S and vertical irregularity with plan irregularity, and others 18 (35.29%) infrastructures
didn’t need detailed evaluation (Fig. 6). According to SAARC report (2011), if any of theseirregularities (plan and vertical irregularity) are noticed, the building may undergo much more severe
damage even up to Grade 4 or 5 and should be recommended for detailed.

Fig. 6. Detailed evaluations of the infrastructures is needed or not to needed.
Conclusion
Some of the schools and colleges in Tangail municipality were new and earthquake resistant. In
contrast more than half of the buildings were made of concrete, but most of the buildings were
ancient and visually they need further evaluation, some of them were built in British Period. Modern
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19May 2014engineering concrete-framed buildings were generally safer than non engineering infrastructures
because old buildings are devoid of modern engineering technology for what their architectural
longevity is vulnerable as they sometimes collapse due to earthquake or other natural forces. The
ultimate result of the fault line in architectural activity is considerably more lethal which kills higher
percentage of people than masonry structures. The worst victims will be the school and college
students. The observation found that the majority of the buildings were more than 20 years old andwere not appropriately followed plan irregularity and vertical irregularity. Seismic Performance
Attributes Score Modifiers showed that most of the infrastructures were needed detailed evaluation
to reduce the vulnerability of earthquake and vulnerable buildings or infrastructures should be
replaced by new earthquake resisting buildings; and occupancy load would be maintained in every
building.
Acknowledgements
The author is grateful to engineer K.M. Khaleduzzaman, member of Bangladesh Earthquake Society
and Bangladesh Society for Geo-technical Engineering. Sincere gratitude to the District Education
Officer (DEO), Tangail, and all the Headmasters and the Principals of the schools and colleges,
respectively in Tangail municipality for their kind cooperation during the study period.
References
Ali, M. H. and J. R. Choudhury. 1994. Seismic Zoning of Bangladesh. In: the International Seminaron Recent Developments in Earthquake Disaster Mitigation, Institution of Engineers, Dhaka.
Banglapedia. 2008. National Encyclopedia of Bangladesh. Asiatic Society of Bangladesh.
BIS (Bureau of Indian Standards). 2002. Indian standard criteria for earthquake resistant design ofstructures, Part 1: general provisions and buildings. Engineering, 1893: 41.
FEMA (Federal Emergency Management Agency). 2002. Rapid Visual Screening of Buildings for
Potential Seismic Hazards- FEMA 154. Federal Emergency Management Agency,
Washington DC, USA.
Hays, W., B. Mohammadioun and J. Mohammadioun. 1998. Seismic Zonation: A Frameworkfor Linking Earthquake Risk

Assessment

andEarthquake

Risk

Management(Monograph), Quest Editions Presses Academiques.
Herrera, R. G. and C. G. Soberón. 2008. Papers on Influencing of Plan Irregularity of Building. The
14th World Conference on Earthquake Engineering, October 12-17, 2008, Beijing, China
McCrum, D. P. 2012. Seismic Analysis of Braced Plan Irregular Structures Using Hybrid Testing
and Numerical Modeling. Department of Civil, Structural and Environmental Engineering,
University of Dublin, Trinity College.
20

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OECD (Organization for Economic Cooperation and Development). 2004. Keeping Schools Safe inEarthquakes School Safety and Security. OECD Programme on Educational Building. Paris.
Oldham, T. 1899. Report on the great Indian earthquake of 12th June, 1897, Memoir of Geological
Survey of India, 29: 1-349.
SAARC (South Asian Association of Regional Cooperation). 2011. Rapid Visual Screening of
School and Hospital Buildings in SAARC Countries. SAARC Disaster Management Centre
New Delhi.
Sharfuddin, M. 2001. Earthquake Hazard Analysis for Bangladesh. M. Sc. Engineering Thesis,
Department of Civil Engineering, BUET, Dhaka, Bangladesh.
UNEP (United Nations Environmental Program). 2001. United Nations Environmental Program.
Annual Evaluation Report.
UNISDR (United Nations International Strategy on Disaster Reduction). 2009. Terminology on
Disaster Risk Reduction and Response. Geneva, Switzerland: United Nations International
Strategy for Disaster Risk Reduction.
Wang, Y. and K. A. Goettel. 2007. Enhanced Rapid Visual Screening (ERVS) Method forPrioritization of Seismic Retrofits in Oregon. Oregon Department of Geology and MineralIndustries, California.

2221PART-III
Non-destructive Testing (NDT) in a residential building
located at Gulshan

BANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: KM Khaleduzzaman
Mehedi Ahmed Ansary24May 2014

1.0 Introduction
Mr. Ahmed, a house owner of Gulshan, Dhaka approached BUET for technical assistance to find out as
built status of different structural members of the existing residential building located at Gulshan. It has
been agreed that the terms of reference of the work would be limited to concrete strength determination
using two core tests and Schmidt Hammer test, identification of structural detailing at selected locations
through non-destructive testing (Ferroscan), excavating and physical checking of two foundations.
2.0 Determination of Concrete Strength by Using Schmidt Hammer and Core Test
Figure 1 shows the layout plan (showing the location of in-situ tests) of the area at which locations
Schmidt Hammer test have been carried out. Figure 2 shows the use of Schmidt Hammer and Table 1
shows the results of the Schmidt Hammer test. The concrete (cylinder) strength varies from 4050 to
48300 psi. Also concrete cores have been collected from four locations of the building (three from thefooting and one from the roof column) and concrete strength of core has been measured at the BUET
Concrete laboratory. The concrete strength of core collected from the foundation varies between 3530 to
5670 psi and the concrete strength of the core collected from the roof column is 4070 psi.

Fig. 1 Locations of Schmidth Hammer Test

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Fig. 2 Use of Schmidt Hammer to estimate concrete strength

25

May 2014

Table 1. Results of Schmidth Hammer Test (Beams and Columns)

Location

BD

Horizontal

BD

Vertical(Upward)BB

26

Direction

Horizontal

M±σCompressive
Strength(Cylinder), psi

39, 48, 32, 31, 42, 40,
40, 38, 39, 40

39±4.84050

43, 42, 42, 43, 43, 41

42±.824350

43, 33, 40, 43, 40, 39,
41, 42, 43

40±3.2

4170

Impact Values

Avg. Impact
ValuesBC

Horizontal

42, 39, 40, 41, 36, 38,
41, 40, 39

40±1.84170

C3Horizontal

49, 40, 42, 42, 49, 41,
42, 42, 42, 44

43±3.24830

C4Horizontal

40, 32, 39, 40, 40, 39,
41, 4039±2.84050

C7Horizontal

41, 50, 40, 42, 43, 41,
43, 42,4143±2.94830

S2

Vertical(Upward)49, 49, 42, 30, 51, 43,
41, 4343±6.64590

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3.0

Checking of Footing Sizes

Excavations have been made at the north-east corner of the building to expose two footings (FC2 and F6). It
should be mentioned here that the owner of the building allowed the BUET consultants to excavate only
these two locations. After excavation, the thickness and smaller width of the foundation have been measured.
Figure 2 shows the location of the footings and Table 2 compares the as built dimension with design
values.

Fig. 2 Locations of columns and footings

Table 2 Verification of physical dimensions of footings
Footing
Designation

As-built size(ft)

As-built
thickness (inch )Remarks

FC2

5 ft

24

ok

F6

7 ft

18

ok

27
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May 2014

4.0 Non-Destructive Testing (NDT) Using Ferroscan
The four storied building at Gulshan, Dhaka has been assessed with a view to check the as-built
condition of the structural design of different structural members (i.e, column, beam, and slab) of
the building. It is important to note that several cracks have been observed at the bottom side of thehanging cantilever verandah. Several ties (suspenders) have been provided in the design to support
the bottom part of the cantilever verandah. Cracks are also observed at the false ceiling of twobathrooms. Initially, few columns and some parts of slab (including RCC false ceiling of twobathroom) of ground floor and 2nd floor have been scanned with ferroscan machine to check thenumber and diameter of the steel used in these structural members. Figure 3 shows the position of
scanned columns and roof slabs of second floor.
3'-6"

C-1

3'-6"

S-5
3'-6"

S-4

S-3

C-2
S-1

S-6

S-2

Figure 3 Position of scanned columns (red circle) and roof slabs (green rectangle) of second floor

4.1

Scanning of Columns of Second Floor

Figures 4 and 5 are showing the Image scan result of column C-1 (long side and short side
respectively) at a height of 2'-8" from the ground. Figure 6 shows the cross section andreinforcement in column after scanning. The spacing of column ties (as per structural design)is 150 mm c/c. H o w e v e r , f rom the As-Built drawing, it shows that the spacing varies from 175
to 217 mm c/c.

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Figure 4 : Image scan result of column C-1(long side)

10"

Figure 5: Image scan result of column C-1(Short side)

10 mm Φ @ 150 mm c/c

10 mm Φ @ 175-217 mm c/c(a) As-Built(b) As per Structural Design

Figure 6: Column C-1 showing cross-section and reinforcement

Similarly Figures 7 and 8 show the Image scan result of column C-2 (long side and short side
respectively) at a height of 2'-0" from the ground. Figure 9 shows the cross section the column
reinforcement. The spacing of column ties (as per structural design) is 100 mm c/c. H o w e v e r ,f rom the As-Built drawing, it shows the spacing varies from 101 to of 110 mm c/c.
4.2 Scanning of Ceiling of Second Floor
Due to problems with accessibility, only bottom layer reinforcements of floor slab have been
ferroscanned. Figures 10 and 11 indicate the image scan result of six different positions ofceiling of second floor. S-1 position is at the slab of veranda which is just near the position
where some cracks are found. In this location according to design 12 mm Φ @ 300 mm c/c
has been provided with 1-12 mm Φ extra bottom (both directions). S-2 position is at the slab
inside a middle room. In this location according to design 12 mm Φ @ 87.5 mm c/c has
been provided (both directions). S-3 position is at the slab inside a middle room. In thislocation according to design 12 mm Φ @ of 150 mm c/c has been provided (both directions).
In S-4 location according to s t r uc t u r a l design, 12 mm Φ @ of 87.5 mm c/c has been provided
in both directions. In S-5 location according to design 12 mm Φ @ 75mm and 87.5 mm c/c havebeen provided in two directions. S-6 position is situated at edge of the room where integral (socalled concealed) beam, CB-1 has been provided. In this location according to structural design,29
30

May 2014

12 mm Φ @ 75mm and 87.5 mm c/c have been provided in two directions. In integral beam CB1, 4-20 mm Φ rebars has been provided for both top and bottom of the slab.
12 mm Φ @ 75mm and 87.5 mm c/c have been provided in two directions. In integral beam CB1, 4-20 mm Φ rebars has been provided for both top and bottom of the slab.

Figure 7: Image scan result of column C-2 (long side)
Figure 7: Image scan result of column C-2 (long side)

Figure 8: Image scan result of column C-2 (Short side)
Figure 8: Image scan result of column C-2 (Short side)
10 mm Φ @ 100 mm c/c

10 mm Φ @ 100 mm c/c
10 mm Φ @ 101-110 mm c/c(a) As-Built(b) As per Structural Design

10 mm Φ @ 101-110 mm c/c

As per Structural Design(b) reinforcement
9: Column C-2 showing cross-section and(a) Figure
As-Built
Figure 9: Column C-2 showing cross-section and reinforcement

As-Built: 10 mm Φ @ 133 to 171 mm c/c
Design: 12 mm Φ @ 150 mm c/c
Figure10:
Block
As-Built:
10 imagemm Φ of@ slab133 atto S-1171position
mm c/cDesign: 12 mm Φ @ 150 mm c/c
Figure 10: Block image of slab at S-1 position

30

As-Built: 10 mm Φ @ 81 to 109 mm c/c
Design: 12 mm Φ @ 100 mm c/c
As-Built:
10imagemm Φof@slab
81 to
mm c/cFigure11: Blockat 109S-2 position
Design: 12 mm Φ @ 100 mm c/c
Figure 11: Block image of slab at S-2 position

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As-Built: 10 mm Φ @ 135 to 178 mm c/c
Design: 12 mm Φ @ 150 mm c/c
Figure 12: Block image of slab at S-3 position

As-Built: 10 mm Φ @ 160 to 187 mm c/c
Design: 12 mm Φ @ 87.5 mm c/c
Figure 13: Block image of slab at S-4 position

Rebar in Integral Beam

Rebar in Integral Beam`
As-Built: 12 mm Φ @ 61 to 84 mm c/c
As-Built: 10 mm Φ @ 160 to 187 mm and 77 to 103
Design: 12 mm Φ @ 75 mm and 87.5 mm c/c
mm c/cDesign: 12 mm Φ @ 75 mm and 87.5 mm c/c
Integral Beam: 2-20 mm Φ (bottom) after scanning; 4-20 mm Φ (bottom) according to Design
Figure 14: Image scan of Concealed beam at S-5
position (middle steel Diameter around 20mm found)Figure 15: Image scan of Concealed beam at S-6
Position (middle steel Diameter around 20mm found )31
32

May 2014

4.3
Scanning of Cantilever Verandah with Suspended Bottom Slab of Second Floor
A suspended bottom slab of the cantilever verandah of the second floor has been scanned. Locationof the suspender or tie rod has been identified as shown in Figure 16. In structural design, the numberof suspenders is more than the number provided in the construction.

Suspender or tie
Suspender or tie

Hanging portion (sidewise)

Hanging portion (middle)

Figure 16: Location of suspenders in the bottom slab of cantilever verandah

4.4

Scanning of Columns of Ground Floor

Figure 17 shows the position of scanned columns and roof slabs of ground floor. Figures 18 and19 show the Image scan result of column C-1 (long side and short side respectively) at a height of
2’-8’’ from the ground. Figure 20 shows the cross section of the column and reinforcement. The
spacing of the tie bar from the design shows 100 mm c/c. From the As-Built drawing, it shows
the spacing varies from 180 to of 280 mm c/c. Similarly, Figures 21 and 22 shows the Image
scan result of column C-2 (long side and short side respectively). Figure 23 shows the crosssection of the column and reinforcement. The spacing of the tie bar from the design shows 100
mm c/c. From the As-Built drawing, it shows the spacing varies from 120 to of 230 mm c/c.
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S-2

Figure 17: Position of scanned columns (red circle) and roof slabs (green rectangle) of ground floor

S-1

Figure 18: Image scan result of column C-1 (long side)

Figure 19: Image scan result of column C-1 (Short side)(b) As per

Structural
Design(a) As-Built
Figure 20: Column C-1 showing dimension and reinforcement

33
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May 2014

Figure 21: Image scan result of column C-2 (long side)

Figure 22: Image scan result of column C-2 (Short side)(b) As per Structural Design(a) As-Built
Figure 23: Column C-2 showing dimension and reinforcement

4.5

Scanning of Beams of Ground Floor

Ferroscanning has also been performed to know the as built status of floor beams. Beam B1 has been
selected in this case due of its accessibility to the scanner. For beam B1, the spacing of the stirrupfrom the design shows 100 mm c/c. From the As-Built drawing, it shows the spacing varies from88 to of 113 mm c/c. Therefore, it is apparent from scanning that the spacing of stirrup complies
with the structural design.

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Figure 24: Long section of beam after scanning showing
Figure 24:
Long section of beam after scanning showing
spacingof stirrup
spacing of stirrup

Figure 25: Beam soffit after scanning showing two
Figure widthwise
25: Beam soffit after scanning showing two
rebarsrebars widthwise

4.6 Scanning of Ceilings of Ground Floor
4.6
Ceilings
In S-1Scanninglocation ofjustbelow oftheGroundintegralFloor
beam CB1, according to design 12 mm Φ @ of 87.5 mm c/c

In S-1locationjust In
below
integralaccording
to design
12 mm Φto@designof 87.5
mmc/c
Φ
has
been
provided.
S-2 thelocationjustbeam
belowCB1,
the integral
beam
CB, according
12mm
has
been
provided.
In
S-2
location
just
below
the
integralbeam
CB,accordingtodesign12mm
Φ@ of 150 mm c/c has been provided in one direction and 87.5 mm c/c in another direction.
@ of 150 mm c/c has been provided in one direction and 87.5 mm c/c in another direction.

As-Built: 10 mm Φ @ 81 to 103 mm c/c
As-Built:
10 mmΦ @of81
to 103mmc/c
Figure26: Block
image
slab
at S-1position

As-Built: 10 mm Φ @ 95 to 119 mm c/c
As-Built:
10 mmΦ @of95
to 119mmc/c
Figure27: Block
image
slab
at S-2
position

Figure 26: Block image of slab at S-1 position

Figure 27: Block image of slab at S-2 position

35
36
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May 2014

Rebar of roof slab (bottom layer)

Tie of integral beam

Rebar of integral beam(b) As per Structural Design(a) As-Built
Figure 28: Rebar location for integral beam (CB1) at S-1 position(number of rebars in integral beam CB-1 doesn't comply with the structural design)

4.7

Verification of Tie Spacing of Column of Ground Floor by Using Linescaning Technique

From Imagescan results of columns of ground floor, it has been observed that As-Built tie bar
spacing does not match with the structural design spacing in a few locations. A verification of thespacing has been done using Linescaning technique; the results are shown in Figures 29 and 30.

Figure 29: Line scan result of column C-1

Figure 30: Line scan result of column C-2
As-Built tie spacing deviates from the structural design (10 mm Φ @ 4″ c/c or 100 mm c/c))

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5.0

Concluding Remarks

Scanning results show that
1. There is compliance of main rebar in columns with the structural design
2. In general, the as built concrete strength of different structural members (Footing, Columns,
Beams and floor slab) complies with the structural design.
3. Spacing of column ties has found to vary from the spacing provided in the design
4. In general, steel rebars in floor slabs (bottom layer) has found to comply with the design
5. The provision of integral beams along column lines (CB) has been confirmed by thescanning. However, the number of rebars in CB1 location doesn’t comply with thestructural design. Therefore, the integral beam CB1 may not be adequate to transfer
unbalanced moment to the columns. Some of the column-integral beam joints may need to
be strengthened to ensure the transfer of this unbalanced moment.
6. The spacing of the suspenders (to support the bottom slab of the cantilever verandah) does
not comply with the structural design. This may affect the stability of these structuralmembers.
7. Long section of the beam shows the location of the stirrups

37
38

PART-IV
SAVAR BUILDING TRAGEDY IN BANGLADESH: WAY
FORWARDBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Naima Rahman
Mehedi Ahmed Ansary

39

May 2014

As garments industries have become the main source of foreign income of Bangladesh, many new
factories have been established in Dhaka City. But due to lack of concern from authorities, thisindustry has become one of the highly risk working sector for workers. Garment industry has been
experienced many fire accidents in the last decades taking life of many workers. But the recent
accident of building collapse in Savar is the worst of all. This incident took lives of 1132 people andleft many disabled. About 332 people are still missing according to their families. Six garments
factories, one bank and many shops are going into debris within a few minutes without any shakefrom outside. In this study, the authors discuss the reason behind the accident, the role of authorities
in search and rescue, overall co-ordination, rehabilitation and legal activities. The authors also
recommend some measures to avoid this type of disaster in Bangladesh.

1. INTRODUCTION
1.1 BackgroundOn 24 April at 9am, a nine-storey building collapsed in Savar, 25 kilometers north of the Bangladesh
capital, Dhaka (see Figure 1). As of August, 1132 people died (CPD, 2013), 2438 people were
rescued and were provided with immediate basic first aid or transferred to nearby hospitals for
medical attention. The building housed several garment factories, a bank and several shops. The
factories manufactured apparel for brands including Benetton, Bonmarché, Cato Fashions, theChildren's Place, El Corte Ingles, Joe Fresh, Mango, Matalan, Primark and Wal-Mart. According to
BGMEA (Bangladesh Garments Manufacturers and Exporters Association) 2800 workers of the 6garment factories were in the building during the accident. But the actual number is around 3900
(CPD, 2013). Day before the incident, some cracks developed on some pillars and a few floors of thebuilding following a jolt, causing panic among the people working there. They rushed out of thebuilding and some even got injured in the process, said a number of garment workers and locals. The
industrial police visited the building that day and asked the building authorities not to open thebuilding. But the warnings and instructions were ignored. The shops and the bank on the lower floors
immediately closed after cracks were discovered in the building. But workers of at least two garment
factories at Rana Plaza were forced to join their workplaces following a false assurance on thebuilding’s safety from a local engineer, relatives of the victims alleged. As a result the deadliest
garment-factory accident in the history of Bangladesh occurred which is also considered as thedeadliest accidental structural failure in the modern world.

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Figure 1. Location of the collapsed building
1.2 Purpose of the Study
The purpose of the study is to focus on overall scenario of the Savar tragedy. This article
presents the search and rescue effort undertaken by different agencies in Bangladesh to rescue people
from underneath the collapsed building and tries to explain the reasons behind the building collapse.
Figure 2 shows the collapsed building.

Figure 2. The collapsed building
2. REASONS BEHIND THE BUILDING COLLAPSE
Rana Plaza was a 9-storied industrial building with a single basement. The local municipality gave
the owner permission to construct a 5 storey commercial building with one basement in 2005 andlater allowed the owner to extend it up to 9-storey, without considering the consequence of suchaction. The width of the building was around 25 m and length around 80 m. A typical grid of thebuilding is 5.2 m by 8.2 m. The column sizes vary from 35 cm by 35 cm to 45 cm by 45 cm. The
building was supported by pile foundation having 450 mm diameter and length of 18.3 m. Threemain reasons can be attributed to the collapse of the structure: (i) Addition of four extra floors; (ii)
Conversion of the building from commercial to industrial use and (iii) Placement of Power41
41

May 2014

Generators at the higher floors. The steel grade used was 60 grade deformed bar and concrete
strength was found around 3000 psi [see Figure 3].

Figure 3. (a) Broken samples collected from the building site and (b)Concrete cores collected from beams, columns and slabs of the collapsedbuilding
2. SEARCH AND RESCUE OPERATIONS
2.1 Search and Rescue
Local Volunteers, volunteers of Bangladesh Red Crescent Society, personnel from Bangladesh
Fire Service and Civil Defense, Bangladesh Armed Forces personnel, Border Guard Bangladesh andlocal police were involved in search, rescue and evacuation operation of trapped garment workers at
Savar Building collapse site. On the day of incident, these organizations rescued 1762 people alive.

Figure 4. Search and rescue operation
The local people started rescue operation immediately after the incident. Then Bangladesh Army,
Navy, Fire Service, BGB, Police and different volunteer teams joined in the rescue activities. Police
and RAB are engaged to maintain law and order situation at the site. Rescue operation iscontinuing.1200 volunteer from Dhaka, Keraniganj and Narayanganj area (trained byComprehensive disaster management Programme (CDMP) under Ministry of Disaster Management
and Relief) are working in Rescue operation. To purchase rescue equipment instantly, MoDMR has
given BDT 5,00,000 to Fire Service and Civil Defense. Figure 4 and 5 shows the acticity of people
during Search and rescue operation

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Figure 5. Search and rescue operation
More than 200 volunteers under the Department of Fire Service and Civil Defense (FSCD) who havereceived training under the previous DIPECHO VI Project implemented under the NARRI
Consortium were immediately deployed after the incident and are working on location.
2.2 Overall Coordination
Armed Forces Division (AFD) of Bangladesh coordinated the search and rescue operation.
Eman medical hospital played an important role for the injured victims by providing medical support.
Fifteen Medical teams from Bangladesh Army, two from Navy, one from Air Force, one from BGB
and ten teams from health department, the doctors and medical workers of local hospital and clinic
are engaged for treatment of injured people.
2.3 Contribution of local volunteer
Some local people involved in search and rescue operation among them some died
unexpectedly. Figure 6 shows the number of death and rescued alive from the day of accident to the
day of last dead body found.
2000
1800

Numbe of
death

1600
1400

Number of
Rescued
Alive

1200
1000
800
600
400
200
12-May-13

11-May-13

10-May-13

9-May-13

8-May-13

7-May-13

6-May-13

5-May-13

4-May-13

3-May-13

2-May-13

1-May-1330-Apr-13

29-Apr-13

28-Apr-13

27-Apr-13

26-Apr-13

25-Apr-13

24-Apr-13

0

Figure 6. Number of death and rescued alive
From the day of accident, 574 people were rescued alive whereas 124 people were found dead. On
the second day the highest number of people (1762) was saved alive. Alive people were found up to
4 days of the accident. But a woman named Reshma was found and rescued alive and almost unhurt
43
43

May 2014

under the rubble 17 days after the accident on 10 May. Dead bodies were found almost every day
from 24 April to 12 May.
The Bangladesh Red Crescent Society was among the first responders on the scene. 100 trained
volunteers are on the ground on a rotation providing search and rescue, basic first aid and safe
drinking water. The organization also established a mobile medical team assisting the wounded. The
Red Crescent Society ambulance service transported wounded people to various hospitals, and theorganization also helped with the management of dead bodies. Restoration of Family Link (RFL)
volunteers provided mobile phone services for the injured (see Figure 8) to connect with theirfamilies and relatives, and also compiled a list of the missing, injured and dead.

AFD
6

BFSCD

5

BDRCS

4

DDM

3

UNO

2

Police1

RAB
PM

VolunteerPM
RAJUK

14-May-13

12-May-13

AFD

13-May-13

11-May-13

9-May-13

10-May-13

7-May-13

BDRCS

8-May-13

5-May-13

6-May-13

4-May-13

2-May-13

3-May-1330-Apr-13

UNO

1-May-13

28-Apr-13

29-Apr-13

26-Apr-13

RAB

27-Apr-13

24-Apr-13

25-Apr-13

0

Figure 7. Number of key words in newspaper articles
Armed Forces Division (AFD) of Bangladesh engaged in the disaster management of the accident
most as their name came in newspaper articles for 37 times. They appeared every day in newspaper
from the day of accident to 14 May. Then come Bangladesh Fire Service and Civil Defence(BFSCD) with 20 times. Local volunteers contributed significantly with 15 times appearance innewspaper. The Department of Disaster Management (DDM) which is responsible for disastermanagement in the whole country appeared only 3 times in newspaper articles. The figure 7 shows
the number of key words in newspaper articles from 24 April to14 May.

Figure 8. Some of the critically injured garments workers

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3. MENTAL TRAUMA AND REHABILITATION
After the Savar tragedy, many victims and volunteers have been suffering from mental trauma of accident. One
volunteer named Rubel committed suicide from the shock. Many of those who survived have lost their limbs,
many have become paralyzed. Ironically, all those people are in their productive age and most of them are theonly earning member of their family. With disability and deformity, it has become extremely difficult for themto get back to work again. But with long term rehabilitation support, they can lead a better life with acquiring
productivity and mobility. After such traumatic experiences, nearly everyone will have the symptoms of stressand grief for the first month which is a natural grieving process. Some will still experience those symptoms andthey cannot come to terms with what has happened and suffer Post Traumatic Stress Disorder (PTSD). Mental
trauma can be solved by rehabilitation for a long time
4. NATIONAL VS. INTERNATIONAL RESPONSE
The Savar tragedy took limelight of both national and international media after the day of incident. Manyinternational leaders including Pope, Secretary General of United Nations, ILO and international NGOs showed
their deepest concern for the victims. The European Union (EU) has raised strong concern over labor conditions
and declared appropriate action to encourage improvements in working conditions in Bangladeshi factories.
Major western clothing retailers are squeezing Asian suppliers and a flawed approach to ensuring even basic
working standards are fuelling conditions for tragedies like the Savar disaster.
United States of America suspended the Generalized System of Preferences (GSP) facilities on the entrance of
Bangladeshi product into the US market after Savar tragedy considering the accident of Savar Rana Plaza,Tazrin Fashion, and unsolved case of murder of a trade union leader. They have also concerned about the safety,
development of the standards of the laborers in Bangladesh as the biggest labor union of the USA, AFL-CIO has
been convincing the government of USA to stop the GSP facilities for Bangladesh since 2007.
World Health Organization is going to provide more emergency drugs as per government request and has
already provided blood transfusions sets, dressing and first aid materials along with emergency medicines to
Savar Upazila Health Complex and Enam Medical College Hospital for the injured persons.
Islamic Relief, Bangladesh provided various equipments to support search and rescue to Fire Service and Civil
Defense (FSCD). Action Aid, Bangladesh has provided emergency rescue equipment worth BDT 2,00,000 for
FSCD’s rescue team and food worth BDT 50,000,00 for Urban Community Volunteers. Emergency medicine
of BDT 10,000.00 is also supplied for injured people.
BDT 20000.00 has been provided to each deceased family. Total BDT 86,60,000 has been distributed to 433
families. Each injured person will get BDT 5000. BDT 47,15,000 has been distributed among 943 injured. BDT
4,00,00,000 has been allocated from MoDMR to DDM. DDM has allotted BDT 3,00,00,000 to District
Administration for distribution.
The following graph shows the number of national and international articles on Savar tragedy in the Daily Star
Bangladesh.

45
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May 2014

Comparison of national and international articles on savar building collapse

Numbe of articles

25
20
15
10

National

5International0

Figure 9. Comparison of national and international articles on savar building collapse
After the disaster, government of Bangladesh promised to give about $1,250 in cash and $19,000 insavings certificates to the families or relatives of died workers, but yet has provided about $1,250 to$5,000 to some 777 families. Nearly 300 bodies were not identified and claimed by families orrelatives.
5. RECOMMENDATION
Bangladesh faced its worst human tragedy through Rana Plaza building collapse at Savar, Dhaka. In
1996 at Kalabagan, in 1997 at Khilgaon, in 2004 at Sakaribazar, in 2005 in Savar, in 2006 at
Mahakhali, in 2010 at Hatirjheel and at Kathalbagan similar incidence occurred where altogether
several hundred people were killed. Enforcement of Bangladesh National Building Code (BNBC)
has become the top priority.
Immediately, we need to set up a Building Regulatory Authority (BRA) as prescribed in BNBC.
BRA will aim to deliver: Better safeguards for consumers; Building industry transformation andLegislative reform. The Building Authority will work closely with four statutory bodies to provide
industry leadership and will regulate building quality. The associated bodies will be the Building
Advisory Council, Building Appeals Board, Building Practitioners Board and the Building
Regulations Advisory Committee. The Authority and four bodies will














Regulate Bangladesh’s building industry
Administer the registration of a country’s building practitioners and monitor their conduct
Advise the relevant Minister and the Government on building regulatory development
Administer building legislation, the Building Act 1952 and Building Regulations 2008
Resolve disputes and appeals arising from the Building Act
Inform consumers about building and renovating
Communicate changes that occur in building legislation
Promote improved building standards nationally and internationally
Provide comprehensive information on building activity
Inform industry decision making through data and analysis
Facilitate industry research
Support the uptake of information technology and e-commerce
Encourage sustainable and accessible building design, construction and use

The BRA will carry out these functions in consultation with a wide variety of stakeholders.

46

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ICUS Report 74

6. CONCLUSIONS
Many questions have already been raised about the future of the garments industry in
Bangladesh after a number of accidents like Spectrum Garment Accident, Tazreen Fashion
Disaster and the latest Savar Building Collapse. A large number of foreign buyers including
Disney have decided not to buy clothes from Bangladesh because of the poor working
condition in the garments industry. It may severely damage the social and economic future of
Bangladesh in long term. The government, the leaders of the garments industry, the NGOs, andthe civil society have to come forward in unity to increase the quality of working conditions
and livelihood of the workers of this sector. The foreign buyers need assurance from thegovernment that they will never again face this kind of disaster in Bangladesh.

47
47

PART-V
SEISMIC RISK ASSESSMENT OF SOMEHISTORICAL MOSQUE OF DHAKA USING NON-DESTRU
CTIVE TESTING METHODSBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: KM Khaleduzzaman
Mehedi Ahmed Ansary48

May 2014

Dhaka city, the capital of Bangladesh is one of the most densely populated cities of the world. Old
Dhaka, the oldest part of Dhaka city, is considered as a highly earthquake vulnerable zone due to itsvery high density of population living in a very compact land area with close proximity of buildings
including vulnerable structures along narrow local streets. In proportion to the population density,
the availability of critical facilities is not sufficient in this area. In this paper, the findings of seismic
vulnerability assessment of five mosques, four educational institutes and one community centre ofward number-65 of Dhaka city have been presented. Initially Rapid Visual Screening (RVS) survey
and Modified Turkish Method have been used to evaluate the vulnerability of these criticalstructures; later Ferroscan and Microtremor have been used to assess their existing condition.
1.

INTRODUCTION

2.

STUDY AREA

In earthquake prone areas there is a need for the assessment of the capacities of large numbers ofexisting buildings. The results of such assessment are essential for rational planning of retrofit
programs for existing buildings before the occurrence of a strong earthquake, for the allocation of
rescue forces and equipment to optimally deal with the forecasted damage. Dhaka city is one of themegacities of the world which has recently experienced earthquakes at regular intervals that have notcaused immense damage but makes us aware about the future risk. As the older part of Dhaka city,
popularly known as old Dhaka, is one of the most densely populated area with a huge number ofolder constructed buildings. Ward 65 of Dhaka City Corporation South is one of these kinds of older
part of Dhaka city. There are around 20 critical facility structures (educational institutions. religious
prayer place, community centre etc.) in this ward. Earthquake vulnerability assessment of 10
structures of these critical structures has been carried out and the findings are presented in this paper.

All the assessed structures are located in ward number-65 of Dhaka city Corporation South. This area
is situated at around 23°42’55.88” N latitude and 90°43’45.40”E longitude. Figure:-1 is showing thelocations of the evaluated structures.

Figure 1: Location of the assessed buildings
50

49
BNUS Annual Report-2013

ICUS Report 74

1. Hazi Abdul Latif Mosque, 2. Mosjid-A-Noor, 3. Islambag Jamia Islamia Madrasah, 4. Islambag
1. HaziIslamia
AbdulMosque,
Latif Mosque,Mosjid-A-Noor,
3. Islambag
Jamia Islamia
4. Center,
IslambagJamia
5. Haji2.Ibrahim
Govt. Primary
School, 6.Jamal
SordarMadrasah,Community
7.
1.
Hazi
Abdul
Latif
Mosque,2.
Mosjid-A-Noor,
3.
Islambag
Jamia
Islamia
Madrasah,
4.
Islambag
Jamia
Islamia
Mosque,5.
Haji
Ibrahim
Govt.
Primary
School,6.JamalSordarCommunity
Center,7.
Rahamotganj Chhata Minar Mosque, 8.Baitul Aman Mosque, 9. Islambag Ashraf Ali HighSchoolJamia
Mosque,5. HajiIbrahim8.Baitul
Govt. Primary
School, 6.Jamal
SordarCommunity
Center,7.
Rahamotganj
ChhataMinar
Mosque,Aman Mosque,9. Islambag
AshrafAli High
Schooland
10.Islamia
Metropolis
DegreeCollege.
Rahamotganj
ChhataMinarCollege.
Mosque, 8.Baitul Aman Mosque, 9. Islambag Ashraf Ali High School
and
10. Metropolis
Degreeand 10. Metropolis Degree College.
3.
3.
3.

RVS RESULTS
RVS RESULTS
RVS RESULTS
Modified
Turkish method tier-1 (RVS) has been carried out for the ten selected structures. The

method tier-1(RVS) hasbeen carried
for thetentheselected
structures.
The
result Modified
of RVS ofTurkish
these structures
is presented
in Table
1. RVSout
scoresof allstructures
are greater
Modified
Turkishmethodtier-1
(RVS)
has
been
carried
out
for
the
ten
selected
structures.
The
result50,
of RVS
these structures
presented
in Table
RVS scoresof all the structures are greaterthanwhichofindicatesthat noneisof
the structuresare 1.
seismicallyvulnerable.
result50,
of RVS
these structures
presented
in Table
RVS scoresof all the structures are greaterthanwhichofindicatesthat noneisof
the structuresare 1.
seismicallyvulnerable.
than 50, which indicates
that
none
of
the
structuresareseismicallyvulnerable.
Table: 1: Modified Tarkish Method tier-1 (RVS) results
Table: 1: Modified Tarkish Method tier-1 (RVS) results
Table: 1: Modified Tarkish Method tier-1 (RVS) results
Name ofName
the ofNameofthestructurethestructure
structure

Metropolis
Metropolis
DegreeDegreeCollege
Metropolis
College
Islambag
DegreeIslambag
AshrafCollegeAli
AshrafAli
High
SchoolIslambagHigh
SchoolHaji
IbrahimAshraf
Ali
Haji
Govt.
Primary
HighIbrahim
SchoolGovt.
Primary
SchoolHaji Ibrahim
SchoolHazi
Abdul
Govt. Primary
Hazi
Abdul
Latif
MosqueSchoolLatif
MosqueMosjid-AHazi Abdul
Mosjid-ANoor
Latif Mosque
Noor
IslambagJami
Mosjid-AIslambagJami
aIslamiaMadr
Noor
aIslamiaMadr
ashah
IslambagJami
ashah
aIslamiaMadr
IslambagJami
ashah
IslambagJami
aIslamiaaIslamia
MosqueIslambagJami
MosqueaIslamia
Rahamotganj
MosqueRahamotganj
ChhataMinar
ChhataMinar
MosqueRahamotganj
MosqueJamal
SordarChhataMinar
Jamal
SordarCommunity
MosqueCommunity
Center
Jamal Sordar
CenterBaitulAman
Community
BaitulAman
MosqueCenterMosqueBaitulAman
MosqueNo. ofStoriesNo. ofStoriesNo. ofStories

5
5
5
4
4
4
4
4
43
3
23
2
25
5
5
2
2
2
3
3
3
5
5
53
3
3

Base
ScoresBase(BS)
ScoresBase(BS)
Scores(BS)
Zone II
Zone II
Zone II

85
85
85
100
100
100
100
100
100
120
120
130
120
130
130
85
85
85
130
130
130
120
120
120
85
85
85
120
120
120

Vulnerability Scores (VS)
Vulnerability Scores (VS)
Vulnerability Scores (VS)
Soft
Story
Soft
Story
Soft

Heavy
Overhang
Heavy

Story

Overhang
Heavy
Overhang

0
0
0
-20
-20
-20
-20
-20
-20
-15
-15
0
-15
0
00
0
0
0
0
0
-15
-15
-15
-25
-25
-25
-15
-15
-15

0
0
0
0
0
0
0
0
00
0
0
0
0-15
-15
-15
0
0
0
0
0
0
0
0
00
0
0

Apparent
Quality
Apparent
Quality
Apparent

Short
ColumnShort
ColumnShort

Pounding
EffectPounding
EffectPounding

Topo.
EffectTopo.
Effect
Topo.

