BNUS ANNUAL REPORT-2011

BANGLADESH
NETWORK OFFICE
FOR

URBAN
SAFETY
BUET, DHAKA,BANGLADESH
Prepared By:

Mehedi Ahmed Ansary

CONTENTS
PART-I: COMMUNITY UNDER FIRE THREAT: ASSESSMENT OFCOMMUNITY FIRE HAZARD VULNERABILITY OF
WARD 65 IN DHAKA CITY ---------------------------------------------- 1
PART-II: APPLICABILITY OF H/V MICROTREMOR TECHNIQUE
FOR SITE RESPONSE ANALYSIS IN DHAKA CITY--------------27
PART-III: ESTIMATION OF SHEAR WAVE VELOCITY USING 3D
MICROTREMOR MEASUREMENT IN SYLHET CITY --------- 147
PART-IV: STRONG MOTION RECORDINGS DURINGSEPTEMBER 18, 2011 SIKKIM EARTHQUAKE------------------ 159
PART-V: APPLICATION OF NON-DESTRUCTIVE TESTINGTECHNIQUES FOR STRUCTURAL SAFETYEVALUATION IN BANGLADESH----------------------------------- 175
PART-VI: VULNERABILITY EVALUATION FOR ZINDABAZAR
GOVERNMENT PRIMARY SCHOOL,SYLHET, BANGLADESH---------------------------------------------- 187
PART-VII: GEOPHYSICAL INVESTIGATION AT MEGHNADHONAGODA IRRIGATION PROJECT (MDIP) USINGGROUND PENETRATING RADAR METHOD -------------------- 197
PART-VIII: TRAINING COURSES, SEMINARS AND
WORKSHOPS ------------------------------------------------------------ 2092

PART-I
COMMUNITY UNDER FIRE THREAT: ASSESSMENT
OF COMMUNITY FIRE HAZARD VULNERABILITY
OF WARD 65 IN DHAKA CITYBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Naima Rahman
Mehedi Ahmed Ansary3ICUS Report 59

1. INTRODUCTION
Dhaka City has been experiencing many fire accidents at present and in most cases lack ofproper precautionary measures along with the institutional inefficiency, insufficientequipment support and lack of public awareness are making the situation worse. To mitigate
the impact of fire at community level, public participation is important. As a high risk area offire hazard, no vulnerability assessment has been conducted in Dhaka City. In this study, a
traditional community of ward 65 of Dhaka has been selected for vulnerability assessment.
Community Vulnerability Assessment Tool (CVAT) (Lisa et al, 2002) method has been
applied to assess vulnerability of the community to fire hazard. At first, a hazard map
showing the different risk zones of fire has been developed by land use in the study area.
Then four vulnerability analyses have been conducted namely social vulnerability, criticalfacilities vulnerability, economic vulnerability and structural vulnerability. To accomplishthese vulnerability analyses different field surveys have been conducted for getting complete
scenario of the community. By using some parameters and attributes, community
vulnerability has been evaluated with respect to fire hazard. Finally some recommendations
have been provided to improve the present condition of the community.
2. BACKGROUND
A fire hazard is any situation in which there is a greater than normal risk of harm to people orproperty due to fire. The physical vulnerability of the country’s population and infrastructure
is compounded by economic vulnerability. Extensive fire inevitably causes upheavals not
only in the physical but also in the social and economic context where it occurs. Urban fires
have devastating impact on the communities. An analysis of disaster impacts on urbanizing
areas show that fires cause the greatest loss of life and property. Fires hazards occur
frequently in Bangladesh especially in urban areas. Table 1 describes number of fire
accidents originated by various causes in the last three years in Bangladesh. Electric fault,
kitchen fire, cigarette, naked fire, burning ash, fireworks, friction of machine, sabotage, mob,
unknown and misc (engine misfire, spontaneous ignition, and chemical reaction) are different
causes of fire. Among these most of the fire occur due to electric fault and kitchen fire.

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Table 1: Causes of Fire in Bangladesh
SL

Cause of Fire

1
2
3
4
5
6
7
8
9
10
11

Number of Fire Incident
2009
2010
3754
43.27% 3188
39.44%
2254
25.98% 2166
25.67%
865
9.97%
789
9.75%
542
6.24%
528
6.52%
229
3.41%
267
3.16%
162
2.41%
204
2.41%
134
1.99%
170
2.01%
85
1.26%
149
1.76%
113
1.68%
241
2.85%
868
1105
536
6.17%
389
4.61%

Electric Fault
Kitchen Fire
Cigarette
Naked fire
Burning Ash
Fire Works
Friction of Machine
Sabotage
Mob
Unknown
Misc (Engine misfire, spontaneous
ignition, Chemical reaction)
Total
12182
Source: Bangladesh Fire Service and Civil Defense, 2012

14682

3760
2137
828
450
358
161
244
104
78
726
464

2011
43.86%
24.89%
9.64%
5.24%
4.17%
1.87%
2.84%
1.21%
0.90%
5.40%

13041

Fire incidents are categorized into different causes. This categorization has been done
according to the building use and electrical system in the building. Figure 1 describes thetrends in fire accidents in Bangladesh with different categories from 2005 to April 2011.
Residential fire events are increasing in every year tremendously and it causes loss ofproperty and injures many people badly. Industrial fire is also in increasing trend.

Figure 1: Trends in fire accidents in Bangladesh (2005 to April 2011)(Source: Bangladesh Fire Service and Civil Defense)

Economic loss due to fire incidents is high. Figure 2 describes amount of loss due toresidential fire in Taka crore from 2002 to 2010. Among these years the highest amount ofloss (Tk. 272.64 crores) is seen in 2005. In most of the years the loss amount is above Tk.
100 crores. As Bangladesh is a developing country it cannot afford the huge amount of loss
due to fire accidents every year.
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Figure 2: Extent of losses due to fire hazards in recent years (1 Million USD = Taka 8.6 crore)(Source: Bangladesh Fire Service and Civil Defense)

Dhaka the capital of Bangladesh often faces fire hazards due to its dense building
concentrations, narrow roads, flammable building materials, aging water supply and electricalwire, chemical factory in residential areas as well as the lack of preparedness and response
skills among local people and the fire authority. Figure 3 shows the trend of fire in Dhaka
City in the last six years. Most of the fire events occurred in 2010 than the other statistical year.

Figure 3: Number of fire event in Dhaka city

(Source: Bangladesh Fire Service and Civil Defense, June 2011)

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.

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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 65 (Map 1) of Old Dhaka is selected for thevulnerability assessment. This ward is one of most vulnerable to fire hazard than other becauseof 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.

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Map 1: Study Area (ward 65 of Dhaka city)
Source: Dhaka City Corporation

3. METHODOLOGY
The research has been conducted with the following methodology:
3.1 Study Design
For achieving the objectives, depending on the literature review a checklist for the study has
been designed which has been modified on the basis of findings from pilot survey. The
checklist is given in Appendix-A.
3.2 Study Area Selection
The Ward 65 of Old Dhaka is selected as the study area to assess the fire hazard vulnerability.
The study includes the vulnerability assessment of the building stocks. Buildings adjacent to
the roads were surveyed.
3.3 Sampling
As the total number of buildings of Ward 65 is 3210, so the total sample size of this research
is 3210. For these sample size, total 1078 buildings survey has been conducted keeping theconfidence level at 95% and confidence interval is 2.43. That means the result of this85March 2012

research varies from -2.43 to +2.43. (http://www.surveysystem.com/sscalc.htm, accessed on
25th March, 2011).
3.4 Data Collection
3.4.1 Base map collection and updating map from field survey
A base map of the study area was collected from Dhaka City Corporation (DCC) office tobecome familiar with the environment of the study area. Field survey of the buildings was
conducted on the basis of the DCC base map.
3.4.2 Primary Data Collection
A checklist survey was conducted in the study area to find out the existing socio-economic
condition of the residents.
3.5 Data Processing and Analysis
Through data collection, raw data have been collected. Information collected from the survey,
have been inputted in MS Access and then converted to SPSS 12 for processing and analysis.
3.5.1 Fire hazard vulnerability analysis
To assess the community vulnerability of Ward 65 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•

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.

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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
on facility types and locations. The type and amount of information collected depends on theintended use of the database. Most local emergency management offices collect and maintain
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
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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.
• 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. (Map 2)

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Map 2: 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)
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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
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.

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ICUS Report 59• 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
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)
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3.6 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 65 in the report.
4. FIRE HAZARD VULNERABILITY ANALYSISThe study area is divided into three risk zones including high risk zone, moderate risk zone
and low risk zone according to their land use from expert opinion. Land uses of various riskzones differ from other (map 3). The total area of Ward 65 is 118.1668 acres (0.478 Square
Kilometer). Among this, high risk zone is 52.84 acres (44.72%), moderate risk zone is 30.89
acres (26.14%) and low risk zone is 27.95 acres (23.65%). (From GIS Map) The livelihoodsof the inhabitants of a zone are primarily based on plastic processing industries like plastic
manufacturing, recycling and processing factories. This zone is considered as high risk area.
The name of this portion is Islambag. The zone also displays a high building density withmulti-storey buildings and very few urban public spaces left. In the moderate risk area
processing factory and different Warehouse (plastic Warehouse, cattle food storage) are
dominant. Residential use with commercial (retail shop, office, bank and storage) use isconsidered as the low risk area.

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Map 3: Fire risk zone in Ward 65
4.1 Critical Facilities Analysis
The critical facilities in ward 65 were identified and a complete inventory of these facilities
was prepared. There are total 22 numbers of critical facilities in the study area. Then criticalfacilities that are in and within close proximity to high risk areas were identified by overlying
the critical facilities location over the map of fire vulnerable areas. Map 4 shows criticalfacilities map in Ward 65. The most common critical facilities in the area are as follow:

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Map 4: Critical facilities Map in Ward 65
Table 2: List of critical facilities of ward 65
Type

Educational institutions
Government organizations
Healthcare facilities
Community facilities
Service facilities
Utility facilities

Name

School and Kindergarten
Rapid Action Battalion (RAB) officeDental Clinic
Mosque and club
Police stations, Bank/other officeElectrical sub station

Fire district

Lalbag Fire Station
Lalbag Fire Station
Lalbag Fire Station
Lalbag Fire Station
Lalbag Fire Station
Lalbag Fire Station

Figure 4 shows that 27.27% critical facilities are located at the high risk, 9.09% are located atmoderate risk area and 63.64% are located at low risk zone. The critical facilities are mainly
educational institution and religious center. Most of the critical facilities are located in the
Lalbagh area which is comparatively low risk zone. In this area land use is mainly residential
and in some case mixed (residential, retail shop, commercial) and the people in this area areless vulnerable to fire hazard. In high risk zone i.e. Islambag, plastic industries are located tovery close proximity to critical facilities.
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Figure 4: Percentage of critical facilities in different risk zones

Critical facilities of the study area are not vulnerable to fire. Besides these are located mainly
adjacent to wider roads. In case of any fire, these can be used as shelter for the inhabitants.
4.2 Social Vulnerability Analysis
Number of population in any building of the study area varies from 0 to 400. Most of thebuildings (28.53%) have 11 to 20 people. 22.03% have 21 to 30 persons and 18.93% have 6
to 10 persons. Building having population more than 100 is very low (1.6%). But most of thedensely populated buildings are situated in the high risk zone (Map 5) which mainly consistsof plastic recycling and processing factories. In these factories generally woman and childlaborers work. With respect to these conditions of the area it can be said that the area isvulnerable to fire hazard.

Figure 5: Population distribution in Ward 65.

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Map 5: Population Map of Ward 65

4.3 Economic Vulnerability Analysis
Among the surveyed households, 57.22% have different types of economic activities. Plastic
manufacturing and processing industry is dominating (20.22%); others are different type offactory (15.19%), warehouse (8.95%), iron/metal shop/factory (2.8%), gold and silver shop
(1.49%), electric goods shop (1.3%), chemical shop/factory (1.21%) and other (6.06%) etc.
Grocery shop, grocery shop and bank, medicine shop, tailoring shop/laundry, clamber storage,
paper shop, bank/services, cloth store, hotel, market and phone shop are in other category.
Figure 6 shows different types of economic activities of the study area.

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Figure 6: Economic Activities of the Study Area
Some economic activities make the study area vulnerable to fire hazard. Among them plastic
manufacturing industry is totally based on chemicals which promote fire to spread within few
seconds to the locality. From land use survey, it is found that the area is mainly a residential
area (36.9%). Mixed activity is found in four categories: 1. residential and commercial(31.87%), 2. residential and industry (16.4%), 3. commercial and industry (0.93%), and 4.
residential and education (0.1%). Figure 7 shows the present land use of the study area.

Figure 7: Present Land Use of the Study Area

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4.4 Structural Vulnerability Analysis
There are other factors in the area which makes it vulnerable to fire hazard. These factors arewidth of staircase, road width of the area and accessibility to the building, position oftransformer and electricity pole. If the roads are not accessible to fire service vehicle todouse/ put off the fire it may cause a loss to the community. For the emergency evacuation
process staircase width is a vital issue to the resident of a building. That’s why these factors
get importance to the vulnerability assessment. The area consists of total 3210 structures.
Among these, 55.66% of the structures are situated in high risk zone; 24.45% structures are
situated in moderate risk zone and 19.89% structures are situated in low risk zone. (Map 6)

Map 6: Structure Map of Ward 65
4.4.1 Age of Structure
From the field survey, 2011, it is found that Ward 65 is composed of both old and newly
developed buildings. 23.3% of surveyed buildings have been constructed 0-10 years ago.
These are the newest structures of the area. Most of the buildings have been constructedaround 11-20 years ago (25.7%). 23.2% and 11.6 % structures have been built 21-30 years
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and 31-50 years before respectively. 15.9% building are 51-100 years old and 0.4% buildings
are more than 100 years old.

Figure 8: Age of building in the study area
4.4.2 Number of Floor
From field survey it has observed that in the study area most of the buildings (29.64% of
surveyed buildings) are one storied. These buildings are mainly used as clamber storage andprocessing activity and plastic manufacturing and processing. In these structures fire can
propagate very swiftly. 22.27% buildings are two storied and mainly used as residential andplastic processing activity. 3 storied are 14.35%, 4 storied are 13.05%, 5 storied are 12.3%
and 6 to 14 storied are 7.36%. 1.03% buildings are under construction.

Figure 9: Number of floor of the building in the study area
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4.4.3 Staircase Width
In the older portion of Dhaka city it is a tradition that the width of staircase is smaller than the
new part of Dhaka. From the field survey it has been observed that staircase width ofbuildings varies from 1-5 feet. Most of the buildings (41.82%) have 3 feet wide staircase. 4
feet wide staircases are seen in 28.09% buildings. In case of some newly constructedbuildings the width is 5 feet (11.73%). Wider staircase is essential for any building during theevacuation process for any disaster. For fire hazard it gets special priority because fire
spreads very quickly in a building. So people need to protect themselves from the rage of firein a very short time. In this respect the study area is vulnerable to fire hazard.

Figure 10: Staircase width (feet) of building in the study area

4.4.4 Road Width/ Accessibility to Building
For emergency response during any disaster road width is an important factor. If the road is
not sufficiently wide to move fire service’s vehicle it may cause another disaster to the people
and it may extend the loss. Building fire can spread very quickly and can overwhelm
properties and life. In the study area accessibility to each household is not good. The main
roads are wide and accessible to the fire service vehicle but the local roads and connecting
roads to the buildings are not accessible to the vehicle. (Map 7)

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Map 7: Accessibility Map of Ward 65
Road width varies from 1-40 feet in the study area. Most of the residents have 6-10 feet roads
in front of their houses (44.73%). 16.31% have 11-15 feet roads and 20.42% have above 15
feet roads. 18.55% households have only 0-5 feet roads which is inaccessible for fire truck.
These narrow roads are totally impossible for evacuation and recue process. In this respect
this community is also vulnerable to fire hazard. They are not aware about widening the road.

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Figure 11: Road width (feet) / accessibility to building in the study area

4.4.5 Transformer and Electricity Pole
Position of transformer and electricity pole to a building is also assessed in this study because
these may cause serious fire hazard to the locality. Recently in old Dhaka a fire incident
occurred due to the blast of a transformer. The buildings in this area are constructed very
closely to each other. So that fire can spread out to another building rapidly. Among thesurveyed buildings electric pole is located in front of 13.51% buildings and transformer islocated in front of 11.37 % building.

Figure 12: Electric pole in the study area

Figure 13: Transformer in the study area

4.4.6 Existence of Fire Source
Most of the buildings of the study area have different type of fire sources. Gas stove, electricwire, chemical factory and plastic factory are the main sources of fire. Besides, there are also
some ornament factories, metal factories, recycled plastic shop, printing press and wholesale
paper market in the area all of which can be source of great fire hazard. Residential houses
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are vulnerable due to gas stove (38.4%) and electric wire (15.84%). Households with mixed
use are mainly vulnerable due to plastic factory (17.8%), chemical shop (16.59%), metal
factory (2.8%) and gold ornament factory (1.5%). 3.26% buildings have no fire source.

Figure 14: Existence of fire sources in the study area

Figure 15: Electric pole and transformer in front ofbuilding

Figure 16: Narrow road within buildings

5. MAJOR FINDINGS
Severe fire incidents have occurred in ward 65. From the fire vulnerability analysis it has
been found that maximum numbers of buildings of the study area are highly vulnerable(55.66%). Most of the highly fire vulnerable buildings are located in Islambag Road.
Buildings of Water works Road and Lalbag area are less vulnerable because of being
residential areas with mixed commercial use.

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March 201227.27% critical facility was found to be within the highly fire vulnerable areas. Most of thesefacilities (63.64%) are situated in the low risk zone. So critical facilities of the study area aremoderately vulnerable to fire.
Population density in the high risk zone is high and the area consists of plastic recycling andprocessing industries. In these factories generally woman and child labors work. So it can besaid that the area is socially vulnerable to fire hazard.
Most of the buildings of the study area have different kind of economic activities. Only
36.9% buildings are residential with no economic activity. 20.22% buildings have plastic
manufacturing and processing industries which is highly vulnerable to fire hazard.
Most of the buildings (41.82%) have 3 feet wide staircase. 18.55% households have only 0-5
feet roads in front of their houses which is inaccessible for fire truck. Besides, electric pole islocated in front of 13.51% buildings and transformer is located in front of 11.37 % building.
96.74% buildings of the study area have different type of fire sources. In this respect thiscommunity is vulnerable to fire hazard.
6.CONCLUSIONS
Urban fire incidents have been determined to have a high likelihood of occurrence in ourcountry. But no mentionable fire risk assessment has been performed although fire hazard
characterization information is available in the Fire Service and Civil Defense (FSCD). In
this study after conducting vulnerability assessment using Community Vulnerability
Assessment Tool (CVAT), it is found that ward 65 is vulnerable to fire hazard. The land use
pattern of ward 65 indicates the possibility of this kind of hazard. The area comprises ofresidential use as well as commercial and industrial uses like plastic manufacturing andprocessing factory and chemical factory which may induce massive fire. As being a mixed
use residential area, the loss due to fire may be catastrophic. To minimize the social andeconomic loss, Mitigation Planning is required. A change in present land use pattern isrequired. Chemical factory and plastic factory should be relocated. Road network as well as
staircase of building should be wider to evacuate the community people. Community
awareness should be raised. Although CVAT has been applied in this small area of Dhaka
city, it can be applied to any type of hazard in any location of the country both at micro andmacro levels.

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REFERENCES•

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

•

http://www.surveysystem.com/sscalc.htm, accessed on 25th March, 2011.

•

BNUS field survey, 2012.

Checklist for Fire Hazard Vulnerability Assessment of Ward 65 in Old Dhaka
Date:
Locality:
HoldingnoConstruction
year

No
of
floor

Front
road
width
(feet)

Total no of
population

Transformer/ electricpoleTransformer Electric:1
pole:2Present land use
Residential:1;
Commercial:2;
Mixed(Residential andcommercial):3;
Mixed(Commercial andindustry):4;
Industry/Factory:
5; School/
Educational
institution:628

Existence of firesourceWholesale paper
market:1;
Printing press:2;
Chemical
shop:3; Goldornament
factory:4; Cloth
market:5;
Recycled plastic
shop:6; Plastic
industry:7; Gas
stove:8

Critical facility

Economic activity

Educational
institution:1;
Religious
center:2; Healthcare facility:3;
Community
facility:4; Water
pump station:5;
Electric
substation:6;
Other office:7;
Katcha bazaar:8;
Police station:9

Plastic industry:1;
Iron/Metal shop:2;
Clamber storage:3;
Gold and silver shop:4;
Chemical shop:5; Paper
shop:6; Bank/service:7;
Electric goods shop:8;
Grocery shop:9;
Medicine shop:10;
Tailoring shop/
laundry:11; Factory:12;
Godown:13

25

Staircasewidth(feet)

PART-IIAPPLICABILITY OF H/V MICROTREMORTECHNIQUE FOR SITE RESPONSEANALYSIS IN DHAKA CITYBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Saidur Rahman
Mehedi Ahmed Ansary29ICUS Report 59

1.1 GENERAL
In the recent past, Bangladesh has not suffered any damaging large earthquakes, but in thepast few hundred years, several large catastrophic earthquakes struck this area. So far, all the
major recent earthquakes have occurred away from major cities, and have affected relatively
sparsely populated areas. In 1897, an earthquake of magnitude 8.7 caused serious damages tobuildings in the northeastern part of India (including Bangladesh) and 1542 people were
killed. Recently, Bilham et al. (2001) pointed out that there is high possibility that a huge
earthquake will occur around the Himalayan region based on the difference between energy
accumulation in this region and historical earthquake occurrence. The population increasearound this region is at least 50 times than the population of 1897 and city like Dhaka has
population exceeding several millions. It is a cause for great concern that the next greatearthquake may occur in this region at any time.
The use of microtremor, an idea pioneered by Kanai et al. (1954) turns into one of the mostappealing approaches in the site effects studies, due to its relatively low economic cost andthe possibility of recordings without strict spatial or time restrictions (Rodriguez andMidorikawa, 2002). The H/V spectral ratio technique of microtremors gained popularity inthe early nineties, after the publication of several papers (Nakamura, 1989; Field and Jacob,
1993; Lermo and Chávez-García, 1994) claiming the ability of this technique to estimate thesite response of soft sedimentary deposits satisfactorily. This method is rather attractive indeveloping countries characterized by a moderate seismicity, where only very limited
resources are available for seismic hazard studies. The H/V spectral ratio determined frommicrotremors has shown a clear peak that is well correlated with the fundamental resonancefrequency at “soft” soil sites (Bard, 2004; Horike et al., 2001; Field et al., 1995; Lachet andBard, 1994; Lermo and Chávez-García, 1993). Comparison of microtremor and earthquake
spectral ratios at strong-motion instrument sites across SW British Columbia showed similar
fundamental periods and in greater Victoria remarkably similar amplitudes, validating the useof the method for linear earthquake site response Molnar et al. (2007).
Ohmachi et al. (1991) and Lermo and Chávez-García (1994) applied the H/V ratio method toanalyze microtremor measurements. Lermo and Chávez-García (1993) used it to assess theempirical function of the S-wave, part of an earthquake record, obtained from three cities in30

27

March 2012

Mexico. Their results clearly indicated that the H/V ratio could provide a robust estimate of
frequency and amplitude of the first resonant mode, albeit not of the higher modes. In themeantime, Field and Jacob (1993) and Field et al. (1995) considered the response of
sedimentary layers to ambient seismic noise and claimed that the H/V ratio method has been
an effective and reliable tool to identify the fundamental resonance frequencies of all layered
sedimentary basin. Further evidence has been given by Suzuki et al. (1995) who used both
microtremor and strong-motion data in Hokkaido, Japan and ascertained that the peakfrequency determined by the H/V ratio seemed to correspond with the predominant frequency
estimated from the thickness of an alluvial layer. Based on numerical calculations, manyother researchers (Lermo and Chávez-García, 1993, 1994; Lachet and Bard, 1994; Dravinski
et al., 1996) have shown that the H/V ratio method is obviously able to predict fundamental
resonant frequency well. Huang et al. (2002) found that the ground vulnerability index (Kg)values in the liquefied areas have been higher than those in the neighboring areas withoutliquefaction at 42 points in central Taiwan. This study shows supporting evidence for the firsttime that the H/V ratios of microtremor can be a good alternative indicator for an area’s
potential for liquefaction. Site amplification characteristics can be evaluated by one-point
two-component surface recordings of earthquake ground motion, in a similar manner as
proposed by Nakamura for microtremor (Ansary et al., 1996).
For seismic microzonation of Dhaka city, microtremor observation has been carried out atfourty five reclaimed and Non-reclaimed area in and around the Dhaka city. Standard
Penetration Test (SPT) has been executed at twenty seven locations of these points. Shear
Wave velocity has been used to develop soil model. Six PS logging as well as SPT data,
which are executed within the study area (CDMP, 2009) and eight Shear Wave Velocity as
well as SPT data has been collected (Hossain, 2009). The SPT boring data of BUET campus
has also been collected. Empirical SPT correlation developed by Ansary et al. (2010) has
been used in this study to convert Field SPT N-value to Shear Wave Velocity. Finally, Soilmodel has been developed using 1D Response Analysis using the programme SHAKE.
Comparison between microtremor and theoretical Transfer Function by the programme
SHAKE has been carried out.

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For Resonance analysis microtremor observation has been carried out at one hundred andthirty two selected locations within BUET campus and fourty five buildings in BUET campus.
Finally, seismic damage has been assessed using Nakamura (2000)’s Vulnerability Index.
Although it is not possible to prevent such calamities, it is however, possible to mitigate theimpacts of earthquake. Specific roles and responsibilities relating to earthquake hazard shouldbe emphasized in our disaster mitigation plan. Bangladesh is a country characterized by amoderate seismicity with almost no resources available for large scale seismic hazard studies.
The objective of this thesis is to analyze seismic hazard in and around Dhaka city in terms ofdynamic charactersistics of soil (Predominant frequency and Amplification).
1.2

OBJECTIVE OF THE RESEARCH

The main purpose of this research is to estimate the dynamic response of soil using
microtremor H/V technique. Dynamic response of soil is very important for the seismic
hazard assessment of densely populated urban city like Dhaka. In order to carry out thisresearch specific locations have been selected.
The followings are the specific objectives of the research:(i)

To examine the effectiveness of using Horizontal to Vertical Spectral Ratio (H/V) of
microtremor to estimate predominant frequency and amplification.

(ii)

To develop soil models to obtain transfer function using the computer programme
SHAKE.

(iii)

To compare microtremor results with ID response analysis of SHAKE.

(iv)

To justify resonance criterion between soil and structure in the study area.

(v)

To estimate damage of soils using Nakamura’s (2000) Vulnerability Index (Kg).

1.3

STUDY AREA AND SITE SELECTION

To check the stability of microtremor observation fourteen locations of West Palashi within
BUET campus has been selected. For this purpose, observation has been made at different
time instants within a day from morning to midnight. After checking the stability of
microtremor data, microtremor observation has been carried out at one hundred and eighteen
additional locations within the BUET campus, where latitude varies from 23°43'16.58" N to
23°43'59.44" N and longitude varies from 90°23'13.31"E to 90°23'43.56" E (see Figure 1.1).
32

29

March 2012

To assess the characteristics of soils in the reclaimed and non-reclaimed area in and aroundthe Dhaka city fourty five locations have been selected to obtain microtremor observation(See Figure 1.2). These microtremor observation sites are situated at latitude from2338΄15.10 N to 2356΄46.54 N and longitude from 9020΄24.92 E to 9033΄50 E.
Among these fourty five locations, at twenty seven locations sub-soil investigation has been
carried out. The geology and geomorphology of the study area has been illustrated in section
1.5 of this chapter.

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BNUS Annual Report-2011

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Figure 1.1: One hundred and thirty two microtremor observation in the freefield locations of BUET campus.

34

31

March 2012

Figure 1.2: Fourty five selected locations for microtremor observation in and around the
Dhaka city. (Source: Google map)

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1.4

OUTLINE OF METHODOLOGY

The amplitude ratio (H/V) of horizontal to vertical spectra of microtremor has become
popular to determine predominant period and amplification of a site. It is well known that,
degree of damage during earthquakes strongly depends on dynamic characteristics ofbuildings as well as amplification of seismic waves. Among the other time consuming
and expensive approaches, microtremor is the easiest and cheapest way to understand the
dynamic characteristics of soil as well as structural element. In a short period of time it
provides several information including natural frequency, amplification and vibration
characteristics of soil and structure at different frequencies.
Following steps have been followed in this research:
A. Microtremor Analysis
Microtremor observation has been carried out in selected locations of Dhaka city. Each
record comprises of three components, viz., EW, NS and UD. For spectral analysis threenoise-free segments of 20.48s of the recordings have been taken at 100 Hz instrumental
sampling. At each point of sensor location microtremor data recording have been carriedout at different time of the day.
Time domain data is not suitable for the clear identification of soil response due toambient noise. This is why First Fourier Transformation (FFT) has been applied on thetime domain records. After smoothing the corresponding spectra, spectral ratio (H/V)
technique have been applied to derive transfer functions. The applied sequences are given
below:
1.