0
0
0
-10
-10
-10
-10
-10
-10
0
0
-5
0
-5
-5
-15
-15
-15
0
0
0
0
0
0
-15
-15
-15
0
0
0

-5
-5
-5
-5
-5
-5
-5
-5
-5
-5
-5
-5
-5
-5
0
0
0
-5
-5
-5
-5
-5
-5
-5
-5
-5
-5
-5
-5

-3
-3
-3
-3
-3
-3
-3
-3
-3
-2
-2
0
-2
0
0
-3
-3
-3
0
0
0
-2
-2
-2
-3
-3
-3
-2
-2
-2

0
0
0
0
0
0
0
0
00
0
0
0
00
0
0
0
0
0
0
0
0
0
0
00
0
0

Quality

ColumnEffect

RVS
Score
RVS
Score
RVS
Score

Effect

77
77
77
62
62
62
62
62
62
98
98
120
98
120
120
52
52
52
125
125
125
98
98
98
37
37
37
98
98
98

4. MICROTREMOR OBSERVATION
4. MICROTREMOR OBSERVATION
4. MICROTREMOR OBSERVATION

Soil characteristics can be assessed by Microtremor measurement. Hard soil gives highSoil andcharacteristics
canlow
befrequency.
assessed byMicrotremor
measurement.
Hard soil
gives
high
frequency
soft soil gives
A structure
may experiencea vibration
periodat whichSoilcharacteristics
canbeassessedby
Microtremor
measurement.
Hard
soil
gives
high
frequency
softearthquake
soil gives low
frequency.
structure
maytoexperience
vibration
periodat which
it oscillatesandin thevibration
motionAand
will tend
response toa that.
Naturalfrequencyoffrequency
softearthquake
soil gives low
frequency.
structure
maytoexperience
vibration
periodat which
it oscillatesandin thevibration
motionAand
will tend
response toa that.
Naturalfrequencyof
it oscillates in the earthquake vibration motion and will tend to response to that. Natural frequency 50
of
50
51
50

May 2014

structure is obtained based on the spectral ration of horizontal component of the structure to that ofground. Wave propagation mechanism of Microtremor and its relation with ground vibration
characteristics were studied from the beginning of Microtremor studies (Aki, 1957; Kanai andTanaka, 1961).
Basically there are two types of Microtremor observations to the number of observation points.
These are point and array observations of microtremors (Ansary et al., 1996). From the arrayobservation of Microtremor of period greater than 1 sec, Rayleigh-wave and Love-wave originatingfrom natural sources, such as sea wave, variation of air and wind pressure can be recognized. On theother hand, short-period Microtremor of period less than 1 sec is thought to be generated by artificial
noises such as traffic vehicles, industrial plants, household appliances, etc. Some researches (Sato etal., 1991; Tokimatsu and Miyadera, 1992; Tokimatsu et al., 1994) have showed that microtremors
are mainly composed of Rayleight-wave and some (Nakamura, 1989; Wakamatsu and Yasui, 1995)
have showed that short-period Microtremor bears resemblance to shear-wave characteristics. On theother hand, Microtremor can also be dominated by Love–wave (Tamura et al., 1993). Recently,
Suzuki et al. (1995) have applied Microtremor measurements to the estimation of earthquake groundmotions based on a hypothesis that the amplitude ratio defined by Nakamura can be regarded
identical with half of the amplification factor from bedrock to the ground surface. However, the real
generation and nature of microtremors have not yet been established.
In general, the approaches to the identification the dynamic properties of structure can be categorized
into three main approaches: (1) empirical, (2) numerical analysis, and (3) direct measurement
approaches. The empirical approach provides simplified formulas for estimating the fundamental
periods of structures in terms of geometric dimensions of the structures. The second approach, thenumerical analysis, is normally used during the design process. A finite model of the structure is first
formulated. Dynamic properties such as natural frequencies and vibration mode shapes are obtainedby the Eigen analysis. The third approach is the direct measurement approach, which first measures
dynamic responses of existing structures, and then identifies their dynamic properties from themeasured responses.
4.1. DATA COLLECTION AND PROCESSING
For Microtremor observation at the selected buildings, initially the sensors are deployed. One
sensor is fixed on the roof of the buildings and another one on the free field near the structure. Aftertaking the observation with the help of microtremor, the time domain velocity data is converted tofrequency domain data and the natural period of the structures have been estimated. Around theinvestigated structure three 3-dimensional accelerometers are assembled to measure the groundresponse of the ambient excitation.

52

BNUS Annual Report-2013
51

ICUS Report 74

3-D
Accelerometer

Figure 2: Typical floor plan of Jamal Sardar Community Centre
The computation steps of the spectrum analysis is shown in Figure 4 and described as follows:•
Pre-Processing:- 3-dimensional input (the accelerometer in northward direction to get North-South, East-West andvertical components)- Windowing of the signal (in our case only the ambient parts are of interest, observe, in case oftransient excitation only the transient parts of the time response are of interest)•
Main Data-Processing:Hence the three different components of the signal were considered separately. The main dataprocessing is repeated for every input-signal (n-Steps according to the numbers of preliminary
separated windows).
- FFT is applied to obtain the several spectral amplitudes of the three components- Smoothing of the three spectral amplitudes with a bandwidth factor of 10 to 15- Afterwards the resulting horizontal component and vertical component are plotted to obtain theamplitude in frequency domain.

53
52

May 2014

Figure 3: Data collection by Microtremor
Figure 3: Data collection by Microtremor
4.2. MICROTREMOR ANALYSIS RESULTS
4.2. MICROTREMOR ANALYSIS RESULTS
Figure 4 shows individual time histories for X, Y and Z components for a building. Figure 5 shows
Figureshowstime
individual
time
histories
for X, theY andZ components
for a building.
Figure 5inshows
FFT of4thosehistories.
Table
2 presents
predominantfrequencyof the buildings
both
FFT
of
those
time
histories.
Table
2
presents
thepredominantfrequencyofthebuildings
inboth
directions.
directions.

Figure 4: Time history data on the soil and top of the building of Jamal Sardar Community Centre
Figure 4: Time history data on the soil and top of the building of Jamal Sardar Community Centre
Figure 5: Smoothed
FigureSmoothed
data of5:horizontal
dataofhorizontal
Fourier spectra of
Fourier
spectraatof
microtremors
microtremorsatsoil and top of thesoil
and topof thebuildingof Jamalbuildingof
Jamal
Sardar Community
SardarCentre
CommunityCentreTable 2: Predominant frequency of the buildings
the buildings
Name of the Structure Table
First2: Predominant frequency
Modeof Second
Mode
Name of the Structure
First
Mode
SecondMode(X Direction)(Y Direction)(X Direction)(Y
Direction) Period (s)Frequency(Hz) Period (s)Frequency
Frequency (Hz) Period (s)Frequency
Period (s)(Hz)
Metropolis Degree College
2.58
0.39 (Hz)2.96
0.34
Metropolis
DegreeCollege
2.58
0.39
2.96
0.34
Islambag Ashraf Ali High
2.51
2.48
Islambag Ashraf Ali High
0.40
0.40
School
2.51
2.48
0.40
0.40
SchoolHaji Ibrahim Govt. Primary
4.01
20.01
Haji
Ibrahim
Govt.
Primary
0.25
0.05
School
4.01
20.01
0.25
0.05
School54

BNUS Annual Report-2013
53
53

ICUS Report 74
Hazi Abdul Latif Mosque
Mosjid-A-Noor
Islambag Jamia Islamia
Madrashah
Islambag Jamia Islamia
MosqueRahamotganj Chhata Minar
MosqueJamal Sordar Community
CenterBaitul Aman Mosque

5.

7.79
5.42

0.13
0.18

14.85
14.9

0.07
0.07

5.69

0.18

5.69

0.18

6.70

0.15

9.49

0.11

10.15

0.10

6.32

0.16

8.2

0.12
0.18

3.12

0.32
0.21

5.5

4.73

FERROSCAN RESULTS

Imagescan and linescan results of beam, column and slab have been carried out for a beam, column
and slab of the buildings in the first floor. Figure 6 shows the observation by using Ferroscan. Figure
7 presents the findings of Ferroscan measurement for column C1 (marked at figure 1) and figure 8
represents the findings for beam B-1(marked at figure 1). Table 3 presents linescan analysis ofcolumn C1.

Figure 6 : Ferroscan observations of Column and beam

Column-C1 (Long side)

Column-C1 (Short side)

Figure 7: Cross section (in built) of column C1 (marked at figure 2)
55
54

May 2014

Image scan of long section beam at B- Image scan of long section beam at
1 position (side face)B-1 position (bottom face)

Figure 8: Cross section (in built) of beam at B-1 position (marked in figure 1) at ground floor
Table 3: Line Scan, hoop position check (Ref: American Concrete Institute, 2002)
Transverse Reinforcement Requirements - Rectangular hoop reinforcement for Column (C1-1F)xy
L0 ≥Column Dimension
12
12
12in
Larger of C1 or C2
9.75
ft
Clear Span/6
19in
Column Height (Clear Span)117
in18" 18inLongitudinal Bar Used
Diameter , D
Max. Value between tie (in aplane), hx
End Strip Length
Middle Strip length

16
0.62

mm

7
19
76

in
in
in

in

Spacing Recommended for End Strip :S
Existing Spacing
Remark3

in

5
in
Not Satisfied

S≤
0.25 X Smaller of C1 orC2 3in
6 X Longitudinal Bar
Diameter, D 3 in
Sx = 4+[(14 hx|)/3]
6in

Spacing Recommended for Middle Strip
S
3.75
in
Existing Spacing
8
in
56

S≤
6" 6in
BNUS Annual Report-2013
55

ICUS Report 74

RemarkNot Satisfied

Clear Cover
Cover depth ≥Existing min Depth

38.1 mm
44 mm

Remark6.

6 X Longitudinal Bar
Diameter, D 3.75in

Satisfied

CONCLUSION

This paper presents the findings of seismic vulnerability assessment of five mosques, four
educational institutes and one community centre of ward number-65 of Dhaka city. Initially Rapid
Visual Screening (RVS) survey and Modified Turkish Method have been used to evaluate thevulnerability of these critical structures; later Ferroscan and Microtremor have been used to assess
their existing condition. According to the Turkish Tier-1 survey, none of the buildings areseismically vulnerable. The building heights vary from 1 to 5 stories and their periods vary from 0.1
to 0.5 seconds. None of the critical facilities in this ward have any as-built drawings. Using
Ferroscan and other NDTs, BNUS have helped the local community people to develop the as-built
drawings of those structures.
REFERENCES
Aki, K. (1957). Space and time spectra of stationary stochastic waves, with special reference tomicrotremors, Bull. Of earthquake research institute, 35, 415-456
Ansary, M.A., Yamazaki, F. and Katayama, T. (1996). Application of Microtremor Measurements tothe estimation of site amplification characteristics, Bulletin of ERS, Vol 29, PP: 96-113.
Kanai, K. and Tanaka T. (1961).On Microtremor VIII, Bull.Earthq.Res.Inst. Tokyo University,
Vol.39, pp.97-114.
Nakamura, Y. (1989). A method for dynamic characteristics estimation of subsurface using
microtremor on the ground surface, QR of RTRI, 30, 25-33
Sato, T. H. Kawase, M. Matsui, and S. Kataoka (1991). Array measurement of high frequency
microtremors for underground structure estimation, proc. 4th int. conf. on seismic zonation,
11,409-416
Tamura, T., O. Nagai, H. Kikubo, and H. Sumita (1993).Charactesistics of wave group microtremors
obtained by array measurement, J. Struct. Consr. Eng. AIJ 449, 83-91 (in Japanese).
Toshinawa, T., Inoue M., Yoneyama N., Hoshino Y., Mimura K., and Yokoi Y. (2003),Geologicprofile estimates of Kofu Basin, Japan, by making use of microtremorobservations,GeophysicalResearch Abstracts, Vol. 5, 02079.
Tokimatsu, K. and Y. Miyadera (1992), “Characteristics of Rayleigh waves in microtremors andtheir relation to underground structures, J.stucture. consr. Eng. AIJ 439, 81-87

57
56

PART-VI
APPLICABILITY OF PS SUSPENSION LOGGINGDOWNHOLE SEISMIC METHODFOR INVESTIGATION OF DYNAMIC SOIL
PROPERTIES OF BANGLADESHBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Fahad Hossain
Mehedi Ahmed Ansary

57

May 2014

Abstract:
With the increased use of machines on super structures along with frequently occurring
natural hazards like earthquakes, liquefactions, slope failures; requires analysis forfoundation vibrations which subsequently leads us to characterize and investigate soils for
its dynamic properties. The paper deals with the methodology and the use of PS
suspension logging down-hole seismic testing system for measurement of shear wave
velocities. It also covers the relationships of wave velocities with the dynamic parameters.
It’s basically a review paper which will provide detailed application process and analysis
method to the researchers requiring the use of PS Suspension Logging down-hole seismic
testing method to determine earthquake waves and dynamic properties.
Introduction:
Few of the major earthquakes over the years, alike the Sumatran Earthquake [1] or the Great Indian
Earthquake [2] along the coast of bordering countries of Bangladesh has augmented the demand forearthquake resistant designs for the vibration induced parameters of soil. For this reason accurate andproper soil investigation has become an essential concern to grasp precise knowledge about theunderground soil condition.
The PS suspension logging method (Kitsune zaki, 1980) directly measures and provides accurate andhigh-resolution Shear (S) wave velocity profiles. The primary (P) or the compression wave velocity
profiles can also be created accurately by using PS Suspension Logging.
During an earthquake, the subsurface soil column acts like a filter with strain-dependent properties
that can increase the duration and amplitude of shaking in a narrow frequency band related to the soil
thickness, physical properties (P and S-wave velocities, densities), shape of the surface andsubsurface boundaries [3] .The spectral content (amplitude, period, and phase) and duration ofearthquake recordings can therefore be significantly affected by local site conditions, especially at
unconsolidated soil and sediment sites with a near-surface impedance contrast with underlying
bedrock. The resonant period of the ground is therefore of great importance for earthquake
engineering. Also the response of soils to cyclic loading is controlled mostly by the mechanicalproperties of the soil [4].
The most common types of dynamic loadings are, machine vibrations, seismic loading, liquefactions
and cyclic transient loading, etc. The dynamic properties associated with these dynamic loadings are
shear wave velocity (Vs), shear modulus (G), damping ratio (D), and Poisson’s ratio (n), Young’s
Modulus (E) of soil. [5]6058BNUS Annual Report-2013

ICUS Report 74

History of PS SuspensionLogging:
P-S suspension velocity logging was first developed in the mid-1970s to measure seismic shear-wave
velocities in deep, uncased boreholes; it was originally used by researchers at the OYO Corporationof Japan (Kaneko et al, 1990). It gained acceptance in Japan in the mid-1980s and was used for othervelocity measurement methods to characterize earthquake site response. Public Works ResearchInstitute (PWRI) has measured S-wave velocities in boreholes using the PS suspension logging tool
since 1980. Since the early 1990s it has gained acceptance in the U.S., especially among earthquake
engineering researchers. [6]Worldwide Use of PS Suspension logging:
PS Logging techniques are using worldwide and some example of some research works includes,
Tomio Inazaki [7] investigations; where shear wave velocities of surficial unconsolidated sediments
was used to correlate with geotechnical properties determined by laboratory testing. The S-wave
velocity data, all of them were accurately measured in boreholes using the PS suspension logging
tool. N-values obtained by in situ Standard Penetration Test (SPT), bulk densities, solidities, andmean grain sizes measured by the standard soil test, and elastic constants determined by tri-axial
dynamic loading tests were correlated with the S-wave velocities at the same horizons in the same
boreholes. However the dynamic range and measurement accuracy of SPT was too low to comparewith S-wave velocity data obtained using the suspension logging tool. So it was possible to estimate
N-values from S-wave velocity data using his empirically synthesized equation.
Ming-Hung Chen et al. [8] showed that 175 strong-motion station sites were investigated by National
Center for Research on Earthquake Engineering (NCREE) and Central Weather Bureau (CWB) to
characterize the subsurface conditions that affect measured ground motions measuring in soil, gravel
and rock layers throughout Taiwan. The suspension P-S Logging method was applied at most sites
because of its high accuracy and resolution. He showed that that the frequencies and wave lengths ofreceiving signals varied with different subsoil materials. The investigated shear wave velocity
profiles of an alluvial deposit in southwestern Taiwan were introduced. Based on the abundant andreliable shear wave velocities, an empirical formula for alluvial deposits was developed. Depth andcorrected SPT-N value were chosen to be two major parameters of the empirical formula. For somespecific sites, surface wave, seismic refraction, or down-hole velocity measurements were also
executed. The results of various tests are generally very close and increase the reliability of themeasurements.
Emre Biringen and John Davie [9] made correlations between the values of P-wave velocity anddynamic elastic modulus through in-situ dynamic testing (suspension P-S logging) and the values ofuniaxial compressive strength (UCS) and static elastic modulus through laboratory static testing
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May 2014(uniaxial compressive) of sound rock from two sites located in South Carolina and Virginia. For bothsites, the bedrock, which classified as good to excellent, is hard fresh to slightly discoloredmetamorphic rock, or igneous rock with numerous metamorphic inclusions. Suspension P-S logging
tests were performed in 12 uncased fluid-filled boreholes, to rock depths of over 120 m.
Ming-Hung Chen and Bing-Ru Wu [10] showed in another paper, the site investigation at 175
TSMIP stations was completed by National Center for Research on Earthquake Engineering(NCREE) cooperating with Central Weather Bureau (CWB) in Taiwan. By sampling soils in theborehole and using the Suspension P-S Logger Technique, specific geological and geotechnical data
are obtained including the soil profile, the physical properties of soils, and the wave velocities of thestratum. This database is helpful to the site effect analysis and the earthquake-resistant design.
Michael W. Asten and David M. Boore [11] showed that measurement or estimation of the shearvelocity (Vs) profile of sediments overlying geological basement is a vital part of site zonation
studies for earthquake hazard prediction, and more generally for geotechnical studies. A series ofboreholes drilled in the Santa Clara Valley Water District provide opportunity for the comparison ofgeophysical methods (Ps Logging, SASW, MASW) with known geological data.

The author

compared the shear-wave velocity profiles obtain from fourteen invasive and non-invasive
methodologies obtained in and near a single 300 m borehole.
Itzair Perez et al. [12] compared SASW and PS-logging (in-hole) seismic techniques with therelatively new ReMi (Refraction Micro tremor) method at a common site with a well-known
soil profile: a recently constructed high-speed railway embankment. The author showed that the
PS-logging is the most accurate technique in identifying the soil profile of the embankment followed
by Re-Mi and SASW. Mean shear wave velocity estimations are also higher for PS-logging,followed by SASW and ReMi, while mean deviation is similar in each technique.
Methodology for Downhole Seismic Test:
The down hole seismic test requires only 1 borehole (preferably a 3 inch diameter hole with PVC
pipe installed upto the depth in which competent soil or rock is reached) to be used for the geophonereceiver. Usually PVC pipes are used to permanently stabilize the hole. The standard for the test
technique is set forth in the ASTM D4428/D4428M. A installed cased borehole is shown in figure 1.
For the test, a wooden plank source shown in is used. A 6 in x 30 in area approximately 3 m (10 ft)
from the borehole is cleared off. 6 in x 6 in x 30 in (or similar) wooden plank in the cleared off area
is positioned and pinned down by driving a vehicle onto the plank (as shown in Figure 2) so that oneof the drive wheels is centered on the plank as shown below. The plank should extend farther beyond
the outside diameter of the tire. Then the accelerometer should be mounted on to the wooden plankusing grease/ epoxy glue.
The plank is hit separately on both ends to generate shear wave energy in two different directions.
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The plank is also hit vertically in the downward vertical direction to generate vertically polarizedcompresional wave energy. The shear wave energy is polarized in the direction parallel to the plank
as is the transverse component (marked T on the geophone shell). The transverse component is used
to measure the shear wave energy. The vertical component marked V on the geophone shell is used
to measure the vertically polarized compressional wave energy. Typically 3-5 records are taken foreach type of wave – shear east going, shear west going and compressional vertical. Using the testplans that come with the Freedom Data PC Downhole Seismic / Cross Hole Seismic – 2 system, 8records are taken for each wave type. In all, 3 different tests are performed at each depth for the 3
different wave polarizations collected; all depths are recorded together in one file. [13]Figure 1: PVC pipe cased borehole.
Figure 2: Wooden Plank Source Used In
Downhole Seismic Test
The set up of the equipment may be shown below as flow chart:
Some data found from a PS Logging test in Down-hole Seismic method are shown in Figure 4 forcalculating compression wave and shear wave. In figure we can see the data of compression wave.
For computing the arrival time of the compression wave, take the first point of the time domain dataof the vertical component when the response starts for both geophones.

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Figure 3: Installation of PS Logging test (Downhole seismic method)

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Figure 4: Time Domain data for compression wave.
In figure 5 we can see the data of shear wave generated by giving blow with hammer in bothhorizontal directions. For computing the arrival time of the shear wave, take the first point of thetime domain data of the radial and transverse component when both wave generated from bothhorizontal direction just overlap each other.

Figure 5: Time Domain data for shear wave.
From the calculated travel time of the compression and shear wave, the velocity can be determinedby dividing the distance of the source to receiver by the travel time. Both compression wave andshear wave velocity are determined in this method. The calculation is shown below with figure 6 andequations.
Dt  ( z 2  x 2 )Db  ( y 2  x 2 )Vp 

Db  Dttb  ttHere,
Dt = Distance between top receiver to source
Db = Distance between bottom receiver to source
Tt = Travel time of wave to top geophone
Tb = Travel time of wave to bottom geophone

Figure 6: PS Loging test in Seismic Downhole method.
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The data sheet for the calculation of compression and shear wave is shown in Appendix-1, Table 1
and Table 2.
Determination of Different Dynamic Soil Properties of Soil:
As stated above, some dynamic properties of soil such Shear Modulus, Constrain Modulus, Poisson’s
Ratio and Young Modulus can be determined from the shear wave velocity. The equations fordetermining the dynamic properties are given below. The data sheet for computing the dynamic
properties is given in Appendix 1, Table 3.
G  VS2M  V

2
P

V
VS

V
VS

  [0.5( P ) 2  1] /[( P )2  1]
E  2G (1   )G = Shear Modulus
M = Constrained Modulus
 = Density
Vs = Shear Wave Velocity
Vp = Compressional Wave Velocity
 = Poisson’s Ratio
E = Young’s Modulus

Conclusion:
PS Logging test is a precise and accurate testing method among the available geophysical methods
for seismic wave velocity determination. Using this test compression and shear wave velocity can bemeasured quite easily rather than the other methods. For this reason, it is getting its importance day
by day among the researchers. But its demerits are, it is costly, its installations and set-ups requires
expertise and skilled manpower, it also takes much time, data acquisition should be done very
carefully. That may be the cause that it is not widely used in Bangladesh for research work. But
considering its accuracy its use should be increased in Bangladesh.
References:[1] Ali, M.H and Choudhury, J.R (1992) “Tectonics and Earthquake Occurrence in Bangladesh”, 36th
Annual Convention, IEB, Dhaka.
[2] U.S Geological Survey, National Seismic Hazard Maps (2012).
[3] Molnar, S., Cassidy, J.F., Monahan, P. A. and Dosso1, S. E., “Comparison Of Geophysical
Shear-Wave Velocity Methods” in Ninth Canadian Conference on Earthquake Engineering Ottawa,
Ontario, Canada, 26-29 June, 2007, pp. 390-391.
[4,5] Luna, R. and H. Jadi, "Determination of Dynamic Soil Properties Using Geophysical Methods,"
Proceedings of the First International Conference on the Application of Geophysical and NDTMethodologies to Transportation Facilities and Infrastructure, St. Louis, MO, December 2000.
[6] “SUSPENSION P-S VELOCITY LOGGING METHOD”-GEO Vision.
[7] Inazaki, T., “Relationship between S-Wave Velocities And Geotechnical Properties Of Alluvial
Sediments” in 19th EEGS Symposium on the Application of Geophysics to Engineering and
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Environmental Problems, Apr. 2006.
[8] Chen, M.H., Wen, K. L., Loh, C. H. and Nigbor, R. L., “Experience of Suspension P-S Logging
Method and Empirical Formula of Shear Wave Velocities in Taiwan” presented at - U.S.-Taiwan
Workshop on Soil Liquefaction, Mar 2, 2012.
[9] Biringen, E. and Davie, J., “Assessment of dynamic and static characteristics of igneous bedrockby means of suspension P-S logging and uniaxial compressive strength tests” in “2011 Pan-Am
CGS Geotechnical Conference” October 2-6, 2011.
[10] Chen, M.H., Wu, B. R., “The Engineering Geological Database for Strong Motion Stations In
Taiwan”[11] Asten, M. W. an Boore, D. M., “Comparison of Shear-Velocity Profiles of Unconsolidated
Sediments near the Coyote Borehole (CCOC) Measured With Fourteen Invasive and Non-Invasive
Methods”, U.S. Geological Survey Open-File Report 2005-1169.
[12] Perez-Santisteban, I., Garcia-Mayordomo, J., Martin, A. M., Carbo, A., “Comparison among
SASW, ReMi and PS-Loggong techniques: Application to a railway embankment” in journal of
applied geophysics, Vol 1; pp. 59-64, 2011.
[13] System Reference Manual 2007 Crosshole and Downhole Seismic Test by Olson Instruments,
Inc. Revised (May 2007).
Appendix 1
Table 1: Determination of P wave Velocity:

Table 2: Determination of S wave Velocity:

Table 3: Determination of Dynamic Properties:

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PART-VII
ENGINEERING CHARACTERISTICS OF GROUNDMOTIONS RECORDED BY NORTHEAST INDIAN
STRONG MOTION INSTRUMENTATION NETWORKFROM 2005 TO 2013

BANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Mehedi Ahmed Ansary66May 2014

ABSTRACT
Indian Institute of Technology, Roorkee (IITR) is operating a nationwide network of
instruments for recording strong ground motion. Total 298 instruments are installed in seismiczone III, IV and V along Himalayan belt. Primary goal of this project is to acquire strong groundmotion (SGM) data for various studies in the field of earthquake engineering and seismology in
general and in particular to understand propagation and site response characteristics of thesediments that underlie and are thought to produce large site amplification and seismic hazard.
This network has so far recorded around 150 earthquake events having magnitude from 3 to 7
starting from 2005 to 2013. Ground-motion prediction equations (GMPEs) based on PeakGround Motions and Spectral Values are presented for the first time using local SGM data. This
paper also presents an engineering analysis of 13 ground motion records of 2011 Sikkim
Earthquake. H/V ratio is estimated for 9 soil and 4 rock sites. H/V ratios indicate that soil sites
show predominant site frequencies of about 0.6 to 2.5 Hz and Rock sites show predominant site
frequencies between 3 to 5 Hz.
IntroductionMore than half of the area of India is susceptible to strong ground motions from earthquakes;
therefore it is essential to know about the probable characteristics of strong ground motion of futureearthquakes in this region. For earthquake engineering purposes, a number of different parameters
are typically used to characterize strong motion records. These parameters include peak acceleration,
peak velocity, peak displacement, duration of strong shaking, and response spectra. A rational
assessment of the expected seismic hazard in different regions of the country will lead to substantial
monetary savings in the design of structures and reduce potential losses from earthquakes. Indian
Institute of Technology, Roorkee (IITR) is operating a nationwide network of instruments forrecording strong ground motion. Total 298 instruments are installed in seismic zone III, IV and V
along Himalayan belt [1-2]. Primary goal of this project is to acquire strong ground-motion (SGM)
data for various studies in the field of earthquake engineering and seismology in general and inparticular to understand propagation and site response characteristics of the sediments that underlie
and are thought to produce large site amplification and seismic hazard.
Ground-motion prediction equations (GMPEs) describe the scaling of ground-motion amplitudes
with magnitude, style-of-faulting and site class, and the decay (attenuation) of the amplitudes atincreasing distances from the source. GMPEs based on Peak Ground Motions and Spectral Values
are presented for the first time using local SGM data recorded from 2005 to 2013. For this purpose
two attenuation models proposed by Joyner and Boore [3] and Bommer and Akkar [4] are used inthis study to fit the SGM data.
The amplification of ground motions due to the local site condition plays an important role in seismic
damage [5-7]. Idriss [5] found that the PGA values recorded at soft-soil sites during the 1989 Loma
Prieta earthquake were significantly greater than those recorded at other sites at distances of about 45
to 100 km. The use of the site soil stiffness represented by the shear wave velocity in the upper 30 mof soil deposits was then initiated in the early 1990s [8] by assigning a range of VS30 to different site
categories (e.g., NEHRP categories). However, prior to Sikkim earthquake, there has not been one
single large earthquake that recorded 9 strong ground motions at soft-soil sites in Indian subcontinent. Such a limitation makes the strong motion records at soft-soil sites from this earthquake
very valuable for studying the effect of soft soil on site responses.
In addition, the horizontal-to-vertical (H/V) ratio technique proposed by Nakamura [9] was used toestimate predominant site periods of soft-soil sites with VS30 between 200 and 375 m/s and rock sites
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with VS30 between 700 and 1620 m/s, which is an important parameter for assessing building damage
and in evaluating local site amplification.
Strong Motion Network
The main objective of the seismic instrumentation is to record the ground motion arising due tonatural and manmade disturbances and, in particular, to monitor the seismicity of a given region.
This Strong Motion Network is also a first step toward developing a “Rapid Response and Damage
Prediction System” for India where near real-time strong ground-motion records can be used tocompute ground- shaking maps showing the area most strongly affected by earthquakes [2].
The Strong motion instrumentation network of IITR covers the Indian Himalayan range from Jammu
and Kashmir to Meghalaya. In total, 298 strong motion stations have been installed in the states ofHimachal Pradesh, Punjab, Haryana, Rajasthan, Uttarakhand, Uttar Pradesh, Bihar, Sikkim, West
Bengal, Andaman and Nicobar, Meghalaya, Arunachal Pradesh, Mizoram and Assam. 20
instruments out of 298 are installed in Delhi, the national capital of India. Figure 1 shows location of
stations of this network along the Himalayan belt while Figure 2 shows location of stations installedin Delhi.
Site Characterization
The local site conditions play an important role in the recorded time history of earthquake
ground motions. Different site conditions can induce amplifications of different period
ranges in the response spectra [10-11]. Therefore, the local site conditions become
important in ground motion analysis and in earthquake resistant designs. This network hasrecorded large numbers of ground motion histories. These data are invaluable for strongmotion studies and site effect analyses, as well as for the study of a practical siteclassification system. The objective of site classification is to classify a group of strong
motion station sites into several classes so that the conditions within the same site classare similar and design engineers may understand the general site condition by the classthat it belongs to.
Because quantitative subsurface soil properties are not commonly available for every site,
the use of surface geology becomes important in understanding the subsurface geologic
conditions. Most site effect studies of earthquake ground motion are based on the soil
properties in the upper 30 meters. Some researchers had combined the use of surface
geology and shear-wave velocity for site classification [8].
Site characterization is a must for strong ground motion studies. Ideally, detailed geotechnicalinvestigation using bore hole of 20 to 30 meter depth should be carried out at each site. Such database is available for large number of strong motion stations of Japan. However, such tests are costly
and therefore other simple approaches for site characterization are being employed at several places
[2].

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Figure 1. Map showing the location of Figure 2. Map showing
instruments along the Himalayan belt
instruments in Delhi

thelocationofRecorded Database

10

10

8

8

6

6

Magnitude

Magnitude

This state-of-the-art instrumentation has partially filled the long-felt need for monitoring groundmotion generated by earthquakes in the Himalayas using modern strong motion instruments. Since
its installation, the instrumentation has been working in a satisfactory manner and has captured about
300 strong ground motion records from 150 earthquakes between 2005 and 2013. This database
contains PGA values within 1000 km of the fault from earthquakes having magnitudes (M) in therange of 2.5 to 7.8. The distribution of PGA, PGV, PGD, ARS (Acceleration Response Spectrum)and VRS (Velocity Response Spectrum) for 0.3s, 1.0s and 2.0s values against M and hypocentral
distance (r) is shown in Figure 3.

4

4

2

2

Rock Sites
Soil Sites
0
1

10

100

Distance (km)

1000

3000

0
0.1

1

10

100

1000

2

PGA (cm/s )BNUS Annual Report-2013

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8

8

6

6

Magnitude

Magnitude

ICUS Report 74

4

2

4

2

0
0.01

0
0.1

1

10

20

0.1

1

PGV (cm/s)

1000

100

1000

100

0.3 s
1.0 s
2.0 s

100

0.3 s
1.0 s
2.0 s

10

VRS (cm/s)

2

ARS (cm/s )10

PGD (mm)

1

1

0.1

0.01
0

2

4

6

8

10

0.01

Magnitude

0

2

4

6

8

10

Magnitude

Figure 3. Distribution of different SGM parameters with respect to distance and magnitude

Ground Motion Prediction Equations
GMPEs based on Peak Ground Motions and Spectral Values are presented for the first time using
local SGM data recorded from 2005 to 2013. For this purpose two attenuation models proposed by
Joyner and Boore (Eq. 1) [3] and Bommer and Akkar (Eq. 2) [4] are used in this study to fit the SGM
data. These models predict PGA, PGV, PGD, ARS and VRS spectral ordinates at response periods of
up to 2 seconds as a function of magnitude (M), hypocentral distance (r) and site class.
 ܻ ൌ ܾଵ ൅ ܾଶ ‫ ݎ‬൅ ܾଷ ‫ ܯ‬൅ ܾସ ݈‫ݎ݃݋‬ ܻ ൌ  ܾଵ ൅  ܾଶ ‫ ܯ‬൅ ܾଷ ‫ܯ‬ଶ ൅ ሺܾସ ൅ ܾହ ‫ܯ‬ሻ݈‫ݎ݃݋‬

(1)
(2)

where bi are coefficients. Tables 1 and 2 show coefficients determined by multistage regression
analysis for rock and soil sites for Joyner and Boore GMPE. Tables 3 and 4 show coefficientsdetermined by multistage regression analysis for rock and soil sites for Bommer and Akkar GMPE.

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Table 1. Regression coefficients for Peak Ground Motions and Spectral Values using Joyner andBoore GMPE for rock sites
Y
Acceleration: All (n=229)
Acceleration: Depth < 70 km (n=201)
Acceleration: M > 4 and h < 70 km(n=160)Velocity
Displacement
ARS (0.3s)
ARS (1.0s)
ARS (2.0s)
VRS (0.3s)
VRS (1.0s)
VRS (2.0s)

b1
0.57259
0.58663
0.43375b2-5.77618E-4-4.85358E-4-5.97479E-4

b3
0.169540.17325
0.2742b4-0.20404-0.22588-0.406320.360130.36984
0.35759R2
0.17680.12567
0.21903-1.61154
0.0276-0.52966-2.13378-2.57562-1.53457-1.89432-1.87658-6.0865E-4-4.00625E-4-7.94703E-4-5.71718E-4-5.87236E-4-7.53946E-4-5.43274E-4-6.4472E-4

0.28710.162
0.33601
0.53349
0.509840.276020.362110.33797-0.11565
0.01906
0.02032-0.19762-0.21742
0.02851-0.12884-0.10632

0.36277
0.393690.43034
0.43887
0.38974
0.40357
0.399170.374250.240780.089310.257960.452590.478170.21130.301220.29547

Table 2. Regression coefficients for Peak Ground Motions and Spectral Values using Joyner andBoore GMPE for soil sites
Y
Acceleration: All (n=187)
Acceleration: Depth < 70 km (n=163)
Acceleration: M > 4 and h < 70 km(n=147)
Velocity
Displacement
ARS (0.3s)
ARS (1.0s)
ARS (2.0s)
VRS (0.3s)
VRS (1.0s)
VRS (2.0s)

b10.80932
1.112111.53895b2-5.09526E-4-2.89605E-4-1.19581E-4

b3
0.2297
0.27169
0.21482b4-0.46683-0.74158-0.80811


0.37550.38073
0.38551

R2
0.23661
0.29250.27896-1.57759
0.23063-0.93043-2.58486-2.87772-1.83674-2.08334-1.94739-6.49273E-4
4.12536E-5-0.00124-0.00105-7.2129E-4-0.00112-7.631E-4-5.44397E-4

0.35968
0.197170.3956
0.584220.64174
0.34558
0.451420.4944-0.27458-0.16678
0.11090.01915-0.28807
0.03888-0.194-0.42454

0.342270.44828
0.406390.385190.34534
0.39250.365640.33371

0.386190.124070.411020.630440.69558
0.35311
0.48627
0.55687

Table 3. Regression coefficients for Peak Ground Motions and Spectral Values using Bommer andAkkar GMPE for rock sites
Y
Acceleration: All(n=229)Acceleration: Depth <70 km (n=201)
Acceleration: M > 4
and h < 70 km(n=160)Velocity
Displacement
ARS (0.3s)
ARS (1.0s)
ARS (2.0s)
VRS (0.3s)
VRS (1.0s)
VRS (2.0s)

b1-1.29562

b2
0.33231b3
0.05844b4
1.38054b5-0.36172
0.34269R2
0.25789-1.32206

0.30076

0.069021.5027-0.39510.350740.21764-2.71702

1.14476-0.03585

0.52328-0.22012

0.3476

0.2668-3.05898
0.8236-3.33127-3.78211-3.48421-3.99831-3.39839-3.36514

0.20369-0.69163
1.055120.58329
0.09253
0.83772
0.356420.254310.092030.15131-0.01043
0.072220.137180.00662
0.07683
0.09473

1.64876
1.36491
1.26107
1.438
1.804111.30091.48971.70841-0.40306-0.31162-0.30505-0.37273-0.45637-0.30979-0.3676-0.41611

0.34590.37426
0.40898
0.42590.36826
0.38627
0.38551
0.357320.31280.18066
0.33278
0.48677
0.536170.28066
0.351110.36064

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Table 4. Regression coefficients for Peak Ground Motions and Spectral Values using Bommer andAkkar GMPE for soil sites
Y
Acceleration: All(n=187)
Velocity
Displacement
ARS (0.3s)
ARS (1.0s)
ARS (2.0s)
VRS (0.3s)
VRS (1.0s)
VRS (2.0s)

b10.53083b2
1.0689b3-0.13013

b4-2.0099b5
0.24215
0.35542R2
0.31984-2.37111
1.37341-3.48393-4.4399-3.53819-3.95773-3.18244-2.5624

1.01273-0.12068
1.93489
1.771840.96448
1.735991.44493
1.11056-0.07409
0.01496-0.15661-0.12272-0.01719-0.14831-0.12206-0.07643-0.84805-0.54034-0.66353-0.66217-0.20032-0.84031-1.23378-1.11373

0.04971
0.07860.02995
0.03155-0.0769
0.06138
0.124780.080310.339440.445540.368630.36735
0.35488
0.36153
0.34789
0.32884

0.39958
0.139480.51802
0.665730.680290.454150.53746
0.57205

Figure 4 shows comparison of predicted PGA values for magnitude 6 earthquake using Joyner andBoore and Bommer and Akkar GMPEs at various distances for rock as well as soil sites. The data ofthree earthquakes having magnitude 6 or a little more have been also plotted for comparison. From
the figures, it can be said that rock site data fits relatively well with Bommer and Akkar GMPE andon the other hand soil site data fits well with Joyner and Boore GMPE.
Figure 5 compares Bommer and Akkar GMPE for rock site data for different datasets. The threedatasets show almost similar prediction values. Since the dataset where M > 4 and h < 70 km has aslightly higher correlation coefficient, this prediction values are plotted with ±. Figure 5 also
compares Joyner and Boore GMPE for soil site data for different datasets. The three datasets also
show almost similar prediction values. Since the dataset where h < 70 km has a slightly higher
correlation coefficient, this prediction values are also plotted with ±.
1000

1000
Soil Sites:
Joyner-Boore Model (1981)
Bommer-Akkar Model (2012)

Rock Sites:
Joyner-Boore Model (1981)
Bommer-Akkar Model (2012)

2

2

PGA (cm/s )100

PGA (cm/s )

100

10

10

1

1
10

100

Distance (km)

1000

3000

0.1

1

10

100

1000

3000

Distance (km)Figure 4. Predicted PGA values for a M = 6.0 earthquake at various distances, using two
GMPEs

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1000

1000

Rock Sites: Bommer-Akkar Model (2012)
All Data
Data (depth < 70 km)
Data (Depth < 70 km & M >4)
Data (Depth < 70 km & M >4)+/-

100

2

2

PGA (cm/s )PGA (cm/s )

100

10

10

Soil Sites: Joyner-Boore Model (1981)
All Data
Data (Depth < 70 km)
Data (Depth < 70 km & M> 4)
Data (Depth < 70 km)+/-
1

1
10

100

1000

3000

1

10

100

1000

3000

Distance (km)Distance (km)Figure 5. Predicted PGA values for a M = 6.0 earthquake at various distances, for different
datasets for a fixed GMPE

Site Response Characteristics
Nakamura (1989) proposed a methodology of using the H/V ratio of Fourier amplitude spectra toestimate local site response characteristics. Although the absolute level of the H/V ratio depends on
the wave field and source mechanism, extensive studies [12-15] have demonstrated that the H/Vratio shape shows good stability and is insensitive to source location and mechanism. If a clear
impedance contrast exists at the site, the H/V ratio has been shown to provide an adequate estimateof the predominant period of a site, which is an important parameter for assessing building damage[16-17] and in evaluating local site amplification. In this study, the H/V ratio technique was used toinvestigate the site response characteristics.
The main shock of the 18 September 2011 Sikkim Earthquake generated a total of 9 ground motion
records from stations located on soft-soil sites (VS30 ranging from about 200 to 375 m/s) with r
ranging from about 100 to 900 km. On the other hand, a total of 4 ground motions were recorded onrock sites (VS30 ranging from about 700 to 1620 m/s) with r ranging from about 50 to 800 km. The
H/V ratio is calculated as the Fourier amplitude spectral ratio between the geometric mean of the twohorizontal components and the vertical component. These Fourier amplitude spectra were smoothedby a Parzen window of 0.4 Hz bandwidth.
Figure 6b shows plots of H/V ratios of Fourier amplitude spectra of 9 ground motions on the soft-soilsites along with the geometric mean. Overall, these soft-soil sites appear to show broadband
predominant site frequncies ranging from around 0.6 to 2.5 Hz corresponding to the peak of thegeometric mean H/V ratio curve. In general, a typical predominant site frequency of about 1.6 to 3
Hz should be anticipated for a similar soft-soil site with VS30 of between 200 and 375 m/s. The
observed lengthening in the predominant site period for some of the soft-soil sites is likely caused by
the nonlinear behavior of soil deposits under a relatively high level of excitation. The predominantsite period has been observed to be lengthened when the soil deposit behaves more nonlinearly
during a strong shaking. Figure 6a plots H/V ratios of Fourier amplitude spectra of 4 ground motions
on rock sites along with the geometric mean. In general, these rock sites showed a predominant site
frequency between 3 to 5 Hz, which is typical for a rock site. For ease of comparison, the geometricmean H/V ratios for soft-soil sites and for rock sites are plotted in Figure 6c.

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50

50

20

20

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5

2

2
1

H/V Ratio

H/V Ratio

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0.5
0.2
0.1

0.5
0.2
0.1
0.05

0.05
0.02

0.02

Average of all Rock Curves

0.01

0.01

Average of all Soil Curves

0.005

0.005

0.002

0.002
0.001
0.1

0.2

0.3 0.4 0.5 0.7

1

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3

Frequency (Hz)(a)

4 5 6 7 8 10

0.001
0.1

20

0.2

0.3 0.4 0.5 0.7

1

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Fequency (Hz)4 5 6 7 8 10

20

(b)

10
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5
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H/V Ratio

2
1
0.7
0.5
0.4
0.3

Rock Sites (Average of 4 sites)
Soil Sites with Vs30 = 200 to 375 m/s (Average of 9 sites)

0.2
0.1
0.1

0.2

0.3 0.4 0.5 0.7

1

2

3

Frequency (Hz)4

5 6 7 8 1020(c)Figure 7. H/V ratios of Fourier amplitude spectra of the 2011 Sikkim earthquake: (a) all
rock sites; (b) all soil sites; thick lines represent the geometric mean H/V ratios and, (c)geometric mean H/V ratios for the soft-soil sites and for the rock sites.
It is noted that the predominant site frequencies, amplitudes, and shapes of the H/V ratios are
remarkably different between the two site classes, which revalidates the capability of the H/V ratio toestimate the predominant frequency of soil deposits. To clarify the issue further, H/V ratios ofFourier amplitude spectra of Gangtok (rock) [around 50 km from the epicentre] and Siliguri (soil)[around 100 km from the epicentre] site during the 2011 Sikkim earthquake has been compared andshowed in Fig 7. The Siliguri site shows a predominant peak at 2 Hz and the Gangtok site shows apredominant peak at 9 Hz.
10
7
5
4
3

H/V Ratio

2
1
0.7
0.5
0.4
0.3

Gangtok with Vs30 = 700 - 1400 m/s
Siliguri with Vs30 = 200 - 375 m/s

0.2
0.1
0.1

0.2

0.3 0.4 0.5 0.7

1

2

3

Frequency (Hz)4

5 6 7 8 10

20

Figure 7. H/V ratios of Fourier amplitude spectra of Gangtok (rock)and Siliguri (soil) site during the 2011 Sikkim earthquake

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Conclusions
In this study, two GMPE proposed by Joyner and Boore and Bommer and Akkar were used to fit the
SGM data. The recorded peak ground accelerations from three earthquakes having magnitude greaterthan six were also compared with those GMPEs for soil and rock sites. The study found that for soil
sites, Joyner and Boore GMPE may be used to predict peak ground acceleration values and on theother hand for the rock sites Bommer and Akkar proposed GMPE may be used.
Results of H/V ratios reveal that some soft-soil sites with VS30 between 200 and 375 m/s show a
predominant site frequency around 0.6 to 2.5 Hz. The lengthened predominant site periods are likely
results from the nonlinear behavior of soil deposits under a high level of excitation. The rock sites
show a predominant site frequency around 3 to 5 Hz. The remarkably different predominant site
frequencies, amplitudes, and shapes of the H/V spectral ratios between the two sites revalidate thecapability of the H/V spectral ratio method for estimating predominant site periods, which is an
important parameter for assessing building damage.
Acknowledgments
The author would like to acknowledge the support provided by PESMOS, India regarding
strong motion data usage.
References
1. Kumar A, Mittal H, Sachdeva R, Kumar A. Indian Strong Motion Instrumentation Network,
Seismological Research Letters 2012; 83 (1): 59-66.
2. Mittal H., Kumar A, Ramhmachhuani, R. Indian National Strong Motion Instrumentation
Network and Site Characterization of Its Stations, International Journal of Geosciences 2012; 3:1151-1167.
3. Joyner WB, Boore DM. Peak Horizontal Acceleration and Velocity from Strong Motion Records
Including Records from the 1979 Imperial Valley, California, Earthquake, Bull. Seism. Soc. Am.
1981; 71 (6): 2011-2038.
4. Bommer JJ, Akkar S. Consistent Source-to-Site Distance Metrics in Ground-Motion Prediction
Equations and Seismic Source Models for PSHA, Earthquake Spectra 2012; 28 (1): 1-15.
5. Idriss IM. Earthquake ground motions at soft soil sites, Proceedings of the 2nd International
Conference on Recent Advances in Geotechnical Earthquake engineering and Soil Dynamics, St.
Louis, MO, 1991; 2265–2272.
6. Singh JP. Site specific ground motions for high-tech seismic design, ATC/JSCA 8th U.S.-Japan
Workshop on the Improvement of Structural Design and Construction Practices, Honolulu, HI,
1998.
7. Liao Y, Meneses J. Engineering Characteristics of Ground Motion Records from the 2010 Mw
7.2 El Mayor–Cucapah Earthquake in Mexico, Earthquake Spectra 2013; 29 (1): 177-205.
8. Borcherdt RD. Estimates of site-dependent response spectra for design (methodology andjustification), Earthquake Spectra 1994; 10: 617–653.
9. Nakamura T. A method for dynamic characteristics estimation of subsurface using microtremor
on the ground surface, Quarterly Report of Railway Technical Research Institute 1989; 30: 25–
33.
10. Seed HB, Ugas C, Lysmer J. Site-Dependent Spectra for Earthquake-Resistant Design, Bulletinof the Seismological Society of America 1976; 66 (1): 221-243.
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11. Mohraz B. A Study of Earthquake Response Spectra for Different Geological Conditions,
Bulletin of the Seis-mological Society of America 1976; 66 (3): 915-935.
12. Field EH. Spectral amplification in a sediment-filled valley exhibiting clear basin-edge induced
waves, Bulletin of Seismological Society of America 1996; 86: 991–1005.
13. Yamazaki F, Ansary MA. Stability of H/V spectrum ratio of earthquake ground motion,
Transactions of the 14th International Conference on Structural Mechanics in Reactor
Technology (SMiRT 14); Lyon, France, August 17–22, 1997.
14. Rodríguez VHS, Midorikawa S. Comparison of spectra ratio techniques for estimation of site
effects using microtremor data and earthquake motions recorded at the surface and in boreholes,
Earthquake Engineering and Structural Dynamics 2003; 32: 1691–1714.
15. Ansary MA, Rahman MS. Site amplification investigation in Dhaka, Bangladesh, using H/V ratioof microtremor, Environ. Earth Science 2013; 70: 559-574.
16. Fellahi A, Alaghebandian R, Miyajima M. Microtremor measurements and building damage
during the Changureh-Avaj, Iran, earthquake of June 2002, Journal of Natural Disaster Science
2003; 25: 37–46.
17. Gosar A. Microtremor HVSR study for assessing site effects in the Bovec Basin (NW Slovenia)
related to 1998 Mw 5.6 Earthquakes, Engineering Geology 2007; 91: 178–193.

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PART-VIII
STRUCTURAL QUALITY ASSESSMENT OF PADMAPICTURE LTD. MALIBAG, DHAKABANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA
Prepared By: Pushpendu Biswas
Mehedi Ahmed Ansary77

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Image Scan of Column’s:-

Figure 2 and Figure 3 are showing the Image scan result of column S-1(long side and short side
respectively) at a height of 2’-8’’ from the ground. And figure 4 is the cross section of that column.

Figure 2 : Image scan result of column S-1(one side)

Figure 3: Image scan result of column S-1(other side)ͳͶ‫ݎܾܽ ݈ܽܿ݅ݐݎ݁ݒ ݉݉Ͳʹ׎‬
Figure 4: Cross section of Column S -1
Figure5 and Figure6 are showing the Image scan result of column S-1(long side and short side
respectively) at a height of 2’-8’’ from the ground. And figure 7 is the cross section of that column.

Figure 5 : Image scan result of column S-2(Long side)

Figure6 : Image scan result of column S-2(shortside)ʹͲ‫ݎܾܽ ݈ܽܿ݅ݐݎ݁ݒ ݉݉Ͳʹ׎‬

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Figure 7:- Cross section of Column S -2
Figure 8 and Figure 9 are showing the Image scan result of column S-3(long side and short side
respectively) at a height of 2’-8’’ from the ground. And figure 10 is the cross section of that column.

Figure 8: Image scan result of column S-3(Long side)

Figure 9: Image scan result of column S-3(otherside)ͳͶ‫ݎܾܽ ݈ܽܿ݅ݐݎ݁ݒ ݉݉Ͳʹ׎‬
Figure 10 : Cross section of Column S -3

Figure 11 and Figure 12 are showing the Image scan result of column S-4(long side and short side
respectively) at a height of 2’-8’’ from the ground. And figure 13 is the cross section of that column.

Figure 11 : Image scan result of column S-1(Longside)

Figure 12: Image scan result of column S-1(shortside)ͳͶ‫ݎܾܽ ݈ܽܿ݅ݐݎ݁ݒ ݉݉Ͳʹ׎‬
Figure 13 : Cross section of Column S -4

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Figure 14 and Figure 15 are showing the Image scan result of column S-5(long side and short side
respectively) at a height of 2’-8’’ from the ground. And figure-16 is the cross section of that column.

Figure 14 : Image scan result of column S-5(Long side)

Figure 15: Image scan result of column S-1(short side)ͳͶ‫ݎܾܽ ݈ܽܿ݅ݐݎ݁ݒ ݉݉Ͳʹ׎‬
Figure 16 : Cross section of Column S -5

Figure 17 and Figure 18 are showing the Image scan result of column S-8(long side and short side
respectively) at a height of 2’-8’’ from the ground. And figure 19 is the cross section of that column.

Figure 17: Image scan result of column S-1(oneside)

Figure 18: Image scan result of column S-1(other side)ͺ‫ݎܾܽ ݈ܽܿ݅ݐݎ݁ݒ ݉݉Ͳʹ׎‬

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Figure 19 : Cross section of Column S -8

The Image scan result of column S-9(both side respectively) at a height of 2’-8’’ from the ground.

Figure 20 : Image scan result of column S-1(oneside)

Figure21: Image scan result of column S-1(other side)ͺ‫ݎܾܽ ݈ܽܿ݅ݐݎ݁ݒ ݉݉Ͳʹ׎‬
Figure 22 : Cross section of Column S -9
The Image scan result of column S-10(both side respectively) at a height of 2’-8’’ from the ground.

Figure 23 : Image scan result of column S-1(one side)

Figure24: Image scan result of column S-1(other side)ͺ‫ݎܾܽ ݈ܽܿ݅ݐݎ݁ݒ ݉݉Ͳʹ׎‬
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Scan of Beams:-

Figure 25 : Cross section of Column S -10

Figure 26, Figure 27 and Figure 28 are showing the Image scan result of Beam B-1(depth, Bottom
and top respectively) at . And figure 29 is the cross section of that beam.

Figure 26 : Image scan result of beamB-1(Side)

Figure 27: Image scan result of beam B-1(Bottom)

Figure 28:-Image scan result of beamB-1(Top slab)

Figure 29:- Cross Section of Beam B-1

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Figure 30 and Figure 31 are showing the Image scan result of Beam B-2(depth and Bottom
respectively) at . And figure 32 is the cross section of that column.

Figure 30 : Image scan result of beamB-2(Side)

Figure 31: Image scan result of beam B-2(Bottom)

ʹ‫݉݋ݐݐ݋ܾ ݐܽ ݎܾܽ݉݉Ͳʹ׎‬

Figure 32:- Cross Section of Beam B-2
Figure 33 and Figure 34 are showing the Image scan result of BeamB-4(depth and top respectively)
at . And figure 35 is the cross section of that Beam.

Figure 33 : Image scan result of beamB-4(Side)

Figure 34: Image scan result of beamB-4(top)ʹ‫݉݋ݐݐ݋ܾ ݐܽ ݎܾܽ ݉݉Ͳʹ׎‬Ƭ ‫݌݋ݐ‬

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Figure 35:- Cross Section of Beam B-4

Image Scan of Slab:-

Figure:- Image Scan of Slab at slab -1 position

Figure:- Section of slab position -1

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2. Image Scan of Slab Position -:-Figure:-image of slab at Slab-2 position (Top)

3.Image Scan of Slab-3:-

Figure:-image of slab at Slab-3 position

Figure:- Section of Slab-3 position

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4. Image of Top Slab position -4:

image of slab at Slab-4 position

Figure 9: Block image of slab at Slab-5
position

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PART-IX.

APPLICABILITY OF EXISTING CPT, SPT AND SOIL
PARAMETER CORRELATIONS FORBANGLADESHBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Mominul Haque
Mehedi Ahmed Ansary87

May 2014

ABSTRACT: Many correlations have been established between CPT, SPT and other soil parametersthat relate to direct applications in engineering practice. In this research, four pairs of CPT and
SPT tests were performed in order to examine the applicability of various existing CPT-SPT
correlations to the studied soils. The recovered samples from SPT tests contain appreciable
amount of fines (fc) ranging from 3.5 to 39.2 percent and mean grain size (D50) ranging from 0.09
to 0.23 mm. Study results indicated that qc/N ratio as a function of D50 and fc based correlations
are poorly applicable to the local soils. This paper suggests that qt1/(N1)60 ratio as a function ofmultiplying constant can be better correlated in local soils instead of laboratory based D50 or fc
correlations. An effort has also been made to perform a comparative analysis for the effective
angle of internal friction obtained from CPT, SPT, direct shear and triaxial tests
1

INTRODUCTION

At the present time, the cone penetration test (CPT) is becoming increasingly popular in
subsoil investigation for its rapid and convenient way to measure continuous soil stratigraphy.
On the other hand, the standard penetration test (SPT) is one of the most commonly used insitu test procedure for subsoil investigation in many places around the world. However,application of the CPT has started in Bangladesh since last decade for soil exploration andengineering design purpose, but SPT is still the most widespread and economic mean for
subsoil investigation than any other test.
Due to the lack of soil sampling during CPT, in many engineering projects it is mostcommon to use both CPT and SPT together for subsoil investigation and a combination ofobtained soil parameters from these tests are being used for design purpose. From that pointof view, many empirical correlations have been established between CPT cone tip resistance(qc), SPT N-value and other engineering soil properties that relate to direct applications inengineering practice. Most of the currently available correlations apply only to ideal soils.
Sometimes where the soils are not ideal the usual correlations are inadequate or lead toinconsistent conclusions. Although designers use these correlations in practice, it is necessary
to examine the applicability of various existing correlations prior to direct application in local
soils.
The primary objective of this research is to examine the applicability of various existing
CPT-SPT correlations for local soils and to propose possible new correlations. The study
included field explorations, laboratory testing, comparative analyses of resulting data. For
this study purpose, four pairs of high quality CPT and SPT tests were carried out up to 25 m
at the bank of the JamunaRiver, Bangladesh. Although, this is a small-scale research work, it
is hoped that this work will provide useful contribution for further improvement of region
specific CPT-SPT correlations.
2

LITERATURE REVIEW

Since last few decades, much research have taken place to properly utilize abundant
experiences and available database on SPT to more reliable CPT. As a result, a considerable
number of correlations have been proposed by several researcher between CPT cone tip
resistance (qc), SPT N-values and other engineering soil properties. These correlations can beconsidered in three major groups. Most of the primary correlations considered qc/N as afunction of grain characteristics, such as mean grain size (D50) and/or fines content (fc). Someother researchers proposed a constant value of qc/N for different soil types in a chart ofcorrected cone tip resistance (qt) versus friction ratio (Rf).
Compiling a number of studies, Robertson et.al (1983) accumulated several research
outputs and presented a relationship of qc/N60 as a function of mean grain size (D50). Similar
effort has been made by Kasim et al. (1986) and, KulhawyandMayne (1990), where they
have presented more updated databases to correlate qc/N as a function of mean grain size(D50) compared to the proposed relationship by Robertson et.al (1983). These correlations
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provide a very useful guideline to convert the CPT tip resistance to the equivalent SPT Nvalue for soils with D50 varying between 0.001 mm to 10 mm. From these correlations it isobserved that the qc/N ratio increases with increasing mean grain size. They have also notedthat the scatter in qc/N ratio appears to increase with increasing mean grain size.
Unfortunately, correction factors for qc or N-value have not been applied to most of their
original data. It should be noted that, energy measurements on SPT data indicate that the
average energy ratio of about 55 to 60 % may represent the average energy level associatedwith the qc/N correlation (Robertson et.al 1983). Robertson andCampanella (1985) suggested
a representative value of qc/N60 ratio of 4.5-5.0 and 4.0 for medium and silty soils,
respectively.
In other studies, Chin et al. (1988) have presented correlation between qc/N as a functionof percentage fines (smaller than 0.074 mm). In their study measured N-values werecorrected corresponding to 55 % of the maximum energy. They showed that, for sands qc/N
decreases significantly with increasing fine content. In addition to these data,
KulhawyandMayne (1990) summarized several research results (Muromachi 1981,
Jamiolkowski et al. 1985, Kasim et al. 1985, Chin et al. 1988) which display a similar trend
between qc/N and fines content as proposed by Chin et al. (1988).McNulty and Harney(2010) have compared effective angle of internal friction (∅) estimated from the CPT withthose determined from SPT N-values and laboratory triaxial tests. Their study revealed that
effective angle of internal friction (∅) obtained from triaxial tests correlated well with thoseobtained from the CPT and SPT below the water table, but above the ground water obtained∅ values from the CPT and SPT were significantly high compared to laboratory measurement.
Research by Elbanna et al. (2011) suggested that, in the absence of site specific CPT-SPT
correlations, it is suitable to use the general correlation proposed by Robertson, et al (1983).
In the absence of grain size data, they have also proposed a new correlation using theqt1/(N1)60 ratio of 0.45. However, some of the existing correlations provide best estimatedrelationship between qc and N-value, but region specific study result presented by Elkateb
and Ali (2010) represents quite inapplicability of existing correlations. Therefore, direct
application of the average relationship presented in several correlations may lead tosignificant deviation from exact result.
3

FIELD INVESTIGATIONS

Field investigations were carried out mainly through the application of cone penetration
testing (CPT) and standard penetration testing (SPT). A total of four pairs of CPT and SPT
were performed in different locations within the study area and each pair of CPT and SPT
were carried out as close as possible, maximum horizontal distance was not greater than 10 m.
In this research, field investigations were carried out along the riverbank of the Jamuna River,Bangladesh. The geologic formations of the research site are mainly consisting of alluvial
sand and silt deposits of Holocene age. The alluvial sands are light to brown-grey colored,coarse to fine silty sand of subrounded in shape. The sand contains mostly quartz, feldspar,mica and significant amount of heavy minerals. The alluvial silts have the same color as the
sands, but arefine sandy to clayey silt and arepoorly stratified(Alam et al. 1990).
3.1 Cone Penetration Test (CPT)CPT soundings were advanced using a Hogentoglar type piezoconepenetrometer with a crosssectional area of 10 cm2 and which can measures the pore water pressure (u2), as well as thecone tip resistance (qc) and sleeve friction (fs). To perform the test, the cone was pushed
vertically into the ground at a constant rate of approximately 20 mm/sec. During theadvancement, measurements of dynamic pore water pressure, tip resistance and sleeve
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friction were recorded continuously at 10 mm depth increments. The typical penetration
depth for this study was approximately 25 m below from ground surface.
3.2 Standard Penetration Test (SPT)SPT were conducted according to ASTM D1586. Boreholes for the SPT were advanced by
percussion (chopping) method with Bentonite clay. The split spoon sampling method wasused to obtain soil samples from boreholes and disturbed representative samples werecollected. Samples recovered from boreholes were stored in plastic bags that were used forlaboratory testing. An automatic type SPT hammer-release was used for the SPT. Potential
source of uncertainty that may affect SPT N-values have been carefully taken into account.
Borehole drilling, soil sampling and SPT N-value recording procedures were observed byexperienced geologist during the entire test program and this individual provided visualdescriptions of the collected samples. The SPT N-value and samples were collected every
1.52 m intervals. The corrected cone tip resistance (qt)in MPa(top scale), measured SPT N,
N60 and (N1)60 values (bottom scale) are presented in Figure 1.
boreholes.

Based on the results of the subsurface explorations, the subsoil profile at the study area canbe divided into two strata. The soil within the test area is primarily comprised of clay, silt,
fine and medium sand particles. As such, the combination of fines and sand are generally
non-plastic and the combination of fines and clay are low-plastic. The top layer consists ofsilt and clay mixture with a total thickness approximately varied from 3 m to 7.3 m.
Immediately below this layer a combination of fine to medium sand and with some silt layer
extended to a depth of 25 m. Soil layers are moist from ground surface to ground water tableand ground water table is located at 3 m below from ground surface. Note that, there wasconsiderable variability in the measured SPT N-value in different boreholes at different
depths ranging from 1 to 52 and maximum cone tip resistance (qc) was close to 20MPa.
Consistency of the soils at different depth varies from stiff to loose.
4

LABORATORY INVESTIGATIONSLaboratory investigations included sieve analysis, direct shear tests and triaxial tests. The
main objectives of the laboratory investigations are to classify the soil samples recoveredfrom SPT tests and to estimate effective angle of internal friction. Details of the laboratory
investigations are described in the following sections.
4.1 Sieve analysis

Soil samples recovered from various depths were individually assessed and classified basedon dry sieve analysis. Sieve analysis was performed on each soil sample according to ASTM
C136. Among the 64 recovered samples only 51 of the sandy samples were used both forsieve analysis (excluding silty clay samples) and to examine existing correlations. Note thatthese soils are containing appreciable amount of fines ranging from 3.5 to 39.2 percent,fineness modulus(defined as cumulative percent retained on standard sieve divided by 100)
ranging from 0.18 to 1.11 and mean grain size (D50) ranging from 0.09to 0.23 mm. Based on
the sieve analysis results, the soils are generally classified into two groups; either well gradedsands with little silt or poorly graded sands with silt. According to the unified soil
classification system, the soils can be symbolized as SW and SP-SM respectively. The mean
grain size (D50), percent finer than 0.074 mm (fc) and fineness modulus (F.M.)for eachborehole are presented in Table 1.

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20

10

40

20

60

CPT– qt
SPT– N
SPT– N60
SPT– (N1)60

15

10

5

0

25

20

15

0

0

5

20

10
.
.
.
.

40

15

Borehole-01

60

20

0

0

5

20

10

40

15

Borehole-02

60

20

0

0

91

Figure 1. Depth versus corrected cone tip resistance (qt), SPT N, N60 and (N1)60 values for all

05

Depth (m)0Borehole-03
5

20

10

40

15

Borehole-04

60

20

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Table 1. Sieve analysis results.

Depth Borehole-01
m
D50
fc
F.M.
3.05
0.1
26.8
0.21
4.57
0.09
32.5
0.16
6.10
0.095
32.5
0.16
7.62
0.09
38.4
0.39
9.14
0.23
11.3
1.11
10.67
0.2
12.4
0.87
12.19
0.2
8
0.92
13.72
0.18
17.3
0.71
15.24
0.2
12.5
0.88
16.76
0.2
7.68
0.96
18.29
0.09
32.03
0.18
19.81
0.1
22.7
0.23
21.33
ND*
ND*
ND*
22.86
ND*
ND*
ND*
24.38
ND*
ND*
ND*
* Not determined andD50 in mm

Borehole-02
D50
fc
ND*
ND*
0.16
32.44
0.175
26.39
0.095
36.35
0.1
39.2
0.095
38.1
0.095
38
0.09
22
0.14
24.4
0.195
5.85
0.195
7.5
0.195
6.85
0.195
6.95
0.195
6.8
0.18
8.55

F.M.
ND*
0.64
0.62
0.28
0.33
0.3
0.31
0.48
0.44
0.81
0.79
0.78
0.77
0.77
0.73

Borehole-03
D50
fc
0.16
17.96
0.15
16.89
0.175
19.8
0.16
20.7
0.195
16.95
0.17
17.8
0.2
7.44
0.2
5.5
0.2
4.15
0.2
5.05
0.2
4.95
0.2
3.7
0.2
3.5
0.2
5.2
0.2
7

F.M.
0.51
0.51
0.55
0.51
0.83
0.57
0.9
0.92
0.94
0.93
0.93
0.95
0.95
0.95
0.94

Borehole-04
D50
fc
ND*
ND*
ND*
ND*
ND*
ND*
0.185
5.85
0.18
6.25
0.18
5.5
0.18
5.5
0.185
5.39
0.185
5.4
0.185
5.15
0.18
6.75
0.18
6
0.18
4.7
ND*
ND*
ND*
ND*

F.M.
ND*
ND*
ND*
0.66
0.67
0.68
0.68
0.71
0.71
0.71
0.67
0.67
0.7
ND*
ND*

4.2 Preparation of reconstituted laboratory sample

To acquire sufficient amount of soils for direct shear and triaxial tests, samples with similar
grain size distribution curve, mean grain size (D50) and fines content (fc) were selected to bemixed together to prepare reconstituted samples for direct shear and triaxial tests. Mixing was
carried out by carefully stirring small portions of the selected samples together until all soil
was mixed homogeneously. After mixing the sample was stored in an air-tight plastic box
and handled carefully to avoid any significant loss of sample.
4.3 Direct shear test

A total of 36 direct shear (DS) tests, with three tests at each stress level, were carried out onreconstituted specimens at different relative densities varying from 42% to 70% and different
effective stresses varying from 25 kPa to 200 kPa. The selected test stresses and relative
densities were considered equivalent to field conditions at depths of 6 m, 12 m and 18 m.
Specimen relative densities were back calculated from SPT N-values in different boreholes atthat depth by using N-value versus relative density relationship proposed by Meyerhof (1956).
First, the amount of dry samples required to prepare the specimens at desired density were
calculated. After taking required amount of dry sample in a container, a measured amount of
de-aired water was added to the soil to bring the soil moisture content of approximately 10
percent. Specimens were prepared in a shear mold with inside diameter of 63.5 mm andheight of 25.4 mm by hand tamping method. All tests were performed on saturated samples.
During the test, vertical displacement gage, shear load gage and horizontal displacement gagereading were recorded until the horizontal shear load peaks and then falls. Angle of internal
friction was calculated in a plot of maximum shear stress versus corresponding normal stress.
4.4 Triaxial test

A total of 36 consolidated undrained triaxial tests (TX), with three tests at each stress level,
were carried out on reconstituted specimens. The effective stresses and relative densities fortriaxial tests were the same as the direct shear tests. Cylindrical soil specimens of 142 mm
height and 71 mm diameter were used and prepared using wet tamping technique. The
specimens were first saturated with back-pressure saturation until the pore pressure parameterreaches a value equal to 0.90. Following saturation, the specimens were then isotropicallyconsolidated at the desired effective stress. To cause shear failure in the specimen, deviator
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stress was applied to the specimen until the maximum axial deformation reaches to a value of
15%. The deviator stress was applied at a rate of 0.08 percent/min. During the test, deviator
stress, shear stress, normal stress and pore water pressure was recorded at every 10 sec
interval. Angle of internal friction was calculated by plotting effective-stress Mohr’s circles
for various tests (three tests at each depth) and drawing a common tangent to these Mohr’s
circles passing through the origin. The effective angle of internal friction obtained from direct
shear and triaxial tests are given in Table 2.
Table 2. Effective angle of internal friction calculated from direct shear and triaxial tests.
Depth
m
6
12
18

5

Direct shear tests
Triaxial tests
Borehole-01 Borehole-02 Borehole-03Borehole-04Borehole-01Borehole-02 Borehole-03 Borehole-04
∅
∅
∅
∅
∅
∅
∅
∅
31.8
28.81
28.81
31.38
32.5
31.8
31.5
33.5
33.82
32.21
34.22
33.02
37
35
35.5
35
40.03
34.21
36.87
35
38.5
37
36.5
36

RESULTS AND DISCUSSIONS

Based on the most commonly used CPT, SPT and soil parameter relationships, several
calculated and correlated soil parameters were determined as part of the data interpretationand to check the applicability of existing correlations to the local soils. A total of 51 data
points for the sand deposits from the 4 boreholes presented in Table 1 were selected for thisstudy to perform comparative analysis with mean grain size (D50) and percent finer (fc) based
CPT-SPT correlations. Calibrations were performed on recorded cone tip resistance data toeliminate pore pressure effect on tip resistance by a calibration factor of 0.32, as provided by
the cone manufacturer. Furthermore, the normalized cone tip resistance (qt1) was calculated
foreffective overburden stress level as proposed byJamiolkowski et al. (2001) and Kulhawy
and Mayne (1990). The SPT energy corrections and overburden pressure corrections wereapplied to the recorded field N-values to calculate (N1)60. The assumed energy level was
60 % for energy correction and soil unit weight was calculated from the SPTN-value versus
soil unit weight correlation proposed by Bowles (1982)to normalize N-value. Both the CPT
and SPT data presented in this study are normalized for overburden stress. If overburden
corrections on cone tip resistance (qc) and N-values would not have been made, the ratio of
qc/N is more deviated from the average line presented in correlations. It should be noted that,in this study the same CPT equipment and SPT rig were used in all tests to minimize inherent
test variability.
Mean grain size (D50) based correlations illustrated by Robertson et al. (1983) andKulhawy and Mayne (1990) are presented in
Figure 2. The data sets selected for this study are than plotted on the same figure toevaluate the applicability of these correlations to the local soils. A significant scatter in thedata can be seen around the average correlation curves of these two correlations. It can also
be observed that with a small change in D50 can cause significant change in qt1/(N1)60 ratio
and most of the cases qt1/(N1)60 ratio deceases with increasing D50,whichis somewhat
contradictory to the existing correlations. Furthermore, no general trend can be observed in
the plotted data with the change in D50 suggesting poor applicability of these correlations to
the local soils.
The fines content correlation proposed by Chin et al. (1988) and Kulhawy and Mayne(1990) are presented in Figure 3 along with collected data sets of this study. The collected
data sets showed a poor fit to the fines content based correlations and cannot substantiate ageneral trend between fines content and qt1/(N1)60ratio. From the plotted data it can also be
noted that the qt1/(N1)60ratio increased with increasing fines content, which is quite
contradictory to the existing correlations. In a similar fashion, fines content based correlations
also indicate poor applicability to the study soils.
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The data scatter in compared results may be due to the inherent variability of the two
penetration tests and inaccuracy of overburden calculation during N-value correction. Besides
soil structure, site geology or changes in subsurface conditions some of the inconsistency
may be due to the somewhat large distance between the SPT and CPT locations. Figure 4
compares the measured data from Jamuna with the single value of qt1/(N1)60 ratio of 0.45
suggested by Elbanna et al. (2011) for sands. The data set from this study shows good
agreement and clusters together around the average relationship. However, the plotted datashows a slightly higher value than the average value of 0.45, but it is surprising that thisrelationship shows a general trend and less scatter plot relative to previous comparisons. It isbelieved that the correlation between normalized cone tip resistance (qt1) and normalized SPT(N1)60can serve as a better relationship for these sandy soils. The main advantage of thisrelationship is that it can be used in the absence gradation results. Therefore, it is a need tocollect additional high quality CPT and SPT data to develop a better relationship.
The fundamental shear strength parameter of sands is the effective angle of internal
friction. Therefore, an effort has been made to perform a comparative analysis between theangle of internal friction estimated from CPT, SPT, and those measured in direct shear (DS)and triaxial (TX) tests. In-situ effective angle of internal friction were calculated fromestablished correlations given by Robertson and Campanella (1983) and Meyerhof (1956) for
CPT and SPT tests. Laboratory friction angles were estimated from consolidated undrained
triaxial and direct shear tests on reconstituted soil specimens at the estimated in-situ relative
densities. The effective angle of internal friction values estimated from CPT and SPT tests
and those obtained from laboratory triaxial and direct shear tests are presented in Figure 5.
From Figure 5 it can be seen that ∅ value obtained from laboratory triaxial and direct shear
test place within a narrow rage and compared well with each other and increased withincreasing depth. The ∅ value calculated from CPT and SPT data shows no general trend andrepresents higher value at smaller depth and lower value at greater depth than those obtained
from direct shear and triaxial tests.
6

SUMMARY AND CONCLUSIONSThis paper presents the applicability of various existing correlations between CPT and SPT
for local soils. It was observed that the CPT and SPT data used for this study better suit with
(qt1/N1)60 ratio of 0.45. Except that, results of this study considerably vary from existinglaboratory dependent CPT-SPT correlations and indicating that most of these existingcorrelations are poorly applicable to the local soils. Therefore, it would be significant value toestablished reliable correlations based on locally available soils. General speaking, available
established correlations provide a good framework to start with, but the direct application of
the average curve in engineering practice may lead to significant deviation. Unfortunately it
is true that, only selected data sets were used which place relatively narrow range to develop
most of the prominent correlations. Thus, it is need to further investigation by accumulatinglarge amount of high quality data from various soils types, ranging from clay to gravelly sand.