FFT Transformation:

At first, Fourier spectra of the two horizontal directions (East-West and North-South) andthe vertical component (Up-Down) have been calculated.
2. Smoothing of the Spectra
After Fast Fourier transformation (FFT), the combined horizontal and vertical spectra
have been digitally filtered applying a logarithmic window with a suitable bandwidthcoefficient. These filtering techniques have been applied to reduce the distortion of peak
amplitudes.
3. Calculation of the Soil Response functions:33

33

March 2012

The smoothed combined horizontal spectrum have been divided with the smoothed
vertical component to plot Horizontal to vertical spectral ratio (H/V) which will provide
the desired predominant frequency and corresponding amplification factor of theinvestigated portions (20.48 s) of records.
4. Estimation of Predominant Frequency and Amplification:
After calculating three sets of the H/V ratios at selected grid, they have been normalized
to obtain a relatively non-biased site specific H/V ratio. Then, Normalized H/V ratios at
different time of the day have been plotted in Logarithmic window. From this normalized
H/V ratio the predominant frequency and corresponding amplification factor of this site
have been taken.
B. Soil Investigation
Twenty seven Standard Penetration Test (SPT) have been carried out for subsoil
investigations at study locations. Empirical soil correlation has been used to convert SPT
N-value to Shear Wave Velocity.
C. Develop Soil Model for Site Response Analysis
Soil model of investigated locations have been developed using the program SHAKE.
D. Comparison between Theoretical Transfer Function with Microtremor H/V ratio
Theoretical transfer function obtained from one dimensional soil response analysis using
the programme SHAKE has been compared with microtremor H/V ratio. This output data
have been used for estimation of predominant frequency and site amplification.
The brief methodology of this research has been shown through a flowchart in Figure 1.3.

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BNUS Annual Report-2011

ICUS Report 59

Stability check ofMicrotremor
Site Selection forMicrotremor Study
BUET campus(132 locations)

Outside of BUET
Campus (45 locations)

Microtremor data
recordingSub-soil
Investigation

Microtremor data
Analysis

Soil Model using the
programme SHAKE

H/V ratio

CompareTransfer Function

Damage Assessment
Nakamura’s Vulnerability
Index (Kg) of soil

Resonance of Building

Figure 1.3: Flow chart for Microtremor Research in the Dhaka city.
The whole research has been carried out in the following phases according to Figure 1.3.:a.

Stability of microtremor data has been carried out at fourteen different locations indifferent time instants from morning to midnight within a day. Time domain data
has been converted to frequency domain data because time domain data do notshow dynamic properties of soil. So, Fourier transformation of three segments of
20.48 s long time history data along EW, NS and UD of these locations has been
carried out. Then, the stability of Fourier spectra data has been checked at
different time instants. Fourier spectra data do not show the amplification andstable data for site response. Therefore, Horizontal to Vertical spectral ratio data
35

35

March 2012

has been calculated from these Fourier spectra data. The mean H/V spectra datawith half standard deviation with mean have been calculated and shown inlogarithmic window. Stability of H/V ratio data at fourteen locations has been
compared. H/V ratios are more stable than Fourier spectra data. From thisconclusion, the analysis of Horizontal to Vertical spectra ratio (H/V) has been
applied for microtremor data analysis.
b. For details study of microtremor observations, one hundred and thirty two points
have been selected within BUET campus from morning to midnight. These data
are located in the same geological units. However, from the analysis of these data,
most of the locations did not show significant amplification due to the presence ofstiff soil within BUET campus. For this reason, fourty five locations outside
BUET have been selected. These locations include both reclaimed and nonreclaimed areas of Dhaka city.
c. For the assessment of soil response of reclaimed and non-reclaimed sites outside
the BUET campus microtremor observation has been conducted at fourty fivelocations in and around the Dhaka city in consideration of different geologicalunits. Microtremor observation has been carried out about ten geomorphic units(According to Figure 2.2) and nine geomorphic units (According to Figure 2.3).
d. Field investigations include 27 (Twenty seven) boreholes up to a depth of 20 m
out of 45 locations outside BUET. For another 15 locations SPT-N value data
have been collected from other sources. PS-loggings at 6 locations and SSMM
data at 8 locations for Shear Wave Velocity exist among these locations.
e. Soil model has been developed at 42 locations out of 45. Among these locations,for 14 locations, shear-wave data have been directly obtained from the field. For
rest 28 locations, empirical soil correlations developed by Ansary et al. (2010) andother empirical correlations (After TC4, ISSMFE, 1993) have been used toconvert SPT-N value to shear-wave velocity.
f.

Microtremor H/V ratio has been compared with the transfer function obtained
from 1D soil response analysis at 42 locations.

g. Microtremor observation at fourty five buildings in the BUET campus havealready been carried out. The predominant frequency of these observed building

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BNUS Annual Report-2011

ICUS Report 59

and adjacent soil obtained in this study has been compared to establish theresonance criteria.
h. For the damage assessment of soils at the observed locations Nakamura’s (2000)

Vulnerability Index (Kg) has been used.

DATA COLLECTION AND ANALYSIS
2.1 GENERAL
Damage in recent earthquakes showed that local site conditions have a significant effecton ground motion. Site response studies play an important role in seismic microzonation
studies. The application of microtremor is to determine dynamic characteristics(predominant frequency and amplification factor). Nowadays microtremor measurements
are generalized in site characterization due to their simplicity, low cost and minimal
disturbance to other activities.

P37

In the traditional spectral ratio method, ��//�� , site and source effects are estimated fromobservation at a reference site. In practice, adequate reference site are not always
P78
available especially in flat areas where exposed rock is not available. Therefore, methods
2.4…..
を次のページに移動
have been developed that do not needreferencesites (Bard 1994). Several recent
applications of this technique have proved
P88 to be effective in estimating predominantfrequency (Field and Jacob 1973; Ohmachi et al. 1994) and amplification factors (Lermo������ ���� ���� = ������ = �� ��� , ��� ��� ����� of microtremor��� H/Vand Chavez-Garcia 1994; Konno and Ohmachi
1995). The reality
technique for site response analysis has been discussed in Chapter 2.

Several methods have been proposed forP95
spectral calculation of ground motions including
microtremor. Fourier spectrum is the most convenient one that is used widely. Some����� � ����investigations showed that different methods give similar results (Dimitriu et al. 1998).
������ �����
However some researchers declare that= a�suitable
spectral method gives more reliable�

results (Ghayamghamian and Kawakami 1997). That’s why three segments of spectra
�
�
�����
� ����
have been selected to compute the mean segmental
cross spectra. Standard deviation of�������deviation
mean has also been calculated to show ��
theof mean value from six spectra in�East-West and North-South direction. Subsoil investigation has also been executed in the

P98
test location to compute the Shear Wave
Velocity which has been used in 1D response
analysis using the programme SHAKE.

���� �����

– � �

�����

�

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�

���

���

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�

=

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�

�� � ��� �

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���

���

�

���

���

��

��� �

���

���

37

�

March 2012

2.2

LOCATION OF INVESTIGATED SITES WITHIN THE
STUDY AREA

2.2.1 Geological and Geomorphological classification
Local site conditions substantially affect the characteristics of seismic waves during
earthquakes. Soft alluvial deposits tend to amplify certain frequencies of ground motionand extend the duration of motion which may cause further earthquake damage. The
expected variation in the ground motion, according to the geological site conditions, makeit necessary to perform a more detailed seismic hazard assessment for a metropolitan area.
To accurately identify the variation of seismic hazards at different locations within themetropolis, one may conduct seismic microzonation that requires subdividing an area into
zones with respect to the geological characteristics of the sites.
Therefore, microtremor measurement at 45 selected locations in and around Dhaka city as
well as 132 locations within BUET campus has been executed in consideration ofdiversified geological and geomorphological units. Most of the locations in and around
Dhaka city are situated in various geomorphological units. But, all of the selected points
in BUET campus are located in the same geological and geomorphological unit. 45
selected locations have been shown in Figure 2.1.
Two geomorphological maps of Dhaka city from different source are shown in Figure 2.2
and Figure 2.3. Microtremor measurements points have been superimposed in these two
geomorphological maps. Some locations are situated out of the geomorphological map in
Figure 2.2 and Figure 2.3. The geomorphological classifications of these locations havebeen presented in Table 2.1. Table 2.1 represents 45 test locations, their ID, latitude,
longitude and geomorphological classification according to Figure 2.2 and Figure 2.3.
The test locations have been classified in different geomorphological unit. Figure 2.2 hasbeen divided by 15 geomorphological units. On the other hand, Figure 2.3 has been
divided by 22 geomorphological units. 132 selected locations of BUET campus in Figure
2.55 has been classified as Upper Modhupur Terrace according to Figure 2.2 and Higher
Pleistocene Terrace according to Figure 2.3.

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BNUS Annual Report-2011

ICUS Report 59

SBH 01
SBH 02 SBH 04
SBH 03
SBH 07 (A) SBH 05
SBH 08
SBH 07 (B)SBH 06
SBH 10 (A)SBH 09
SBH 11
SBH 10 (B)SBH 14(C)SBH 13

SBH 12 (B)SBH 19
SBH 18
SBH 17 (C)SBH 14(B)SBH 17(A)SBH 17(B)SBH 12 (A)SBH 16

SBH 21

SBH 26
SBH 22

SBH 25

SBH 23 SBH 24
SBH 28

SBH 38
SBH 27
SBH 14 (A)SBH 29
SBH 30
SBH 31

SBH 36

SBH 32

SBH 35

SBH 34

SBH 33
SBH 37

Figure 2.1: Microtremor observation at fourty five selected locations in and around Dhaka
City.

39

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March 2012

From Table 2.1, 45 selected locations are situated in 10 different geomorphic units
according to Figure 2.2. On the other hand, same 45 locations are located in 9 different
geomorphic units according to Figure 2.3. Most of the points in Table 2.1 have been
selected on the basis of recent filling. But, there is no specific classification ofgeomorphological unit of filling area in Figure 2.2. However, Figure 2.3 shows specificgeomorphic unit of recent filling. So, both Figure 2.2 and Figure 2.3 have been justified
to classify 45 sites in different geomorphic units.
Table 2.1: Geological and Geomorphological classification of the study area

40

Location

Latitude

ID

1

SBH01

National
University

2356΄46.54

9022΄43.93

2

SBH02

Board Bazaar,
Gazipur

2356΄18

9023΄58

3

SBH03

Kaunia, BoroBari, Moddopara

2355΄37

9023΄03

Shallow
Alluvium Gully

4

SBH04

Tongi,
Ershadnagar

23°54'48"

90°24'11"

Lower
Modhupur
Terrace5

SBH05

Tongi BSCIC
area

23°53'37.18"

90°25'13.35"

6

SBH06

Abdullahpur

2352΄31

9024΄01

Lower
Modhupur
Terrace
Deep Alluvium
Gully

7

SBH07(A)2353΄31.13

9023΄53.39

Shallow
Alluvium Gully

8

SBH07 (B)2352΄59.96

9023΄37.91

Shallow
Alluvium Gully

Deep alluvial
valley9

SBH08

Ijtema field(North and East
side)
Ijtema Field(South and West
side)
Ashulia Toll
Plaza

HighlyErosional
Lower
Pleistocene
terrace
Deep alluvial
valley23°53'25.40"

90°21'54.61"

Deep Marshly
Land

Deep marshly
land

37

Longitude

GeomorphologicalClassification

SL.
No.

After Figure
2.2
Upper
Modhupur
Terrace
Upper
Modhupur
Terrace

After Figure
2.3
High
Pleistocene
terraceModeratelyHigh
Pleistocene
terraceModeratelyHigh
Pleistocene
terraceModeratelyHigh
Pleistocene
terraceThick fill

BNUS Annual Report-2011

ICUS Report 59

SL.
No.

ID

10

SBH9

Uttar Khan

23΄52΄30

9025΄28

11

SBH10(A)
SBH10(B)
SBH11

Uttara Phase 3( North side)
Uttara Phase 3(South side)
Azampur School,
Uttara2352΄22

9021΄40

2351΄15

9021΄16

2352΄03

9024΄04

14

SBH12 (A)

Mirpur DOHS
(South side)2349΄59

9022΄42

15

SBH12 (B)

Mirpur DOHS
(North side)

2350΄11

9022΄42

16

SBH13

2350΄49

9025΄37

17

SBH14(A)Ashiyan city,
Askona, Dakkhin
Khan
Purbachal-1,
Randokpur Hazibari, Rupganj

2345΄03

9031΄17

18

SBH14(B)

Purbachal-2,
American City

2349΄33

9033΄50

19

SBH14(C)

Purbachal Picnic
Park, Gazipur

2351΄28

9031΄14

20

SBH15
SBH16

Adjacent toMirpur Zoo
Field Ground,
Pallabi

2349΄04.14

9020΄29.63

2349΄06

9022΄08

22

SBH17 (A)Block-B,
Basundhara

2348΄38

9025΄54

23

SBH17 (B)

Block-D,
Basundhara

2349΄00.49

9026΄12.95

12
13

21

Location

Latitude38

Longitude

GeomorphologicalClassification
After Figure
2.2
Lower
Modhupur
Terrace
Deep Marshly
Land
Deep Marshly
Land
Upper
Modhupurterrace
Upper
Modhupurterrace
Upper
Modhupurterrace
Swamp/Depres
sion

After Figure
2.3
HighlyErosional
Lower
Pleistocene
terraceModerately
thick fill
Moderately
thick fill
ModeratelyHigh
Pleistocene
terraceHigh
Pleistocene
terraceHigh
Pleistocene
terraceModerately
Thick fill

Lower
Modhupur
Terrace
Lower
Modhupur
Terrace
Lower
Modhupur
TerraceNatural levee

Thick fill

Upper
Modhupurterrace
Lower
Modhupur
TerraceThick fill

Back swamp

Thick fill
Thick fill
Thick fill

ModeratelyHigh
Pleistocene
terraceModeratelyHigh
Pleistocene
terrace41

March 2012

SL.
No.

ID

24

SBH17 (C)Block-H,
Basundhara

2349΄19

9026΄34

25

SBH18

Civil Aviation
Quarter

23050΄33.61

90025΄11.22

26

SBH19
SBH20
SBH 21
SBH22
SBH23
SBH24

Kuril Flyover

27
28
29
30
31

32
33
34
35
36

37
38
39
40
41
42
43

42

Location

Sarengbari,
Mipur-2
Purachal, Uttar
Badda
City Corporation,
Gabtoli
AdaborLatitudeLongitude

GeomorphologicalClassification
After Figure
2.2
Back swamp

Upper
Modhupurterrace2349΄41.51 9026΄32.06 Swamp/Depressi
on2348΄03.24 9020΄47.10 Swamp/Depression
2346΄51
9026΄29
Back swamp

After Figure
2.3
ModeratelyHigh
Pleistocene
terrace
HigherPleistocene
terraceThick fill2346΄41.99

9020΄24.92

Flood plain

2346΄09.75

Shallow
alluvium Gully
Upper
Modhupur
Terrace
Flood plain

Deep marshly
land
Deep marshly
landModerately
thick fill
Moderately
thick fill
HigherPleistocene
terraceThick fill
Moderately
thick fill
Thick fill

Agargoan Trade
Fair area

2346΄10.56

9021΄37.62
9022΄42.73

SBH25
SBH26
SBH27
SBH28
SBH29

Aftab Nagar
Housing Project
Umme Had
Nagar, Nadda
South Banasree2346΄04.98

9026΄03.22

2347΄57.17

9025΄41.61

2345΄07.17

9026΄45.36

Swamp/Depres
sion
Flood plain

Basila Garden
City
Royer Bazar
Boddhobumi

2345΄10.29

9020΄42.36

Back Swamp

Thick fill

2344΄54

9021΄28

River Bar

SBH30
SBH31
SBH32
SBH33
SBH34
SBH35
SBH36

Kalunagar,
Hazaribagh
Rab-10, Plot,
Kamrangirchar
Sosan Ghat,
Kamrangirchar
BasundharaRiver view
Matuail, Demra

2343΄38.50

9022΄08.62

River Bar

Gently sloping
Erosional
terrace edge
Thick fill

2342΄57.58

9022΄42.11

River Bar2342΄44.81"
2339΄10

9023΄26.51

Natural levee9026΄09

Flood plain

2343΄18.24

9028΄16.48

Jilmil Project,
EquriaRajendapur

2340΄33.40

9024΄08.42

2339΄25

9022΄58

Swamp/Depres
sion
Shallow
alluvium Gully
Deep alluvium
Gully

39

Moderately
thick fill
Deep Marshly
landModerately
Thick fill
Younger active
floodplain
Thick fill
Thick fill

BNUS Annual Report-2011

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SL.
No.