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10

Robertson et al. (1983)
Kulhawy & Mayne (1990)
BH - 01
BH - 02
BH - 03
BH - 04

qt1/(N1)60

8
6
4
2
0
0.001

D50 (mm)

0.01

0.1

1

Figure 2.Variation of the ratio qt1/(N1)60 with mean grain size (D50) comparison.
10

Chin et al. (1988)
Kulhawy & Mayne (1990)
BH - 01
BH - 02
BH - 03
BH - 04

qt1/(N1)60

8
6
4
2
0

0

20

40

fc (%)

60

80

100

Figure 3.Variation of the ratio qt1/(N1)60with fines content (fc) comparison.
40

Elbanna et al. (2011)
BH - 01
BH - 02
BH - 03
BH - 04

qt1 (MPa)

30
20
10
0

0

10

20
30
Corrected SPT blow count, (N1)60

40

Figure 4.Variation of normalized cone tip resistance (qt1) with normalized SPT blow count(N1)60 comparison.

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7

SUMMARY AND CONCLUSIONSThis paper presents the applicability of various existing correlations between CPT and SPT
for local soils. It was observed that the CPT and SPT data used for this study better suit with
(qt1/N1)60 ratio of 0.45. Except that, results of this study considerably vary from existinglaboratory dependent CPT-SPT correlations and indicating that most of these existingcorrelations are poorly applicable to the local soils. Therefore, it would be significant value toestablished reliable correlations based on locally available soils.General speaking, available
established correlations provide a good framework to start with, but the direct application of
the average curve in engineering practice may lead to significant deviation. Unfortunately it
is true that, only selected data sets were used which place relatively narrow range to develop
most of the prominent correlations. Thus, it is need to further investigation by accumulatinglarge amount of high quality data from various soils types, ranging from clay to gravelly sand.

40
35

(φ)

Angle of internal friction

45

30
25

0

TX - ∅phi
DS - ∅phi
CPT - ∅phi
SPT - ∅phi

510Depth (m)15

20

Figure 5. Comparative analysis of effective friction angle calculated from SPT, CPT, DS and TX tests.

8

REFERENCES

Alam, M.K. Hasan, S.A.K.M. Khan, M.R. and Whitney, J.W. 1990. Geological Map ofBangladesh. Dhaka: Geological Survey of Bangladesh.
Bowles, J.E. (3rded.) 1982. Foundation Analysis and Design. New York:McGraw-Hill.
Chin, C.T. Duann, S.W. & Kao, T.C. 1988. SPT-CPT correlations for granular soils.Proc. 1st
international symposium on cone penetration testing. Orlando, USA. (1): 335-339.
Elbanna, M. Quinn, J. & Martens, S. 2011.SPT–CPT correlations for oilsand tailings
sand.Proc. Tailings and Mine Waste, Vancouver, BC, 6-9 November 2011.
Elkateb, T.M. & Ali H.E. 2010.CPT-SPT correlations for calcareous sand in the Persian Gulf
Area.2nd international symposium on cone penetration testing, CPT’10, California, USA,
Paper N0. 2-13.
Jamiolkowski, M. Baldi, G. Bellotti, R. Ghionna, V. &Pasqualini, E. 1985.Penetration
resistance and liquefaction of sands. Proc. 11th international conference on soil mechanics
and foundation engineering, San Francisco, (4): 1891-1896.
Jamiolkowski, M., LoPresti, D.C.F. &Manassero, M. 2001.Evaluation of Relative Density
and Shear Strength ofSands from Cone Penetration Test and Flat Dilatometer Test. Soil
Behavior and Soft Ground Construction (GSP119), ASCE, Reston, Virginia, pp. 201–238.
Kasim, A.Chu, M. &Jensen, C. 1986.Field Correlation of Cone and Standard Penetration
Tests.J. Geotech. Engrg., 112(3): 368–372.
Kulhawy, F.H. &Mayne, P.W. 1990.Manual on estimating soil properties for foundation
design.NewYork: Electric Power Research Inst., Geotechnical Engineering Group, (EPRIEL-6800): 2-28 to 2-36.
McNulty, G. & Harney, M. D. 2010.Comparison of CPT-and DMT-correlated effective
friction angle in clayey and silty sands.2nd international symposium on cone penetration
testing, CPT’10, California, USA, Paper ID 2-53.
Meyerhof, G.G. 1956. Penetration tests and bearing capacity of cohesionless soils. Proc. SM1,(82): 1-19.
Muromachi, T. 1981. Cone penetration testing in Japan, cone penetration testing andexperience: In G.M. Norris and R.D. Holtz (eds), ASCE, New York, 49-75.
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Robertson, P.K. Campanella, R.G. & Wightman, A. 1983.SPT‐CPT Correlations. J. Geotech.
Engrg., 109(11): 1449-1459.
Robertson, P.K.&Campanella, R.G.1985.Liquefaction Potential of Sands Using the CPT. J.
Geotech.Engrg., 111(3): 384-403.
Robertson, P.K.&Campanella, R. G. 1983.Interpretation of cone penetration tests. Part I:
Sand. Canadian Geotechnical Journal. 20(4): 718-733.
Schmertmann,J.H. 1975. Measurement of in-situ shear strength. In ASCE Specialty
Conference on In-Situ Measurement of Soil Properties. (2): 57-138.

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PART-X
SLOPE STABILITY ANALYSIS OF ANEMBANKMENT AT JAMUNA RIVER

BANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA
Prepared By: Nuzhat Fatema
Mehedi Ahmed Ansary114

May 2014
ABSTRACT
A study on Slope Stability Analysis of an embankment has been carried out considering different slopes atdifferent conditions. For this purpose embankment soil has been collected from Basuria in Sirajganj near thebank of Jamuna River. Grain size analysis of the sample reveals that it contains 63% sand, 35% silt and 2%
clay. The cohesion and angle of internal friction are found to be 7 kPa and 21° respectively from shear test. For
the parametric study, shear strength parameters have been modified to be 10 kPa; 14° and 20 kPa; 12°. Basedon the results of soil investigations, stability analysis using STB2010 at some conditions (dry, high flood level,
low flood level and rapid drawdown with slope 1:1, 1:1.5 and 1:2) of the embankment has been performed. It
has been found that the safety factor decreases with steep slope while increasing with flatter one. The maximum
safety factor has been found 2.255 for soil at dry condition with a slope 1:2 while the minimum factor is 0.66 at
rapid drawdown condition with 1:1 slope. The soil having minimum factor possesses very bad condition whichneeds to be protected with a conventional design solution, Revetment Design.
Keywords: Embankment, shear strength, Slope Stability
1.

Introduction

Over the last few decades, nearly 13000 km of flood and river embankments have been repaired in Bangladesh(Hossain, M.Z. and Sakai, T., 2011). But, earthen embankments in Bangladesh are facing problems like erosion,breaching in every year. The major causes of failure identified were breach of the embankment cutting by the
public, overflow, erosion, seepage and sliding. Furthermore, insufficient supervision during construction resultsin poor-quality earthworks with the use of inappropriate soil materials, insufficient or no clod breaking,inadequate compaction and or insufficient laying of topsoil layers, the use of inferior materials, inadequate
maintenance, river migration and cutting by the public (Hoque and Siddique, 1995). The stability of earthen
embankments is influenced by seepage occurred during the increase and decrease of the adjacent water level inthe river or reservoir (Morii and Kunio, 1993). In Bangladesh, nearly 4,600 km of embankments along the bankof big rivers are flowing across the country. JAMUNA, one of the big rivers is flowing alongside of Sirajganj
district of Bangladesh (Figure 1). At 41 locations of its bank, the length of failure occurring is about 160.62km.
The concept of stability is one of the most important issues in Civil Engineering field. Stability concept
comprises some of the important factors in Civil Engineering namely: force, moment and equilibrium. The
factors contributing to the slope stability include: the type of soil, geometry of the cross-section of the slope,weight, loads and load distribution, gravity, increase in moisture content of the soil material, decrease in shear
strength of soil, vibrations and earthquakes, due to human action like excavation, undercutting and overloading.
Revetment Design is the most conventional and gratifying solution for river bank protection(http://www.kennisbank-waterbouw.nl/DesignCodes/rockmanual/chapter%208.pdf). Revetments are used toprotect banks and shorelines from erosion caused by waves and currents. It is assumed to be easily accessible for
Bangladesh. Revetment design using concrete block is considered to be economical rather than using othermaterials. Articulating concrete blocks (ACBs) are designed to provide stability and erosion control in a wide
variety of hydraulic applications. Made on dry cast block machines, the individual units are engineered tocapitalize on the weight of concrete, friction between units, and the interconnection of units into flexible
mattresses. Flexibility between units is provided to allow the mat to conform to minor deformations in the sub
grade. Classes of individual units can be produced at varying thicknesses, providing the designer flexibility inselecting appropriate levels of protection. The range of block classes allows selection of the proper combinationof unit weight, surface roughness, and open area for hydraulic stability. For example, an Armor Flex armor unit,
shown in Figure 2, is substantially rectangular, having a flat bottom to distribute the weight evenly over the sub
grade.
As Slope stability is influenced by physical features of the embankment, for different types of embankment andembankment geometry many comprehensive studies have been conducted in the developed countries andreported in their research reports (Flate and Preber, 1974; Mesri et al, 1994; Olson 1998). This paper is aimed todetermine the stability and settlement characteristics of Jamuna embankment at selected conditions. It presents a
study on the investigation of physical and mechanical properties of Jamuna river embankment materials locatedat Basuria in Sirajganj district of Bangladesh. Attempt has also been made to evaluate the existing design
methodology for embankment stability analysis through a case study.

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Figure 1: Location map of the study area.

Figure 2: Components of typical armor stone revetment.
2. GEOLOGY OF THE STUDY AREA
The study Jamuna River in 1787 a tectonic movement followed by an abnormal flood led changes in
the course of the Brahmaputra and started its flow through a new course known as the Jamuna(Bhuiyan, M.A.H., Rakib, M.A., Takashi, Rahman, M.J.J. and Suzuki, Shigeyuki, 2010). It is the main
channel of the Brahmaputra River when it flows out of India into Bangladesh. Jamuna enters in
Bangladesh from the North West side of Kurigram district and flows to south, ending its independent
existence as it joins the Padma River near Goalundo Ghat. Bounding coordinates of the river area is
W: 89.532, E: 89.871, N: 25.228, S: 23.869. The climate of the study area is tropical monsoon.
Jamuna Bridge site is located between Tangail and Sirajganj town. It lies within latitude 24022′50″–24026′30″N and longitude 89055′30″–89058′45″E. The river reach is characterized by well defined
braiding nature, meta-stable islands, nodes, sandbars, shifting ana-branches and rigorous bankerosion. Geomorphologically, the eastern bank is bounded with the lateral extension of Madhupur
Tract and the west bank is the Barind Tract, which is composed of silty clay. During monsoon, theaverage annual discharge of Jamuna River (JR) at Ba-hadurabad point is about 50000 m3/s.
However, the discharge increased to 100000 m3/s during the 1988 and 1998 flood events. The
average water surface slope is approximately 6.5 cm/km for the lower reach.
The soil deposits mainly consist of the following types of soils: (after Geological Map of Bangladesh,
GSB, 1990)
ASL – Alluvial Silt – Light to medium – grey, fine sandy 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 back swamp deposits and varying amounts of thin, inter stratified
sand, deposited during episodic or unusually large floods. Illite is the most abundant clay minerals.

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May 2014
Most areas are flooded annually. Included in this unit are thin veneers of sand spread by episodic
large floods over flood – plain silts. Historic pottery, artifacts and charcoal (radiocarbon dated 500 –
6000 years B.P.) found in upper 4m.
3. SAMPLE COLLECTION AND LABORATORY TESTSThe soil samples were collected directly from the broken part of the right bank embankment of Jamuna River atBasuria in Sirajganj district. The field investigations consisted of drilling of boreholes, identification of subsoil
layer, assessment of density and consistency of subsoil layers by carrying out Standard Penetration Test,collection of disturbed and undisturbed tube samples. One borehole was drilled at Basuria site on the bank ofJamuna River. Geologic profile of the subsoil is made from the bore log data at Basuria site. The soil overall thewhole depth possesses non – plastic behavior. Silt with little clay, brown in color, having very loose density
exists near the top of the ground surface extending to about 8 feet depth. The SPT – N value of this type of soilat the given depth is 1. Very fine sand with little silt trace mica is encountered just below the top clay layer
having grey in color and non-plasticity behavior. It extends up to the final depth of boring 102 feet (30m) andpossibly beyond. The density varies with depth such as loose density up to 28 feet depth, medium density up to
63 feet depth and dense density for the rest. At the layer up to 28 feet depth, the average SPT – N value is 3
while the range of SPT – N value is 15 – 25 up to 63 feet depth. Again SPT – N value up to 73 feet depth is 26
and up to 102 feet the range is 28 – 32 feet. Polythene bags have been used for the storage of sample forlaboratory tests. The laboratory tests have been conducted in the Laboratory of Bangladesh University ofEngineering And Technology. The testing procedures are in accordance with American Society for Testing andMaterials (ASTM). The following tests were conducted in the laboratory in order to access the collected sample:
Grain size analysis, Compaction test, Consolidated – Undrained Direct Shear test (CU test).
4.

LABORATORY TEST RESULTS AND DISCUSSION

Dry density (kN/m3)% Finer

Figure 3 and 4 shows grain size distribution of sandy soil and moisture content vs.dry density relationship ofsandy soil for Standard Proctor Compaction test respectively. Figure 5 and 6 show Shear stress vs. displacement
curve and Shear stress vs. normal stress graph of soil (c = 7 kPa, φ = 21°) for Consolidated undrained direct
shear test.
100
90
80
70
60
50
40
30
20
10
0

According to
MIT classification
Sand = 63%
Silt = 35%
Clay = 2%

1

0.1 Sieve opening (mm) 0.01
Figure 3: Grain size distribution of sandy soil.

0.001

17.6
17.4
17.2
17

Optimum dry
density = 17.45
kN/m3

16.8
16.6
16.4

6

11

16

21

Moisture content (%)
Figure 4: Moisture content vs.dry density relationship of sandy soil for Standard Proctor Compaction test.

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Shear stress (kPa)60

24.8 kPa49.6 kPa
99.2 kPa

50
40
30
20
10
0

0

0.001

0.002

0.003
0.004
0.005
0.006
0.007
0.008
Shear displacement (m)Figure 5: Shear stress vs. displacement curve for Consolidated undrained direct shear test of soil (c = 7 kPa, φ =
21°).
60

10

30

Shear stress (kPa)

50
40
30
20
10
0

0

20

40
50
60
70
80
90 100 110
Normal stress (kPa)
Figure 6: Shear stress vs. normal stress graph of soil (c = 7 kPa, φ = 21°)
According to MIT classification the percentage of sand, silt and clay at our soil sample have been found 63%,35% and 2% respectively. Hence it can realize that the sample is not the pure sand. According To Unified Soil
Classification system (USCS) the soil sample is SW-SM. It has a portion of silt and clay. From the shear test thevalues of cohesion and angle of internal friction have been obtained for sand. For further parametric study, shear
strength parameters have been modified. Table 1 shows the values of cohesion and angle of internal friction of
three types of soil obtained from Consolidated Undrained direct Shear Test.
Table 1Results from Consolidated Undrained direct Shear Test
Angle of internal friction, φ(degree)
Soil sample
Cohesion, c (kN/m2)
Type 1721Type 21014Type 320
12
From the table 1 we can analyze that cohesion is increasing with the increase of clay while angle of internal
friction is decreasing along with it. The more the cohesion the more would be the presence of clay while thereverse case happens for angle of internal friction. The values of cohesion and angle of internal friction havebeen used in the stability analysis. The shear strength parameters of the underlying soils have been obtainedusing the existing correlation with SPT-N value shown in the bore logs.
5. SLOPE STABILITY ANALYSIS
Civil engineers are often expected to make calculations to check the safety of natural slopes, slopes of
excavations, and compacted embankments. This check involves determining the shear stress developed along
the most likely rupture surface and comparing it with shear strength of the soil. This process is called slope
stability analysis. The most likely rupture surface is the critical surface that has the minimum factor of safety.
THE PROGRAM STB2010
This is a program for the analysis of the stability of slope (Verruijt, A., Delft University, 2010). The program
uses Bishop’s simplified method with some modifications introduced at GeoDelft and the Delft University forthe calculation of the facto of safety of circular slip surface, with Koppejan’s correction for very deep circles,
and a modification to account for the strength reduction of a double sliding model. The program also allows fora possible horizontal body force, to simulate the effect of an earthquake. The soil properties used in the program
are:

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Wd: Dry unit weight (kN/m3).
Ws: Saturated unit weight (kN/m3).
Ko: coefficient of neutral horizontal stress (-).
c: Cohesion (kN/m2).
phi: angle of internal friction (degrees).
P/F: switch for the groundwater condition (-).
p = 0: Zero level of the pore water pressure (m).
cap: Thickness of capillary zone, above groundwater table (m).
The unit weight of water is 10 kN/m3.

6. RESULTS OF STABILITY ANALYSIS USING STB2010
STB2010 is used for the analysis of stability of slope, using Bishop’s method with some conditions. Figure 7
shows the results of Stability Analysis of soil (c = 7 kPa, φ = 21°) at one of the four conditions (dry condition)with slope 1:1.5.

Figure 7: Result of stability analysis of soil (c = 7 kPa, φ = 21°) at dry condition for slope 1:1.5
The results obtained from the analysis using STB2010 are shown in Table 2 to 4. The fluctuation of the safety
factor along with four conditions and three slopes for the soils having different parametric characteristics has
been shown in Figure 8 to 10. From the figures for all kinds of soil, it has been realized that the safety factor
increases with the increase of water due to seepage into the soil. But at rapid drawdown condition the safety
factors have been found to be least among all conditions. It causes due to rapid reduction of external water level.
Figure 11 and 12 show the variation of safety factors at high flood level and rapid drawdown condition fordifferent soil condition respectively.
Table 2
Results of Stability Analysis of Soil Sample Type 1 (c = 7 kPa, φ = 21°)
Dry Condition
Low flood Level
High flood Level
Rapid drawdown
Slope
Condition
Condition
1:1
1.536
1.244
0.904
0.66
1:1.5
2.133
1.634
1.508
0.963
1:2
2.255
1.669
1.478
0.986

Slope
1:1
1:1.5
1:2

Table 3Results of Stability Analysis of Soil Sample Type 2 (c = 10 kPa, φ = 14°)
Dry Condition
Low flood Level
High flood Level
Rapid drawdown
Condition
Condition
1.477
1.206
0.916
0.672
2.092
1.594
1.485
0.953
2.213
1.626
1.461
0.984
Table 4
Results of Stability Analysis of Soil Sample Type 3 (c = 20 kPa, φ = 12°)

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Slope
1:1
1:1.5
1:2

Dry Condition
1.581
2.162
2.284

Low flood Level
Condition
1.305
1.66
1.692

High flood Level
Condition
0.841
1.576
1.554

Rapid drawdown
0.6
1.02
1.054

2.5

Safety factor

2
1.5
1

dry
lfl
hfl
drawdown

0.5
0

0.9

1.2

1.5

1.8

2.1

Side slope
Figure 8: Comparison on three conditions with three slopes for soil sample Type 1 (c = 7 kPa, φ = 21°)
2.5

Safety factor

2
1.5
1

dry
lfl
hfl
drawdown

0.5
0

0.9

1.2

1.5

1.8

2.1

Side slope
Figure 9: Comparison on three conditions with three slopes for soil sample type 2 (c = 10 kPa, φ = 14°)
2.5

Safety factor

2
1.5
1
0.5

dry
lfl

0

0.9
1.2
1.5
2.1
side slope 1.8
Figure 10: Comparison on three conditions with three slopes for soil sample Type 3 (c = 20 kPa, φ = 12°)120109

May 2014
1.7
1.6
1.5

safety factor

1.4
1.3

type 1 (hfl)

1.2

type 2(hfl)

1.1

type 3(hfl)

1
0.9
0.8
0.7

side slope 1.5
0.9
1.2
1.8
Figure 11: Variation of safety factor for different soil condition at high flood level condition.
1.2

2.1

1.1

Safety factor

1
0.9
0.8
Type 10.7Type 20.6Type 3

0.5
0.4

1.8
2.1
Side slope 1.5
Figure 12: Variation of safety factor for different soil condition at rapid drawdown condition.
After analysis the safety factors for all types of soil at high flood level condition with slope 1:1 and at rapid
drawdown for all three slopes have been found to be lower than the minimum recommended factor 1.2. So atypical design is needed to ensure the strength of soil. Revetment design is the most beneficial and affordable
solution for Bangladesh. Using concrete block is considered to be efficient for Revetment design.
In the revetment design, concrete blocks are given in one or two layers, sometimes it extends to three, four orfive layers either along with or without geotextile layer. It depends on the range of safety factor that is to be
increased. From Stability analysis using STB2010, the safety factors for high flood level condition at slope 1:1
and rapid drawdown with three slopes for all categories of soil have been found to be below the minimum
recommended value 1.2. So the revetment design has been performed here to raise the strength of soil. For thedesign, first a thin layer of geotextile has been given of 15 cm thickness. Then a layer is given with 45 cm * 45cm * 45 cm concrete block. For the total layer including concrete block and geotextile, the unit weight would be
the sum of γ * h of both two materials. If the unit weight of concrete and geotextiles are 23.57 kN/m3 (150 pcf)
and 16 kN/m3 (102 pcf) respectively then the total unit weight 13 kN/m2 (γ * h) for 1 m strip would be counted
for one layer in the design. When it is of two layers then the unit weight would be 23.5 kN/m3 by adding extra
unit weight of 2nd layer concrete block. The value of unit weight increases with the increase of concrete block
layer adding 10.5 for each layer. Again it causes huge cost while increasing block layer one by one. As it costs
much to layer the embankment overall with uniform concrete block, we can differ in placing the block layer

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depending on the satisfaction of safety factor. For sandy soil, four layers of concrete block have been placed at
the bottom through toe up to the middle of the slope while two layers have been placed from middle up to the
top of the embankment due to make the design economical. Table 5 shows the safety factor for different soil
conditions at high flood level. For type 1 (c = 7 kPa, φ = 21°), four layers for high flood level condition havebeen placed at the bottom through toe up to the middle of the slope while two layers have been placed frommiddle up to the top of the embankment. For type 2 (c = 10 kPa, φ = 14°) four layers have been placed
uniformly across the embankment for high flood level condition. For type 3 (c = 20 kPa, φ = 12°), four layers
have been placed at the bottom through toe up to the middle of the slope while one layer has been placed frommiddle up to the top of the embankment for high flood level condition. Again for rapid drawdown condition, thedistribution of block layers along with obtained safety factors have been given in table 6. The distribution ofblock layers is on the basis of making the design economical. Figure 13 shows the slope of an embankment
indicating bottom and top. Table 7 shows the variation of safety factor for Type 1(c = 7 kPa, φ = 21°) dependingon the distribution of concrete block layers. Safety factor has been found to be 1.198 for placing 4 layers at thebottom through toe up to the middle of the slope and 1 layer from the middle up to the top of the embankment.
But it doesn’t satisfy the condition. So 2 layers have been placed instead of 1 layer from the middle up to the top
and the safety factor has been found to be 1.208. Table 8 shows the variation of safety factor for Type 2(c = 10
kPa, φ = 14°) depending on the distribution of concrete block layers. Safety factor has been found to be 1.204
for placing 4 layers uniformly across the embankment.
Table 9 shows the variation of safety factor for Type 3(c = 20 kPa, φ = 12°) depending on the distribution of
concrete block layers. Safety factor has been found to be 1.288 for placing 4 layers at the bottom through toe up
to the middle of the slope and 1 layer from the middle up to the top of the embankment which satisfies thecondition. The variation of safety factor for different parametric soil at high flood level condition has beenshown in figure 14 to 16.
Table 5Results of Revetment Design at high flood Level condition.
Embankment Soil Properties
Factor of safetyc = 7 kPa, φ = 21°
1.208
c = 10 kPa, φ = 14°
1.204
c = 20 kPa, φ = 12°
1.288

slope
1:1
1:1.5
1:2

Layer 1
1b + 1t
1b + 2t
1b + 3t
1b + 4t

safetyfactor
0.968
0.981
0.994
1.006

Figure 13: Slope of an embankment
Table 6
Results of Revetment Design at Rapid drawdown condition.
c = 7 kPa, φ = 21°c = 10 kPa, φ = 14°c = 20 kPa, φ = 12°1.201 (7b+1top)
1.200(7b+2top)
1.213 (6b+1top)
1.214 (3b+1top)
1.208 (3b+1top)
1.273(3b+1top)
1.276 (3b+1top)
1.268 (3b+1top)
1.213(1b+1top)
Table 7
Variation of safety factor of Type1(c = 7 kPa, φ = 21°) soil
safetysafetysafetyLayer 2
factorLayer 3factorLayer 4factor2b + 1t
1.043
3b + 1t
1.12
4b + 1t
1.198
2b + 2t
1.055
3b + 2t
1.131
4b + 2t
1.208
2b + 3t
1.067
3b + 3t
1.141
4b + 3t
1.218
2b + 4t
1.078
3b + 4t
1.151
4b + 4t
1.227

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1.3

safety factor

1.2
1.1
1

layer 1layer 2layer 3

0.9
0.8

3.4
3.9
layer 2.9
Figure 14: Safety factor vs. layer graph for Type1(c = 7 kPa, φ = 21°) soil.
Table 8
Variation of safety factor of Type2(c = 10 kPa, φ = 14°) soil
safetysafetysafetyLayer 1
factorLayer 2
factorLayer 3factorLayer 4
1b + 1t
0.951
2b + 1t
1.024
3b + 1t
1.098
4b + 1t
1b + 2t
0.964
2b + 2t
1.036
3b + 2t
1.109
4b + 2t
1b + 3t
0.976
2b + 3t
1.04773b + 3t
1.12
4b + 3t
1b + 4t
0.988
2b + 4t
1.058
3b + 4t
1.131
4b + 4t

safety factor

0.9

1.24
1.2
1.16
1.12
1.08
1.04
1
0.96
0.92
0.88
0.84
0.8

1.4

1.9

2.4

112

safetyfactor
1.175
1.185
1.195
1.204

layer 1layer 2layer 3layer 4

2.9
3.4
layer
Figure 15: Safety factor vs. layer graph for Type2 (c = 10 kPa, φ = 14°) soil.

Layer 1
1b + 1t
1b + 2t
1b + 3t
1b + 4t

4.4

0.9

1.4

safetyfactor
1.059
1.071
1.082
1.092

1.9

2.4

3.9

Table 9Variation of safety factor of Type3(c = 20 kPa, φ = 12°) soil
safetysafetyLayer 2
factorLayer 3factorLayer 42b + 1t
1.134
3b + 1t
1.21
4b + 1t
2b + 2t
1.144
3b + 2t
1.219
4b + 2t
2b + 3t
1.154
3b + 3t
1.228
4b + 3t
2b + 4t
1.164
3b + 4t
1.237
4b + 4t

4.4

safetyfactor
1.288
1.296
1.304
1.312

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safety factor

1.4
1.3
1.2
1.1
layer 1layer 2layer 3layer 4

1
0.9
0.8

0.9

1.4

1.9

2.4

2.9
layer

3.4

3.9

4.4

Figure 16: Safety factor vs. layer graph for Type 3 (c = 20 kPa, φ = 12°) soil.
After Revetment Design the conditions are satisfied for the soil samples at high flood level and rapid drawdown
conditions. For all cases, the safety factors are above the recommended value (1.2). These values have ensured
the shear strength of soil along with the protection of river embankment. The soil having better safety factors are
assumed to be more protective from erosion. After the design, the number of layers at rapid drawdown has beenfound to be greater in quantity than high flood level condition. But in practice, rarely rapid drawdown condition
is considered, so the number of layers used is minimum.
7. CONCLUSION
This research has been carried out to investigate the geotechnical characteristics of the embankment andpresented results of more recent soil investigation along the embankment alignment. For this purpose
embankment soil has been collected from Basuria in Sirajganj near the bank of Jamuna River. Also field borelogs has been done up to a depth of 30 m. Direct from the broken part of the embankment, the soil samples arecollected by which the following laboratory tests: Grain Size Analysis, Compaction Test, Shear Test have been
performed.
The collected sample contains 63% sand, 35 % silt and 2% clay. According to the Unified Soil Classification
System (USCS), the soil sample is SW – SM.
With a view to making a remolded sample to obtain the shear strength parameters of the collected disturbed
sample of the embankment, a Standard Proctor Compaction test has been conducted in the laboratory. The
remolded sample has been made with the corresponding water content of 95% peak value of the dry density at
wet side. The optimum dry density has been found to be 17.45 kN/m3.
Due to obtain the shear strength parameters, Consolidated Undrained Shear test has been performed in thelaboratory. The cohesion and angle of internal friction has been found to be 7 kPa and 21° respectively. For
further parametric study, Shear strength parameters has been modified to be 10 kPa; 14° and 20 kPa; 12°. The
parameters of the soil sample of the embankment have been found directly from the laboratory tests, while forthe underlying soils the shear strength parameters have been obtained from the correlation with SPT – N value
shown in the bore logs.
Based on the data of the present investigation, stability analysis of some critical sections of the embankment has
been carried out. The stability analysis has been conducted using STB2010. The analysis depends on the soil
parameters obtained during the construction of embankment. The analysis has been performed for soils at three
conditions; dry, low flood level, high flood level and rapid drawdown with three different slopes; 1:1, 1:1.5 and1:2. The values of cohesion and angle of internal friction obtained from the shear test have been used in
STB2010. The maximum safety factor has been obtained 2.255 for soil at dry condition with a slope 1:2 while
the minimum factor is 0.66 at rapid drawdown condition with 1:1 slope. As long as water increases, the soil
becomes weakened for steepening slope. But at rapid drawdown condition safety factor has been found to be theleast because of rapid reduction of external water level. So the soil would fail at any time as having lower shear
strength to protest against erosion. It has been realized that, soil at dry condition has better strength to protect
embankment from failure. Again the strength increases with flatter slope rather than steep slope. The main
reason of the failure at high water level is considered to be water seepage into the soil while the reason is rapid
reduction of external water level for rapid drawdown condition. For this type of soil, a design named Revetment
Design with a thin geotextile layer and concrete block layer has been conducted to protect river embankment.

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This design is affordable and suitable for Bangladesh. After Revetment Design a reasonable safety factor has
been achieved for the soils at critical condition which ensures the protective strength of soil against failure.
ACKNOWLEDGEMENTS
Special thanks to Professor Dr. Mehedi Ahmed Ansary, Department of Civil Engineering, BUET
(undergraduate thesis supervisor). I also like to thank my father Md. Nurul Islam and my mother Yasmin Jahan
for inspiring me all time.
REFERENCES
Alam, M.K., Hasan, A.K.M.S., Khan, M.R. “Geological Map of Bangladesh: Geological survey of Bangladesh”,
Whitney, John W., 1990, United States Geological Survey.
Bhuiyan, M.A.H., Rakib, M.A., Takashi, Rahman, M.J.J. and Suzuki, Shigeyuki “Regulation ofBrahmaputra-Jamuna River around Jamuna Bridge Site, Bangladesh: Geoenvironmental Impacts”. J.
Water Resource and Protection, 2010, 2, 123-130 Doi:10.4236/jwarp.2010.22014 Published Online
February 2010 (http://www.SciRP.org/journal/jwarp/).
Das, B.M. (Fifth Edition). “Principles of Geotechnical Engineering”
Flaate, K. and Preber, T. (1974). “Stability of Road Embankments”, Canadian Geotechnical Journal, Vol. 11,
No. 1, pp. 72 – 78.
Hoque, M.M. and M.A.B Siddique, 1995. Flood control projects in Bangladesh: Reasons for failure andRecommendations for improvement. Disasters, 19: 260-263. DOI: 10.1111/j.1467- 7717.1995.tb00344.x
Hossain, M.Z. and Sakai, T. “River Embankment and Bank Failure: A Study on Geotechnical Characteristics
and Stability Analysis”, American Journal of Environmental Sciences 7 (2): 102-107, 2011
http://www.kennisbank-waterbouw.nl/DesignCodes/rockmanual/chapter%208.pdf
Morii, T. and H. Kunio, 1993. Finite element analysis of stress and stability of earth dams during reservoir
filling. J. Fac. Agric., Tottori Univ., 29: 45-53.
M. Z. Hossain and T. Sakai. “Severity of Flood Embankments in Bangladesh and Its Remedial
Approach”. Agricultural Engineering International: the CIGR Ejournal. Manuscript LW 08 004.
Vol. X. May, 2008.
Thornton, Christopher I. and Kane, Richard (October 2007). “Revetment Design Considerations in Sheltered
Water Wave Conditions”. Professional Development Series.
Verruijt, A., Delft University, 2010, a.verruijt@verruijt.net

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PART-XI
LIQUEFGACTION ESTIMATION USING CPTBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Ripon Hore
Mehedi Ahmed Ansary126May 2014

1.1 General
The objective of this chapter is to describe the different parts of the cone penetration test
mechine. It also describes the variation of the different parametes like friction, cone
resistance, friction ratio and SPT value (N value) with depth. Here the locations of the tests
for the research have been described.
1.2 General Specifications of CPT
Pushes down the CPT cone at a nominal rate of 2 cm per second. Pull up rate is 5 cm persecond. Handled by two men, the complete equipment can be transported on a pick-up van.
After that the soil anchors have been installed, the machine has been positioned on the test
site, the wheels have been removed and the reaction beams installed and secured. The
anchors can give between 8 and 16 tons reaction force. The Machine can also be used as aseparate stand alone unit with the wheels arrangement removed. Figure 3.1 shows a typical
CPT machine.

Fig 3.1 : CPT
Machine (Ref: Envi 200 kN CPT Pusher / Puller
Operating Manual)In the following articles different preparatory steps of CPT have been described. Figure 3.2
shows these steps.
3.2.1
Soil Anchors
Start to install the 4 SOIL ANCHORS in a square configuration with the size 1.3 x 1.6 m.
Install the MANUAL CROSS HEAD or the MOTOR DRIVE on top of the SOIL ANCHOR
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using two 12 mm BOLTS. Use 2 or 3 CPT RODS to turn the SOIL ANCHOR into theground. Screw down the auger until the top of the rod is 0.6 m above the ground. If the soil ishard, it can be enough with the soil anchor rod, but if the upper soil is soft, use the extension
rods. Use wood pieces to support the pusher and erect it horizontally. The SUPPORTS shallbe high enough so that the wheels are free from the ground. Remove the bolts that are locking
the wheel and pull out the wheels. Insert the two SHORT BEAMS inside the machine like thepicture shows.
3.2.2 Hydraulic pump
Before connecting the HYDRAULIC HOSES, clean the quick coupling with a rag. Before
starting the engine, the PUMP VALVE shall be in OPEN position. Check the OIL LEVEL
in the engine.
3.2.3

Start Engine

Turn the FUEL VALVE to OPEN. To apply CHOKE on a cold engine, turn the choke leverto the left. Put the INGITION SWITCH to ON. Start the engine by pulling the starter line.
3.2.4

Operation

Firstly Close the PUMP VALVE . Then run the CYLINDERS UP. With no load or light loadon the machine, Both VALVES can be used to increase the speed going upwards. This does
not function going down. Pull the right lever for push dawn. The speed has been regulated bychanging the engine r.p.m. For CPT, the standard RATE OF PENETRATION shall be 1.2
meter/minute + / - 25 %.
3.2.5

Prepare for CPT

Before the penetration can be started, the Memocone must have been prepared. This incudes
filling the filter point and connecting to the Datalogger for start up and zero readings. Ref. to
PC-mon manual. When the MEMOCONE has been prepared and started up together with thedatalogger, put it inside the machine. Adjust the DEPTH SENSOR WHEEL. Turn the
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LEVER to the right. Adjust if necessary on the screw so that the wheel is turning when thememocone is moving up and down. Do not press the wheel too hard against the memocone,
only so much that it turns the wheel safely. Depth sensor. Connect the depth sensor cablewith the datalogger. Insert the PUSHING HEAD or MICROPHONE into the ANVIL It will
stay in position by the means of magnets. Move the head down and guide the Memocone into
the center. When the head makes contactact with the Memocone, press the + button on the
datalogger and start the penetration. When the resistance is getting higher, check that the
automatic locks are gripping OK. PUSH about 0.5 meter.
3.2.6

PRESSURE READING

It is possible to know the pushing force by checking the hydraulic pressure.
50 Bar = 6 ton
100 Bar = 12 ton
150 Bar = 18 ton
200 Bar = 24 ton
3.2.7

Maintenance:

Every 1 year should be executed the following scheme:
1. Change engine oil.
2. Lubricate the depth sensor wheel with oil.
Every 2 year:
1. Change the hydraulic oil.

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Use wood pieces to support the pusher and erect ithorisontally.

Place the two LONG BEAMS on top of the shortones.

Insert the two SHORT BEAMS inside the machine

AUTOMATIC LOCKS on the auger rods.

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Hydraulic pump

Close the PUMP VALVE

DEPTH SENSOR WHEEL

LEVER to the right

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Insert the PUSHING HEAD

Start the pull up.

Fig 3.2: Cone Penetration Test Procedure.

3.2.8

PC-Mon.

PC-mon stands for PC Interface monitor. This unit is the link between the CPTU probes
Memocone type II and type III and a portable PC. The portable PC is NOT INCLUDED in
the delivery. The software PC-mon v 1.0 or later has to be installed in the portable PC. The
handling of the PC-Mon is totally menu operated. All possibilities at upstart, operation,
registration of data and collection of data is clearly described on the screen. All input has
been done by the keyboard and arrow-up and arrow-down buttons.
Technical specification:
Size: 420 x 300 x 55 mm
Weight: 5 Kg
Cabinet: Machined Aluminium
Power requirement: 12 V DC ( Car battery )Consumption: 1 A , FUSE : 6 A
Inputs: 12 Volts power, CPT Probe, Depth transducer encoder, Microphone,132
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Pressure sensor (Bosch type)Outputs: 12 Volts for PC, USB port
3.3 Selected areas for the Research
Total ten areas of the Dhaka city have been selected for this research. The main targeted areas
have been reclaimed lands since some of these lands found susceptible to liquefaction(Ahmed, 2005). Total ten areas have been selected which almost surrounding the Dhaka city.
The reclaimed areas are Bramangaon, Ashian City, Badda, Banasree, Gabtoli, Kawran
Bazar, Purbachal, United City, Uttara and Kamrangirchar. Figure 3.3 shows the selectedstudy area.

Fig 3.3: Map Showing the selected areas of Dhaka City for the Research

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3.4 Standard Penetration Test (SPT)
It has been conducted at all ten areas. SPT has been used for the determination of liquefaction
potential. To utilize SPT results in measuring liquefaction potential, SPT have been
conducted according to ASTM D1586 (ASTM,2000). The main objective of SPT are as
follows:(a)Boring and recording of soil stratification.

(b)

Sampling (both disturbed and undisturbed)(c)

Recording of SPT N value(d)Recording of ground water table.

3.5 Cone Penetration Test (CPT)
It has been conducted at all ten areas. CPT is being used for the determination of liquefaction
potential. Tip resistance (q), sleeve friction (f) have been found from this test.
3.6 Laboratory Tests
Disturb and undisturb samples have been collected during SPT. Collected samples have beentested at geotechnical laboratory of

BUET. Grain size analysis have been performed

according to the procedure specified by ASTM D 422. These test results have used in thecorelation between CPT and SPT.
3.7 Sub-Soil characteristics
Total ten locations have been selected for investigating liquefaction potential in Dhaka city inthis research. SPT has been conducted and disturbed as well as undisturbed samples collectedfrom all these locations. Sub-soil characteristics ,SPT and laboratory test results of thesesamples have been presented in this section. Besides this CPT test results have also been
described.
3.7.1 Sub- Soil characteristics of BRAMANGAONThis site has been situated in southest part of Dhaka city. It is a private land development
project where main filing has been done by dredged river sand. The depth of filling of finesand is 5.0 m from existing ground level. The clayey silt layer exists from 5.0 m to 6.5 m
from EGL. After that 1.5 m is sandy silt layer. Then 12.0 m is clayey silt. The uncorrected
SPT N value of filling fine sand varies from 4 to 5. The SPT N value of clayey silt layers
varies from 5 to 8. The maximum value of SPT N is 8. The minimum value of SPT N is 4.
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From the CPT test, the cone resistance varies from 0.51 to 16.78 MPa. The average value ofcone resistance is 3.88 MPa. Friction varies from 0 to 120.2 kPa. The average value ofFriction is 30.79 kPa. Friction ratio varies from 0 to 4.13 kPa. The average value of Friction
ratio is 1.11 kPa. Figure 3.4 shows a) Depth (m) vs N b) Depth (m) vs Cone Resistance(MPa) c) Depth (m) vs Friction (kPa) d) Depth (m) vs Friction Ratio at BRAMANGAON.

qc

a)

b)

f (kPa)c)d)

Fig 3.4: a) Depth (m) vs N b) Depth (m) vs Cone Resistance (MPa) c) Depth (m) vsFriction (kPa) d) Depth (m) vs Friction Ratio at BRAMANGAONSPT Results:
SPT has been conducted in the area following procedure described in ASTM D1586. The
SPT N values of the boreholes have been shown in the Table 3.1(a). The graph between
depth vs N value has been shown in Fig 3.4 (a).
CPT results:
The graph between depth vs friction and cone resistance have been shown in Fig 3.4(c) and3.4(b). From the CPT test, the cone resistance varies from 0.51 to 16.78 MPa. The maximum

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value of cone resistance is 16.78 MPa. The minimum value of cone resistance is 0.51 MPa.
The average value of cone resistance is 3.88 MPa. Friction varies from 0 to 120.2 kPa. The
maximum value of Friction is 120.2 kPa. The minimum value of Friction is 0 kPa. The
average value of Friction is 30.79 kPa. Friction ratio varies from 0 to 4.13 kPa. The
maximum value of Friction ratio is 4.13 kPa. The minimum value of Friction ratio is 0 kPa.
The average value of Friction ratio is 1.11 kPa.
Grain size analysis results:
Results from grain size analysis of the soil samples have been presented in Table 3.1(a). The
mean grain size (d50), fine content (Fc) of filling sand varies 0.16 to 0.17 mm, 20 to 21%
respectively. The mean grain size (d50), fine content (Fc) of silt are 0.046 mm, 71%
respectively. Table 3.1 b shows Probable soil classification using CPT data ( Robertson,1990) at BRAMANGAON.

Table 3.1(a) : Grain size analysis at BRAMANGAON

Depth(m)
1.5
3
4.5
6
7.5
9
10.5
12
13.5
15
16.5
18
19.5

Description of Soil
Filling Sand
Filling Sand
Filling Sand
Clayey Silt
Sandy silt
Clayey Silt
Clayey Silt
Clayey Silt
Clayey Silt
Clayey Silt
Clayey Silt
Clayey Silt
Clayey Silt

SPT N
Value

4
5
5
7
8
5
5
5
4
5
6
7
8

Fc(%)
d50(mm)
20
0.16
21
0.17
20
0.17
71
0.046
51
0.076
71
0.046
71
0.046
72
0.046
71
0.046
71
0.046
71
0.046
71
0.046
71
0.046

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Table 3.1(b): Probable soil classification using CPT data ( Robertson, 1990) at
BRAMANGAON
Depth Range(m)Ic Range

0-3
3-6
6-9
9-12
12-15
15-18
18-21
21-24

0.82-1.52
1.22-1.92
1.77-2.82
2.34-3.24
2.48-3.1
2.51-3.11
1.99-3.15
1.66-2.67

3.7.2

Probable Soil
Classification
Sand
Sand
Sand/Silt
Silty Sand/Siltly Clay
Silty Sand/Siltly Clay
Silty Sand/Siltly Clay
Silty Sand/Siltly Clay
Sand

Sub-Soil Characteristics of ASHIANCITY

This site has been situated in Northern part of Dhaka city. The depth of filling of fine sand is
3.5 m from existing ground level. The silty clay layer exists from 3.5 m to 12.5 m from EGL.
After that 4.5 m is fine sand layer. Then 3.0 m is silty clay. The uncorrected SPT N value offilling fine sand varies from 4 to 5. The SPT N value of silty clay layers varies from 3 to 7.
The maximum value of SPT N is 42. The minimun value of SPT N is 3. From the CPT test,
the cone resistance varies from 0.195 to 7.805 MPa. The average value of cone resistance is
1.78 MPa. Friction varies from 0 to 233.9 kPa. The average value of Friction is 31.21 kPa.
Friction ratio varies from 0 to 6.35 kPa. The average value of Friction ratio is 1.29 kPa.
Figure 3.5 shows a) Depth (m) vs N b) Depth (m) vs Cone Resistance (MPa) c) Depth (m) vsFriction (kPa) d) Depth (m) vs Friction Ratio at ASHIANCITY.
SPT has been conducted in the area following procedure described in ASTM D1586. The
SPT N values of the boreholes have been shown in the Table 3.2(a). The graph between depth
vs N value has been shown in Fig 3.5 (a).
CPT results:
The graph between depth vs friction and cone resistance have been shown in Fig 3.5(c) and3.5(b). From the CPT test, the cone resistance varies from 0.195 to 7.805 MPa. The
maximum value of cone resistance is 7.805 MPa. The minimum value of cone resistance is
0.195 MPa. The average value of cone resistance is 1.78 MPa. Friction varies from 0 to 233.9
kPa. The maximum value of Friction is 233.9 kPa. The minimum value of Friction is 0 kPa.
The average value of Friction is 31.21 kPa. Friction ratio varies from 0 to 6.35 kPa. The

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maximum value of Friction ratio is 6.35 kPa. The minimum value of Friction ratio is 0 kPa.
The average value of Friction ratio is 1.29 kPa.
qc(MPa)

N

0

50

10

10

0

5

5

5

10

10

10

15

15

20

20

20

a)

0
0

15

25

500

0

25

b)

25

c)

Depth(m)Depth(m)5Depth(m)00Depth(m)0Friction Ratiof (KPa)

10

15

20

25

d)

Fig 3.5: a) Depth (m) vs N b) Depth (m) vs Cone Resistance (MPa) c) Depth (m) vs Friction(kPa) d) Depth (m) vs Friction Ratio at ASHIANCITY.
SPT Results:
Grain size analysis results:
Results from grain size analysis of the soil samples have been presented in Table 3.2(a). The
mean grain size (d50), fine content (Fc) of filling sand varies 0.16 to 0.17 mm, 20 to 21%
respectively. The mean grain size (d50), fine content (Fc) of clay varies 0.002 to 0.003 mm, 94
to 96% respectively. The mean grain size (d50), fine content (Fc) of sand are 0.16 mm, 21%
respectively. Table 3.2(b) shows the probable soil classification using CPT data ( Robertson,1990) at ASHIANCITY.

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Table 3.2(a) : Grain size data at ASHIANCITY
Depth(m)
1.5
3
4.5
6
7.5
9
10.5
12
13.5
15
16.5
18
19.5

Description of
Soil
Filling Sand
Filling Sand
Silty Clay
Silty Clay
Silty Clay
Silty Clay
Silty Clay
Silty Clay
Sand
Sand
Sand
Silty Clay
Silty Clay

SPT N
d50(mm)Value Fc(%)
4
20
0.16
5
21
0.17
4
94
0.002
3
95
0.0025
3
96
0.003
4
96
0.003
4
96
0.003
7
96
0.003
30
21
0.16
36
21
0.16
42
21
0.16
8
95
0.00251095
0.0025

Table 3.2 (b): Probable soil classification using CPT data ( Robertson, 1990) at
ASHIANCITY
Depth Range(m)
0-3
3-6
6-9
9-12
12-15
15-18

Ic Range
0.64-1.61
1.44-3.25
2.84-3.51
2.81-3.45
2.28-3.05
2.29-3.04

Probable Soil Classification
Sand
Sand/Silty clay
Silty Clay
Sandy silt/Silty Clay
Silty sand/Silty Clay
Silty sand/Silty Clay

LIQUEFACTION POTENTIAL ANALYSIS BASED ON SPT AND CPT
1.1 General
The main objective of this chapter is to present the liquefaction potential of the selected
reclaimed areas. Soil characteristics of the selected reclaimed areas have been determined byfield and labortatory tests. Test results have been presented in Chapter Three. Liquefaction
potential have been estimated using two methods based on CPT (Robertson and Wride,1998)
and SPT (Seed et al;1983) data. The results of these estimations have been presented in thischapter. Results obtained from different methods have been compared and suitable methods
for estimating liquefaction potential has been presented.

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1.2 Liquefaction Potential
In this research liquefaction potential has been estimated by procedures based on both SPT
and CPT test results. Detail procedures have been discussed in chapter Three. Parameter ofanalysis and details results of estimations based on these procedures has been discussed
below.
Parametes for analysis
Liquefaction analysis based on SPT and CPT need ground motion characteristics and moment
magnitude due to earthquake and depth of analysis. In this study, following values of theseparameters have been considered.
1) Ground motion and Moment Magnitude:
In this research , the value of amax has been taken as 0.15g as Dhaka city exist in the zone 2 ofseismic zonation map of Bangladesh (BNBC, 1993). Other researchers (Ansary and Rashid,
2000) also used similar values of amax for the similar purpose. Though at present the value of
amax is being update by various researchers and agencies from 0.15 to 0.2. But it has not beentaken to the consideration for this study since it has not been incorporated to BNBC yet.
Earthquake ground motion has been influenced by a number of factors. Most importantfactors are moment magnitude, epicenter distances, local soil conditions, earthquake sources,
etc. In seed-Idriss simplified procedure moment magnitude (Mw) input parameter is also
important correction factor. From Table 2.1, it is seen that ranges of Mw at nearby faults from
Dhaka varies 7.5~8.5. However, this value can not be considered directly for Dhaka sincethose faults are at quite distant places from Dhaka. Due to non-availability of attenuation law
and suitable correlaions between distance and ground motion characteristics for Dhaka, thedesign moment magnitude has been taken 7.0 for this study, which is the lowest value inTable 2.1.
2) Sources of Damaging Earthquake near Dhaka city:
Bangladesh covers one of the largest deltas and one of the thickest sedimentary basins in theworld. According to the report on time predictable fault modeling (2009), earthquake andtsunami preparedness component of CDMP have identified five tectonic fault zones which
may produce damaging earthquakes in Bangladesh. These are Madhupur fault zone, dauki
fault zone, plate boundary fault zone -1, plate boundary fault zone -2, and plate boundary
fault zone -3. Among these, Madhupur fault zone has been considered as a source ofdamaging earthquake near Dhaka in this study.
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1.2.1

Liquefaction Potential of BRAMANGAON

On the basis of soil characteristics of this locations that have been presented in chapter 3.
Liquefaction potential based on CPT (Robertson and Wride, 1998) and SPT (Seed et al;1983)
data have been estimated. A typical liquefaction potential analysis has been shown in Fig 4.1.
Liquefiable zone is where Fl <1, on the other hand Non liquefiable zone is where Fl >1. Theliquefaction analyses results by different procedures have been presented below:


Liquefaction susceptibility has been estimated based on the method proposed by Seedet al;1983 at different depths. The liquefaction zones vary between 1.5~4.5 m. (Fig
4.1).



Liquefaction susceptibility has been estimated based on the method proposed byRobertson and Wride, 1998. From the Fig 4.1, liquefaction zones vary between 1.5~10 m and from 18~22.5m.

From the above discussion, it has been seen that liquefaction potential result slightly varies inthe two methods. It may be concluded that the soil may liquefy from 1.5~10 m and from
18~22.5 m depth if an earthquake of sufficient energy occurs. CPT is more reliable than SPT
as it is performed at each 0.1m depth.

Depth(m)00.5Factor of Safety
1

0
1.5
3
4.5
6
7.5
9
10.5
12
13.5
15
16.5
18
19.5
21
22.5
24
25.5
27

1.5

2

FS(CPT)
FS(SPT)Fig 4.1: Depth(m) vs FS at BRAMANGAON

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4.2.2 Liquefaction Potential of ASHIAN CITY
On the basis of soil characteristics of this locations that have been presented in chapter 3.
Liquefaction potential based on CPT (Robertson and Wride, 1998) and SPT (Seed et al;1983) data have been estimated. A typical liquefaction potential analysis has been shown in
Fig 4.2. Liquefiable zone is where Fl <1, on the other hand Non liquefiable zone is where Fl>1. The liquefaction analyses results by different procedures have been presented below:


Liquefaction susceptibility has been estimated based on the method proposed by Seedet al;1983 at different depths. The liquefaction zones vary between 1.5~3 m. (Fig 4.2).



Liquefaction susceptibility has been estimated based on the method proposed byRobertson and Wride, 1998. From the Fig 4.2, liquefaction zones vary between
1.8~3.9 m and from 12.9~14.4 m.

From the above discussion, it has been seen that liquefaction potential result slightly varies inthe two methods. It may be concluded that the soil may liquefy from 1.5~3.9 m and from
12.9~14.4 m depth if an earthquake of sufficient energy occurs. CPT is more reliable than
SPT as it is performed at each 0.1m depth.
.

0

0.5

Factor of Safety
1

1.5

2

0
1.5
3
4.5
6
Depth (m)

7.5
9
10.5

FS(CPT)
FS(SPT)

12
13.5
15
16.5
18
19.5
21

Fig 4.2: Depth(m) vs FS at ASHIAN

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Table 4.1: Liquefaction zone of two different method.
Site Name

Liquefaction zone (Seedet al;1983)

Liquefaction
Zone(Robertson and Wride,
1998)

BRAMANGAON

1.5~4.5 m

1.5 ~10 m and18~22.5m

ASHIAN CITY

1.5~3 m

1.8~3.9 m and12.9~14.4 m

BADDA

1.5~4.5 m

4.5 ~5.5 m and8~9.5mBANASREE

1.5~4.5 m

0.7 ~4.8 m and14.4~15.3 m

GABTOLI

1.5~4.5 m

0.6 ~5.4 m

KAWRAN BAZAR

at 12 m depth

11.4 ~12.3 m

PURBACHAL

1.5~6 m

1.5 ~5.0 m and15~15.6 m

UNITED CITY

1.5~3 m3.0~4.5 m. and10.5~12.0 m

UTTARA

1.5~4.5 m

2.7 ~4.8 m and8.7~12.3 m

KAMRANGI CHAR

1.5~7.5 m
10.5~11.5 m

and

from

1.5 ~6 m and7.5~12 m

.

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PART-XII
BURIED GAS PIPELINE DAMAGE ANALYSISBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Sayeed Hossain
Mehedi Ahmed Ansary

144May 2014

3.0 GENERAL
The damageability of buried gas supply pipelines in seismic Zone can be very serious and itis necessary to take preventive measures that eliminate, or at least decrease, thatdamageability. Pipelines that are the main source of gas distribution for important cities inseismic zone should be investigated and analyzed in terms vulnerability to earthquakes.
Institutions and authorities responsible for the design, Construction and operation of buried
pipelines located in seismic zones should demand that the seismic effects are correctly taken
into consideration in order to assure the good behavior of such pipelines during their working
life.
The damage Produced by breakage or disconnection of pipelines is quite variable and can be
related to technical, economical and social aspects. The breakage of gas pipelines, forinstance, besides representing a health hazard and fire risk causes leakage and the repairs in
the pipeline represent an important cost
The damage algorithm for buried pipe is expressed as a repair rate per unit length of pipe, asa function of ground shaking or ground failure. The development of damage algorithms forburied pipe is primarily based on empirical evidence, tempered with engineering judgment
and sometimes by analytical formulations. Empirical evidence means the following: after anearthquake, data is collected about how many miles of buried pipe experienced what levels of
shaking and how many pipes were broken or leaking because of that level of shaking.
Repair rate of pipelines due to earthquake is related to either peak ground acceleration (PGA)or peak ground velocity (PGV). There exist a good number empirical relations such as
Katayama (1975), O’ Rourke (1982), Isoyama & Katayama (1998) and Iosyama (2000) for
the Prediction of earthquake-induced pipeline damage analysis which are Presented inchapter two. In case of PGA O’Rourke (1982) and Isoyama (2000) relations are used. In caseof PGV O’Rourke (2000) and Isoyama (2001) relations are used to predict the damage rate ofpipelines. Finally an estimation of financial loss is presented.
3.1 PIPELINE DATABASE DEVELOPMENT
GIS provides an ideal tool for analyzing relationships amongst spatial datasets. G1S isincreasingly used in lifeline engineering for post earthquake investigation of damage and forrisk assessment.
The history of gas supply system of Dhaka city is very long. The only known maps available
are those created by “TITAS gas T & D Company Ltd” which has been responsible fordesign, finance and construction of gas Supply System. A copy of maps of gas supply
network of I988 covering the whole Dhaka city at a scale of 1:10000 is collected for thisstudy. This map is scanned at first and then the whole gas pipeline networks are digitizedwhich is illustrated in Figure 3.1.
No distinction is made between different pipe materials or diameters, although it is known
from the authority that the network consists of cast iron pipes with diameter 75 mm to300mm.
Microzonation maps of different intensities are grouped presented in chapter three, andpipeline networks of different diameter are laid in these maps on GIS platform which are
shown in Figures 3.2 to 3.3. Finally, the lengths of pipelines are calculated according tointensity from these digitized intensity- pipe maps for analysis which are shown in Table 3.1

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Figure 3.1 Digitized layout of Gas pipe line network of Dhaka City.

Figure 3.2 Digitized layout of Gas pipe line network of Dhaka City showing diameter of
pipe.

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Figure 3.3 Digitized layout of Gas pipe line network superimposed on MM intensity
map of Dhaka city.
Pipe length (km) within different intensity zone of Dhaka city
180
160
140
120
100
80
60
40
20
0
Intensity VIII
20 mm

25 mm

Intensity IX

50 mm

75 mm

100 mmIntensity X

150 mm

200 mm

250 mm

300 mmFigure 3.3A Gas Pipe length (km) within different intensity zone of Dhaka city
Table 3.1 Gas pipe line length within different intensity of Dhaka city
Pipe length (km)Total
Intensity
20
25
50
75
100 150 200 250 300
Length
(MMI)
N/A
mm
mm
mm mm mm mm mm mm mm
(km)
8
9
10

136

10.03
1.27
0.00

92.33
18.58
10.37

167.02
8.14
0.00

33.72
5.53
1.43

24.29
4.06
0.00

23.79
3.35
1.39

15.81
19.09
7.09

0.00
1.50
0.00

0.00

9.04

376.03

1.55

4.24

67.31

1.94

0.00

22.23

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3.2 SELECTION OF PEAK GROUND ACCELERATION (PGA) VALUES FROMINTENSITY
In studies related to earthquake damage estimation and earthquake insurance, it has been
observed that the Modified Mercalli intensity scale is the easiest and most convenient to workwith. Most of the available damage statistics are related to the MM intensity at a site.
However, for the recent instrumentally recorded data, the information on ground motion isusually in the form of peak ground motion parameter such as the PGA. Again, many
empirical data base relationships are available in the literature to relate the MM intensity with
the PGA. Peak ground acceleration is an instrumentally recorded continuous variable whereas
modified Mercalli intensity is a subjectively assigned discrete Integer variable. Thus, it
should be expected that there will be a range of PGA values corresponding to a given
intensity level.
In the past, a number of researchers have developed PGA-MMI relationships. In each of therelationships given below, I is Modified Mercalli intensity and A is peak ground accelerationin cm/sec2.
Gutenber and Richter (1942)
log A = -0.5+0.33I
3.1
Hersberger (1956)
log A = -0.9+ 0.43I
3.2
Ambraseys (1974)
log A =-0.16+0.36I
3.3
Trifunac and Brady (1975)
log A =0.014+0.3I
3.4
All the above relationships are log-linear in format.
Using the above relationships, different PGA values calculated for different MM intensity
and show in Table 3.2
Table 3.2 PGA values bashed on different existing empirical relationships for different
intensity
Gutenberg and Hershberger Ambraseys Trifunac andIntensity(MMI)
Richter (1942) (1956)(1974)
Brady (1975)
5
0.014
0.018
0.045
0.033
6
0.031
0.049
0.102
0.066
7
0.066
0.131
0.234
0.133
8
0.141
0.354
0.535
0.265
9
0.301
0.952
1.226
0.528
10
0.643
2.561
2.809
1.053
11
1.376
6.894
6.434
2.101
MM intensity and PGA values from Table 3.2 have also been plotted in Figure 3.4 forcomparison. It can be seen in the graph of Figure 3.4 that for a particular intensity,
Ambraseys relation shows higher value and Gutenberg & Richter curve shows lower value.
All most all of the remaining curves lie in between these two. The curve from Trifunac &Brady is close to the median value. Henceforth intensity-PGA relationships given byGutenberg-Richter and Trifunac-Brady are considered for our analysis; values in higher side
are ignored.

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May 2014

10.00

1.00
PGA (cm/s2)

Gutenberg & Richter
Hershberger
Ambraseys
Trifunac & Brady

0.10

0.01
5

6

7

8

9

10

11

Figure 3.4 Comparison of PGA values derived from different modified Mercalli
intensity (PGA-MMI) empirical relationships.
3.3 SELECTION OF PEAK GROUND VELOCITY (PGV) VALUES FROMINTENSITY
A number of researchers have also developed PGV-MMI relationships. In each of the relationships
given below, I is Modified Mercalli intensity and V is peak ground velocity in cm/sec. Trifunac andBrady (1975), considered horizontal and vertical components separately.
Trifunac and Brady (1975)
log Vv = -1.10+0.28 I
3.5
3.6
Trifunac and Brady (1975)
log VH = -0.63+0.25 I
Wald et. al. (1999) I = 3.47 log (PGV) +2.35
3.7
Using the above relationships (vertical component discarded), different PGV values calculated for
different MM intensity and show in Table 3.3
Table 3.3 PGV values bashed on different existing empirical relationships for different
intensity
Intensity
Trifunac and Wald et(MMI)
Brady (1975) al (1999)
5
4.169
5.803
6
7.413
11.2697
13.18321.8818
23.44242.486941.68782.4951074.131160.18111
131.826
311.025

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MM intensity and PGV values from Table 4.3 have also been plotted in Figure 3.5 for comparison.
It can be seen in the graph that Trifunac Brady gives higher value than Wald et. al.

PGV (cm/sec)

1000

100
Trifunac and Brady (1975)
10

Wald et al (1999)

1
0

2

4

6

8

10

12

14

Intensity (MMI)

Fig 3.5 Comparison of PGV values derived from different PGV-MMI empirical relationships.
3.3 SELECTION OF DAMAGE ANALYSIS MFTHODS BASED ON PGA
Different pipeline fragility relation give very different predictions of pipeline damage rate forthe same PGA value. The values calculated in Table 3.4 are from katayama et. (1975),
Isoyama & Kaiayama (1982), O‘Rourke et al. (1998) and Isoyama et al. (2000) fragility
relations (Equations 2.9, 2.10, 2.11 and respectively). All these relations assume CI pipe
irrespective of diameters.
Table 3.4 pipeline repair rate from different fragility relations for PGA values based on
Trifunac and Brady and Gutenber and Richter relations
Repair Rate (RR)
Equation Intensity
Katayama Isoyama andO'Rourke
Isoyama
PGA
Used
(MMI)
et
al.
Katayama
et.
al.
et al.
(cm/S2)(1975)(1982)(1998)(2000)
7
130.017
0.011
0.001
0.019
0.002
8
259.418
0.911
0.072
0.044
0.063
Trifunacand Brady
9517.60775.276
4.751
0.105
0.419
10
1032.761 6218.090
312.448
0.250
2.041
7
64.565
0.000
0.000
0.008
0.000
Gutenberg
8138.038
0.016
0.002
0.020
0.004
and
9
295.121
2.077
0.158
0.052
0.094
Richter
10630.957
266.80715.7740.135
0.673
From the selected peak ground acceleration (PGA) values and fragility relations, following
four methods are used for damage analysis.
Method 1: In this method PGA and repair rate are based on Trifunac – Brady MMI-PGA
relations and O’Rourke damage prediction relation.
Method 2: This method is based on Gutenberg-Richter MMI-PGA relation and O’Rourke
damage prediction relation.

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Method 3: This method involves Trifunac-Brad MMI-PGA relation and Isoyama damage
prediction relation.
Methodmethodinvolves
Trifunac-Brad
relation and Isoyama
damageMethod3:4: This
Where
damageanalysis
is basedMMI-PGA
on Gutenberg-Richter
MMI-PGA
relation andprediction
Method3: relation.
This method involves Trifunac-Brad MMI-PGA relation and Isoyama damage
Isoyama damage prediction relation.

MethodWheredamageanalysis
is based on Gutenberg-Richter
relationandprediction
Method 4:
3: relation.
This method
involves
Trifunac-Brad
MMI-PGA relationMMI-PGA
and Isoyama
damageIsoyamadamageprediction
relation.
Method4:
Wheredamageanalysis
is
based
on
Gutenberg-Richter
MMI-PGA
relationandprediction
Method3: relation.
This method involves Trifunac-Brad MMI-PGA relation and Isoyama damage
3.4
GAS
PIPELINE
DAMAGEANALYSIS
BASED
ON
PGA
Isoyamadamageprediction
relation.
Method 4: relation.
Where damage analysis is based on Gutenberg-Richter MMI-PGA relation andprediction
Pipelinedamageestimation
isANALYSIS
relatedtoondamage
prediction
relationship.
Relative
3.4
GAS4:
PIPELINE
DAMAGE
BASEDON
PGA MMI-PGA
Isoyamadamageprediction
relation.
MethodWheredamageanalysis
is based
Gutenberg-Richter
relationand results ofdifferent
damageprediction
relationships
arestudiedintheprevious
articles.
Pipelinedamageestimationis related
to damageprediction
relationship. Relative results ofUsing the
3.4
GAS damage
PIPELINE
DAMAGEANALYSISBASEDON PGA
Isoyamaprediction
relation.
different
damageprediction
areBASED
studiedin thepreviouscalculated
articles.
the
Pipelineestimation
isrelationships
relatedtodamageprediction
relationship.
Relative Using
resultstheof digitized
methods
outlinedinDAMAGE
the precedingarticlesandpipeline
lengthsfrom
3.4
GAS damage
PIPELINE
ANALYSIS
ON
PGA
methods
outlinedintheprecedingarticlesandpipeline
lengths
calculated
fromthedigitized
different
damageprediction
relationships
arestudiedintheprevious
articles.
Using
the
maps
which
are
shown
in
Table
3.1.
Repairrates
andnumberof
repairsareworkedPipelinedamageestimationisrelatedtodamageprediction
relationship.
Relative
resultsof out and3.4 GAS PIPELINE DAMAGE ANALYSIS BASED ON PGA
maps
which
are
shown
in
Table
3.1.
Repairrates
andnumberof
repairsareworkedout
andmethods
outlinedintheprecedingarticlesandpipeline
lengths
calculated
fromthedigitized
different
damageprediction
arestudiedintheprevious
Using
Pipelinedamageestimation
isrelationships
relatedto damageprediction
relationship.
resultsofpresented
in Table
3.5 to 3.8
and finallya different
table,
table
3.9 articles.
isRelative
prepared
forthecomparisonpresented
in Table
3.5thetoinpreceding
3.8
andfinallya different
table,
tableis prepared
forthecomparison
maps
which
are rates
shown
Table
3.1.
Repairrates
andnumberofprevious
repairsareworkedout andmethods
outlinedinarticlesandpipeline
lengths
calculated
from
digitized
different
damageprediction
relationships
arestudiedinthearticles.
Using
theof these
repair
which
are
also
presented
ingraphof 3.9Figure
3.7.
of
these
repairwhich
areandalso
presented
in pipeline
graphofnumberFigure3.7.
presented
in Table
3.8
finallya different
table,
table 3.9
is prepared
forthecomparison
maps
which
arerates
shown
Table
3.1.
Repairrates
andof
repairsareworkedout andmethods
outlined
in3.5
thetoinprecedingarticlesandlengths
calculated
from
digitizedof
these
repair
rates
which
are
also
presented
in
graph
of
Figure3.7.
presented
in
Table
3.5
to
3.8
and
finallyadifferent
table,
table3.9
ispreparedforcomparison
maps
which
are
shown
in
Table
3.1.
Repairrates
andnumberof
repairsareworkedout and
Table 3.5Intensity
Intensity
andnumberof repairs
based
on O'Rourke
and Trifunac
and Brady
Table
andnumberof
repairs
based
onofO'Rourke
Trifunacand Bradyof these3.5
repairrates3.5
whichareandalsofinallypresented
ingraph
Figure3.7.isandpresented
in Table
to 3.8a different
table,
table 3.9
preparedfor comparison
relation Intensity and number of repairs based on O'Rourke and Trifunac and Brady
relationTableof these3.5
repair rates which are also presented in graph of Figure 3.7.
relationTable
3.5 Intensity and number of repairs based on O'Rourke and Trifunac and Brady
relation
Total
Total
Table
3.5 Intensity and number of repairs
based
on O'Rourke
and Trifunac
and Brady
length(km)
PipePipe
length(km)
Intensity
Intensity PGA
PGA
LengthRepai
relation
Length Repair
Repai
Pipe
(km)
20 20 25 25
75 length
150
200
2 2
75100 100
150 250200 300
250 N/A300 Total(MMI)(MMI) (cm/s) ) mm50 mm
Intensity(cm/s
50 mmmm
N/A
PGA
mm mm
mm
mm
mm
mm
mm
mm
mm
mm
mm
mm
mm
mm
(km)
r
rate
numberLengthRepai
Repair
20
25
75
100
150
200
250
300
(km)
r rate2
Total
Pipe length (km)
(MMI)
(cm/s
50 mm
N/A
Intensity
PGA) 10.03
mm
mm
mm
mm
mm
mm
mm
mm
9.04 Length
88
(km)
r
rate
number
376.030.044
17259.4292.33
167.02
33.72
24.3
23.8
15.8
0.00
0.00
Repai
RepairTotal
Pipelength(km)
2010.03 25 92.33
75 33.72
100 24.3
150
200
250
2
376.030.044
259.42167.0223.8
15.8 300
0.00 N/A0.00 9.04
(MMI)
(cm/s
)
50 mm
Intensity
PGA
mm
mm
mm
mm
mm
mm
mm
mm
9.04
8
4.24
9
376.030.044
17259.4210.03
92.33
167.02
33.72
24.3
23.8
15.8
0.00
0.00
(km)
r
rate
numberLengthRepai
Repair
67.31
0.105
7
517.61
1.27
18.58
8.14
5.53
4.06
3.35
19.1
1.50
1.55
20
25
75
100
150
200
250
300
2
(MMI)
9
(cm/s
)
67.31
0.105
517.61
1.27 mm18.5850 mm 8.14
5.53
3.35
19.1 mm1.50 N/A1.55 4.24mm
mm
mm 4.06
mm
mm
mm
9.04
0.00
89
(km)
rate number
10
67.31
0.105
7
517.61 10.03
1.27
8.14
5.53
376.0317259.4292.33 167.02
24.3 3.35
23.8 19.1
15.8 1.50
0.00 4.24
22.23 r 0.044
0.250
61032.70.00 18.58
10.37
0.00 33.72
1.43 4.06
0.00
1.39
7.09
0.00 1.55
1.94

Repairnumber
17
7

10
22.23
0.250
1032.70.00 10.37
0.00
1.43 0.00 1.39 7.09 0.00 9.04
1.94 0.00
0.00
89
10
376.030.044
17259.4292.33 167.02
24.3 3.35
23.8 19.1
15.8 1.50
0.00 4.24
22.23
0.250
6
1032.7
0.00
0.00
1.43
1.39
7.09
0.00 1.55
1.94
67.31
0.105
7
517.61 10.03
1.27 10.37
18.58
8.14 33.72
5.53 0.00
4.06
4.24
9
Table
3.6
Intensity
andnumberof
repairs
basedon
O'Rourke
andGutenberg-Richter
10
67.31
0.105
7
517.61
1.27
8.14
5.53
22.23
0.250
6
1032.70.00 18.58
10.37
0.00
1.43 4.06
0.00 3.35
1.39 19.1
7.09 1.50
0.00 1.55
1.94 0.00
Table
3.61032.7
Intensity
andnumberof1.43
repairs
on O'Rourkeand Gutenberg-Richter
Table
Intensity
andnumberof repairs
basedbasedon O'Rourke
0.00
10 3.6
22.23
0.250
6
0.00
10.37
0.00
0.00
1.39
7.09 0.00 and
1.94 Gutenberg-Richter