ID

44

SBH37
SBH38

45

Location

LatitudeLongitude

GeomorphologicalClassification

Bramangaon

2338΄15.10

9027΄37.35

After Figure
2.2
Flood plain

Meradia, Uttar
Banasree2345΄43.57

9026΄19.67

Flood plain

After Figure
2.3
Deep alluvial
valleyThick fill

According to Figure 2.2, 45 selected locations have been classified into following groups:
8-Upper Modhupur Terrace [ SBH 01; SBH 02; SBH 11; SBH 12(A); SBH 12(B); SBH
16; SBH 18 ; SBH 24], 5-Shallow Alluvium Gully [ SBH 03; SBH 07(A); SBH 07(B);SBH 23; SBH 35], 7-Lower Modhupur Terrace [ SBH 04; SBH 05; SBH 09; SBH 14(A);SBH 14(B); SBH 14(C); 17(A)], 2-Deep Alluvium Gully ( SBH 06; SBH 3), 3-DeepMarshly Land [SBH 08; SBH 10(A); SBH 10(B)], 5-Swamp/Depression ( SBH 13; SBH
19; SBH 20; SBH 26; SBH 34), 2-Natural Levee ( SBH 15; SBH 32), 4-Back Swamp[ SBH (B); SBH 17(C); SBH 21; SBH 28], 6-Flood Plain (SBH 22; SBH 25; SBH 27;
SBH 33; SBH 37; SBH 8) and 3- River Bar (SBH 29; SBH 30; SBH 31).

The common geomorphic unit is Deeply Marshly Land, which is found at SBH 8(Ashulia Toll Plaza, Latitude-23°53'25.40" and Longitude- 90°21'54.61") in both Figure
2.2 and Figure 2.3. Out of 45 selected locations, 8 selected locations have been classified
into Upper Modhupur Terrace geomorphological unit, which is the most predominantgeomorphological unit in Figure 2.2. The second most common geomorphological unit isLower Modhupur Terrace. However, it is not possible to classify filling area because of
not having any geomorphological unit in Figure 2.2. Therefore, Figure 2.3 is required tojustify these locations in actual geomorphic unit.

40

43

March 2012

SBH 01
SBH 02
SBH 03

SBH 04

SBH 08

SBH 07 (A)SBH 05

SBH 07 (B)SBH (10 A)

SBH 09

SBH 06

SBH 11

SBH 10 (B)SBH 14(C)SBH 13
SBH 12 (B)SBH 18
SBH 19

SBH 12 (A)SBH 15

SBH 14(B)SBH 17 (C)SBH 17 (B)SBH 20

SBH 17 (A)SBH 26

SBH 22

SBH 21

SBH 23

SBH 25

SBH 28

SBH 14(C)SBH 38
SBH 27

SBH 29BUET CAMPUS
SBH 30

SBH 32
SBH 34

SBH 31

SBH 35
SBH 36
SBH 33

SBH 37Microtremor Test Location

Figure 2.2: Superimposed study points on geomorphological map of Dhaka city. (Source:
Geological Survey of Bangladesh, GSB)

44

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ICUS Report 59

SBH 01

SBH 02
SBH 04

SBH 03

SBH 05

SBH 07 (A)SBH 08

SBH 07 (B)SBH 10 (A)SBH 06

SBH 09
SBH 11
SBH 14(C)SBH 10 (B)SBH 13

SBH 18

SBH 12 (B)SBH 19

SBH 12 (A)SBH 15

SBH 14 (B)SBH 17 (C)SBH 16

SBH 17 (B)SBH 17 (A)SBH 20

SBH 26
SBH 22

SBH 21

SBH 23

SBH 25

SBH 28

SBH 38

SBH 29

SBH 27

SBH 14 (A)BUET CAMPUS
SBH 30
SBH 32
SBH 31

SBH 36

SBH 34

SBH 35

SBH 33

SBH 37Microtremor Test Location

Figure 2.3: Superimposed study points on Geomorphological Map of Dhaka City.
(Source: A. S. M. Maksud Kamal)

41

45

March 2012

According to Figure 2.3, 45 selected locations are classified into following groups:
14-Thick fill [SBH 05; SBH 14(A); SBH 14(B); SBH 14(C); SBH 15; SBH 16; SBH 19;
SBH 25; SBH 27; SBH 28; SBH 30; SBH 35; SBH 36; SBH 38], 8-Moderately Thick fill
[SBH 10(A); SBH 10 (B); SBH 13; SBH 22; SBH 23; SBH 26; SBH 31; SBH 33], 5Higher Pleistocene Terrace [SBH 01; SBH 12(A); SBH 12(B); SBH 18; SBH 24], 7Moderately Higher Pleistocence terrace [SBH 02; SBH 03; SBH 04; SBH 11; SBH
17(A); SBH 17(B); SBH 17(C)], 3-deep alluvium valley [07(A); 07(B); SBH 37], 4-DeepMarshly Land (SBH 08; SBH 20; SBH 21; SBH 32), 2-Highly Erosional Lower
Pleistocene Terrace (SBH 06; SBH 09), 1-Younger active flood plain (SBH 34) and 1Gently Sloping Erosional Terrace (SBH 29).

Out of 45 sites, the most predominant geomorphological unit is Thick fill, which is foundin 14 locations in Figure 2.3. The second most common geomorphological unit ismoderately thick fill. The geomorphological unit of Moderately Higher Pleistocene
Terrace, which is 7, is higher than Higher Pleistocene Terrace.
Therefore, it can be said that the majority of the microtremor test locations are situated inrecent fill area.
2.2.2 Sub-Soil Characteristics
Sub-soil investigation is necessary for the analysis of dynamic characteristics of soil.
Shear wave velocity (SWV) is used to develop soil model. For this study Standard
Penetration Test (SPT) has been carried out at 27 locations in and around the Dhaka city.
SPT data has been collected from other sources as well. SPT is conducted in the area
following procedure described in ASTM D1586. Shear wave velocity from 6 PS loggings
as well as SPT data has been collected (CDMP, 2009). SWV from Small Scale
Microtremor Measurement (SSMM) as well as SPT data has been collected at the
microtremor Test location (Hossain, 2009). Finally, SWV has been estimated using SPT
and SWV correlation (Ansary et al., 2010) where there is no SWV test result. The otherthree soil correlations (Ohta and Goto 1978; Imai and Yoshimura 1970; Ohba and

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Toriumi 1970) have been used to compare SWV. Various sub-soil investigation results
have been presented in this section and Appendix-A.
(1)
Sub-Soil Characteristics of National University, Tongi ( SBH 01)
SPT Results
The soil profiles of the borehole are shown in Table A3.1. From the disturbed soil sample,
the borehole consists of two soil layers. The silty clay layer, which is light brown medium
stiff and high plastic, varies from 0 to 5.0 m from EGL. On the other hand, the silty clay
layer, which is light brown to brown stiff to very stiff, exists from 5 to 18.5 m from EGL.
The uncorrected SPT N-value of this site varies from 4 to 19. The SPT-N value of
medium stiff light brown silty clay varies from 4 to 7. The SPT N-value of stiff to very
stiff light brown to brown silty clay layer varies between 7 and 19.
Shear Wave Velocity Results
There is no PS logging and SSMM test result in National University, Tongi. Therefore,shear wave velocity has been estimated using correlation. Table A3.1 shows estimatedSWV using different soil correlation. According to soil correlation proposed by Ansary etal. (2010), the shear wave velocity varies from 135 to 229 m/sec. From soil correlation
developed by Ohta and Goto (1978), SWV exists from 123 to 261 m/sec. On the other
hand, SWV of Ohba and Toriumi (1970), which varies from 129 to 206 m/sec, showsslightly higher value than Imai and Yoshimura (1970), which shows ranging between 120
and 201 m/sec.
(2)
Sub-Soil Characteristics of Board Bazaar, Gazipur ( SBH 02)
SPT Results
The soil profiles of the borehole are shown in Table A2.2. The borehole consists of four
soil layer. The silty clay layer, which is soft light brown and high plastic, varies from 0 to
2.50 m from EGL. The silty clay of stiff light brown with high plastic exists from 2.5 to
8.5 m from EGL. The medium dense brown silty fine sand varies from 8.5 to 10.0 m. The
stiff to very stiff light brown silty clay varies between 10 and 20 m. The uncorrected SPT
N-value of this site varies from 3 to 18. The SPT-N value of stiff light brown silty clay
varies from 5 to 9. The SPT N-value of stiff to very stiff light brown to brown silty clay
varies from 15 to 18.
Shear Wave Velocity Results
There is no PS logging and SSMM test result in Board Bazaar, Gazipur. Therefore, shear
wave velocity has been estimated using soil correlation. Table A2.2 presents SWV using
112

47

March 2012

different methods. From soil correlation proposed by Ansary et al (2010), SWV varies
from 150 to 247 m/sec. From SPT correlation developed by Ohta and Goto (1978), SWV
exists from 117 to 267 m/sec.

(3)

Sub-Soil Characteristics of Kaunia, Boro Bari, Moddopara ( SBH 03)

SPT Results
The soil profiles of the borehole are shown in Table A2.3. The borehole consists of fivesoil layers. The grey loose silty fine sand varies from 0 to 2.0 m from EGL. The stiff tovery stiff light brown Silty Clay with trace fine sand high plastic exists from 5.5 to 15.5 mfrom EGL. The medium dense brown silty fine sand varies from 8.5 to 10.0 m. The very
stiff brown clayey silt with fine sand med. compress varies between 15.5 to 18.5 m. The
uncorrected SPT N-value of this site varies from 4 to 28. The SPT-N value of stiff to very
stiff light brown silty clay with trace fine sand high plastic varies between 8 and 18. The
SPT N-value of very stiff brown clayey silt with fine sand medium compress layer exists
between 18 and 24.
Shear Wave Velocity Results
There is no PS logging and SSMM test result in Kaunia, Boro Bari. So, the value of shear
wave velocity has been estimated using soil correlation. Table A2.3 presents SWV using
different methods. From soil correlation proposed by Ansary et al. (2010), the shear wave
velocity varies from 135 to 261 m/sec. From SPT correlation developed by Ohta andGoto (1978), SWV exists between 103 and 237 m/sec.
(4)
Sub-soil Characteristics of Tongi, Ershadnagar ( SBH 04)
SPT Results
The soil profile of the borehole has been demonstrated in Table A2.4. The borehole
consists of six soil layers. The medium stiff to stiff light brown silty Clay with trace grits
and fine sand high plastic varies from 0 to 3.5 m from EGL. The medium dense to loose
brown sandy silt with trace mica exists from 6.5 to 9.5 m from EGL. The medium densebrown silty fine sand with trace mica varies from 8.5 to 10.0 m. The stiff grey to lightbrown silty clay with fine sand high plastic varies between 12.5 to 17.0 m. The
uncorrected SPT N-value of this site varies from 6 to 17. The SPT N-value of stiff tomedium stiff light brown silty clay varies between 2 and 11. The SPT N-value of medium

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dense brown silty fine sand layer exists from 9 to 12. The SPT N-value of stiff grey tolight brown silty clay varies between 10 and 12.

Shear Wave Velocity Results
Table A2.4 represents shear wave velocity using four different methods. From soil
correlation proposed by Ansary et al. (2010), SWV varies from 182 to 221 m/sec. FromSPT correlation developed by Ohta and Goto (1978), SWV exists from 132 to 244 m/sec.
On the other hand, SWV of Ohba and Toriumi (1970), which varies from 146 to 202
m/sec, shows slightly higher value than Imai and Yoshimura (1970), which shows
ranging between 137 to 194 m/sec.
(5)
Sub-Soil Characteristics of Tongi BSCIC area ( SBH 05)
SPT Results
The soil profile of the borehole has been shown in Table A2.5. The borehole consists ofsix soil layers. The grey loose silty Fine Sand with trace mica varies from 0 to 3.5 m from
EGL. The soft dark grey silty clay with trace organic matter exists from 3.5 to 6.5 m from
EGL. The medium stiff to stiff light brown to grey silty clay trace fine sand varies from
6.5 to 9.5 m. The medium dense brown silty fine sand with trace clay varies between 12.5
to 15.5 m. The uncorrected SPT N-value of this site varies from 4 to 37. The SPT N-valueof soft dark grey silty clay varies from 4 to 5. The SPT N-value of medium dense brownsilty fine sand varies from 13 to 20. The SPT N-value of medium dense to dense grey
silty fine sand varies between 20 and 37.
Shear Wave Velocity Results
Table A2.5 represents shear wave velocity using four different methods. From soil
correlation proposed by Ansary et al. (2010), SWV varies from 135 to 287 m/sec. FromSPT correlation developed by Ohta and Goto (1978), SWV exists from 103 to 253 m/sec.
On the other hand, SWV of Ohba and Toriumi (1970), which varies from 129 to 257
m/sec, shows slightly higher value than Imai and Yoshimura (1970), which shows
ranging between 120 to 250 m/sec.
(6)
Sub-Soil Characteristics of Abdullahpur ( SBH 06)
SPT Results
The soil profile of the borehole is presented in Table A2.6. The borehole consists of four
soil layers. The top layer of soil exist rubbish which varies from 0 to 2 m. The stiff
reddish brown silty clay trace grits and fine sand high plastic exists from 2 to 5 m from
114

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EGL. The stiff brown silty clay trace fine sand high plastic varies from 5 to 8 m. The
medium dense to very dense brown silty clay trace mica varies between 8 and 20 m. The
uncorrected SPT N-value of this site varies from 11 to 50. The SPT-N value of stiff
reddish brown silty clay varies from 5 to 12. The SPT N-value of medium dense to very
dense brown silty clay varies between 10 and 50.
Shear Wave Velocity Results
Table A2.6 represents shear wave velocity using four soil correlations. SWV varies from122 to 318 m/sec (Ansary et al., 2010). SWV exists between 90 and 266 m/sec (Ohta andGoto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which varies from
118 to 282 m/sec, shows slightly higher value than Imai and Yoshimura (1970), whichshows ranging between 109 to 276 m/sec.
(7)
Sub-Soil Characteristics of Ijtema Field ( SBH 07 (A))
SPT Results
The soil profile of the borehole is shown in Table A2.7. The borehole consists of four soil
layers. The top layer of soil exist medium stiff to stiff light brown silty clay which varies
from 0 to 5 m. The medium dense to dense brown silty fine sand trace clay varies
between 8 and 20 m. The uncorrected SPT N-value of this site varies from 5 to 45. The
SPT-N value of medium stiff to stiff light brown silty clay varies from 5 to 11. The SPT
N-value of medium dense to dense brown silty fine sand varies from 17 to 45.
Shear Wave Velocity Results
Table A2.7 represents shear wave velocity using four different methods. SWV varies
from 172 to 307 m/sec (Ansary et al., 2010). SWV exists between 128 and 262 m/sec(Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which
varies from 138 to 273 m/sec, shows slightly higher value than Imai and Yoshimura(1970), which shows ranging between 129 to 267 m/sec.
(8)
Sub-Soil Characteristics of Ashulia Toll Plaza ( SBH 08)
SPT Results
The soil profile of the borehole is shown in Table A2.8. The borehole consists of four soil
layers. The top layer of soil exists filling grey very loose silty fine sand which varies from0 to 2 m. The medium dense to dense reddish brown to brown silty fine sand varies
between 5 and 20 m. The uncorrected SPT N-value of this site varies from 1 to 40. The
SPT-N value of medium dense to dense reddish brown to brown silty fine sand varies
between 5 and 39.

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Shear Wave Velocity Results
Table A2.8 represents shear wave velocity using four different methods. SWV varies
from 84 to 295 m/sec (Ansary et al., 2010). SWV exists between 82 and 256 m/sec (Ohtaand Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which varies
from 84 to 264 m/sec, shows slightly higher value than Imai and Yoshimura (1970),
which shows ranging between 76 and 257 m/sec.
(9)
Sub-Soil Characteristics of Uttar Khan (SBH 9)
SPT Results
The soil profiles of the borehole are shown in Table 2.2. The only thick clay layer exists
in this borehole. The thick clay layer exists from 0 to 24 m. The SPT N-value of clay
layer varies between 14 and 74.
Table 2.2: SPT-N and Shear Wave Velocity at Uttar Khan
Shear wave velocity (m/s) from PS-logging
Depth
Soil
(m) Description
1.5
Clay
3.0
Clay
4.5
Clay
6.0
Clay
7.5
Clay
9.0
Clay
10.5
Clay
12.0
Clay
13.5
Clay
15.0
Clay
16.5
Clay
18.0
Clay
19.5
Clay
21.0
Clay
22.5
Clay
24.0
Clay

SPT-N
Value
20
45
50
40
62
30
14
22
22
24
28
24
24
38
74
44

CDMP
(2009)
412
412
412
412
292
292
292
292
292
292
292
292
292
292
292
292

Ansary etal. (2010)
254
319
329
309
349
285
230
261
261
268
279
268
268
304
367
317

Ohta and
Goto(1978)
162
213
236
240
271
248
225
249
255
265
277
274
279
306
348
322

Imai and
Yoshimura(1970)
204
267
276
257
297
233
182
211
211
217
228
217
217
252
315
265

Ohba
and
Toriumi(1970)
213
273
282
264
302
241
190
219
219
225
236
225
225
259
319
271

Shear Wave Velocity Results
Table 2.2 represents shear wave velocity by direct PS logging (CDMP, 2009) and four
soil correlations. According to PS logging, SWV varies from 292 to 412. From soil
correlation proposed by Ansary et al (2010), SWV varies between 254 and 349 m/sec.
SWV exists from 162 to 348 m/sec (Ohta and Goto, 1978). On the other hand, SWV of116

51

March 2012

Ohba and Toriumi (1970), which varies from 190 to 319 m/sec, shows slightly higher
value than Imai and Yoshimura (1970), which shows ranging between 182 to 315 m/sec.
(10)

Sub-Soil Characteristics of Uttara Phase-3 ( SBH 10 (A))

SPT Results
The soil profile of the borehole is represented in Table A2.9. The borehole consists offive soil layers. The top layer of soil exists filling grey very loose silty fine sand which
varies from 0 to 3.5 m. The stiff grey silty clay trace fine sand varies between 3.5 to 8 m.
The loose to medium dense grey sandy silt with clay varies between 9.5 and 17 m. The
uncorrected SPT N-value of this site varies from 2 to 18. The SPT N-value of the stiffgrey silty clay varies from 3 to 13. The SPT N-value of loose to medium dense grey
sandy silt varies between 9 and 15.
Shear Wave Velocity Results
Table A2.9 represents shear wave velocity using four different methods. SWV varies
from 107 to 225 m/sec (Ansary et al, 2010). From SPT correlation developed by Ohta andGoto (1978), SWV exists between 96 and 197 m/sec. On the other hand, SWV of Ohba
and Toriumi (1970), which varies from 104 to 206 m/sec, shows slightly higher value
than Imai and Yoshimura (1970), which shows ranging between 96 and 197 m/sec.

(11)

Sub-Soil Characteristics of Azampur School, Uttara (SBH 11)

SPT Results
The soil profile of the borehole is shown in Table 2.3. This borehole exist three soil layers.
The top layer exists clay from 0 to 6 m. The sandy silt layer varies between 6 and 13.5 m.
The lower clay layer varies between 13.5 and 20. The uncorrected SPT N-value of thissite varies from 12 to 20. The SPT N-value of the uppermost clay layer varies from 12 to
20. The SPT N-value of silty clay layer varies from 12 to 18. The SPT N-value of thebottom clay layer varies between 13 and 20.

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Table 2.3: SPT-N and Shear Wave Velocity at Azampur School, Uttara
Shear wave velocity (m/s) from SSMM
Depth
Soil
(m) Description
1.5
Clay
3.0
Clay
4.5
Clay
6.0
Clay
7.5
Sandy Silt
9.0
Sandy Silt
10.5
Sandy Silt
12.0
Sandy Silt
13.5
Sandy Silt
15.0
Clay
16.5
Clay
18.0
Clay
19.5
Clay
20.0
Clay

SPT-N
Value
15
20
17
12
12
14
17
18
17
20
13
14
17
18

SSMM
Hossain(2009)
210
208
208
212
230
230
245
265
265
285
285
305
325
325

Ansaryet al.
(2010)
235
254
243
220
196
206
221
225
221
254
225
230
243
247

Ohta and
Goto(1978)
154
186
196
196
172
183
195
202
205
257
243
250
263
267

Imai and
Yoshimura(1970)
186
204
194
173
173
182
194
197
194
204
177
182
194
197

Ohba
and
Toriumi(1970)
194
213
202
181
181
190
202
206
202
213
186
190
202
206

Shear Wave Velocity Results
Table 2.3 represents shear wave velocity using SSMM method (Hossain, 2009) and four
soil correlations. According to SSMM, SWV varies from 208 to 325. SWV varies
between 221 and 247 m/sec (Ansary et al., 2010). SWV exists between 154 and 267
m/sec (Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970),
which varies from 181 to 213 m/sec, shows slightly higher value than Imai and
Yoshimura (1970), which shows ranging between 173 to 204 m/sec.
(12)

Sub-Soil Characteristics of Mirpur DOHS (South side) (SBH-12(A))

SPT Results
The soil profile of the borehole is shown in Table 2.4 (Tanvir, 2009). The borehole exists
three soil layers. The top layer exists filling sand layer from 0 to 3 m. The organic clay
layer varies from 3 to 9 m. The bottom sand layer varies between 9 and 18 m. The
uncorrected SPT N-value of this site varies from 2 to 19. The SPT N-value of theuppermost clayey silt layer varies from 6 to 8. The SPT N-value of sand layer varies from
4.5 to 18.

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Table 2.4: SPT-N and Shear Wave Velocity at Mirpur DOHS (South side)
Shear wave velocity (m/s) from SSMM
Depth
(m)
1.50
3.00
4.50
6.00
7.50
9.00
10.50
12.00
13.50
15.00
16.50
18.00

Soil
Description
Filling Sand
Filling Sand
Organic
Clay
Organic
Clay
Organic
Clay
Organic
Clay
Sand
Sand
Sand
Sand
Sand
Sand

SPTN
Value
3
4

SSMM
Hossain(2009)
78
92

Ansaryet al.
(2010)
122
135

Ohta and
Goto(1978)
98
119

Imai and
Yoshimura(1970)
109
120

Ohba
and
Toriumi(1970)
118
129

1

102

110

121

76

84

2

105

133

144

96

104

3

115

150

162

109

118

5
7
9
10
17
18
20

115
125
135
135
142
142
150

145
163
178
184
221
225
233

153
168
180
187
209
215
223

129
144
157
162
194
197
204

138
154
166
172
202
206
213

Shear Wave Velocity Results
Table 2.4 represents shear wave velocity by direct SSMM method (Hossain, 2009) and
four correlated methods. According to SSMM, SWV varies from 78 to 150. SWV varies
from 110 to 233 m/sec (Ansary et al., 2010). From SPT correlation developed by Ohta
and Goto (1978), SWV exists from 98 to 223 m/sec. On the other hand, SWV of Ohba
and Toriumi (1970), which varies from 84 to 213 m/sec, shows slightly higher value than
Imai and Yoshimura (1970), which shows ranging between 76 and 204 m/sec.
(13)

Sub-Soil Characteristics of Mirpur DOHS (North Side) (SBH 12 (B))

SPT Results
The soil profile of the borehole is shown in Table A2.10. The borehole consists of fivesoil layers. The top layer of soil exists filling grey very loose silty fine sand which varies
from 0 to 5.5 m. The stiff to very stiff light brown silty clay with trace fine sand highplastic varies between 16 and 22 m. The uncorrected SPT N-value of this site varies from
6 to 22. The SPT N-value of the grey very loose silty fine sand varies from 5 to 6. The

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SPT N-value of stiff brown clayey silt with fine sand medium compress varies from 8 to
10. The SPT N-value of stiff to very stiff light brown silty clay varies between 16 and 22.
Shear Wave Velocity Results
Table A2.10 represents shear wave velocity using four different methods. SWV varies
from 155 to 264 m/sec (Ansary et al., 2010). SWV exists from 111 to 278 m/sec (Ohtaand Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which varies
from 146 to 222 m/sec, shows slightly higher value than Imai and Yoshimura (1970),
which shows ranging between 137 and 214 m/sec.
(14)

Sub-Soil Characteristics of Ashiyan city, Askona, Dakkhin Khan (SBH 13)

SPT Results
The soil profile of the borehole is shown in Table A2.11. The borehole consists of six soil
layers. The top layer of soil exists filling grey loose silty fine sand which varies from 0 to
3.5 m. The soft to medium stiff grey silty clay trace fine sand medium plastic varies
between 7 and 12.5 m. The dense brown silty fine sand trace mica varies between 12.5
and 17 m. The uncorrected SPT N-value of this site varies from 4 to 42. The SPT N-valueof soft to medium stiff grey silty clay varies from 3 to 7. The SPT N-value of stiff grey
silty clay varies from 17 to 20.
Shear Wave Velocity Results
Table A2.11 represents shear wave velocity at four different methods. SWV varies from
135 to 300 m/sec (Ansary et al., 2010). SWV exists between 103 and 249 m/sec (Ohtaand Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which varies
from 129 to 268 m/sec, shows slightly higher value than Imai and Yoshimura (1970),
which shows ranging between 120 to 261 m/sec.
(15)

Sub-Soil Characteristics of Purbachal-1, Randokpur Hazi Bari, Rupganj(SBH 14(A) )SPT Results
The soil profile of the borehole is shown in Table A2.12. This borehole consists of six
soil layers. The soft grey silty clay trace fine sand medium plastic varies from 2 to 8 m.
The medium dense grey silty fine sand trace mica varies between 15.5 and 20 m. The
uncorrected SPT N-value of this site varies from 2 to 17. The SPT N-value of soft grey
silty clay varies from 2 to 4. The SPT N-value of medium dense grey silty fine sandvaries from 13 to 16.
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Shear Wave Velocity Results
Table A2.12 shows shear wave velocity using four different methods. SWV varies from
133 to 216 m/sec (Ansary et al., 2010). SWV exists between 117 and 219 m/sec (Ohtaand Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which varies
from 104 to 202 m/sec, shows slightly higher value than Imai and Yoshimura (1970),
which shows ranging between 96 and 190 m/sec.

(16)

Sub-Soil Characteristics of Purbachal-2, American City (SBH 14(B))

SPT Results
The soil profile of the borehole is represented in Table A2.13. This borehole consists ofthree soil layers. The top layer exists filling of very loose grey silty fine sand trace mica
varies from 0 to 6.5 m. The very soft grey silty clay trace fine sand medium to highplastic varies between 6.5 and 18.5 m. The bottom layer of medium stiff grey silty clay
varies from 18.5 to 20. The uncorrected SPT N-value of this site varies from 1 to 8. The
SPT N-value of filling is 1. The SPT N-value of very soft grey silty clay varies between 1
and 2.
Shear Wave Velocity Results
Table A2.13 represents shear wave velocity using four different methods. SWV varies
from 84 to 197 m/sec (Ansary et al., 2010). SWV exists between 98 and 233 m/sec (Ohtaand Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which varies
from 84 to 160 m/sec, shows slightly higher value than Imai and Yoshimura (1970),
which shows ranging between 76 and 151 m/sec.

(17)

Sub-Soil Characteristics of Purbachal Picnic Park, Gazipur (SBH 14(C))

SPT Results
The soil profile of the borehole is shown in Table A2.14. This borehole consists of four
soil layers. The top layer exists filling of loose grey silty fine sand trace mica varies from0 to 5.5 m. The bottom layer of stiff to very stiff light brown clayey silt varies between

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11.5 and 20 m. The uncorrected SPT N-value of this site varies from 2 to 20. The SPT Nvalue of filling loose grey silty fine Sand varies from 4 to 6.
Shear Wave Velocity Results
Table A2.14 represents shear wave velocity using four different methods. SWV varies
from 133 to 233 m/sec (Ansary et al., 2010). SWV exists between 107 and 228 m/sec(Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which
varies from 138 to 213 m/sec, shows slightly higher value than Imai and Yoshimura(1970), which shows ranging between 96 and 204 m/sec.