Table 3.6 Intensity and number of repairs
based(km)on O'Rourke and Gutenberg-Richter
Total
Pipe length
Intensity
PGA
LengthTable
3.6
Intensity
andnumberof
repairs
basedon
O'Rourke
andGutenberg-Richter
Total Repai
Total Repair
Pipelength(km)
20
25
75 Pipe
100 length
150
200
250
300
(km)
2
(MMI)
)
50 mm
N/A
Intensity
PGA
Intensity (cm/s
PGA
mm
mm
mm
mm
mm
mm
mm
mm
(km) Lengthr rate number
Repai
Repair20 20 25 25
75 length
150
200
Repai
2
Total
75100 100
150 250200 300
250 N/A300 Length
Pipe
(km)
(MMI)
50 mm
(MMI) (cm/s(cm/s) 2) mmmm
50 mmmm
N/A
Intensity
PGA
mm mm
mm
mm
mm
mm
mm
9.04mm Length
8
(km)
r
rate
number
mm
mm
mm
mm
mm
376.030.02
138.0410.03
92.33
167.02
33.72
24.3
23.8
15.8
0.00
0.00
Repai
RepairTotal(km)
r 8rate
Pipe
(km)
20
25
75 length
100
150
200
250
300
(MMI)
(cm/s
50 mm
N/A
Intensity
PGA2) 10.03
mm
mm
mm
mm
mm
mm
mm
mm
9.04
89
4.24
376.030.02
84
138.0492.33
167.02
33.72
24.3
23.8
15.8
0.00
0.00
(km)
r
rate
numberRepai
67.31
0.052 Repair
295.12
1.27
4.06
3.35
19.1
1.50
2010.0318.58
25 92.33 8.14
75 33.72
100 24.3
150
200
250
300
9.04
8
2
(MMI)
376.030.02
138.04167.025.53
23.8
15.8 1.55
0.00 N/A0.00Length
(cm/s
)
50 mm
mm
mm
mm
mm
mm
mm
mm
mm
4.24
9
0.00
8
(km)
r 0.052
rate
10
67.31
295.12 10.03
1.27
8.14
5.53
376.030.02 number
84
138.0492.33 167.02
24.3 3.35
23.8 19.1
15.8 1.50
0.00 9.04
22.23
0.135
3
630.960.00 18.58
10.37
0.00 33.72
1.43 4.06
0.00
1.39
7.09
0.00 1.55
1.94
4.24
9
295.12

1.27

18.58

8.14

5.53

4.06

3.35

19.1

1.50

67.31

1.55

0.00
89
10
4.24
376.030.02
138.0492.33 167.02
24.3 3.35
23.8 19.1
15.8 1.50
0.00 9.04
22.23
0.135
630.96
0.00
0.00
1.43
1.39
7.09
0.00 1.55
1.94
67.31
0.052
295.12 10.03
1.27 10.37
18.58
8.14 33.72
5.53 0.00
4.06
10
22.23
630.960.00 number
10.37
0.00
1.43based
0.00on 1.39
7.09 and
0.00Trifunac
1.94 0.00
4.24
9
Table
3.7
Intensity
andofrepairs
Isoyama
and
Brady
10
67.31
0.052
295.12
1.27
8.14
5.53
22.23
0.135
630.960.00 18.58
10.37
0.00
1.43 4.06
0.00 3.35
1.39 19.1
7.09 1.50
0.00 1.55
1.94 0.00

8140

138.04138.04

10.03

92.33

10.03

167.02

92.33

33.72

167.02

24.3

33.72

23.8

24.3

15.8

23.8

0.00

15.8

0.00

0.00

9.04

0.00

376.03
9.04

151
0.004
376.03
151
151

8
4

83
4
0.135
4
3

3

Repairnumber

0.063

24

24
45
28
0.419
28
45

28

2.041

45

45

Table 3.8 Intensity and number of repairs
based(km)on Isoyama and Gutenberg-Richter
Total
Pipe length
Intensity 3.8
PGA
Table
Intensity
andnumberof
repairs
basedon
IsoyamaandGutenberg-Richter
LengthTable
Intensity20and numberof repairs
basedon Isoyama
Gutenberg-Richter
Total Repai Repair
Pipe
(km)
25
75 length
100
150
200
250and300(MMI) 3.8(cm/s
50 mm
N/A
Intensity
PGA2) mm
mm
mm
mm
mm
mm
mm
mm
(km) Repair rate number
LengthRepair
20
25
75
100
150
200
250
300
2
Total
Pipe length (km)
(MMI)
(cm/s
50 mm
N/A
Intensity
PGA) 10.03
mm
mm
mm
mm
mm
mm
mm
mm
9.04 Length
8
(km)
r
rate
number
376.030.004
1138.0492.33
167.02
33.72
24.3
23.8
15.8
0.00
0.00
Repai
Total
Total Repair
Pipelength(km)
20
25
75 Pipe
100 length
150
200
250
300
(km)
2
(MMI)
(cm/s
)
50 mm
N/A
Intensity
PGA
Intensity
PGA
mm
mm
mm
mm
mm
mm
mm
mm
9.04 Length
8376.030.004
1138.0410.03
92.33
167.02
33.72
24.3
23.8
15.8
0.00
0.00
(km) Lengthr rate number
Repai
Repair20 20 25 25
75
150
200
Repai
2 2
(MMI)
75100 100
150 250200 300
250 N/A300) ) mm
50 mm(MMI) (cm/s
(cm/s
50
mm
N/A
151
mm
mm
mm
mm
mm
mm
mm
8
rate number
mm 92.33mm167.02 33.72 mm
mm 0.00mm 0.00mm 9.04mm (km)376.03 r(km)0.004
138.04 10.03
24.3 mm
23.8 15.8
r 1rate8

Repairnumber0.052

relation
Table
Intensityand10.37
numberbased
Isoyamaand Brady
0.00
10 3.7630.96
22.23
0.135
3
0.00
0.00of repairs
1.43 0.00
1.39on7.09
0.00 and1.94 Trifunac
Table3.7
3.7Intensity
Intensity
andnumberof repairs
on Isoyama
and Trifunac
and Brady
relationTable
andnumberof repairs
basedbasedon Isoyama
and Trifunac
and Brady
relation
relation
Total
Table
3.7 Intensity and number of repairs
basedon Isoyama and Trifunac
and Brady
Pipe length(km)
Intensity
PGA
Lengthrelation
Total Repai Repair
Pipe
(km)
20
25
75 length
100
150
200
250
300
(MMI)
(cm/s
50 mm
N/A
Intensity
PGA2) mm
mm
mm
mm
mm
mm
mm
mm
(km) Repai
rTotalrate number
LengthRepair
20
25
75
100
150
200
250
300
2
Total
PipePipe
lengthlength(km) (km)
(MMI)
(cm/s
)
50 mm
N/A
Intensity
PGA
mm
mm
mm
mm
mm
mm
mm
mm
Intensity
PGA
9.04 Length
(km)
r
rate
number8376.030.063
24259.4210.03
92.33
167.02
33.72
24.3
23.8
15.8
0.00
0.00
Repai
Pipe
(km)
20 20 25 25
75 length
150
200
Length Repair
Repai
275100 100
150 250200 300
250 N/A300 Total(MMI)(MMI) (cm/s
50 mm
Intensity
PGA(cm/s) 2) 10.03
50 mmmm
N/A
mm
mm
mm
mm
mm
mm
mm
9.04
89
4.24
376.030.063
259.4292.33
167.02
33.72
24.3
23.8
15.8
0.00
0.00
(km)
r(km)
rate numbermm
mm 1.50mm 1.55mm
mm Length
Repair
67.31 Repai
0.419
28
517.61
1.27
5.53
4.06
3.35
19.1
20 mm 18.58
25 mm 8.14
75 mm
100
150
200
250
300
r24
rate
(MMI)
(cm/s2)
50 mm
N/A
mm
mm
mm
mm
mm
mm
mm
mm
4.24
0.00
(km)
r
rate
number
898
10
67.31
0.419
28
517.61 10.03
1.27
8.14
5.53
376.030.063
24259.4292.33 167.02
24.3 3.35
23.8 19.1
15.8 1.50
0.00 9.04
22.23
2.041
45
1032.70.00 18.58
10.37
0.00 33.72
1.43 4.06
0.00
1.39
7.09
0.00 1.55
1.94
9.04
376.03259.42 10.03 92.33 167.02 33.72 24.3 23.8 15.8 0.00 0.00
0.00
8
10
4.24
9
376.030.063
259.42
10.03
92.33 167.02
24.3 3.35
23.8 19.1
15.8 1.50
0.00 9.04
22.23
2.041
1032.7
0.00
0.00
1.43
1.39
7.09
0.00 1.55
1.94
67.31
0.419
517.61
1.27 10.37
18.58
8.14 33.72
5.53 0.00
4.06
9
67.31
517.61
1.27 18.58
8.14
5.53 4.06 3.35 19.1 1.50 1.55 4.24
4.24
9
Table
3.8
Intensity
andnumberof
repairs
basedon
IsoyamaandGutenberg-Richter
10
67.31
0.419
517.61
1.27
8.14
5.53
22.23
2.041
1032.70.00 18.58
10.37
0.00
1.43 4.06
0.00 3.35
1.39 19.1
7.09 1.50
0.00 1.55
1.94 0.00
10
22.23
1032.7 and0.00 number
10.37 of 0.00
1.43
1.39 7.09 0.00
1.94 0.00
Table
Intensity
based0.00
on Isoyama
Gutenberg-Richter
0.00
10 3.81032.7
22.23
2.041
0.00 10.37
0.00 repairs
1.43 0.00
1.39
7.09 0.00and
1.94

6

1

Repairnumber0.004

151
BNUS Annual Report-2013

1

ICUS Report 74
99

295.12
4.06 4.06
3.35
295.12 1.271.2718.58
18.58 8.14 8.145.53 5.53
630.960.00 10.37
0.00
1.43 0.00 1.39
630.960.00 10.37
0.00
1.43 0.00

10
10

4.24
19.1
3.35 1.50
19.1 1.55
1.50 1.55
7.09 0.00 1.94 0.00

1.39

7.09

0.00

1.94

67.31
4.24
22.23
0.00

0.094
67.31
0.673
22.23

6
0.094

15
0.673

The result presented in Table 3.5 shows pipeline length, repair rate und number of repairs
The result
presented
in Table
3.5 showslength,und number
basedon O’Rourke
damageprediction
relation pipeline
for different
peak repair
groundrate
acceleration(PGA)of repairs
based onO’Rourke
prediction
relationfor different
groundin acceleration
derivedfrom
Trifunacdamage
and Brady
PGA-MMI
relation.
The resultpeak
presented
Table 3.6 (PGA)
derivedfrom
Trifunacand
Brady
PGA-MMI
relation.
The
resultpresented
in Table 3.6
shows pipeline length, repair rate and number of repairs based on O‘Rourke damageshows pipeline
length,repairandacceleration
number of
repairs
basedO‘Rourke
prediction
relation fordifferent
peakrate
ground(PGA)
derivedfrom onGutenberg
and damage
Richter
PGA-MMIThe resultin table 3.7 shows
repairprediction
relationrelation.
for different
peakpresented
ground acceleration(PGA)pipeline
derivedlength,from Gutenberg
and
rate
and
numberof
repairs
basedon
Isoyamadamageprediction
relationfordifferent
peakRichter PGA-MMI relation. The result presented in table 3.7 shows pipeline length, repair
groundderivedTrifunac &damage
Brady PGA-MMI
rate andacceleration
number of(PGA)
repairs
basedfromon Isoyama
prediction relation.
relationThefor result
different peak
presented
in
Table
3.8
shows
pipeline
length,repairrate
andnumberof
repairs
based
ground acceleration (PGA) derived from Trifunac & Brady PGA-MMI relation.onThe result
Isoyama damage prediction relation for different peak ground acceleration (PGA) derived
presented in Table 3.8 shows pipeline length, repair rate and number of repairs based onfrom Gutenberg and Richter PGA-MMI relation.

Isoyama damage prediction relation for different peak ground acceleration (PGA) derived
from Gutenberg
andRichter
PGA-MMI
Table
3.9 Intensity
andnumberof repairsrelation.
based on O'Rourke and Trifunac and Brady
relation

Table 3.9 Intensity and number
repairs
on O'Rourke
Pipeline of
RepairRate based(RR) basedon relations:and Trifunac and Brady
Intensit
relation
Isoyama andIsoyama andO'Rourke andO'Rourke andyRepair Rate (RR)
based
Trifunac-Brady Pipeline
GutenbergTrifunac
andon relations:
Gutenberg(MMI)
Intensit
Richter(OGR) and Brady Isoyama(ITB)
Richter (IGR)(OTB) andO'Rourke
O'Rourke
andIsoyama andyTrifunac-Brady
GutenbergTrifunac and 0.004 Gutenberg8
0.044
0.020
0.063
(MMI)
(OTB)
Richter(OGR)
Brady (ITB) 0.094Richter (IGR)
9
0.105
0.052
0.419
0.044
0.250

0.1350.020

2.041 0.063

9

0.105

0.052

0.419

0.094

102.500

0.250

0.135

2.041

0.673

Pipeline
Rate,
Pipeline Repair
Rate, Repair
RR (perkm)RR (per km)

108

0.004

0.673

O'Rourke Trifunac & Brady(OTB)
O'Rourke Gutenberg & Richter

2.000
2.500

O'Rourke Trifunac & Brady
Isoyama (OTB)
Trifunac & Brady

1.500

O'Rourke Gutenberg & Richter2.000

Isoyama Gutenberg & Richter

Isoyama Trifunac & Brady

1.000

1.500
Isoyama Gutenberg & Richter

0.500

1.000

0.000
7

8

0.500

9

10

11

Intensity (MMI)

Figure 3.7 Comparison of pipeline repair rate for different Intensity and fragility
relation.
0.000

7

8

Intensity (MMI)

9

10

11

152

Figure 3.7 Comparison of pipeline repair rate for different Intensity and fragility
relation.
152
141

6
15

May 2014

From the table 3.9 and Figure 3.7 it is seen that repair rates of O’Rourke and Trifunac andBrady realtion are two times higher than those of O’Rourke and Gutenberg and Richter
relation for all intensities. On the other hand Isoyama and Trifucan and Braddy relationshows 15 times higher repair rate than the repair rate obtained from Isoyama and Gutenberg
and Richter relation for intensity 8 while it is 5 times and 3 times higher for intensity 9 and
10 respectively. On the whole it is seen from these relations that repair rates vary from 0.004
to 0.06 for intensity 8, 0.052 to 0.424 for intensity 9 and 0.134 to 2.029 for intensity 10.
However due to absence of real repair rate data in Bangladesh, it is advisable to use a rangeof repair rates instead of a single value in the event of damage analysis of buried water supply
pipelines due to earthquake.
3.5 SELECTION OF DAMAGE ANALYSIS MFTHODS BASED ON PGV
Different pipeline fragility relation give very different predictions of pipeline damage rate forthe same PGA value. The values calculated in Table 4.10 are from O’Rourke & Ayla (1993),
Endinger et al. (1995, 1998), Isoyama et al. (2000) & O’Rourke et al. (2001).
Table 3.10 Pipe line repair rate form different fragility relations for PGV values basedon Trifunac and Brady and Wald et. al. relations.
Repair Rate (RR)
Equation Intensity
O'Rourke
Endinger et
PGVIsoyama et O'Rourke et
Used
(MMI)
& Ayalaal. (1995,(cm/sec)al. (2000)
al. (2001)(1993)
1998)
13.183
0.033
0.027
7
Trifunac23.442
0.121
0.086
0.050
0.119
8
and Brady
41.687
0.442
0.267
0.222
0.287
9
(1975)
74.131
1.613
0.836
0.625
0.455
10
21.881
0.104
0.075
0.038
0.099
7
42.486
0.461
0.278
0.231
0.293
8
Wald et al(1999)
82.495
2.051
1.033
0.743
0.487
9
160.181
9.128
3.843
2.010
0.681
10
From the selected peak ground acceleration (PGV) values and fragility relations, following
four methods are used for damage analysis.
Method 1: In this method PGV and repair rate are based on Trifunac – Brady MMI-PGV
relations and Isoyama damage prediction relation.
Method 2: This method is based on Wald et al MMI-PGV relation and O’Rourke damage
prediction relation.
Method 3: This method involves Trifunac-Brad MMI-PGV relation and Isoyama damage
prediction relation.
Method 4: Where damage analysis is based on Wald et al MMI-PGV relation andO’Rourke damage prediction relation.
3.6 GAS PIPELINE DAMAGE ANALYSIS BASED ON PGVUsing the methods outlined in the preceding articles and pipeline lengths calculated from thedigitized maps which are shown in Table 3.1. Repair rates and number of repairs are worked
out and presented in Table 3.11 to 3.14 and finally a different table, table 3.15 is prepared forcomparison of these repair rates which are also presented in graph of Figure 3.8.

142

153
BNUS Annual Report-2013

ICUS Report 74

TableTable
3.11 3.11
Intensity
andnumberrepairsbased
based
O'Rourke
and Trifunac
and Brady
Intensity
andnumber ofof repairs
on onO'Rourke
and Trifunac
and Brady
relation
relation

Table 3.11 Intensity and number of repairs based on O'Rourke and Trifunac and Brady
Pipe length
relation
Total
Pipe
length(km)
(km)
Total
Intensity Intensity
PGV PGV
75of repairs
100
150 on200O'Rourke
250 300
Table 3.11
Intensity
andnumberbased
andTrifunacandRepair
Brady Repair
Length
(MMI)(cm/s)
75
100
150
200
250
300
20 mm 25 mm 50 mm
N/A
LengthRepair(MMI) Intensity(cm/s) relation
mmPipe length
mm (km)mmmm
mm mm
20 mm 25 mm 50 mm
N/A
(km)
rate
number
Total
PGV
mm
mm
mm
mm
mm
mm
(km)
rate
75
100
150
200
250
300
Table
3.11
Intensity
andnumberof
repairs
basedon
O'Rourke
andTrifunacand
Brady
Length 0.119
Repair Repair
8(MMI)(cm/s) 20
23.44
10.03
92.33
45
mm 25
mm 167.02
50 mm 33.72 24.29 23.79 15.81 0.00 0.00 9.04
N/A 376.03
mm
mm
mm
mm
mm
mm
(km)
rate
numberPipelength(km)
89.04
relation
10.03
92.33 167.02 33.72 24.29 23.79 15.81 0.00 0.00
0.119
Total 376.03
Intensity
923.44 PGV
4.24
41.69
1.27
18.58
8.14
5.53
4.06
3.35 19.09 1.50 1.55
67.31
75
100 23.79
150 15.81
200 0.00
250 0.00
300 9.04 376.03
8Length
23.44
10.03
92.33
167.02
33.72
24.29
(MMI)
(cm/s)1.2720mm18.5825mm 8.1450mm 5.53
N/A 4.24
10
0.00
41.69 74.13
4.06(km)3.35 7.09
19.09
1.50
1.55
0.00
10.37
0.00
1.43
0.00
1.39
0.00
1.94
22.23
Pipe length
mm
mm
mm
mm
mm
mm
(km)
Total
9
Intensity
PGV
41.69
1.27
18.58
8.14
5.53
4.06
3.35 19.09 1.50 1.55 4.24
67.31
75
100
150
200
250
300
10
0.00
Length
74.13
0.00
10.37
0.00
1.43
0.00
1.39
7.09
0.00
1.94
8
9.04
(MMI)
(cm/s)
23.44 2010.03
92.33
167.020.00 1.94
0.00 0.00
mm 25
mm 50
mm 33.72
N/A 376.03
10
74.13
0.00
10.37
0.00
1.43 24.29
0.00 23.79
1.39 15.81
7.09 0.00
22.23
mm
mm
mm
mm
mm mm Wald
(km)
Table
Intensityand numberof repairs
O'Rourke
941.693.12 1.27
18.58
8.14
5.53
4.06 based
3.35 on19.09
1.50 and1.55 4.24
67.31
8
9.04
23.44
10.03
92.33 167.02 33.72 24.29 23.79 15.81 0.00 0.00
376.03
10
0.00
74.13
0.00
10.37
0.00
1.43
0.00
1.39
7.09
0.00
1.94
22.23
Pipe
length
(km)
Table
3.12
Intensity
andnumberofof repairs
basedon
O'Rourke
and
Table
Intensity
andnumberrepairs
O'Rourke
and WaldTotal
94.24 Wald
41.69 3.12 1.27
18.58
8.14
5.53
4.06 based
3.35 on19.09
1.50 1.55
67.31
Intensity
PGV

9

0.287
Repair
0.119
67.31
0.455
rate
0.287
Repair
22.23
0.119
0.455
rate
0.287
0.119
0.455
0.287

Repairnumber45

19
Repair45
0.287
10number19
Repair0.455
45
10
number
19
45
10
19

19
10

20
25
50
75
100 150 200 250 300 0.00 Length Repair Repair
10(cm/s)
(MMI)
74.13
0.00
10.37
0.00 Pipe
1.43 length
0.00 (km)1.39
0.00 1.94 N/A
22.23
10
Pipe
lengthTotal 0.455
Table
3.12
numberof repairs
based
on7.09O'Rourke
and Wald (km)mmIntensity
mm andmmmm
mm (km)
mm
mm
mm mm
Total
rate number
Intensity
PGV
Intensity PGV
20 25 25 5050
75
100 150
200200250 250
300 9.04 Length Repair Repair(cm/s)
8
20 10.0375
10015015.81(MMI)
N/A 376.03 Length
Repair
92.33 167.02 33.72
24.29
23.79
0.00 0.00 300
0.293
110
Pipe
length(km)(cm/s) 42.49
Table 3.12
Intensity
andmm
numberof repairs
basedon
O'Rourke
and Wald(MMI) Intensity
Total
mm
mm
mm
mm
mm
mm
mm
mm
N/A
(km)
rate number
PGV
9
4.24
mm
mm
mm
mm
mm
mm
mm
mm
mm
82.49
1.27
18.58
8.14
5.53
4.06
3.35
19.09
1.50
1.55
67.31
0.487
33
(km)
rate
20
25
50 33.72
75 24.29
100 23.79
150 15.81
200 0.00
250 0.00
300 9.04 Length
8
42.49
10.03
92.33
167.02376.03 Repair
0.293 Repair
110(cm/s)
(MMI)
N/A
Pipe
length
(km)
10
0.00
Total
160.18
0.00
10.37
0.00
1.43
0.00
1.39
7.09
0.00
1.94
22.23
0.681
15
mm
mm
mm
mm
mm
mm
mm
mm
mm
8
9.04
(km)
rate
numberIntensity
42.49
10.03 1.2792.3318.58167.02
33.72
24.29
23.79 19.09
15.811.50 0.00
0.00
376.03
0.293
PGV
9
4.24
82.49
8.14
5.53
4.06
3.35
1.55
67.31
0.487
33
20
25
50
75
100 150 200 250 300 9.04 Length Repair Repair(cm/s)
8
(MMI)
N/A
42.49
10.03
92.33
167.02
33.72
24.29
23.79
15.81
0.00
0.00
376.03
0.293
110
9
4.24
10
0.00
82.49 Table
18.58
4.06 based
3.35onmm
19.090.00
1.55
67.31
0.487
160.181.27
0.00
10.37
0.00 5.53
1.43
0.00
1.39
7.09
1.94
22.23
0.681 number
15
mm
mm
mm
mm
mm
mm1.50mmTrifunac
3.13mmIntensity
and8.14
numberof repairs
Isoyama
and
and
Brady
(km)
rate
9
82.49
1.27
18.58
8.14
5.53
4.06
3.35 19.09 1.50 1.55 4.24 0.00
67.31
0.487
33
10
relation
89.04
160.18
0.00
10.37
0.00
1.43
0.00
1.39
7.09
0.00
1.94
22.23
0.681
42.49
10.03
92.33 167.02 33.72 24.29 23.79 15.81 0.00 0.00
376.03
0.293
110
10
0.00
Table
Intensityof repairs
Isoyamaand160.18 3.13 0.00
10.37and number
0.00
1.43
0.00 based
1.39 on
7.09
0.00 and1.94 Trifunac
22.23Brady
0.681
15
9
82.49
1.27
18.58
8.14 Pipe
5.53 length
4.06 (km)3.35 19.09 1.50 1.55 4.24
67.31
0.487
33
relation
Total
Intensity
PGV
10
0.00 Trifunac
Table
3.13
andandnumberofofrepairs
basedon
Isoyamaand160.18 Intensity
10.37
0.00 75
1.43
0.00 150
1.39 200
7.09
0.00 300
1.94 and
22.23Brady
0.681Brady
15
Table
3.13
Intensity
repairs
basedon
IsoyamaandTrifunacand200.0025
50number
100
250
RepairRepair(cm/s)(MMI)
N/A Length
Pipelength(km)
Total
relation
relationmm
mm mm mm mm mm mm mm(km)
rate number
Intensity PGV mm
Table 3.1320 Intensity
numberbased onand Trifunac
and Brady
25 and50
75of repairs
100 150
200Isoyama
250 300
LengthRepair Repair(cm/s)
8
9.04
(MMI)
N/A
23.44
10.03
92.33 167.02 33.72
24.29
23.79
15.81
0.00
0.00
376.030.050
19Pipelength
lengthrelation mm
Total Total
mm
mm Pipemm
mm (km)mm mm mm mm
(km)
(km)
rate number
Intensity
PGV
9
4.24
41.69
1.27
18.58
8.14
5.53
4.06
3.35
67.31
0.222
15
Intensity PGV
2025
50 33.72
75 24.29
100 23.79
150 19.09
200 1.50
250 1.55
300 9.04 Length
RepairRepair
8
23.44
92.33
167.020.00
0.00
376.03 Length
0.050 Repair
19(cm/s)(MMI)
20 10.03
25 10.37
50
75
100
150 15.81
2000.00
250
300
N/A Total
Pipe length
(km)
10
0.00
0.00
0.00
1.43
0.00
1.39
7.09
1.94
22.23
0.625
14
(cm/s) 74.13(MMI) Intensity
mm
mm
mm
mm
mm
mm
mm
mm
mm
N/A
(km)
rate
number
PGV
9
4.24
41.69
1.27mm 18.58
8.14 mm
5.53
4.06 150
3.35
1.55
67.31 (km)0.222 Repair
15mm 20mm 19.09mm1.5025 mm50
75 mm
100
200
250mm
300 mmrate
Repair(cm/s)
8
9.04 Length
(MMI)
N/A
23.44
10.03
92.33 167.02
24.29
23.79
0.00 1.94
0.00 0.00
376.03
0.050
19
10
74.13
0.00
10.37
0.00 33.72
1.43
0.00 based
1.39 on15.81
7.09
0.00
22.23
0.625
14
mm
mm
mm
mm
mm
mm
mm
mm
mm
Table
3.14
Intensity
andnumberof
repairs
Isoyama
and
Wald
(km)
rate
number8
23.44
10.03 1.2792.3318.58167.02
23.79
15.811.500.00
0.050
94.24 9.04
41.69
8.14 33.72
5.53 24.29
4.06
3.35 19.09
1.55 0.00
67.31 376.03
0.222
15
9

10

8
23.44
10.03
92.33 167.02 33.72 24.29 23.79 15.81 0.00 0.00 9.04 4.24
376.03
0.050
19
Pipe
length100.00 Total
41.69 Table
18.5810.37and
8.14
4.06
3.35on7.09
19.090.001.50
1.55
0.222
3.14 0.00
Intensity
numberof repairs
basedIsoyamaand74.131.27
0.00 5.53
1.43
0.00 (km)1.39
1.94Wald
22.23 67.31
0.625
14Intensity
9
PGV
41.69
1.27
18.58
8.14
5.53
4.06
3.35 19.09 1.50 1.55 4.24
67.31
0.222
15
25
50
75
100
1501.39200 7.09
250 0.00
300 1.94 Length
RepairRepair
0.00
74.13 (cm/s)
0.00200.0010.37
0.00
1.43
0.00
22.23
0.625
(MMI)
N/A
Pipe
length
(km)
10
0.00
74.13
10.37
0.00
1.43
0.00
1.39
7.09
0.00
1.94
22.23
0.625
14
Total
Table 3.14
numberbased mmon Isoyama
and Wald (km)mmIntensity
mm andmm
mmof repairs
mm mm
mm mm
rate number

Intensity PGV
20
25
50
75
100 150 200 250 300 9.04 Length Repair(cm/s)8(MMI)
N/A 376.03
42.49
10.03
92.33
167.02 33.72
24.29
23.79
15.81
0.00 0.00 and
0.231
Pipe
length
(km)
Table
3.14
Intensity
andnumberof
repairs
basedon
IsoyamaTable
3.14
Intensity
andnumberof
repairs
basedon
Isoyama
Total
mm
mm
mm
mm
mm
mm
mm
mm andmm WaldWald
(km)
rate
Intensity
PGV
9
4.24
82.49
1.27
18.58
8.14
5.53
4.06
3.35
19.09
1.50
1.55
67.31
0.743
20
25
50
75
100
150
200
250
300
LengthRepair
8
9.04
42.49
10.03
92.33
167.02
33.72
24.29
23.79
15.81
0.00
0.00
376.030.231(cm/s)(MMI)
N/A Total
Pipelength
length10Pipe(km)160.18
0.00
10.37
0.00
1.43
0.00
1.39
22.23 Total
2.010
mm
mm
mm
mm
mm (km)mm 7.09mm 0.00mm 1.94mm 0.00(km)
rate
Intensity
PGV
9
4.24
1.27
18.58
8.14
5.53
4.06 150
3.35 19.09
1.50 1.55
67.31 Repair
0.743
Intensity PGV 82.49
20
25
50
75
100
300 9.04 Length(cm/s)
8(MMI)
20 10.03
25 10.37
75
100
150 200
200250N/A 376.03
42.49
92.33 50167.020.00250
0.00 300
0.231
Length0.00
0.00 33.72
1.43 24.29
0.00 23.79
1.39 15.81
7.09 0.00
22.23
2.010
(cm/s) 160.18(MMI) 10
mm
mm
mm
mm
mm
mm
mm
mm 1.94mm 0.00 N/A
(km)
rate
9
4.24
mm
mm
mm
mm
82.49
1.27
18.58mm8.14 mm
5.53 mm
4.06
3.35
19.09
1.50mm1.55 mm67.31 (km)
0.743
8
9.04
Table
Intensityand numberof repairsvarious
PGV0.00
based
relation.
42.493.15 10.03
92.33
167.02 33.72
24.29based
23.79on15.81
0.00
376.03
0.231
10
0.00
160.18
0.00
10.37
0.00
1.43
0.00
1.39
7.09
0.00
1.94
22.23
2.010
8
42.49
10.03 1.27
92.3318.58
167.0233.72
24.29
15.811.500.00
9
4.24 9.04
Pipeline
RepairRate(RR)
relations:
82.49
8.14
5.53 based
4.06 on23.79
3.35
19.09
1.55 0.00
67.31 376.03
0.743
Table
3.15
Intensity
andnumberof
repairs
basedonvarious
PGV
based
relation.
9
4.24
10
0.00
82.49 160.181.27 0.00
18.58
8.14
5.53
4.06
3.35
19.09
1.50
1.55
67.31
10.37
0.00
1.43
0.00
1.39
7.09
0.00
1.94
22.23
2.010
Isoyama et O'Rourke et Isoyama O'Rourke
Intensity
Pipeline Repair Rate (RR) based on relations:al.
(2000) and0.00
al.number(2001)&
et0.00al. based
et on
al. various
10
0.00
3.15
Intensityof
160.18 Table
0.00
10.37
1.43
1.39
7.09 PGV
0.00 based
1.94 relation.
22.23
(MMI)
Isoyamaet Trifunac
O'Rourke
et repairs
IsoyamaO'Rourke&
Trifunac(2000)(2001)&
Intensity
Pipeline
Repair
Rate
(RR)
based
on
relations:al. (2000)andBradyal.
(2001)of&repairs
al. basedeton
al.various PGV based relation.
Table
3.15 Brady
Intensity
number&etWald
Wald(MMI)
Isoyamaet Trifunac
O'Rourke et (2000)
Isoyama (2001)
O'Rourke&
Trifunac&
Intensity
Pipeline Repair0.000
Rate (RR) basedon relations:
0.000
0.038
0.099
7
al.
(2000)
al.
(2001)
&
et
al.
et
al.
Brady
Brady
&
Wald
Wald
Table 3.15
Intensity
andetnumberof repairs
based
on various PGV based relation.
(MMI)
IsoyamaO'Rourke
IsoyamaO'Rourke
0.050
0.119 et (2000)
0.231
0.293 &
8&
Trifunac
Trifunac(2001)
Intensity
0.000
0.000
0.038
0.099
7 Pipeline
Repair
Rate
(RR)
based
on
relations:al.0.222(2000)
al. 0.287(2001) & &etal.
et0.487
al.
0.743
9
Brady
Brady
Wald Wald
(MMI)
0.050
0.119
0.231
0.293&
8&
Trifunac
Trifunac(2000)(2001)
0.625
0.455
2.010
0.681
Isoyamaet O'Rourke
IsoyamaO'Rourke
0.000
0.000et0.038
0.099
Intensity1097
0.222
0.287
0.487
Brady
Brady
&0.743
Wald Waldal.
(2000)
al.
(2001)
&
et
al.
et
al.
0.050
0.119
0.231
0.293
8
0.625
0.455
2.010
0.681
(MMI) 10
0.000
0.000
0.038
0.099
7 & Trifunac(2000)(2001)
0.222 Trifunac
0.287
0.743
0.487 &
9
0.050
0.119
0.231
0.293
8
&2.010Wald Wald
0.681
10Brady 0.625 Brady0.455
0.222
0.287
0.743
0.487
9
0.000
0.038
0.099
7
0.625
0.455
2.010
0.681
10 0.000

8
9
10

0.050
0.222
0.625

0.119
0.287
0.455

0.231
0.743
2.010

Repair87
number50
Repair87
45
number50
Repair87
Repair45
number
50
rate
87

45
0.231
50

Repairnumber110
33
15

Repairnumber19
15
14

Repairnumber
87

0.743
45

50

2.010

45

0.293
0.487
0.681

143

Pipeline Repair Rate, RR (per km)

May 2014

2.500
2.000

Isoyama et al. (2000) & Trifunac
Brady

1.500

O'Rourke et al. (2001) &Trifunac Brady

1.000

Isoyama et al. (2000) & Wald
0.500
O'Rourke et al. (2001) & Wald
0.000
7

8

9

10

11

Intensity (MMI)

Figure 3.8 Comparison of pipeline repair rate for different Intensity and PGV based
fragility relation.
3.7 Comparison of Repair rate
From above analysis a comparison of pipeline repair rate based on PGV and PGA has done
and presented in figure 3.9 figure 3.10 & figure 3.11. Although pipe line repair rate of various
fragility relations are available but fragility relations based on PGA is more acceptable incontext of Bangladesh since all data available are based on PGA. But PGV based fragility
relation is more reliable than PGA as discussed in chapter 2.
50
45
40
35
30
25

Intensity VIII

20

Intensity IX

15Intensity X

10
50O'Rourke andTrifunac and Brady
relation (PGA)

O'Rourke andIsoyama and Trifunac
Isoyama andGutenberg-Richter and Brady relation Gutenberg-Richter
(PGA)
(PGA)
(PGA)

Figure 3.9 Comparison of pipeline repair rate for different Intensity and PGA based
fragility relation.

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120
100
80
60

Intensity VIII
Intensity IX

40Intensity X

20
0
O'Rourke andTrifunac and Brady
relation (PGV)

O'Rourke and Wald
(PGV)Isoyama andTrifunac and Brady
relation (PGV)

Isoyama and Wald
(PGV)

Figure 3.10 Comparison of pipeline repair rate for different Intensity and PGV based
fragility relation.
120
100

No. of Repair

80
60
40
20
0

O'Rourke
andO'Rourke
TrifunacandandGutenberBrady
g-Richter
relation
(PGA)
(PGA)

IsoyamaO'Rourke
andIsoyamaandTrifunacandTrifunac O'Rourke
andGutenberandand Wald
Brady
g-Richter
Brady
(PGV)
relation(PGA)
relation
(PGA)
(PGV)

IsoyamaandTrifunac Isoyama
andand Wald
Brady
(PGV)
relation(PGV)

Intensity VIII

17

8

24

1

45

110

19

87

Intensity IX

7

4

28

6

19

33

15

50

Intensity X

6

3

45

15

10

15

14

45

Figure 3.11 Comparison of pipeline repair rate both for PGV & PGA based fragility
relation for different Intensity at Dhaka City.

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3.8 ESTIMATION OF THE EXPECTED MONETARY LOSSES
In this study only the direct loss is taken into account. The direct loss for the gas pipeline
consists of two major parts: (1) The vented gas cost and (2) The repair cost.
3.8.1 THE VENTED GAS COST
Usually repairing the damaged gas pipeline includes welding procedure and grinding forpolishing the surface. As the natural gas is explosive, it is necessary to completely vent thepipeline section gas before welding procedure. The isolation and then ventilation tasks areapplicable by using Line Break Valve (LBV) among the pipeline in each 20 km. This type ofvalve has the ability to sense pipeline breaks at the upstream or downstream and shuts off theline immediately in the associated section. In the case of line break or line leak, the closest
two LBVs to the damaged joint isolate the pipe section and only the containing gas of thissection is vented for the purpose of repairing. Therefore this amount of vented gas is thewasted gas. By assuming the average working pressure of pipeline equal to 55 bars andnatural gas as an ideal gas, the wasted gas volume can be calculated as written in Eqn. 4.8
D 2
V * L * Pave
4
3.8
Where V is the volume of gas with standard pressure (1 bar), D is pipe diameter, L is lengthof pipe and Pave is average working pressure. Usually pipe having diameter 20 mm to 100 mm
is subjected to low pressure as 15 bar (200 psi) and 150 to 200 mm is subjected to relatively
high pressure like 55 bars. Considering this the amount of vented gas has been calculated andpresented in table 4.10
Table 3.10 Vented gas cost within pipe
Length in
Length inVolume of gas
Pipe dia KM intensity Length in KM KM
usinig equation 4.6(mm)
8intensity 9
intensity 10 (in cum)
20
10.03
1.27
2.34
25
92.33
18.58
10.37
39.23
50
167.028.14
226.60
75
33.72
5.53
1.43
118.44
100
24.29
4.06
146.70
150
23.79
3.35
1.39
1,217.61
200
15.81
19.09
7.09
3,187.39
250
1.50
177.30
300
1.55
1.94
596.00Total 5,711.59
Cost considering Tk 50/cum is Tk. 2.86 million
3.8.2 THE PIPELINE REPAIR COST
Generally when a pipe is damaged due to ground failure, the type of damage is likely to be abreak while when a pipe is damaged due to seismic wave propagation, the type of damage islikely to be leak. In the loss of methodology, it is assumed that damage due to seismic waves
will consist of 80% leaks and 20% breaks, while damage due to ground failure will consist of

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20% leaks and 80% breaks. As damage due to ground failure is beyond the scope of this work
it is assumed that 80% leak and 20% breaks will occur.
Pipeline repair cost is approximately 5 to 7 times more than the construction procedure as aconsequence of the mobilization costs, machinery transfer for each repair and lack of time forpressurizing the line after repair to make the line alive. Usually the cost of construction of
300 mm dia pipe is Tk. 12 million/km. This has been found from information of “Newswatch of National Geographic” and by article published in “Daily Star” analyzing the
proposed India Myanmar natural gas pipeline project through Bangladesh. From above rate
analysis it is assumed that repair cost for 20mm to 150mm diameter pipe is Tk. 45 million/km
and for 200mm to 300 mm diameter pipe Tk.60 million/km. Based on this data pipe line
repair cost for both case of PGA and PGV based analysis has been furnished in table 3.11 &3.12Table 3.11 Pipe line repair cost from PGA base fragility relations.
Pipe dia
(mm)

No of
repairRepair cost / Total repair costpoint
(in million of Tk.)

20

2

45,000.00

0.09

25

36

45,000.00

1.62

50

15

45,000.00

0.68

75

9

45,000.00

0.41

100

4

45,000.00

0.18

150

7

45,000.00

0.32

200

24

60,000.00

1.44

250

1

60,000.00

0.06

300

5

60,000.00

0.30

Total

5.09

Total loss is Tk.2.86 million (vented gas) + Tk. 5.09 million (Lline repair) = Tk. 8.00 million
for PGA based relation.

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Table 3.12 Pipe line repair cost from PGV base fragility relations.
Pipe dia
(mm)
20
25
50
75
100
150
200
250
300

No of
repair
4
57
46
16
10
12
34
2
6

Repair cost / Total repair costpoint
(in million of Tk.)
45,000.00
0.18
45,000.00
2.57
45,000.00
2.07
45,000.00
0.72
45,000.00
0.45
45,000.00
0.54
60,000.00
2.04
60,000.00
0.12
60,000.00
0.36
Total
9.05

Total loss is Tk.2.86 million (vented gas) + Tk. 9.05 million (Lline repair) = Tk. 12.00
million for PGV based relation.
3.9 SUMMARY
The pipeline network is very important for daily life in Dhaka city like elsewhere. It must be
kept well maintained, especially to the city. It offers basic need, but it can be greatly damagedby earthquake. In Order to predict the damage of gas pipeline network after earthquake, thefragility curves are very useful means to do so. Different available pipeline fragility relations
such as Katayama (1975), O‘Rourke (1982), Isoyama and Katayama (1998) and Isoyama(2000) are compared. Finally using two relations namely O‘Rourke (1982) and Isoyama(2000) damage rate of pipe lines is determined where PGA/PGV values obtained from
Trifunac and Brady, Guutenberg and Richter & Wald MMI-PGA/PGV relations are used.
Pipeline damage rate is expressed in number of repairs per unit length of pipe. No of repairs
for both PGA and PGV based fragility relations has been furnished and compared. It has beenfound that PGV based fragility relation results higher number of repair than PGA.
Any hazard especially earthquake hazard invokes financial involvement. So monetary loss
estimation directly related to pipeline damage due to earthquake is a first step to mitigate therisk. This study also presented a picture of monetary loss due to earthquake damage of gas
pipeline network for different intensity. Total cost estimated for damage of pipeline is Tk-8.0
million. Though this figure of amount apparently is not large, secondary or indirect loss due
to damage of buried gas supply pipelines may be greater, such as interrupted gas supply tobusiness and industrial sectors cause reduction of output. The fire hazard following gas
leakage may be tremendous in many cases.

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PART-XIII
STRUCTURAL ASSESSMENT OF LIBRARY
BUILDING, BUET, DHAKABANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA
Prepared By: Shoeb Ahmed
Mehedi Ahmed Ansary160

May 2014

Structural Assessment of Library Building, BUET, Dhaka
Library building of BUET, Dhaka has been assessed on request of Chief Engineer of BUET
with a view to check the recent condition of roof beams as a number of cracks have been seen.
This assessment has been carried out by Shoyeeb Ahmed and Mr. Marful Hassan. The cracks
are detected by UPV.
According to ACI 224R-90, (Table 4.1) Tolerable crack widths, reinforced concrete:Tolerable Crack Width
Exposure Condition
(mm)
(in)
Dry air or protective membrane
0.016
0.41
Humidity, moist air, soil
0.012
0.30
Decing chemicals
0.007
0.18
Seawater and sea water spray:
0.006
0.15
wetting and drying
Water Retaining Structure
0.004
0.10
***So according to this guideline our tolerable crack width is 0.30 mm

Figure: Structural design of library building (plan)

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Plan:-

Figure: Location of testing points marked at the plan

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UPV DATA:-

Beam No. 1:-

SL. Beam Location

X-Section

Interior
Joint
crack

���"� � ���� �� "
�

Location

X-Section

1

B1

Beam No. 2:SL. Beam2

B2

Shrinkage
crack

Beam No. 3:SL.

Beam Location

3

Atbottomflexuralcrack

B3

Beam No. 4:SL
.

4

Beam

B4

Location
Shrinkage
crack
Shrinkagecrack

4���"� � ���� �� "
�
X-Section
���"� � ���� �� "
�
X-Section
���" � ���� �� "
�At bottom
flexural
crack

4

Depth
(mm)

�� ���� �� ����
71.9

20

140.0

��
����

��
����

Crack
Comments
width(mm)Negligible
Crack
width

0.12

Depth
Crack
Comments(mm) width(mm)90Negligible
Crack
width

89.1

132.9

0.12

��
����

��
����

Depth
(mm)

61.6

97.5

74

��
����

��
����

Depth
(mm)

Crack
width
(mm)

124.16

193.9

79

0.12

147.7

246.4

61

0.12

76.4

109.8

101

0.12

��
����

��
����

Depth
(mm)

Crack
width
(mm)

Crack
width(mm)Comments
Negligible
Crack
width

0.12

Beam No. 5:SL
.

152

Beam

Location

X-Section

Comments

Negligible
Crack
width
Negligible
Crack
width
Negligible
Crack
width

Comments

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5

B5

At Jointcrack

���" � ���� �� "
�

112.0

169.6

86

0.12

148.9

217.8

95

0.22

546.9

368.6

91

0.12

��
����

Depth
(mm)

155.0

��
����

269.0

52

0.12

98.2

190.6

21

0.12

8

Shrinkage
Crack

139.4

196.9

106

0.12

8

Flexural
Crack

89.6

147.2

65

0.22

��
����

Depth
(mm)

Crack
width
(mm)

82.2

��
����

125.3

84

0.12

80.6

11.7

112

0.12

��
����

Depth
(mm)

Crack
width
(mm)

99.9

��
����

143.9

100

0.12

87.6

164.4

32

0.12

6

Shrinkage
crack

7

Shrinkage
crack

Beam No. 6:SL. Beam

Location

X-Section

8

Shrinkage
crack���" � ���� �� "
�

B6

Shrinkage
crack

8Beam No. 7:SL.

Beam

Location

9

B7

At Bottom

10

X-Section

At Joint

���" � ���� �� "
�

Location

X-Section

Crack
width
(mm)

Beam No. 8:SL.

11

12

Beam

B8

Flexural
Crack

Shrinkage
Crack���" � ���� �� "
�

Negligible
Crack
width
Moderate
Crack
width
Negligible
Crack
width

Comments
Negligible
Crack
width
Negligible
Crack
width
Negligible
Crack
width
Moderate
Crack
width

Comments
Negligible
Crack
width
Negligible
Crack
width

Comments
Negligible
Crack
width
Negligible
Crack
164
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May 2014

width
Beam No. 9:SL.

13

Beam

B9

Location
Flexural
Crack

Beam No. 10:SL.

14

14

154

Beam

B10

Location
Flexural
Crack
Shrinkage
Crack

X-Section
���"� � ���� �� "
�
X-Section
���"� � ���� �� "
�

��
����
67.4

��
����
97.5

Depth
(mm)

Crack
width
(mm)

94

0.12

Crack
Depth width(mm) (mm)

��
����

��
����

85.5

157.2

38

0.12

83.0

164.4

12

0.12

Comments
Negligible
Crack
width

Comments

Negligible
Crack
width
Negligible
Crack
width

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BNUS Annual Report-2013

PART-XIV
NON-DESTRUCTIVE TESTING AT FACTORYBUILDING OF V GARMENTS LIMITEDBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Pushpendu Biswas
Mehedi Ahmed Ansary

166

May 2014

1.0
Introduction
The Deputy General Manager (Admin, HR & Compliance) of Windy Group vide his letter
dated 23/12/2013 (Appendix-A) has approached the Director, BRTC, Bangladesh University ofEngineering & Technology (BUET), Dhaka for technical assistance and advice of Bureau of
Research, Testing and Consultation (BRTC), BUET for undertaking non-destructive testing on
their factory site at Ashulia.
It has been agreed that the terms of reference of the work would be limited to collection of
concrete cores to determine concrete strength and non-destructive testing of the factory at
different levels using Ferro scanning to detect rebars. This report is the outcome of their findings.
2.0

Determination of Concrete Strength by Core Test

Concrete cores have been collected from six locations of the factory building and concrete
strength of core has been measured at the BUET Concrete laboratory. The concrete strength ofcore collected from those locations varies between 2360 and 5120 psi for Brick Aggregates.
Figure 1 shows core cutting locations. The results and location has been included in Appendix-B.

3.0
Rebar Detection for Buildings Using Ferroscanner
Altogether ten locations (columns and roof slabs) have been scanned with ferroscan machine

to check the number and diameter of the steel used in the factory building. Figure 2 shows the
position of scanned beams, columns and roof slabs. Figures 3 to 28 show all the results ofscanning. At all locations, image scan and line scan have been carried out.

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Figure 1. Core cutting locations in the factory building

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Figure 2. Scanning Plan for the factory building

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COLUMNS
Figures 3 and 4 are showing the Image scan result of column GFS-1 (long side and short side
respectively) at a height of 4’-2’’ from the ground. Figure 5 is the cross section of thatcolumn.

Figure 3 Image scan result of columnGFS1 (long side)

Figure 4 Image scan result of column GFS1 (Short side)

Figure 5 Cross section of Column GFS1

170159

May 2014

Figures 6 and 7 are showing the Image scan result of column GFS2 (long side and short side
respectively) at a height of 1’-10’’ from the ground. Figure 8 is the cross section of thatcolumn.

Figure 6 Image scan result of columnGFS2 (long side)

Figure 7 Image scan result of columnGFS2 (Shortside)

Figure 8 Cross section of Column GFS2

Figures 9 and 10 are showing the Image scan result of column GFS3 (long side and short side
respectively) at a height of 3’-0’’ from the ground. Figure 11 is the cross section of thatcolumn.

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Figure 9 Image scan result of column GFS3 (longside)

Figure 10 Image scan result of column GFS3 (Shortside)

Figure 11 Cross section of Column GFS3

172161

May 2014

Figures 12 and 13 are showing the Image scan result of column GFS4 (long side and shortside respectively) at a height of 3’-0’’ from the ground. Figure 14 is the cross section of thatcolumn.

Figure 12 Image scan result of column GFS4 (longside)

Figure 13 Image scan result of column GFS4 (Shortside)

Figure 14 Cross section of Column GFS4162

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Figures 15 and 16 are showing the Image scan result of column 2FS5 (long side and shortside respectively) at a height of 3’-0’’ from the ground. Figure 17 is the cross section of thatcolumn.

Figure 15 Image scan result of column 2FS5 (longside)

Figure 16 Image scan result of column 2FS5 (Shortside)

Figure 17 Cross section of Column 2FS5

Figures 18 and 19 are showing the Image scan result of column 2FS6 (long side and shortside respectively) at a height of 3’ and 6’ respectively from the ground. Figure 20 is the crosssection of that column.

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May 2014

Figure 18 Image scan result of column 2FS6 (longside)

Figure 19 Image scan result of column 2FS6 (Shortside)

Figure 20 Cross section of Column 2FS6

Figures 21 and 22 are showing the Image scan result of column 2FS7 (long side and shortside respectively) at a height of 3’ and 6’ respectively from the ground. Figure 23 is the crosssection of that column.

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Figure 21 Image scan result of column 2FS7 (longside)

Figure 22 Image scan result of column 2FS7 (Shortside)

Figure 23 Cross section of Column 2FS7

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Figures 24 and 25 are showing the Image scan result of column 2FS8 (long side and shortside respectively) at a height of 3’ and 6’ respectively from the ground. Figure 26 is the crosssection of that column.

Figure 24 Image scan result of column 2FS8 (longside)

Figure 25 Image scan result of column 2FS8 (Shortside)

Figure 26 Cross section of Column 2FS8

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SLABS
Figures 27 and 28 are showing the Image scan result of Slab at locations 1 (2FS9) and 2(2FS10). The bars in both directions are 10 mm diameter at both slab locations.

Figure 27 is showing the Image scan result of slab 2FS9

Figure 28 Image scan result of slab 2FS10

178167

PART-XV
MULTIHAZARD VULNERABILITYASSESSMENT OF WARD 29 IN DHAKA CITYBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Naima Rahman
Mehedi Ahmed Ansary

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1.INTRODUCTION
Dhaka City is at risk of earthquake and has been experiencing many fire accidents at present
and in most cases lack of proper precautionary measures along with the institutional
inefficiency, insufficient equipment support and lack of public awareness are making thesituation worse. In this study, ward 29, an old part of Dhaka city has been selected forvulnerability assessment of both earthquake and fire. The earthquake vulnerability
assessment of buildings has been conducted by two different visual screening methods, i.e.
FEMA-RVS and Turkish Simple Survey (Level-I) and fire vulnerability has been conductedby Community Vulnerability Assessment Tool (CVAT). From the opinion of experts weightof factors of vulnerability has been determined by Analytical Hierarchal Process (AHP).
Finally vulnerability scores for earthquake and fire have been calculated using Statistical
Package for Social Survey (SPSS). From the vulnerability analysis, it has found that about
28.6% buildings are highly vulnerable to earthquake according to RVS (FEMA) and 35.3%
are highly vulnerable to earthquake according to RVS (Turkish level I). 78% building arevulnerable to fire.
2.BACKGROUND
According to the World Risk Report prepared by the Geneva-based World Economic Forum(WEF) Bangladesh is the fifth most natural disaster prone country in the world due to lack ofadequate mangrove forests and absence of coastal embankment. According to a study
conducted by Comprehensive Disaster Management Programme (CDMP) under Ministry ofFood and Disaster Management, some 78,323 buildings will be destroyed completely if a 6magnitude earthquake shakes Dhaka originating from its beneath, causing havoc throughout
the densely populated capital city. In case of a 7.5-magnitude earthquake originating from
Madhupur Fault, some 72,316 buildings in the city will be damaged totally while 53,166
partially. If an 8.5-magnitude of tremor from the plate boundary of Fault-2 hits the region,some 238,164 buildings will be destroyed completely across the country. CDMP conducted
the study from February 2008 to August 2009. There will be an economic loss of about US$ 1,112 million for only structural damage in case of a 7.5-magnitude earthquake from the
Madhupur Fault, it estimates. Economic loss due to damage of structures will be US $ 650
million and US $ 1,075 million respectively in case of an 8-magnitude earthquake from theplate boundary-2 and in case of a 6-magnitude earthquake from under Dhaka city. Some 30

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million tonnes of debris, equal to 2,880,000 truckloads (25 tonnes for per truck), will be
generated if a 6-magnitude earthquake jolts the city from beneath of it. A 7.5-magnitude
earthquake from the Madhupur Fault will generate a total of 30 million tonnes of debris,killing some 131,029 people instantly and injuring 32,948 others. According to the study, atleast 10 major hospitals, 90 schools in the capital will be destroyed completely and another241 hospitals and clinics, 30 police stations and four fire stations partially in case of a 7.5
magnitude quake. Bangladesh is situated at a high risk zone for earthquake and an
unprecedented human disaster may occur in the city anytime for even a moderate to heavy
tremor. A powerful earthquake needs at least 100-150 years to be originated for a particularregion and in that sense it is overdue for Bangladesh and parts of Assam, as 112 years havepassed by since a heavy tremor from Dawki Fault hit the region. Bangladesh is highly
vulnerable to a powerful earthquake. There is need for demolishing old and risky buildings ofthe city as a first step towards minimizing casualties in such natural disasters. As a number ofmoderate to heavy earthquakes are overdue for some parts of the country, including thecapital, it is important to get ready for the possible disasters by raising safety awareness ofpeople. If a quake of lower magnitude lasts for a minute it may destroy 80-90 percent of theurban concrete structures. Gas leakage management, power supply control, firefighting,alternative power generation, wireless communication system, heavy equipments forremoving debris and emergency clinical facilities are the top priority areas for attention.
According to a research conducted by Professor Roger Bilham of Colorado State University
in the USA, major earthquakes might take place in the sub-Himalayan region, including
Bangladesh. Another study of Michigan University has pinpointed that Dhaka is one of theearthquake vulnerable city out of top cities because of its unplanned urbanization. A strong
earthquake of 8.6-magnitude occurred in Assam on August 15 in 1950, killing 1,526 people.
Another 8.1-magnitude quake hit Assam on June 12 in1897, killing 1,500 people. The
casualties were less because of low density of population and fewer numbers of concrete
structures at that time (The daily star, 2010).
The historical seismicity and recent tremors occurred in Bangladesh and adjoining areas
indicate that the country is at high seismic risk. Recently, a series of earthquakes has been
experienced throughout the country. The existing urban trend and urbanization process of
Bangladesh have caused increased vulnerability to natural disasters like earthquake. The risk
in urban center is compounded due to unplanned urbanization and development in high riskzones. Dhaka, the capital of Bangladesh is the center of economy, commerce, politics, etc.
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and accommodates a large estimated population of 12.8 million in the wider metropolitan
area while the population of Dhaka city stands at approximately 7.0 million as of 2008 (BBS,2009). According to a report published by United Nations IDNDR-RADIUS Initiatives,
Dhaka and Tehran are the cities with the highest relative earthquake disaster risk (Rahman,2004). Although no moderate to large earthquake has struck Dhaka city in historical past, it
experiences minor tremors almost all the year round which indicates the region to beseismically active (Khan, 2004).
Dhaka is vulnerable to earthquake due to high population density, vulnerable structures, lowpreparedness of people etc. Particularly the older part of the city is relatively more vulnerable
to earthquake due to its relatively high density of population e.g. the projected density of
population in Kotwali Thana, a major part of Old Dhaka is 1,61,198 per square kilometer in2009 (BBS, 2001). Besides, the densely built fabric consisting of vulnerable, aged, nonreinforced masonry buildings along with narrow local streets make the locality more
earthquake disaster prone.
Earthquake is a cataclysmic event that needs to be addressed in a more concerted way. An
important aspect of preparedness for an earthquake is evaluating the building stock
particularly in terms of structural vulnerability. When the vast majority of properties do notmeet the earthquake resistance standards in the design of buildings, it exposes the occupants
to the risk of injury or death arising from the building collapse in the event of a major
earthquake. Earthquake induced large destruction occurs due to vast majority of properties
not meeting the earthquake resistant standards in building design. One of the reasons for thehigh level of destruction is the poor building quality particularly of residential in nature. Aspart of earthquake preparedness, it is essential to undertake a structural vulnerability
assessment of properties to determine its resistance level in earthquake and advice necessary
steps, such as retrofitting, to rectify any deficiencies. These initiatives will benefit thecommunity providing safeguards from earthquakes as well as the preparedness andtechnology to address other catastrophes.

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Table 1: Major historical earthquakes affecting Dhaka
Name of Earthquake
Cachar Earthquake, 1869
Bengal Earthquake, 1885
Great Indian Earthquake, 1897
Srimangal Earthquake, 1918
Dhubri Earthquake, 1930

Magnitude
7.5
7.0
8.7
7.6
7.1

Intensity
at Dhaka
V
VII
VIII+
VI
V+

Source: Ansary, 2006

Distance between Epicenterand Dhaka (Km)
250
170
230
150
250

Once a great earthquake occurs, Dhaka may suffer immense loss of life and property due tounplanned city development. This will have severe long term consequences for the entire
country. Damaged structures are the main cause of human injury and death. Earthquake
vulnerability assessment of an area put a remarkable importance in proposing an effective
evacuation plan considering the prevailing local condition and in any disaster mitigation
measures such plan is of utmost importance in reducing the loss to a great extent. The
evacuation plan can make the locality self-dependent in coping with a disaster to minimize
the risk in time. This research will study the present scenario of the study area, assess theearthquake vulnerability and propose an evacuation plan for the community.
Along with earthquake fire hazard has become a major issue of concern as Dhaka City has
been experienced a number of notable fires in the recent years. A report of Bangladesh Fire
Service and Civil Defense (BFSCD) shows a rising trend in the number of fire incidents inthe Dhaka City (table 2). Dhaka the capital of Bangladesh often faces fire hazards due to its
dense building concentrations, narrow roads, flammable building materials, aging watersupply and electrical wire, chemical factory in residential areas as well as the lack of
preparedness and response skills among local people and the fire authority. The annual
monetary loss due to fire accidents is very high in Dhaka City compared with the other urban
centers in Bangladesh because of its high concentration of economic activities (table 2).
Table 2: Year-wise number of fire incidents and economic loss
Year
Number of Incident
Economic Loss (in Million Dollar)
2003
1861
13.8
2004
2053
26.7
2005
2279
34.1
2006
1220
29.8
2007
1100
21.6
2008
1110
7.1
2009
1775
11.6
2010
2068
13.4

Source: BFSCD report 2010.

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Moreover, fire incidents in shops, industrial and commercial buildings cause heavy toll of lifeand property. In the recent time, there were huge losses of property due to some big fireincidents in the garments factories. The major causes of those incidents were noncompliance of government's fire fighting and extinguishing law 2003. Besides, disasters inmany family lives, such fire incidents also tarnished image of the country. Unplanned
urbanization and rapid industrialization are the major causes of a huge number of fire related
accidents inflicting colossal damage to lives and property in the country every year.
According to a report on Role of Fire Services in Mitigating Losses in Fire Related Incidents,
the major accidents occur in readymade garment (RMG) factories that have been flourishingin the country since early nineties. Over 350 garment workers have died and some 1,500 been
injured in fire-related incidents since 1990 (The Daily Star, 2006).
In 3rd June 2010, a devastating fire broke out in the densely-populated part of Old Dhaka city
at Nimtoli. Fire killed at least 117 people and caused injury to a hundred people. Most of theaffected peoples were women and children. 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 and spread to the chemical warehouses nearby and resulted high casualties anddamages.
Two back to back fires occurred in 15th and 16th January 2012 in Islambag and Lalbag areas
in Ward 65 in Old Dhaka. The first incident occurred in a plastic warehouse near the Eidgah
ground in West Islambag at around 10:45 PM started from a gas stove. The next day again at
the same time another fire occurred in Shahid Nagar area at Lalbag around 10:30 PM. In thiscase fire originated from a tin shed house. Around 100 shanties, five shops and a printingpress caught by fire. (BNUS field Survey, 2012).
This is a common situation in Old Dhaka where most of the buildings have small factories
like chemical, plastic, rubber etc. and Warehouse and food shops up to second floor of theresidential building. In Old Dhaka no house is equipped with fire fighting equipments likeextinguisher, hose pipe etc. They don’t have sufficient width of staircase let alone theemergency exit. In this respect, assessment of fire hazard vulnerability in Dhaka City
especially in the old part is very important. The old part ‘Puran Dhaka’ is the most vulnerable
area in Dhaka City. In this study Ward 29 (Map 2) of Old Dhaka is selected for thevulnerability assessment. This ward is one of most vulnerable to fire hazard than other because
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of its traditional land use and population density. Fire incidents are very common phenomenon
in this area. It is also one of the oldest areas of Dhaka City. This ward is mainly used as
manufacturing industrial area. Besides several land uses like Warehouse, commercial use,chemical shop, clamber storage and processing shops are also prominent. Land use of this area
makes it more unique than the other area of Dhaka City. In this study, assessment of fire hazard
vulnerability of the community has been conducted to examine the existing risk of fire in thearea and prepare the residents to face this sort of disaster.
Fire is considered as the most common secondary hazard of earthquake (Horwich, 2000), so
it is important to assess the integrated vulnerability of fire and earthquake because of theirclose association. A number of researches have been carried out on fire and earthquake in
Dhaka City Corporation (DCC). In a study, Old DCC is categorized into different fire hazard
zones according to the frequency of fire incidence (Alam, 2004). About 53% buildings ofWard 68 (Old DCC) are vulnerable to earthquake (Jahan, 2011). But none of the studies
focused the integrated vulnerability of fire and earthquake hazard. In this research, an
integrated vulnerability assessment of Ward No. 29 in Dhaka South City Corporation(DSCC) will be conducted incorporating both fire and earthquake hazard.
3. METHODOLOGY
The research has been conducted with the following methodology:
3.1

Selection of the Study Area

Ward No. 29 of DSCC which is selected for the vulnerability assessment of fire andearthquake in this research. This ward is one of the oldest areas in the city with 58233
populations (BBS, 2011) in 0.457 square kilometer area (GIS map). A common scenario of
this ward is mixed land use (15.3%) of buildings where most of these have small factories
like chemical, plastic, rubber etc., warehouse and small shops up to second floor andresidence at upper floors (GIS map). This ward is mainly comprised of manufacturing andprocessing industries of plastic, warehouses of chemical and unprocessed leather. As a result,fire incident is very common phenomenon in this area (Rahman, 2012). Being the one of theoldest parts of the city, no house is equipped with fire fighting equipments like extinguisher,hose pipe etc. and sufficient accessibility to the adjacent road and staircase for emergency
exit of people (Islam, 2008). According to a microzonation map of Dhaka City, the study area

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is located in zone 2 with earthquake intensity of IX (Map 1). So a small scale earthquake may
cause disaster in this ward.

Study Area

Map 1: Microzonation Map of Dhaka City
considering Earthquake Hazard (Rahman, 2004)
3.2

Map 2: Ward 29

Sampling

The total number of buildings of Ward 65 is 3,210. For these sample size, survey of 343
buildings will be conducted by stratified sampling procedure keeping the confidence level at
95% and confidence interval is 5. Stratification of sample will be chosen according to thepercentage of construction type, number of storey and structure use of the study area.
Socioeconomic survey will be conducted by random sampling to know social vulnerability offire and earthquake in the study area. The total number of household in the study area is13,123. But survey of households living in 343 sample buildings will be conducted toinvestigate the overall condition of each building.

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3.3

Data Collection

Base map of the study area will be collected from Dhaka City Corporation (DCC) in both
hard copy and GIS shapefile. Field survey of the buildings will be conducted on the basis of
the DCC base map by checklist. Based on field survey GIS map will be edited.
Characteristics of building such as construction type, land use, number of storey, floor area,
land area, age of building, having fire source, having pounding effect, soft storey, soft
column etc will be identified by the building survey. Socio-economic survey will be
conducted by questionnaire to know age, gender, income level, education level, awareness of
local people and number of disable people etc in the study area. Focus group discussion(FGD) will be conducted to know the view of local people to adopt various risk reduction
strategies of fire and earthquake in their locality. The focus group will be community basedorganization (CBO), local government representatives, NGOs, cooperative societies, andgoverning bodies of mosque, madrasa and schools etc.
3.4

Data Analysis

The data obtained through field survey would be classified, tabulated and presented in theform of maps, tables and graphs by using MS-Excel and SPSS for processing and analysis of
the collected data and to end up with meaningful results. ArcGIS 10 would be used formapping hazard zones. To assess the community vulnerability of fire hazard of Ward 29 in
Old Dhaka, Community Vulnerability Assessment Tool (CVAT) will be used (Flax, 2002).
The earthquake vulnerability assessment of buildings will be conducted by two different
visual screening methods, i.e. FEMA-RVS (FEMA 154, 2002) and Turkish Simple Survey(Level-I) procedure (Sucuoglu and Yazgan, 2003). The results of fire and earthquake
vulnerability assessments will be integrated using opinion of fire and earthquake experts. A
panel of at least 10 to 15 experts of fire and earthquake expert will be consulted to determine
the combined vulnerability score of fire and earthquake. Weight of factors of vulnerability
will be determined by Analytical Hierarchal Process (AHP). Findings of focus group
discussion will be compiled to develop risk reduction strategy which is acceptable to the local
people and community.

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3.4.1 Earthquake vulnerability analysis
The vulnerability assessment of the existing buildings was done following two different
visual screening methods, i.e. FEMA-RVS and Turkish Simple Survey (Level-I) procedurethat are universally accepted for quick assessment of the buildings. In Bangladesh both of themethods are well accepted considering the physical context of the region. The basic scores ofthe buildings found in the two methods suggest whether the building should perform well in aseismic event or require further investigation by an experienced seismic design professional.
Thus the safest buildings are segregated from those needed more detailed structural analysis.
In this study the building vulnerability assessment survey was conducted by the fresh
graduated students in civil engineering. So data authentication can be ensured up to a limit.
The detailing of the used survey procedures are discussed in the following sections.
3.4.1.1 FEMA- Rapid Visual Screening (RVS) method
The Federal Emergency Management Agency (FEMA) of the United States of America hasdeveloped pre-earthquake screening method of potential seismic hazard assessment ofbuildings based on rapid visual screening method, widely known as RVS method, originatedin 1988, with the publication of the FEMA 154 Report, a Handbook. It is generally used for
rapid evaluation of seismic vulnerability profiles of existing building stocks. RVS provides aprocedure to identify record and rank buildings that are potentially seismically hazardous(FEMA 154, 2002).
RVS method is used to quickly determine if detail evaluation of existing building is required.
The rapid visual screening method is designed to be implemented without performing any
structural calculations. The objective of these methods is to identify, make inventory and rank
all high-risk buildings in a specified region so that a strategy of priority based interventions tobuildings can be formed. Although RVS is applicable to tall buildings, its principal purpose is
to identify:
Older buildings designed and constructed before the adoption of adequate
seismic design and detailing requirements.



Buildings on soft or poor soils, orBuildings having performance characteristics that negatively influence theirseismic response.

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This screening methodology is encapsulated in a one page form, which combines a
description of a building, its layout and occupancy, and a rapid structural evaluation related toits seismic hazard. This procedure requires only visual inspection and limited data collection.
The inspection, data collection and decision-making process typically occurs at the buildingsite. It is a “sidewalk survey” approach that enabled users to classify surveyed buildings into
two categories: those acceptable as to risk to life safety or those that may be seismicallyhazardous and should be evaluated in more detail by a design professional experienced inseismic design. Once identified as potentially hazardous, such buildings should be further
evaluated by a design professional experienced in seismic design to determine if, in fact, they
are seismically hazardous.
The Data Collection Form of RVS includes space for documenting building identification
information, including its use and size, floor area, etc., a photograph of the building,sketches- building plan and elevation and documentation of pertinent data related to seismic
performance, including the development of a numerical seismic hazard and vulnerability
score. The scores are based on the expected ground shaking levels in the region as well as theseismic design and construction practices for the city or region. The scores use probability
concepts and are consistent with the advanced assessment methods. Basic Structural Hazard
Scores based on Lateral Force Resisting System for various building types are provided on
the form, and the screener circles the appropriate one. The screener modifies the Basic
Structural Hazard Score by identifying and circling Score Modifiers related to observed
performance attributes, by adding (or subtracting) them a final Structural Score, ‘S’ isobtained.
The score below which a structure is assumed to require further investigation is termed as“cut-off” score. The value of “cut off” score and choice of RVS form depends on the seismic
zonation of the area. It is suggested that buildings having an S score less than the “cut-off”
score should be investigated by an experienced seismic design professional experienced inseismic design. If the obtained “final score” is greater than the “cut-off” score the building
should perform well in a seismic event. According to FEMA 154 a “cut-off” score of 2 isused in this study. According to the experts, considering the existing site condition it can beassumed that such a large number of buildings may not be vulnerable if an earthquake hits
and so 1.5 can be considered as a “cut-off” score.

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The Rapid Visual Screening (RVS) method is less time consuming respective to the Turkish
screening method. The RVS methodology is not intended for structures other than buildings.
For important structures such as bridges and lifeline facilities, the use of detailed evaluation
methods is recommended. Even in urban areas, some very weak forms of non-engineeredbuildings are well-known for their low seismic vulnerability and do not require RVS toestimate their vulnerability. These building types are also not included in the RVS procedure.

Use of RVS results
The results from rapid visual screening can be used for a variety of applications that are an
integral part of the earthquake disaster risk management program of a city or a region. The
main uses of this procedure are:


To identify if a particular building requires further evaluation for assessmentof its seismic vulnerability.



To rank a city’s or community’s (or organization’s) seismic rehabilitationneeds.



Design seismic risk management program for a city or a community.

Plan post-earthquake building safety evaluation efforts.



Develop building-specific seismic vulnerability information for purposes suchas regional rating, prioritization for redevelopment etc.



Identify simplified retrofitting requirements for a particular building (tocollapse prevention level) where further evaluations are not feasible.



Increase awareness among city residents regarding seismic vulnerability ofbuildings.

Classification of damage to buildings
The likely damage has been categorized in different grades depending on their impact on theseismic strength of the building. The different damage levels that have been recommended by
European Macro Seismic Scale (EMS-98) are described in Table 3 Table 4 provides guidance
regarding likely performance of the building in the event of design-level earthquake; thisinformation can be used to decide necessity of further evaluation of the building using higher
level procedures. It can also be used to identify need for retrofitting and to recommend simple
retrofitting techniques for the ordinary buildings where more detailed evaluation is not

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feasible. Generally the score S<0.7 indicates high vulnerability requiring further evaluation
and retrofitting of the building.
The damage classification based on the European Macro Seismic Scale (EMS-98) definebuilding damage to be in Grade 1 to Grade 5.The damage classification helps in evaluation ofearthquake intensity following an earthquake. They are used in RVS to predict potential
damage of a building during code level earthquake.
Table 3: Classification of damage to buildings
Classification of damage to masonrybuildings
Grade1: Negligible to slight damage (Nostructural damage, slight non-structural
damage)Hair-line cracks in very few walls.
Fall of small pieces of plaster only.
Fall of loose stones from upper parts ofbuildings in very few cases.
Grade 2: Moderate damage (Slight structural
damage, moderate non-structural damage)
Cracks in many walls.
Fall of fairly large pieces of plaster.
Partial collapse of chimneys and mumptys.
Grade 3: Substantial to heavy damage(Moderate structural damage, heavy nonstructural damage)
Large and extensive cracks in most walls. Rooftiles detach. Chimneys failure at roof line;
failure of individual non-structural elements.
(partitions, gable walls etc)
Grade 4: Substantial to heavy damage(Moderate structural damage, heavy nonstructural damage)
Serious failure of walls. Partial structural failureof roofs and walls.
Grade 5: Destruction (Very heavy structural
damage)Total or near total collapse of a building.