(18)

Sub-Soil Characteristics of Adjacent to Mirpur Zoo (SBH 15)

SPT Results
The soil profile of the borehole is shown in Table A2.15. The borehole consists of six soil
layers. The top layer exists filling of loose grey silty fine sand trace mica varies from 0 to
5.5 m. The medium stiff to stiff grey silty clay trace fine sand high plastic varies from 8 to12.5 m. The bottom layer of medium dense brown silty fine sand trace mica varies
between 16 and 26 m. The uncorrected SPT N-value of this site varies from 15.5 to 26.
The SPT N-value of medium stiff to stiff grey silty clay varies from 6 to 11. The SPT Nvalue of the bottom layer varies between 16 and 26 m.
Shear Wave Velocity Results
Table A2.15 demonstrates shear wave velocity using four different methods. SWV varies
from 145 to 255 m/sec (Ansary et al., 2010). From SPT correlation developed by Ohta
and Goto (1978), SWV exists from 107 to 238 m/sec. On the other hand, SWV of Ohba
and Toriumi (1970), which varies from 138 to 231 m/sec, shows slightly higher value
than Imai and Yoshimura (1970), which shows ranging between 129 to 223 m/sec.
(19)

Sub-Soil Characteristics of Field Ground, Pallabi (SBH 16)

SPT Results
The soil profile of the borehole is shown in Table 2.5. The borehole consists of four soil
layers. The top layer exists filling of loose grey silty fine sand trace mica varies from 0 to
1.5 m. The clay layer varies from 3 to 18 m. The bottom layer of clay layer varies
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between 21 and 24 m. The uncorrected SPT N-value of this site varies from 1 to 22. The
SPT N-value of thick clay layer varies from 1 to 12. The SPT N-value of sand layer varies
from 8 to 22 m.
Shear Wave Velocity Results
Table 2.5 demonstrates shear wave velocity using four different methods. SWV by PS
logging varies from 78 to 230 (CDMP, 2009). From soil correlation proposed by Ansary
et al. (2010), SWV varies from 84 to 247 m/sec. From SPT correlation developed by Ohta
and Goto (1978), SWV exists from 82 to 277 m/sec. On the other hand, SWV of Ohba
and Toriumi (1970), which varies from 84 to 206 m/sec, shows slightly higher value than
Imai and Yoshimura (1970), which shows ranging between 76 and 197 m/sec.
Table 2.5: SPT-N and Shear Wave Velocity at Field Ground, Pallabi
Shear wave velocity (m/s) from PS-logging
Depth
(m)

SPTN
Value

CDMP
(2009)

1
1
1
1
1
5
4
3
1
1
7
12
8
22
10
18

78
78
78
78
78
134
134
134
134
134
134
230
230
230
230
230

Ansary etal. (2010)

Ohta and
Goto(1978)

Imai and
Yoshimura(1970)

Ohba
andToriumi(1970)

84
110
110
110
110
172
162
150
110
110
190
220
171
241
209
247

82
112
121
128
134
183
182
178
151
154
219
244
194
234
247
277

76
76
76
76
76
129
120
109
76
76
144
173
151
211
162
197

84
84
84
84
84
138
129
118
84
84
154
181
160
219
172
206

1.5
3.0
4.5
6.0
7.5
9.0
10.5
12.0
13.5
15.0
16.5
18.0
19.5
21.0
22.5
24.0

Soil
Description
Filling
Sand
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Sand
Sand
Clay
Clay

(20)

Sub-Soil Characteristics of Block-B, Bashundhara (SBH 17 (A))

SPT Results
The soil profile of the borehole is shown in Table 2.6. This borehole exists three soil
layers. The top layer exists filling of sand from 0 to 3 m. The thick clay layer exists
between 3 and 13.5 m. The bottom layer of sand varies from 13.5 to 21 m. The

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uncorrected SPT N-value of this site varies from 5 to 34. The SPT N-value of filling sandvaries from 5 to 7. The SPT N-value of thick clay layer varies from 5 to 14. The SPT Nvalue of bottom sand layer varies from 10 to 34.
Shear Wave Velocity Results
Table 2.6 represents shear wave velocity using SSMM method and four correlated
methods. According to SSMM, SWV varies from 120 to 270. SWV varies from 145 to
279 m/sec (Ansary et al., 2010). From SPT correlation developed by Ohta and Goto
(1978), SWV exists between 107 and 252 m/sec. On the other hand, SWV of Ohba andToriumi (1970), which varies from 138 to 251 m/sec, shows slightly higher value than
Imai and Yoshimura (1970), which shows ranging between 129 and 243 m/sec.
Table 2.6: SPT-N and Shear Wave Velocity at Block-B, Bashundhara
Shear wave velocity (m/s) from SSMM
Depth
Soil
(m) Description
Filling
1.5
SandFilling
3.0
Sand
4.5
Clay
6.0
Clay
7.5
Clay
9.0
Clay
10.5
Clay
12.0
Clay
13.5
Clay
15.0
Sand
16.5
Sand
18.0
Sand
19.5
Sand
21.0
Sand
(21)

SPT-N
Value

SSMM
Hossain(2009)

Ansaryet al.
(2010)

Ohta and
Goto(1978)

Imai and
Yoshimura(1970)

Ohba
andToriumi(1970)

5

120

145

107

129

138

7
5
11
14
7
8
10
12
10
11
27
30
34

120
140
170
190
190
212
225
225
230
230
245
270
270

163
172
215
230
190
197
209
220
184
190
258
268
279

130
159
193
210
194
204
218
230
191
198
235
243
252

144
129
168
182
144
151
162
173
162
168
226
233
243

154
138
177
190
154
160
172
181
172
177
233
241
251

Sub-Soil Characteristics of Block-D, Bashundhara (SBH 17 (B))

SPT Results
The soil profile of the borehole is shown in Table 2.7. This borehole exists three soil
layers. The top layer exists filling of very soft to soft light brown to brown silty clay trace
fine sand from 0 to 11 m. The very soft silty dark grey silty clay trace fine sand varies
12459March 2012

between 11 and 18.5 m. The bottom layer of medium dense grey silty fine sand varies
from 18.5 to 21.5 m. The uncorrected SPT N-value of this site varies from 1 to 21. The
SPT N-value of filling sand varies from 1 to 4. The SPT N-value of medium dense grey
silty fine sand varies from 2 to 21.

Table 2.7: SPT-N and Shear Wave Velocity at Block-D, Bashundhara
Shear wave velocity (m/s) from SSMM
Depth
Soil
(m) Description
1.5
Silty Clay
3.0
Silty Clay
4.5
Silty Clay
6.0
Silty Clay
7.5
Silty Clay
9.0
Silty Clay
10.5
Silty Clay
12.0
Silty Clay
13.5
Silty Clay
15.0
Silty Clay
16.5
Silty Clay
18.0
Silty Clay
Silty Fine
19.5
Sand
Silty Fine
21.0
Sand

SPT-N
Value
1
2
4
3
3
4
2
1
1
1
1
2

SSMM
Hossain(2009)
101
101
101
101
101
137
137
137
137
137
137
137

Ansaryet al.
(2010)
110
133
162
150
150
162
133
110
110
110
110
133

Ohta and
Goto(1978)
97
126
153
155
162
176
162
147
151
154
157
180

Imai and
Yoshimura(1970)
76
96
120
109
109
120
96
76
76
76
76
96

Ohba
and
Toriumi(1970)
84
104
129
118
118
129
104
84
84
84
84
104

17

137

221

221

194

202

21

231

237

232

208

216

Shear Wave Velocity Results
Table 2.7 represents shear wave velocity using SSMM method (Hossain, 2009) and four
correlated methods. According to SSMM, SWV varies from 101 to 231. From soil
correlation proposed by Ansary et al. (2010), SWV varies from 110 to 237 m/sec. FromSPT correlation developed by Ohta and Goto (1978), SWV exists between 97 and 232
m/sec. On the other hand, SWV of Ohba and Toriumi (1970), which varies from 84 to
216 m/sec, shows slightly higher value than Imai and Yoshimura (1970), which shows
ranging between 76 and 208 m/sec.

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Sub-Soil Characteristics of Block-H, Bashundhara (SBH 17 (C))

SPT Results
The soil profile of the borehole is shown in Table 2.8 (CDMP, 2009). This borehole existsof two soil layers. The top layer exists filling of fine sand from 0 to 3 m. The thick clay
layer varies between 3 and 21 m. The uncorrected SPT N-value of this site varies from 3
to 37. The SPT N-value of clay varies from 1 to 4. The SPT N-value of the bottom layer
varies from 17 to 37.

Table 2.8: SPT-N and Shear Wave Velocity at Block-H, Bashundhara
Shear wave velocity (m/s) from PS-logging
Depth
Soil
(m) Description
1.5
Fill
3.0
Fill
4.5
Clay
6.0
Clay
7.5
Clay
9.0
Clay
10.5
Clay
12.0
Clay
13.5
Clay
15.0
Clay
16.5
Clay
18.0
Clay
19.5
Clay
21.0
Clay

SPTN
Value
3
5
17
15
10
12
13
28
21
35
37
20
27
21

CDMP
(2009)
96
259
259
259
259
259
259
364
364
364
364
364
364
364

Ansary etal. (2010)
122
145
243
235
209
220
225
279
258
297
302
254
277
258

Ohta and
Goto(1978)
98
123
196
203
199
212
222
260
253
282
290
266
285
277

Imai and
Yoshimura(1970)
109
129
194
186
162
173
177
228
208
246
250
204
226
208

Ohba
and
Toriumi(1970)
118
138
202
194
172
181
186
236
216
253
257
213
233
216

Shear Wave Velocity Results
Table 2.8 represents shear wave velocity using PS logging (CDMP, 2009) and four
correlated methods. According to PS logging, SWV varies from 96 to 364. SWV varies
from 122 to 302 m/sec (Ansary et al., 2010). SWV exists between 98 and 285 m/sec(Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which
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March 2012varies from 118 to 253 m/sec, shows slightly higher value than Imai and Yoshimura(1970), which shows ranging between 109 and 250 m/sec.
(23)

Sub-Soil Characteristics of Kuril Flyover (SBH 19)

SPT Results
The soil profile of the borehole is shown in Table A2.16. This borehole consists of four
soil layers. The top layer exists filling of loose grey silty fine sand trace mica varies from0 to 3.5 m. The very soft grey silty clay trace fine sand medium plastic varies between 3.5
and 8 m. The stiff grey to light brown silty clay varies from 8 to 14.0. The bottom layer ofvery stiff light brown clayey silt with fine sand varies from 14 to 20. The uncorrected
SPT N-value of this site varies from 1 to 27. The SPT N-value of filling is 4. The SPT Nvalue of very soft grey silty clay varies from 1 to 4.
Shear Wave Velocity Results
Table A2.16 represents shear wave velocity using four different methods. SWV varies
from 135 to 258 m/sec (Ansary et al., 2010). SWV exists between 103 and 240 m/sec(Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which
varies from 84 to 233 m/sec, shows slightly higher value than Imai and Yoshimura (1970),
which shows ranging between 76 and 226 m/sec.
(24) Sub-Soil Characteristics of Purachal, Uttar Badda (SBH 21)
SPT Results
The soil profile of the borehole is represented in Table A2.17. The borehole consists offive soil layers. The top layer exists filling of loose grey silty fine sand trace mica varies
from 0 to 5 m. The medium stiff to stiff light brown silty clay varies between 8 and 14.5
m. The medium dense to dense brown sandy silt varies from 14.5 to 18.5. The bottom
layer of dense brown silty fine sand varies from 33 to 38. The uncorrected SPT N-valueof this site varies from 1 to 38. The SPT N-value of filling varies from 5 to 8. The SPT Nvalue of medium stiff to stiff light brown silty clay trace grits varies between 3 and 12.
Shear Wave Velocity Results
Table A2.17 represents shear wave velocity using four different methods. SWV varies
from 163 to 290 m/sec (Ansary et al., 2010). SWV exists between 114 and 254 m/sec(Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which

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varies from 84 to 259 m/sec, shows slightly higher value than Imai and Yoshimura (1970),
which shows ranging between 76 and 252 m/sec.
(25) Sub-Soil Characteristics of City Corporation, Gabtoli (SBH 22)
SPT Results
The soil profile of the borehole is shown in Table A2.18. This borehole consists of fivesoil layers. The top layer exists filling of loose grey silty fine sand trace mica varies from0 to 5 m. The medium stiff dark grey silty clay trace organic matter medium plastic varies
between 5 and 8 m. The loose to medium dense grey sandy silt with clay varies from 11
to 18.5 m. The bottom layer of medium dense grey silty fine sand trace mica varies from13 to 15 m. The uncorrected SPT N-value of this site varies from 3 to 15. The SPT Nvalue of filling varies from 3 to 6. The SPT N-value of loose to medium dense grey sandy
silt varies between 7 and 13.
Shear Wave Velocity Results
Table A2.18 represents shear wave velocity using four different methods. SWV varies
from 155 to 211 m/sec (Ansary et al., 2010). From SPT correlation developed by Ohta
and Goto (1978), SWV exists from 111 to 216 m/sec. On the other hand, SWV of Ohba
and Toriumi (1970), which varies from 138 to 194 m/sec, shows slightly higher value
than Imai and Yoshimura (1970), which shows ranging between 109 to 186 m/sec.
(26) Sub-Soil Characteristics of Adabor (SBH 23)
SPT Results
The soil profile of the borehole is shown in Table 2.9 (Tanvir, 2009). The borehole
consists of four soil layers. The top layer exists filling of fine sand from 0 to 3 m. The
clay layer varies between 3 and 10.5 m. The sand layer varies between 12 and 16.5. The
uncorrected SPT N-value of this site varies from 2 to 37. The SPT N-value of clay varies
between 2 and 13. The SPT N-value of sand layer varies from 22 to 37.
Shear Wave Velocity Results
Table 2.9 represents shear wave velocity by direct SSMM method (Hossain, 2009) and
four correlated methods. According to SSMM, SWV varies from 85 to 230. From soil
correlation proposed by Ansary et al. (2010), SWV varies from 107 to 287 m/sec. SWV
exists between 92 and 258 m/sec (Ohta and Goto (1978). On the other hand, SWV of
Ohba and Toriumi (1970), which varies from 104 to 216 m/sec, shows slightly higher
value than Imai and Yoshimura (1970), which shows ranging between 96 and 250 m/sec.
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Table 2.9: SPT-N and Shear Wave Velocity at Adabor

Depth
Soil
SPT-N
(m) Description Value
Filling1.5
Sand2
Filling
3.0
Sand
3
4.5
Clay
2
6.0
Clay
2
7.5
Clay
2
9.0
Clay
5
10.5
Clay
13
12.0
Sand
30
13.5
Sand
35
15.0
Sand
37
16.5
Sand
22
18.0
Clay
21
(27)

Shear wave velocity (m/s) from SSMM
Ohta
SSMM
and
Imai andHossainAnsary et
Goto
Yoshimura(2009)al. (2010)(1978)(1970)

Ohba
andToriumi(1970)

85

107

92

96

104

108
130
150
165
165
180
198
220
220
220
230

122
133
133
133
172
225
268
282
287
241
258

113

109
96
96
96
129
177
233
246
250
211
208

118
104
104
104
138
186
241
253
257
219
216

136
144
151
183
222
220
232
239
223
268

Sub-Soil Characteristics of Agargoan Trade Fair area (SBH 24)

SPT Results
The soil profile of the borehole is shown in Table 2.10 (CDMP, 2009). This borehole
consists of two soil layers. The top layer exists filling of fine sand from 0 to 4.5 m. The
bottom thick clay layer varies between 4.5 and 24 m. The uncorrected SPT N-value of
this site varies from 5 to 35. The SPT N-value of the uppermost filling sand varies from 5
to 23. The SPT N-value of the bottom clay layer varies between 21 and 35.
Shear Wave Velocity Results
Table 2.10 represents shear wave velocity by direct PS logging method (CDMP, 2009)
and four correlated methods. According to PS logging, SWV varies from 150 to 300
m/sec. SWV varies from 145 to 297 m/sec (Ansary et al., 2010). From SPT correlation
developed by Ohta and Goto (1978), SWV exists from 107 to 310 m/sec. On the other
hand, SWV of Ohba and Toriumi (1970), which varies from 138 to 253 m/sec, showsslightly higher value than Imai and Yoshimura (1970), which shows ranging between 129
and 246 m/sec.