Classification of damage to reinforced concretebuildings
Grade1: Negligible to slight damage (No structural
damage, slight non-structural damage)Fine cracks in plaster over frame members or inwalls at the base.
Fine cracks in partitions and infills.
Grade 2: Moderate damage (Slight structural
damage, moderate non-structural damage)
Cracks in columns and beams of frames and in
structural walls.
Cracks in partition and infill walls; fall of brittle
cladding and plaster. Falling mortar from the jointsof wall panel.
Grade 3: Substantial to heavy damage (Moderate
structural damage, heavy non-structural damage)
Cracks in columns and beam-column joints offrames at the base and at joints of coupled walls.
Spalling of concrete cover, buckling of reinforcedbars.
Large cracks in partition and infill walls, failure ofindividual infill panels.
Grade 4: Substantial to heavy damage (Moderate
structural damage, heavy non-structural damage)
Large cracks in structural elements withcompression failure of concrete and fractures ofrebars. Bond failure of bars, tilting of columns.
Collapse of a few columns or of a single upper floor.
Grade 5: Destruction (Very heavy structural
damage)Collapse of ground floor parts.(e.g. wings of thebuilding)

Source: FEMA-154, 2002

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Table 4: Expected damage level as function of RVS score
RVS score
S<0.3
0.3<S<0.7
0.7<S<2.0
2.0<S<3.0
S>3.0

Damage Potential
High probability of Grade 5 damage; very high probability of Grade 4 damage.
High probability of Grade 4 damage; very high probability of Grade 3 damage.
High probability of Grade 3 damage; very high probability of Grade 2 damage.
High probability of Grade 2 damage; very high probability of Grade 1 damage.
Probability of Grade 1 damage.
Source: FEMA-154, 2002

The probable damage can be estimated based on the RVS score. However, it should be
realized that the actual damage will depend on a number of factors that are not included in
RVS procedure. As a result, this table should only be used as indicative to determine thenecessity of carrying out simplified vulnerability assessment of the buildings. These results
can also be used to determine the necessity of retrofitting buildings where morecomprehensive vulnerability assessment may not be feasible.
3.4.1.2 Turkish Simple Survey Method: A Two level seismic risk assessment procedures
Another approach of rapid visual screening was employed for assessment of seismic
vulnerability of structure in Turkey. The Turkish Simple Survey procedure is a two level
seismic risk assessment procedure which has been proposed on the basis of statisticalcorrelations obtained by employing a database of 477 damaged buildings surveyed after the1999 earthquake in the cities of Kocaeli and Düzcec in Turkey. Researchers from various
universities were involved in this program supported by the government of Turkey and JICA
(Sucuoglu and Yazgan, 2003). The method uses two levels seismic assessment based on
several building parameters that can be easily observed or measured during a systematicsurvey.
In Turkish data collection form, the structural characteristics and site aspects such as potential
pounding between buildings, apparent quality is judged. The basic scoring for both the levels
are based on the Height of the building (number of stories) and Local Soil Conditions where
three intensity zones are specified in terms of associated PGV (Peak Ground Velocity) ranges.
This method considers buildings up to 7 stories where the increasing number of stories
reduces the performance score by influencing almost all other Vulnerability Parametersnegatively. Pounding effects and apparent quality of the building as well as the structural

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characteristics, redundancy and stiffness index, act as weighted vulnerability parameters inthe scoring system of Turkish screening.
Once the vulnerability parameters of a building are obtained from two-level surveys and its
location is determined, the seismic performance and vulnerability scores are calculated as
defined in Figure 2.3. A “cut-off” performance score of 50 has been suggested for bothsurvey levels. In this study, the Turkish Level-I & Level-II method, a more detail evaluationof buildings has used to assess the vulnerability of the structures to be proposed as evacuation
places.
Level- I Survey
Level-1 survey is a street side survey procedure based on simple structural and geotechnicalparameters that can be observed easily from the sidewalk. The first level incorporates
recording of building parameters regarding a structural form and the ground condition
The trained observers collect data through walk-down visits. The parameters that are selectedin Level-1 survey for representing building vulnerability are the following:a. The number of stories above groundb. Presence of a soft story (Yes / No)
c. Presence of a short column (Yes / No)
d. Presence of heavy overhangs such as balconies with concrete parapets (Yes/No)
e. Apparent building quality (Good, Moderate or Poor)
f. Pounding between adjacent buildings (Yes / No)
g. Local soil conditions (Stiff/ Soft)h. Topographic effects (Yes / No)
All of the above parameters are found to have a negative feature on the building system underearthquake excitations on a variable scale.
3.4.2 Fire hazard vulnerability analysis
To assess fire hazard vulnerability of Ward 29 in Old Dhaka, Community Vulnerability
Assessment Tool (CVAT) is used to find out the existing scenario of the area. This tool has 7
steps including:

Hazard identification

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Hazard analysis



Critical facilities analysis

Social analysis

Economic analysis

Environmental analysis



Mitigation opportunities analysis

In this report only critical facilities analysis, social vulnerability analysis, economic
vulnerability analysis and in addition structural vulnerability analysis has been done to assess
the vulnerability of the community. The tools and methodologies used in this analysis consistof GIS and spatial mapping analysis.
Hazard analysis
Fire score of each building will be calculated from the following equation:
Score for building = weight for accessibility × (1 for No access or 0 for Access) + Weight fortransformer and power line× ( 0 for Not Vulnerable or 1 for Vulnerable for electricity pole or
2 for Vulnerable for Transformer) + Weight for floor area ratio× (0 for Very Low floor area
ratio or 1 for Moderately Low floor area ratio……..) + Weight for building material type × (1for Pucca or 2 for Semi-kutcha or 3 for Kutcha) + Weight for availability of fire source × (1for Available of fire sources and 0 for No available of fire source)
Each building was given a score on the basis of five attributes where weight of each attribute
was selected by using the Analytical Hierarchy Process (AHP). AHP is a multi-attributemodeling methodology. AHP is a systematic method for comparing a list of objectives oralternatives or attributes. The process of obtaining the weight of factors is given below:
The five attributes are road accessibility (A1), transformer and electrical wiring system (A2),floor area ratio (A3), building material type (A4) and availability of fire source (A5). A
normalized set of weights was established to be used when comparing alternatives using
these attributes. A pair wise comparison matrix M was formed where the number in the ith
row and jthe column gives the relative importance of Ai as compared with Aj. 1-5 Scale wasselected from the eight expert’s opinion. aij = 1 if the two objectives are equal in importanceand aij = 2 if Ai is more important than Aj.

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Matrix M which was made by expert opinion is given in the following:


1
1

3
M=  1
2
1

2
2

3

2

2

1

1
2

2

2

1

1
2

2

1

2

3

1
2
3

1
2
1

3
1
2
1

3
1

To normalize the weights, the sums of each column were computed and then each column
was divided by the corresponding sum. Thus N was used to denote normalization.
 0.2310.077
N= 0.115
0.115
0.462

0.316 0.267 0.235 0.188 
0.105 0.067 0.235 0.125 
0.211 0.133 0.059 0.188 

0.053 0.267 0.118 0.125 
0.316 0.267 0.353 0.375 

The next step was to compute the average values of each row and used these as the weights inthe attribute Hierarchy.
0.247 0.122
W=  0.141
0.1350.354

The weights are shown in the map.
Table 5: weight of the attributes
Accessibility
Transformer and power line
Floor Area Ratio (FAR)
Building material type
Availability of fire source

0.247
0.122
0.141
0.135
0.354

Consistency of the comparison matrix
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It is unusual for the entire comparison matrix to be consistent. Indeed, given that humanjudgment is the basis for the construction of this matrix, some degree of inconsistency is
expected and should be tolerated provided that it is not unreasonable.
To determine whether or not a level of consistency is reasonable a quantifiable measure forcomparison matrix M was developed. To determine the consistency of the comparative
matrix consistency ratio was computed by the following equation.

CR 

CI
RI

Where, CI= Consistency Index of M
RI= Random Consistency of M

CI 

nmax  nn 1 ,

Where,
n = Number of Attributes
nmax= M*W (Weighted Matrix)

RI 

1.98(n  2)n

In that case,
nmax = M*W= 5.383

n=5Consistency Index of M,

CI 

nmax  nn 1= 0.096
Random Index,

RI 

1.98(n  2)n

= 1.118
Consistency Ratio

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CR 

CI
RI

= 0.081
The Consistency Ratio (CR) is acceptable if CR is less or equal to 0.1. As the calculated CR
comes below 0.01, consistency of comparison matrix is acceptable.
Hazard score for each building was calculated by the above equation using the derived weight.
On the basis of this hazard score all the buildings were classified and it is shown in the Fire
Vulnerability Map 5.8. The map was classified into five classes: low, moderately low,
moderate, moderately high and high.
Critical facilities analysis
This analysis focuses on determining the vulnerabilities of key individual facilities, lifelines,
or resources within the community. Critical facilities include emergency shelters, schools,
hospitals, nursing homes, public buildings, and facilities for fire and rescue, police, utilities,
communications, transportation, etc., or those identified as critical by the risk andvulnerability assessment working group. It is important to protect critical facilities (e.g.,through relocation, elevation, or retrofit: backup of essential records; and backup of power
supplies) to ensure that service interruption is reduced or eliminated, because these facilities
play a central role in disaster response and recovery. Because it is not usually feasible toconduct a structural and operational analysis for every structure in a community, this step
helps to prioritize which facilities are most vulnerable, so that individual assessments may be
performed later. A structural analysis is used to examine the structural integrity of thebuilding and its ability to withstand potential hazard damage; whereas, an operational
analysis helps determine how daily activities will be affected if the building is damaged or if
utility services are interrupted. The critical facilities vulnerability analysis has four
components:• First, critical facilities are identified by type and location to determine facilities that provide
essential services to the community on a regular basis and are integral to disaster response
and recovery operations.
• Second, a critical facilities inventory must be established by collecting general information
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information on certain categories of critical facilities, which may provide a starting point forthe critical facilities inventory. It is imperative to collect accurate information because thesedata will be essential for completing the individual facility assessments in the last step of thisanalysis.
• Third, critical facilities that are in and within close proximity to high-risk areas are
identified by overlaying the critical facility locations over the map of hazard-risk areas.
• Next, critical facilities that will require further structural and operational assessments are
identified by completing a critical facilities inventory, which should include but is not limited
to construction type and quality, location, age, size, occupancy rates, monetary value,
insurance coverage, auxiliary-power capability, backup capacity and process for electronic
files, and protection and storage procedures for hard-copy documents. Assessment questions
should be designed to meet the needs of the audience or investigators. Some questions may
require professionally trained inspectors or engineers, while others may rely on subjective
evaluations from managers or property owners.
Social analysis
This analysis focuses on societal vulnerability by analyzing special consideration areas(preferably at the neighborhood level), where individual resources for loss prevention anddisaster recovery tend to be minimal. Individuals that reside in special consideration areas are
more likely to be uninsured or underinsured for hazard damages and have limited financial
resources for pursuing individual hazard mitigation options. The population in these areas
would be most dependent on public resources (e.g., disaster relief and recovery grants,
unemployment assistance, subsidized health care and child care, social services, public
transportation, etc.) after a disaster and therefore could indicate good investment areas forhazard mitigation activities. Special consideration areas can be identified by utilizing existing
low-to-moderate income designations for community development grants or by analyzing key
census data categories. Demographic characteristics can be selected to help identify special
considerations such as mobility, literacy, or language, which can significantly hinder disasterrecovery efforts. A societal vulnerability analysis is accomplished as follows:• First, special consideration areas (e.g., areas with high concentrations of poverty, elderly,minorities, single-parent households, rental dwellings, no high school diplomas, public
assistance recipients, non-English speaking populations, no vehicle available, etc.) are
identified by type and location to determine which populations may require special care or
may have more difficulty with disaster response and recovery.
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ICUS Report 74• Second, special consideration areas that are in high-risk areas are identified by overlaying
the special consideration neighborhoods onto the risk areas.
• Next, a general inventory is completed of special consideration areas that are located inhigh-risk areas. There are several ways to complete this type of inventory. A community
might elect to conduct a windshield survey to determine the number and type of vulnerable
facilities in high-risk areas, unless these data are readily available from the local tax
assessor’s office. New Hanover County used a parcel-based land use inventory in a GIS
format to distinguish the number and type of residential structures located in each census
block group that was identified as a special consideration area.

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Map 3: (Color) Examples of GIS maps used for the Community Vulnerability Assessment
Tool process in New Hanover County, North Carolina: (a) Natural hazard summary risk areas(Step 2-Hazard analysis); (b) Special consideration residential areas with high risk areas (Step
4-Societal vulnerability analysis); (c) Economic sectors in high-risk areas (Step 5-Economic
vulnerability analysis); (d) Tracts of undeveloped land in high-risk areas (Step 7-Mitigation
opportunities analysis)
Economic analysis
This analysis focuses on economic vulnerabilities to hazard impacts by identifying major
economic sectors and mapping primary centers of activities in those sectors. Economic
centers are areas where hazard impacts could have adverse effects on the local economy andwould therefore be ideal locations for targeting certain hazard mitigation strategies. Some of
the most devastating disaster costs to a community include the loss of income associated withbusiness interruptions and the loss of jobs associated with business closures. A progressive
community will actively pursue business continuity plans and hazard mitigation options toprevent or minimize such losses. It is important to begin this step by conducting a general
overview of the local economy to provide a basis for targeting business sector partners incommunity-wide hazard mitigation efforts. The identification process will rely on local
expertise such as the chamber of commerce or economic development council. Economic
information can also be derived from widely available data sources such as the county
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business patterns located on the U.S. Census Bureau Web site (http://www.census.gov/).
Land use or zoning data can often help in mapping business and industrial centers. Steps toaccomplish an economic vulnerability analysis are as follows:• First, the primary economic sectors and their geographic locations must be identified (i.e.,
economic centers) to determine which businesses are most important to the community (e.g.,
products and services, employment, tax revenue, disaster response and recovery capabilities,etc.).
• Second, primary economic centers that are located in high-risk areas are identified byoverlaying the economic center locations over the risk areas.
• Third, a general inventory of high-risk economic centers is conducted. A community may
choose to conduct a windshield survey to determine the number and type of vulnerable
facilities in high-risk areas if this information is not readily available. A table (e.g., GIS
attribute table or spreadsheet) can be used to summarize the type of industries, the number offacilities within each industry, the number of employees, the percentage of employees perindustry and/or facility, and the annual payroll to help narrow the focus for facilities to betargeted for hazard mitigation.
• Fourth, large employers that are located in high-risk areas are identified to help prioritize
the facilities on which to perform further analyses. Economic census data can help identify
employment levels by economic sector and determine the size threshold.
• Next, a structural and operational vulnerability analysis is conducted. While this step islargely up to the private sector, it is recommended that vulnerability assessments for large
employers be addressed in a manner similar to critical facilities. FEMA endorses engaging
with key private sector establishments in hazard mitigation partnerships and asking them toassess their structural and operational vulnerability to hazards.
Environmental Vulnerability Analysis
This analysis focuses on identifying locations where secondary environmental impacts caused
by natural hazards (primary impacts) may occur. Before embarking on this step, it isnecessary to explain the terms ‘‘secondary impacts’’ and ‘‘secondary risk sites.’’ Secondary
impacts occur when natural hazards (e.g., flood) trigger additional hazards such as toxic
releases or hazardous spills. Therefore, a solid-waste facility or a building that stored
hazardous materials would be characterized as ‘‘secondary risk sites’’ if they are in close
proximity to areas of environmental concern (e.g., wetland). Although CVAT uses the term‘‘secondary risk sites,’’ these are often called ‘‘hazardous facilities.’’ Environmental impacts
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are important to consider, as they not only jeopardize habitats and species, but can also
threaten public health (e.g., water quality), various economic sectors (e.g., tourism andfishing), and quality of life (e.g., access to natural landscapes and recreational activities). For
example, flooding (a primary hazard) can result in contamination (a secondary hazard)
whereby raw sewage, animal carcasses, chemicals, pesticides, hazardous materials, etc. aretransported through sensitive habitats, neighborhoods, and businesses. These circumstances
can result in major cleanup and remediation activities, as well as natural resource degradation.
Data can be obtained from state and local emergency management offices, local planningcommissions, and environmental and natural resource management agencies to locate natural
resources and secondary risk sites. Steps to accomplish an environmental vulnerability
analysis are as follows.
• First, secondary risk sites (e.g., hazardous materials, toxic release sites, solid-waste facilities,
nuclear power plants, underground storage tanks, oil facilities, ports, marinas, discharge sites,etc.) and key natural resource sites (e.g., wetlands, sensitive/endangered species and habitats,
fisheries, wildlife refuges, aquaculture sites, shellfish harvest areas, groundwater recharge
areas, etc.) are identified.
• Next, secondary risk sites and environmentally sensitive areas are overlaid onto the risk
areas to determine the types of hazardous materials and locations of potential releases into
environmentally sensitive areas. (Lisa et al, 2002)
3.5 Preparation of Final Report
All information and finding are gathered and presented by tables, graphs and maps to prepare
the final report. Some recommendations based on the findings are provided to improve theoverall conditions of Ward 29 in the report.

4. EXISTING SCENERIO OF STUDY AREA
Ward 29 is situated at the old part of Dhaka City also named as ‘Puran Dhaka’ beside theriver Buriganga. Total 343 building which cover 16.76% of existing buildings in the study
area were surveyed including mosques, schools, college, community centers and clubs etc toassess earthquake and fire hazard vulnerability of buildings.

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4.1 Age of Building
As the study area is one of the oldest parts of Dhaka city, there are some buildings aged
above 50 years. In contrast, newly constructed buildings which were constructed up to 10
years before dominate with about 49% share. 29% buildings are constructed 11 to 20 years
before and 15% buildings are constructed 21 to 30 years before. Figure 1 shows distributionof age of buildings in the study area.
Age of building
1%
5% 1%

Lowest - 10
11-20

15%

49%

29%

21-30
31-40
41-50
51-60

Figure 1: Distribution of age of building

Figure 2: Old buildings

4.2 Building TypeAmong 343 surveyed buildings 228 buildings are pucca, 114 are semipucca and only one iskatcha (figure 3). Among pucca only 2 buildings are C2 (Concrete shear wall buildings) typebuilding. C3 (Moment resisting frame) type building dominates with 74.1% occupancy. URM(Unreinforced masonry buildings) buildings which are mostly semipucca buildings are 25.4%
in the study area (figure 4).
Building material Type

Building construction Type

0.3%

0.6%

33.2%

Pucca

66.5%

Semipucca
Katcha25.4%

C2 (shear wall)

Figure 3: Distribution of building material Figure 4: Distribution
construction type
type

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C3 (URM inf)

74.1%

URM

of

building

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4.3 Number of Storey
The area mainly comprises of one to six storey buildings where two storey buildings are thehighest with 22.7% occupancy. Buildings above 6 storey are very limited (3%). The tallest
building in the study area is a 9 storey building. One storey building is 12.8%. 4 storey and 5
storey buildings dominate with 18.7 % and 18.1% share respectively. The following tableshows the frequency and percentage of buildings with different number of floor.
Table 6: Distribution of different number of storey
Number of Storey
1
2
3
4
5
6
7
8
9
Total

Frequency
44
78
50
64
62
34
9
1
1
343

Percent
12.8
22.7
14.6
18.7
18.1
9.9
2.6
0.3
0.3
100

Figure 5: High-rise building

4.4 Floor Area of building
Owners of the buildings of the study area do not follow the building construction regulationof RAJUK. So Floor Area Ratio (FAR) of buildings is equal to the number of floor for thisward. Building floor area covers the total land area of the plot. Floor area varies from 120
square feet to 8000 square feet. Most of the buildings (28.3%) have 501-1000 square feet
floor area. Buildings with 120-500 square feet which are mostly commercial shops andshanty are 19.2% (figure 6).
Floor Area of building

28.3

Percentage

30.0
25.0
20.0

19.2

17.5

17.2

15.0

7.6

10.0

10.2

5.0
0.0
120-500

501-1000

1001-1500

1501-2000

2001-8000

No information

Floor area in square feet

Figure 6: Distribution of floor area in the study area

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4.5 Use of Buildings
From the field survey, it has been found that about 60% buildings are used as mixed use
activity such as shops and industry at ground floor and residence at upper floor. This is acommon scenario of Old Dhaka. 20% buildings are of pure residential use. Commercial andindustrial uses are 10% and 7% respectively. Community services and service facility are 2%
and 1% respectively (figure 7).
Use of building

7%

Residential

20%

Commercial

10%
60%

Community Service
2%
1%

Service Facility
Mixed
Industry

Figure 7: Distribution of use of building in the study area

Figure 8: Different uses of building
5. EARTHQUAKE VULNERABILITY ANALYSIS
5.1 Apparent Quality, Pounding Effect, Soft Storey, Short Column and Heavy
OverhangAmong 343 surveyed buildings, 185 buildings (54%) are good quality structures; 29% aremoderate and 17% are poor in apparent quality. Most of the buildings (91.84%) have noP a g e | 205

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space in between the adjacent buildings. About 8% buildings have soft storey while 4% haveshort column.
Gap with adjacent building

Apparent quality
100

17%

80

54%

Percentage

Good
29%

91.84

Moderate
Poor

60
40
20
0

0 ft

0.58

2.92

2.62

0.87

0.29

0.58

1 ft

2 ft

3 ft

4 ft

6 ft

10 ft 20 ft

0.29

Gap with adjacent building in feet

Figure 9: Apparent quality of

Figure 10: Gap with adjacent buildingbuilding

Figure 11: Poor quality building

Figure 12: Heavy overhang of building

Soft storey

Short column
4%

8%
No
92%

Figure 13: Soft storey

No
96%

Yes

Yes

Figure 14: Short column

22% buildings in the study area have heavy overhang which lead to earthquake vulnerabilityof building. Width of overhang varies from 0.5 feet to 5 feet. Most of the buildings have
overhang with 2 feet (8.75%), 1 foot (5.54%) and 3 feet (5.25%).
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Heavy overhang

Width of Heavy overhang

22%

Percentage

10.00

No
78%

Yes

8.75

8.00

5.54

6.00

5.25

4.00
2.00

0.87

0.29

0.29 0.58 0.29

0.29

0.00
0.5

1

1.5

2

2.5

3

3.5

4

5

Width in feet

Figure 15: Heavy overhang

Figure 16: Width of heavy overhang

5.2 Vertical Irregularity and Plan Irregularity
Buildings with irregular shape with respect to both plan and elevation shape tend to be more
vulnerable to earthquake. 25.7 % buildings are vertically irregular and 74.3% buildings are
regular in their elevation shape. It has also found from field survey that 91% buildings of thestudy area have rectangular or square plan i.e. the shape of the plan are regular and rest 9%
buildings have irregularity in their plan.
Comparison between vertical and plan irregularity

91
100

74.3

Percentage

80
60

Yes
25.7

40

No
9

20
0
Vertical irregularity

Plan irregularity

Figure 17: Comparison between vertical irregularity and plan irregularity
5.3 Rapid Visual Screening
Among 373 surveyed buildings, 20 buildings (5.83%) scored less than 1 according to RVS(FEMA). 70.75% buildings scored 3 to 3.4 value which means most of the building are
structurally safe according to RVS (FEMA). According to RVS (Turkish level I), about
56.56% buildings scored above 110. Buildings having scores less than 50 are only 2.62%.
The following charts show category of buildings according to RVS score in the study area.
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RVS (FEMA)

Percentage

60
40
20

18.37
5.83

2.62 0.29 1.46

56.56

60

70.85

80
Percentage

RVS (Turkish)

0.58

40
20

2.62

6.41

13.99

20.41

0

0

Figure 18: RVS (FEMA)

Figure 19: RVS (Turkish level I)

6. FIRE HAZARD VULNERABILITY ANALYSIS
6.1 Existence of Fire Source
As a traditional old part of Dhaka City, Ward 29 contains different types of economic
activities such as plastic manufacturing industries, warehouse of flammable material likechemicals and plastic etc that can trigger a fire or can be vulnerable to fire accidents. That is
why these sort of economic and other uses that can generate a fire disaster in the locality are
identified and classified into some broader categories.
They are given below:
1. Chemical
2. Plastic
3. Leather
4. Generator
5. Gas stove
Buildings where fire sources and flammable materials are available in the study area werelocated during the field survey. Around 9% buildings are found with no fire sources. 38%
buildings have plastic, 9% have chemicals, 6% have leather and 1% have generator. Rest
37% buildings which are mainly residential have gas stove as a source of fire (Fig. 5.3).

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Fire source in front of building

Fire source in building

Electric pole

9%11%
No fire source

9%

Chemical38%

Gas Stove

12%

Generator

6%
1%

Leather

37%

68%

Plastic

Figure 20: Fire source in building

1%
4%
2%

2%

Electric pole, Electric
wireElectric pole, Electricwire, Transformer
Electric wireTransformer
Transformer, Electricpole
No fire source

Figure 21: Fire source around building

Electricity poles are distributed throughout the study area. One or more than one transformer
has been found in every neighborhood. It has been found that in some places twotransformers are located so near to each other that they can create a hazardous situation if any
one explodes. The study reveals that around 11% buildings adjacent to electricity poles arevulnerable to fire where as 12% buildings adjacent to transformers are vulnerable. 2% houses
have electric wire, 2% have both electric pole and transformer, 1% has both electric wire andelectric pole, and 4% have electric wire, electric pole and transformer. The rest 68% have nofire source around. It is shown in figure-5.2.

Figure 22: Fire source in front of building
6.2 Accessibility of fire truck
Accessibility is one of the important attributes for making fire vulnerability map. Fireaffected plots are supposed to be served by fire engines coming from fire stations which carry
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water, ladder and various fire fighting equipments. If the roads leading to the affected plot are
not accessible to fire engines, the plot cannot be served effectively by fire fighters and it
become vulnerable to fire. In our country, fire engines can go through roads at minimum 10
feet width. This information was taken from a fire fighting expert. Besides, traffic jam isanother factor affecting the accessibility by road. From the field survey, it was found that the
number of the buildings that get access is 46%. Rest of the buildings (around 54%) is notaccessible to fire engines (Figure 24)

Figure 23: Narrow road inaccessible for fire truck

Road accessibility

46%
54%

10ft & above
Less than 10ft

Figure 24: Distribution of road accessibility
6.3 Staircase width
From the field survey it was found that widths of the staircase of building in the study areavary from 1 foot to 8 feet. Most of the buildings (16.3%) have 3 feet wide staircase, 14.6%
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Table 7: Distribution of width of staircase
Width in feet
1
2
3
4
5
6
7
8
No information
Total

Frequency
1
24
56
50
17
35
2
14
144
343

Percent
0.3
7
16.3
14.6
5
10.2
0.6
4.1
42
100

6.4 Fire Vulnerability Score
Percentages of buildings having different categories of fire score are shown in figure 25.
The vulnerability score of buildings of the study area range from 0.41 to 1.88. Lower value
indicates less vulnerability whereas higher value indicates high vulnerability. Most of thebuildings (78.5%) have fire score more than 1 which indicates most of the buildings in the
study area are vulnerable to fire. Buildings having fire score less than 0.5 are only 0.9%,
having score 0.51- 0.75 are 5.5% and having 0.76 – 1.00 are 15.2%.

Distribution of fire score
38.5

40.0
35.0

28.3

30.0
25.0
20.0

15.2

11.7

15.0
5.5

10.0
5.0

.9

.0
lowset - .5 .51 - .75.76 - 11.01 - 1.25 1.26 - 1.5

1.51 highest

Figure 25: Distribution of fire score
7. MAJOR FINDINGS
Ward 29 is at risk of earthquake and some fire incidents have already occurred. From the firevulnerability analysis it has been found that maximum numbers of buildings of the study area
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are highly vulnerable (78.5%) to fire. Most of the highly fire vulnerable buildings are locatedin Islambag Road. Buildings of Water works Road and Lalbag area are less vulnerable
because of being residential areas with mixed commercial use. The surveyed buildings cover
16.76% of existing structures in the study area.
The study area comprises both old buildings and newly constructed buildings where buildings
constructed up to 10 years before dominate with about 49% share.
Pucca buildings dominate with about 50% occupancy among which about 74.1% are C3(moment resisting frame) type building. Unreinforced masonry buildings buildings which aremostly semipucca are 25.4% in the study area.
Two storey buildings are the highest with 22.7% occupancy where as buildings above 6
storey are very limited (3%). The tallest building in the study area is a 9 storey building. Mostof the buildings (28.3%) have 501-1000 square feet floor area.
About 60% buildings are used as mixed use activity such as shops and industry at groundfloor and residence at upper floor.
Most of the buildings (54%) are of good apparent quality and most of the buildings (91.84%)
have no space in between the adjacent buildings. About 8% buildings have soft storey while
4% have short column and 22% buildings have heavy overhang which lead to earthquake
vulnerability. 25.7 % buildings are vertically irregular and 9% buildings have irregularity intheir plan.
5.83% scored less than 1 according to RVS (FEMA). 70.75% buildings scored 3 to 3.4 values
which mean most of the buildings are structurally safe according to RVS (FEMA). According
to RVS (Turkish), about 56.56% buildings scored above 110. Buildings having scores lessthan 50 are only 2.62%.
Around 9% buildings are found with no fire sources in building whereas 68% have no firesource around. 54% buildings have no access for fire truck.
Most of the buildings (78.5%) have fire score more than 1 which indicates most of thebuildings in the study area are vulnerable to fire.

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8.CONCLUSIONS
The research assessed the vulnerability of old part of Dhaka city to earthquake and fire
hazard. In many studies, Dhaka is considered as one of the most vulnerable city to earthquake.
Recently the city also followed a number of notable fire accident which means the city is also
at risk of fire. Old part of Dhaka is more vulnerable to any hazard due to high population
density, mixed uses of land and violation of building construction regulation. The study area
was found to more vulnerable to fire but less vulnerable to earthquake. But due to narrow
road, lack of critical facilities and lack of preparedness among local people may lead to agreat disaster if a small scale earthquake occurs.
REFERENCES


http://www.daily-sun.com/details_yes_08-10-2011_Fire-hazard-vulnerability:-Acase-study-in-Dhaka-city_366_2_28_1_0.html.

Islam, M.M. and Adri, N., Fire Hazard Management of Dhaka City: Addressing
Issues Relating to Institutional Capacity and Public Perception. Jahangirnagar
Planning Review, Vol. 6, pp. 57-67, 2008.



Rahman, M.M. and Talukder, M.R.A. “Mapping Earthquake Management in Dhaka
City: A Scoping Study.” Bangladesh Research Publications Journal, ISSN: 1998-2003,
Volume: 6, Issue: 4, Page: 462-466, 2011.

Khan, A.A. “Earthquake hazard: Dhaka city perspective”, The Daily Star, Vol. 5 No.
40, 2004.

The Daily Star, Dhaka city at risk of massive destruction, 2010, accessed fromhttp://archive.thedailystar.net/newDesign/news-details.php?nid=123247.

Horwich, G., “Economic Lessons of the Kobe Earthquake.”Economic Development
and Cultural Change, volume 48, page 521–42, 2000.

Alam, M.J.B and Baroi, G.N., Fire hazard categorization and risk assessment for
Dhaka city in GIS framework, Journal of Civil Engineering (IEB), Volume 32 (1),Page 35-45, 2004.

Jahan I, Ansary M, Ara S, Islam I., Assessing social vulnerability to Earthquake
Hazard in Old Dhaka, Bangladesh; Asian Journal of Environment and Disaster
Management (AJEDM), 3(3):285–300, 2011.



http://www.dhakasouthcity.gov.bd/Documents/New%20DCC_South_Ward%20Report_22.12.2011.doc

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203

May 2014

http://www.bbs.gov.bd/WebTestApplication/userfiles/Image/Census2011/Dhaka/Dha
ka/Dhaka_C01.pdf



http://www.dhakasouthcity.gov.bd/Page/About/Link/2/List_id/220/Ward_no_&_Area_

GIS database of Detailed Area Plan (DAP) of Dhaka City, 2006.



Rahman N., Ansary, M.A. Community under Fire Threat: An Assessment of Fire
Hazard Vulnerability of Ward 65 in Dhaka City, presented in 11th International
Symposium on New Technologies for Urban Safety of Mega Cities in Asia, Mongolia,
2012.



BNUS Annual Report, 2011.



Rahman, M. G. F. “Seismic Damage Scenario for Dhaka City”, M.Sc. Engg. Project
thesis, Department of Civil Engineering, BUET, Dhaka, 2004.



Flax, L. K., Jackson, R. W. and Stein, D. N. “Community Vulnerability Assessment
Tool Methodology” Natural Hazards Review Vol. 3 (ISSN 1527-6988), 162-176,
2002.



F.E.M.A. Federal Emergency Management Agency 154, 2002.

 Sucuoglu, H. And Yazgan, U., Simple Survey Procedures for Seismic Risk
Assessment in Urban Building Stocks. Seismic Assessment and Rehabilitation of
Existing Buildings, 97-118, NATO Science Series, IV/29, Editors: S.T. Wasti and G.
Ozcebe, Kluwer, 2003.
APPENDIX-A
1. Checklist of field survey 2013
SL

Parameter

Value

No.
1

Adjacent road width2

Building material type

3

Number of storey

4

Building floor area

5

Plot land area

6

Present land use

7

Adjacent land use

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8

Total population living in the building

9

Condition of staircase

10

Staircase width

11

Existence of fire source in building

12

Existence of fire source in front of building

13

Apparent quality of building

14

Gap with adjacent building (Pounding effect)

15

Soft storey (only column at ground floor)

16

Short column (only column at any other floor)

17

Heavy overhang

18

Width of heavy overhang
2. FEMA 154 data collection form

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PART-XVI

STANDARD GARMENTS FIRE: AN INTRIGUEAGAINST RMG SECTOR OF BANGLADESHBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Naima Rahman
Mehedi Ahmed Ansary

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On 28th November 2013 two 6-storied and a ten-storied building of Standard Group in
Konabari of Gazipurwereset fire by hundreds of Ready Made Garment (RMG) workers.
Bangladesh Garment Manufacturers and Exporters Association (BGMEA) termed the fireincident as “sabotage” as the blaze had been said to be set upon by workers who wereangered over rumours of two colleagues dying in police firing.
Direct witnesses said that some people announced through the horn speakers of a nearby
mosque that police had killed two workers in the Standard Group factory for demanding aseparate pay structure for the employees in the group’s jumper factory. Hearing theannouncement, at least 200 workers of Standard Group along with some non-workers
stormed and torched the company’s two multi-storied buildings, brushing aside the policemenon duty at the gates. Firefighters around 1:30pm of 29th November were able to douse theflames.

Figure 1: Burning front section of Standard garments factory building in Gazipur

Figure 2: Burning clothes in standard garments
There have been no reports of any life loss or casualty but the ten storied building was totally
damaged due to fire. The workers also torched 31 vehicles inside the compound of which, 18
covered vans were fully loaded with goods. The loss will exceed Tk. 900 crores as demanded
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from the garment owner side. Standard Group was considered as one of the most compliant
factories in Bangladesh by BGMEA and BKMEA for its good reputation.

Figure 3: Police routed aggressive RMG
workers

Figure 4: Fire Fighters working in thebuilding

Figure 5: Fire on the third floor around Figure 6: Covered vans loaded with cloths
1:00pmburnt

Figure 7: Cleaning process after fire-control

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Figure 8: Prime-ministers press conference

209PART-XVII
GROUND PENETRATING RADAR TESTING AT
THE PROPOSED UNDERGROUND LPG
STORAGE TANK AT SOUTHERN AUTOGASSTATION, TEJGAONBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Mominul Haque
Mehedi Ahmed Ansary

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1.0

Introduction

The GPR tests at the autogas station have been carried out on February 13 and 21, 2014. This
report is the outcome of the measurements through GPR. Figure 1 shows the test site.

Figure 1 Investigated site

2.0 Ground Penetrating RADAR (GPR) Test Program
Ground Penetrating Radar (GPR) is a near-surface geophysical technique that can provide
high resolution scan of the dielectric properties of the earth. GPR works by sending a tiny
pulse of energy (Electromagnetic Energy) into a material and recording the strength and thetime required for the return of any reflected signal. A series of pulses over a single area makeup what is called a scan. Reflections are produced whenever the energy pulse enters into amaterial with different electrical conduction properties or dielectric permittivity from thematerial it left. The strength, or amplitude, of the reflection is determined by the contrast in
the dielectric constants and conductivities of the two materials. GPR is a rapid and usefultechnique for nondestructive assessment of subsoil, locating underground pipelines andreinforcement in buildings, foundation and bridges etc.
Scope of this project included subsurface layer investigation and identification of utility
location.
GPR data were collected using 100 MHz and 200 MHz antenna for subsurface layer
investigation and 400 MHz antenna for identification of utility location with a GSSI SIR3000 control unit. All data were collected in simple line scan format. The direction of arrowin site plan and data collection grids indicates the starting and ending point GPR scan.
The collected data sets were processed by specialized software program RADAN. Threebasic 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 correction 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.

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3.0 Results of Ground Penetrating RADAR (GPR):
The results of 100 MHz GPR data are presented in Appendix-B. These data don’t show any
clear contrast of soil layers. The results of 200 MHz GPR data are presented in Appendix-C.
These data show two clear soil layers, one up to a depth of 22 ft (6.5 m) and another below it.
The results of 400 MHz GPR data are presented in Appendix-D. These data show rebar
locations at the top of the soil layer (confirmed by the top concrete slab), a clear soil layer up
to a depth of 6 ft (2.05 m) and probable locations of pipe line at 2 ft and 4 ft locations.

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GPR_ 100MHz

Site Plan & Data Collection Grids:
1.0 m
1.5 m

1.5 m

1.0 m

Scan-08

Scan-07

Scan-06

4.0 m

Scan-05W

4.0 m

Scan-04

4.0 m

Scan-03

4.0 m

Scan-02

Bore Hole
4.0 m

4.0 m

Scan-01

1.0 m

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Scan-02:

Display gain -03
Display mode- True gray
Corrections: (Time-zero correction)
Filters: FIR&IIR
Scan-01:

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GPR_ 200MHz

Site Plan & Data Collection Grids:
1.0 m
1.5 m

1.5 m

1.0 m

Scan-08

Scan-07

Scan-06

4.0 m

Scan-05W

4.0 m

Scan-04

4.0 m

Scan-03

4.0 m

Scan-02

Bore Hole
4.0 m

4.0 m

Scan-01

1.0 m

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