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Table 2.10: SPT-N and Shear Wave Velocity at Agargoan Trade Fair area
Shear wave velocity (m/s) from PS-logging
Depth
(m)
1.5
3.0
4.5
6.0
7.5
9.0
10.5
12.0
13.5
15.0
16.5
18.0
19.5
21.0
22.5
24.0

Soil
Description
Filling Sand
Filling Sand
Filling Sand
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay
Clay

SPT-N
Value
5
11
23
21
21
21
22
22
22
27
26
23
28
30
30
35

CDMP
(2009)
150
150
200
200
200
239
239
239
239
300
300
300
300
300
300
300

Ansaryet al.
(2010)
145
190
244
258
258
258
261
261
261
277
274
264
279
285
285
297

Ohta and
Goto(1978)
107
141
173
215
225
234
243
249
255
270
273
272
286
294
298
310

Imai and
Yoshimura(1970)
129
168
214
208
208
208
211
211
211
226
223
214
228
233
233
246

Ohba
and
Toriumi(1970)
138
177
222
216
216
216
219
219
219
233
231
222
236
241
241
253

(28) Sub-Soil Characteristics of Aftab Nagar Housing Project (SBH 25)
SPT Results
The soil profile of the borehole is shown in Table 2.11 (CDMP, 2009). The borehole
consists of six soil layers. The top filling sand layer varies from 0 to 3 m. The thick sandlayer exists between 12 and 24 m. The SPT N-value of filling sand varies from 2 to 3. The
SPT N-value of the bottom thick sand layer varies between 18 and 29.

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Table 2.11: SPT-N and Shear Wave Velocity at Aftab Nagar Housing Project
Shear wave velocity (m/s) from PS-logging
Depth
(m)
1.5
3.0
4.5
6.0
7.5
9.0
10.5
12.0
13.5
15.0
16.5
18.0
19.5
21.0
22.5
24.0

Soil
Description
Filling Sand
Filling Sand
Sand
Clay
Sand
Clay
Clay
Sand
Sand
Sand
Sand
Sand
Sand
Sand
Sand
Sand

SPT-N
Value
3
2
2
8
10
13
18
18
24
20
17
24
27
27
25
29

CDMP
(2009)
124
124
124
211
211
211
211
211
211
211
211
211
211
211
211
211

Ansary etal. (2010)
122
107
107
197
184
225
247
225
248
233
221
248
258
258
251
264

Ohta and
Goto(1978)
98
105
114
183
166
215
235
202
217
215
213
230
239
242
242
252

Imai and
Yoshimura(1970)
109
96
96
151
162
177
197
197
217
204
194
217
226
226
220
231

Ohba
and
Toriumi(1970)
118
104
104
160
172
186
206
206
225
213
202
225
233
233
228
239

Shear Wave Velocity Results
Table 2.11 represents shear wave velocity by direct PS logging method (CDMP, 2009)
and four soil correlations. According to PS logging, SWV varies from 124 to 211 m/sec.
From soil correlation proposed by Ansary et al. (2010), SWV varies between 107 to 264
m/sec. From SPT correlation developed by Ohta and Goto (1978), SWV exists from 98 to
252 m/sec. On the other hand, SWV of Ohba and Toriumi (1970), which varies from 118
to 239 m/sec, shows slightly higher value than Imai and Yoshimura (1970), which shows
ranging between 96 to 231 m/sec.
(29) Sub-Soil Characteristics of Umme Had Nagar, Nadda (SBH 26)
SPT Results
The soil profile of the borehole is shown in Table A2.19. This borehole consists of ninesoil layers. The top layer exists filling of very loose grey silty fine sand varies from 0 to
3.5 m. The medium stiff grey silty clay varies between 3.5 and 5 m. The stiff light brownsilty clay varies from 8 to 11. The medium dense to dense light brown sandy silt varies
from 12.5 to 15.5. The bottom layer of dense brown sandy silt trace clay varies from 18.5

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to 20. The uncorrected SPT N-value of this site varies from 1 to 36. The SPT N-value offilling is 1. The SPT N-value of stiff light brown silty clay varies from 8 to 15. The SPT
N-value of medium dense to dense light brown sandy silt varies between 13 and 33.
Shear Wave Velocity Results
Table A2.19 represents shear wave velocity using four different methods. SWV varies
from 84 to 285 m/sec (Ansary et al., 2010). From SPT correlation developed by Ohta andGoto (1978), SWV exists from 82 to 251 m/sec. On the other hand, SWV of Ohba andToriumi (1970), which varies from 84 to 253 m/sec, shows slightly higher value than Imaiand Yoshimura (1970), which shows ranging between 76 and 246 m/sec.
(30) Sub-Soil Characteristics of South Banasree (SBH 27)
SPT Results
The soil profile of the borehole is shown in Table A2.20. This borehole consists of four
soil layers. The top layer exists filling of very loose grey silty fine sand trace mica varies
from 0 to 4 m. The medium stiff to very soft dark grey to grey silty clay varies between 4
and 14 m. The bottom layer of medium dense to dense brown silty fine sand varies from
16 to 20 m. The uncorrected SPT N-value of this site varies from 1 to 40. The SPT Nvalue of medium stiff to very soft dark grey to grey silty clay varies from 1 to 6. The SPT
N-value of medium dense to dense brown silty fine sand varies from 9 to 40.
Shear Wave Velocity Results
Table A2.20 represents shear wave velocity using four different methods. From soil
correlation proposed by Ansary et al. (2010), SWV varies from 133 to 295 m/sec. SWV
exists between 107 and 273 m/sec (Ohta and Goto, 1978). On the other hand, SWV of
Ohba and Toriumi (1970), which varies from 84 to 264 m/sec, shows slightly higher
value than Imai and Yoshimura (1970), which shows ranging between 76 and 257 m/sec.
(31) Sub-Soil Characteristics of Kalunagar, Hazaribagh (SBH 30)
SPT Results
The soil profile of the borehole is shown in Table A2.21. This borehole consists of two
soil layers. The top layer of soil exists filling of loose grey silty fine sand varies from 0 to
8 m. The bottom layer of medium dense grey silty fine sand varies from 8 to 20. The
uncorrected SPT N-value of this site varies from 1 to 40. The SPT N-value of filling sandvaries from 4 to 9. The SPT N-value of the bottom layer varies between 9 and 19.

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Shear Wave Velocity Results
Table A2.21 represents shear wave velocity using four different methods. From soil
correlation proposed by Ansary et al. (2010), SWV varies from 135 to 229 m/sec. SWV
exists between 103 and 226 m/sec (Ohta and Goto, 1978). On the other hand, SWV of
Ohba and Toriumi (1970), which varies from 129 to 209 m/sec, shows slightly higher
value than Imai and Yoshimura (1970), which shows ranging between 120 and 201 m/sec.
(32) Sub-Soil Characteristics of Rab-10, Plot, Kamrangirchar (SBH 31)
SPT Results
The soil profile of the borehole is shown in Table A2.22. The borehole consists of fivesoil layers. The top layer exists filling of very loose to loose light brown silty fine sandvaries from 0 to 3.5 m. The loose to medium dense grey fine sand and silt trace mica
varies from 9.5 to 14 m. The bottom layer of medium dense grey silty fine sand trace
mica varies from 14 to 20. The uncorrected SPT N-value of this site varies from 3 to 28.
The SPT N-value of filling sand varies from 3 to 7. The SPT N-value of loose to medium
dense grey fine sand and silt varies from 7 to 19. The SPT N-value of bottom layer varies
from 19 to 28.
Shear Wave Velocity Results
Table A2.22 represents shear wave velocity using four different methods. SWV varies
from 122 to 261 m/sec (Ansary et al., 2010). From SPT correlation developed by Ohta
and Goto (1978), SWV exists from 98 to 261 m/sec. On the other hand, SWV of Ohba
and Toriumi (1970), which varies from 118 to 236 m/sec, shows slightly higher value
than Imai and Yoshimura (1970), which shows ranging between 109 and 228 m/sec.
(33)

68

Sub-Soil Characteristics of Sosan Ghat, Kamrangirchar (SBH 32)

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Table 2.12: SPT-N and Shear Wave Velocity at Sosan Ghat, Kamrangirchar
Shear wave velocity (m/s) from SSMM
Depth
(m)
1.5
3.0
4.5
6.0
7.5
9.0
10.5
12.0
13.5
15.0
16.5
18.0

Soil
Description
Filling Sand
Filling Sand
Filling Sand
Organic
Clay
Organic
Clay
Clay
Clay
Clay
Clay
Clay
Sand
Sand

SPT-N
Value
7
9
10

SSMM
Hossain(2009)
100
112
134

Ansaryet al.
(2010)
163
178
209

Ohta and
Goto(1978)
114
136
179

Imai and
Yoshimura(1970)
144
157
162

Ohba
and
Toriumi(1970)
154
166
172

1

150

110

128

76

84

2
12
13
15
14
15
22
25

160
160
165
170
170
180
180
200

133
220
225
235
230
235
241
251

151
212
222
234
236
244
223
232

96
173
177
186
182
186
211
220

104
181
186
194
190
194
219
228

SPT Results
The soil profile of the borehole is demonstrated in Table 2.12 (Tanvir, 2009). The
borehole consists of four soil layers. The top layer exists filling of fine sand from 0 to 4.5
m. The organic clay layer varies between 4.5 and 7.5 m. The lower clay layer varies
between 7.5 and 15. The uncorrected SPT N-value of this site varies from 1 to 25. The
SPT N-value of filling sand varies from 7 to 10. The SPT N-value of clay layer varies
between 12 and 15.
Shear Wave Velocity Results
Table 2.12 represents shear wave velocity by direct SSMM method (Hossain, 2009) and
four correlated methods. According to SSMM, SWV varies from 100 to 200. SWV
varies from 133 to 251 m/sec (Ansary et al., 2010). SWV exists between 114 and 244
m/sec (Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970),
which varies from 84 to 228 m/sec, shows slightly higher value than Imai and Yoshimura(1970), which shows ranging between 96 and 220 m/sec.
(34) Sub-Soil Characteristics of Basundhara River view (SBH 33)
SPT Results
The soil profile of the borehole is shown in Table A2.23. The borehole consists of six soil
layers. The top layer exists filling of very loose to loose grey silty fine sand varies from 0
to 3.5 m. The medium stiff grey clayey silt with fine sand medium compress varies from13469

March 2012

8 to 14 m. The uncorrected SPT N-value of this site varies from 2 to 10. The SPT N-valueof filling sand varies from 3 to 5. The SPT N-value of medium stiff grey clayey silt varies
from 4 to 10. The SPT N-value of soft silty grey silty clay trace fine sand varies from 2 to5.
Shear Wave Velocity Results
Table A2.23 represents shear wave velocity using four different methods. SWV varies
from 122 to 184 m/sec (Ansary et al., 2010). SWV exists from 98 to 202 m/sec (Ohta andGoto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which varies from
104 to 172 m/sec, shows slightly higher value than Imai and Yoshimura (1970), whichshows ranging between 96 and 162 m/sec.
(35)
(36)

Sub-Soil Characteristics of Matuail, Demra (SBH 34)

SPT Results
The soil profile of the borehole is shown in Table 2.13. This borehole exists five soil
layers. The filling sand varies from 0 to 3.5 m. The stiff grey silty clay varies from 8.5 to
14 m. The bottom layer of grey clayey silt varies from 14 to 20 m. The uncorrected SPT
N-value of this site varies from 2 to 23. The SPT N-value of the uppermost filling sandvaries from 3 to 4. The SPT N-value of stiff grey silty clay varies from 7 to 17.
Shear Wave Velocity Results
Table 2.13 represents shear wave velocity using PS loggings method (CDMP, 2009) and
four correlated methods. According to PS loggings, SWV varies from 101 to 231. SWV
varies from 122 to 244 m/sec (Ansary et al., 2010). From SPT correlation developed by
Ohta and Goto (1978), SWV exists from 98 to 244 m/sec. On the other hand, SWV of
Ohba and Toriumi (1970), which varies from 118 to 222 m/sec, shows slightly higher
value than Imai and Yoshimura (1970), which shows ranging between 96 and 214 m/sec.

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Table 2.13: SPT-N and Shear Wave Velocity at Matuail, Demra

Depth
(m)
1.5
3.0
4.5
6.0
7.5
9.0
10.5
12.0
13.5
15.0
16.5
18.0
19.5
20.0
(37)

Soil
Description
Silty Fine Sand
(Filling)
Silty Fine Sand
(Filling)
Silty Clay
Silty Clay
Silty Clay
Silty Clay
Silty Clay
Silty Clay
Silty Clay
Clayey Silt
Clayey Silt
Clayey Silt
Clayey Silt
Clayey Silt

SPTN
Value

Shear wave velocity (m/s) from PS-logging
Ohta
Ohba
Ansaryand
Imai andandCDMP
et al.
Goto
Yoshimura Toriumi(2009) (2010)(1978)(1970)(1970)

3

101

122

98

109

118

4
2
2
3
8
10
14
17
18
20
22
23
23

101
101
101
137
137
137
137
137
137
137
137
231
231

135
133
133
150
197
209
230
243
225
233
241
244
244

119
136
144
162
198
212
231
244
211
219
227
232
233

120
96
96
109
151
162
182
194
197
204
211
214
214

129
104
104
118
160
172
190
202
206
213
219
222
222

Sub-Soil Characteristics of Jilmil Project, Equria (SBH 35)

SPT Results
The soil profile of the borehole is demonstrated in Table A2.24. This borehole consists ofthree soil layers. The top layer exists filling of very loose grey silty fine sand varies from0 to 2 m. The soft to medium stiff grey silty clay varies from 2 to 8.5 m. The medium
dense to dense grey silty fine sand varies from 8.5 to 20 m. The uncorrected SPT N-valueof this site varies from 2 to 31. The SPT N-value of filling sand is 2. The SPT N-value ofsoft to medium stiff grey silty clay varies between 2 to 15. The SPT N-value of thebottom layer varies from 15 to 31.
Shear Wave Velocity Results
Table A2.24 represents shear wave velocity using four different methods. SWV varies
from 107 to 271 m/sec (Ansary et al., 2010). SWV exists between 92 and 245 m/sec(Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which
varies from 104 to 244 m/sec, shows slightly higher value than Imai and Yoshimura(1970), which shows ranging between 96 and 236 m/sec.

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(38)

Sub-Soil Characteristics of Rajendapur (SBH 36)

SPT Results
The soil profile of the borehole is shown in Table A2.25. This borehole consists of fivesoil layers. The top layer exists filling of loose light grey silty fine sand varies from 0 to
5.5 m. The medium stiff to stiff grey clayey silt varies from 8 to 15.5 m. The uncorrected
SPT N-value of this site varies from 4 to 26. The SPT N-value of filling sand varies from4 to 5. The SPT N-value of medium stiff to stiff grey clayey silt varies from 5 to 9. The
SPT N-value of the bottom layer varies between 21 and 26.
Shear Wave Velocity Results
Table A2.25 represents shear wave velocity using four different methods. SWV varies
from 135 to 255 m/sec (Ansary et al., 2010). SWV exists between 103 and 238 m/sec(Ohta and Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which
varies from 129 to 231 m/sec, shows slightly higher value than Imai and Yoshimura(1970), which shows ranging between 120 and 223 m/sec.

(39)

Sub-Soil Characteristics of Bramangaon (SBH 37)

SPT Results
The soil profile of the borehole is shown in Table A2.26. This borehole exists four soil
layers. The top layer exists filling of loose grey silty fine sand varies from 0 to 5 m. The
medium stiff grey clayey silt with fine sand varies from 8 to 20 m. The uncorrected SPT
N-value of this site varies from 4 to 8. The SPT N-value of filling sand varies from 4 to 5.
The SPT N-value of the bottom layer varies from 5 to 8.
Shear Wave Velocity Results
Table A2.26 represents shear wave velocity using four different methods. SWV varies
from 135 to 171 m/sec (Ansary et al., 2010). SWV exists from 103 to 195 m/sec (Ohtaand Goto, 1978). On the other hand, SWV of Ohba and Toriumi (1970), which varies
from 129 to 160 m/sec, shows slightly higher value than Imai and Yoshimura (1970),
which shows ranging between 120 and 151 m/sec.
(40)

Sub-Soil Characteristics of Meradia, Uttar Banasree (SBH 38)

SPT Results

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The soil profile of the borehole is shown in Table 2.14. This borehole exists three soil
layers. The top layer exists filling of fine sand from 0 to 4.5 m. The organic clay layer
varies between 4.5 and 12 m. The lower clay layer varies between 12 and 18. The
uncorrected SPT N-value of this site varies from 2 to 22. The SPT N-value of filling sandvaries from 2 to 4. The SPT N-value of organic clay layer varies from 2 to 4. The SPT Nvalue of bottom clay layer varies from 17 to 22.
Shear Wave Velocity Results
Table 2.14 represents shear wave velocity using SSMM method (Hossain, 2009) and four
correlated methods. According to SSMM, SWV varies from 90 to 195.

From soil

correlation proposed by Ansary et al (2010), SWV varies from 107 to 261 m/sec. SWV
exists between 111 and 217 m/sec (Ohta and Goto, 1978). On the other hand, SWV of
Ohba and Toriumi (1970), which varies from 104 to 209 m/sec, shows slightly higher
value than Imai and Yoshimura (1970), which shows ranging between 96 and 201 m/sec.
Table 2.14: SPT-N and Shear Wave Velocity at Meradia, Uttar Banasree

Depth
(m)
1.5
3.0
4.5
6.0
7.5
9.0
10.5
12.0
13.5
15.0
16.5
18.0

Soil
Description
Silty Fine Sand
(Filling)
Silty Fine Sand
(Filling)
Silty Fine Sand
(Filling)
Organic Clay
Organic Clay
Organic Clay
Organic Clay
Organic Clay
Clay
Clay
Clay
Clay

SPTN
Value

Shear wave velocity (m/s) from SSMM
Ohta
Ohba
SSMM Ansary
andImai andandHossain et al.
Goto
Yoshimura Toriumi(2009) (2010) (1978)(1970)(1970)

3

90

122

111

137

146

4

102

135

130

144

154

2
2
3
8
10
14
17
18
20
22

118
130
130
138
148
157
157
170
170
195

107
133
150
197
209
230
243
247
254
261

133
111
116
120
142
154
184
194
207
217

151
96
96
96
109
120
162
173
190
201

160
104
104
104
118
129
172
181
198
209

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(41)

Sub-Soil Characteristics of BUET Play ground

SPT Results
The soil profile of the borehole is shown in Table 2.15. This borehole exists two soil
layers. The top layer exist clayey silt layer from 0 to 4.5 m. The bottom sand layer exists
from 4.5 to 18 m. The uncorrected SPT N-value of this site varies from 2 to 19. The SPT
N-value of the uppermost clayey silt layer varies from 6 to 8. The SPT N-value of sandlayer varies from 4.5 to 18.
Shear Wave Velocity Results
Table 2.15 represents shear wave velocity using SSMM method (Hossain, 2009) and four
correlated methods. According to SSMM, SWV varies from 178 to 260 m/sec. SWV
varies from 107 to 229 m/sec (Ansary et al., 2010). From Ohta and Goto (1978), SWV
exists from 121 to 221 m/sec. On the other hand, SWV of Ohba and Toriumi (1970),
which varies from 104 to 209 m/sec, shows slightly higher value than Imai and
Yoshimura (1970), which shows ranging between 96 and 201 m/sec.

Table 2.15: SPT-N and Shear Wave Velocity at BUET Play ground
Shear wave velocity (m/s) from SSMM
Depth
Soil
(m) Description
1.50 Clayey Silt
3.00 Clayey Silt
4.50 Clayey Silt
6.00
Sand
7.50
Sand
9.00
Sand
10.50
Sand
12.00
Sand
13.50
Sand
15.00
Sand
16.50
Sand
18.00
Sand
(42)

74

SPT-N
Value
6
7
8
2
2
2
3
4
10
12
16
19

SSMM
Hossain(2009)
178
178
180
190
205
205
220
230
230
245
245
260

Ansary etal. (2010)
182
190
197
107
107
107
122
135
184
196
216
229

Ohta and Imai and
Goto
Yoshimura(1978)(1970)
135
137
159
144
177
151
121
96
127
96
131
96
145
109
156
120
187
162
197
173
211
190
221
201

Ohba
and
Toriumi(1970)
146
154
160
104
104
104
118
129
172
181
198
209

Sub-Soil Characteristics of West Palashi, BUET campus

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The BUET campus is situated in latitude 23°43'16.58" N to 23°43'59.44" N and longitude
90°23'13.31"E to 90°23'43.56" E. Microtremor observation has been executed at 132
selected points in soil. The geology of whole BUET campus is Upper Modhupur Terrace(Figure 2.2) and High Pleistocene terrace (Figure 2.3). There is no filling in this site.
SPT Results
Total 14 SPT boreholes data have been collected from West Palashi, BUET Campus.
Table A2.27 to A2.31 shows soil profiles of five boreholes at BUET-JIDPUS building,West Palashi, BUET Campus (Dhaka Soil, 2008). Table 2.32 to 2.40 represent soil
profiles of nine boreholes at New Academic building, West Palashi, BUET campus.
From Table A2.27 to A2.31, the uppermost silty clay varies from 0 to 6.0 m. Clayey silt
exists below the silty clay layer between 4.5 to 7.5 m. The bottom layer of silty fine sandvaries from 7.5 to 15 m.
From Table A2.32 to A3.40, clay silt exists between 0 to 1.5 m soils in most of theboreholes. The silty clay varies ranging between 1.5 and 7.5 m. In some borehole, finesandy silt exists between 6 and 9 m. In all the boreholes, the bottom soil layer is silty finesand.
Shear Wave Velocity Results
Table A2.27 to A2.40 represent shear wave velocity using four correlated methods.
From Table A2.27 to A2.31, SWV varies from 110 to 297 m/sec (Ansary et al., 2010).
From SPT correlation developed by Ohta and Goto (1978), SWV exists between 92 and242 m/sec. On the other hand, SWV of Ohba and Toriumi (1970), which varies from 84
to 266 m/sec, shows slightly higher value than Imai and Yoshimura (1970), which shows
ranging between 76 and 259 m/sec.
From Table 2.32 to 2.40, SWV varies from 84 to 309 m/sec (Ansary et al., 2010). FromSPT correlation developed by Ohta and Goto (1978), SWV exists from 82 to 259 m/sec.
On the other hand, SWV of Ohba and Toriumi (1970), which varies from 84 to 275 m/sec,shows slightly higher value than Imai and Yoshimura (1970), which shows ranging
between 76 and 269 m/sec.

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2.3 MICROTREMOR DATA COLLECTION
The ground is always vibrating at minute amplitudes. Microtremors are ambient
vibrations of the ground caused by natural or artificial disturbances such as wind, sea
waves, traffic, human activities and industial machinery. Microtremor data has beencollected in consideration of noise in different geological and geomorphological unit
(Figure 2.2 and Figure 2.3).
Microtremor measurement has been carried out in 132 selected locations (Figure 2.34)
within BUET campus. In BUET campus, 240 second duration were recorded at different
times in the specific locations. The measurements were carried out from morning tomidnight in order to minimize artificial noises due to traffic and human activities. In
BUET campus, most of the selected points were near the busy road. Special care has beentaken during data recording. In West Polashi of BUET campus, there was an 8 MW with
1500 rpm Electric Power Plant. Although there is a machine foundation below thegenerator, this generator produces some noise in adjacent ground. So, microtremor
observation has been executed at different times during ON and OFF condition to justify
soil response due to this effect.
Microtremor observation at 45 sites has been carried out in and around Dhaka city.
Traffic movement, human activities, any power plant and noise from other sources havebeen considered during data recording as well. Most of the microtremor observation has
been executed in consideration of recent filling. However, some non recent filling areas
have also been selected for observation. Figure 2.1 shows 45 selected locations in andaround Dhaka city. Some location is not demonstrated specifically in Dhaka city map due
to not having full area coverage map. These points are shown using arrow mark in Figure
2.1.
Figure 2.4 demonstrates microtremor measurement apparatus for data recording. This
includes Geodas 15-HS equipment (Data logger and Laptop), Sensor, Cable, Battery andGPS. Mtobs.exe software is used to record microtremor data. Although there are fivesensors in this observation system, two or three sensors have been used for data recording.
Sensor has been used in consideration of surface condition, weather, time and geology ofsites. CR4.5-1S velocity type sensor with sensitivity coefficient 0.0882μm/sec/digit has
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been used in observation system. Sensors comprise three components, which can record
the horizontal motion (in Latitude and Longitude directions) and the vertical motions (upand down). Microtremor sensor sensitivity was 295900μm/sec/V. The converting speed
was 50 kHz. The sampling frequency was 100 Hz. The amplification factor was used 20
db in observation system. Figure 2.5 shows some pictures of microtremor measurement at
BUET campus, Demra and Ashulia Toll Plaza. These pictures are taken at different time
during microtremor data recording.

2-SENSOR
BATTERYCable
LAPTOPGPSDATA LOGGER

Figure 2.4: Microtremor measurement apparatus.

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March 2012(a) West Polasi, BUET at 4:00 PM(b) BUET campus at night(c) Matuail, Demra (Left) and Ashulia Toll Plaza (Right) at afternoon
Figure 2.5: Microtremor data recording in and around Dhaka city.

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2.4

MICROTREMOR DATA ANALYSIS

Velocity time history field microtremor data has been recorded in Mtobs.exe softwarewith suitable number of observation channels, observation length, observation frequency,
specific low or high pass filter code, amplification ratio, observation latitude andlongitude, observation time and observation channel mode. Figure 2.6 shows a typicaltime history field data recording of Uttara Phase-3 (North side) at 4:30 PM on 9 April,2011. The content of all input data are 2 CR4.5-1S velocity type sensors, 24000
observation data length, 100Hz sampling frequency, 0.05 Hz Low-pass filter, 20db
amplification ratio, Latitude-2352΄22and Longitude-9021΄40.

Figure 2.6: Time history field data recording at Uttara Phase-3 (North side).

Figure 2.7 [(a), (c) and (e)] shows time history microtremor data at segment 1, 2 and 3
with 2050 observed data length. Segment 1 illustrates time history data of 20.5 s from 40
s to 60.5 s. Segment 2 demonstrates time history data of 20.5 s from 100 s to 120.5 s.
Segment 3 presents time history data of 20.5 s from 60 s to 80.5 s.
Time history data is not suitable to estimate the dynamic properties (predominantfrequency and amplification ratio). So, transformation of time domain data to frequency
domain data is required with Fourier Transformation. Therefore, Fast Fourier
Transformation (FFT) has been used to transfer time domain data to frequency domain
14479March 2012

data. Figure 2.7 [(b), (d) and (f)] presents Fast Fourier Transformation data at segment 1,
2 and 3 in EW, NS and UD directions, respectively. This transformation data is shown inlogarithmic window in frequency from 0.1 Hz to 10 Hz and in Fourier Spectrum from0.01 μm to 10 μm.
Only the Fourier Spectrum along three subsequent directions is not appropriate toestimate the predominant frequency and amplification. So, Horizontal to Vertical spectral
ratio (H/V) is required to determine the dynamic properties of soil. Horizontal to Vertical
Spectral Ratio (H/V) is determined dividing by Fourier Spectrum of UD direction to the
Fourier Spectrum of EW or NS direction.

EW

NS

15

EW1

UD
15

NS1

10

10

5

5

5

0

-5

-10

Amplitude (μm/s)

10Amplitude (μm/s)

Amplitude ( μm/s)

15

0

-5

40

45

50

55

-5

-15

-15

60

0

-10

-10

-15

UD1

40

Time (Sec)

45

50

55

40

60

45

50

55

60

Time (Sec)Time (Sec)

10

1

10

0

10

1

0

-1

10

-2

-1

10

10

0

10

1

10

UD.

0

10

-1

10

-2

10

-2

10

Fourier Spectrum (μm)

-1

10

10

1

10

NS.

EW.

Fourier Spectrum (μm)

Fourier Spectrum (μm)(a) Time History data of segment 1 from 40 sec to 60.5 sec

-1

10

0

10

Frequency (Hz)Frequency (Hz)

10

1

-1

0

10

1

10

10

Frequency (Hz)(b) Fourier Transformation of Segment 1 in EW, NS and UD direction
15

EW2

15

NS2

10

10

5

5

5

0

-5

Amplitude (μm/s)

10Amplitude (μm/s)

Amplitude (μm/s)

15

0

-5

100

105

110

115

120

100

105

110

Time (Sec)Time (Sec)

80

-5

-15

-15

-15

0

-10

-10

-10

UD2

145

115

120

100

105

110

115

120

Time (Sec)BNUS Annual Report-2011

ICUS Report 59(c) Time History data of segment 2 from 100 sec to 120.5 sec

Fourier Spectrum (μm/s)

Fourier Spectrum (μm)

EW.

0

10

-1

10

-2

10

-1

0

10

10

1

10

0

NS.

10

-1

10

-2

10

10

1

10

0

UD.

-1

10

-2

10

10

1

10

Fourier Spectrum (μm)

1

10

-1

10

0

10

Frequency (Hz)Frequency (Hz)

10

1

-1

10

0

1

10

Frequency (Hz)(d) Fourier Transformation of Segment 2 in EW, NS and UD direction
15

EW3

15

NS3

10

5

5

5

0

-5

Amplitude (μm/s)

1010Amplitude (μm/s)

Amplitude (μm/s)

15

0

-5

60

65

70

75

-5

-15

-15

-15

0

-10

-10

-10

UD3

60

80

65

Time (Sec)70Time (Sec)

75

60

80

65

70

75

80

Time (Sec)

1

10

0

1

1

10

EW.

-1

10

10

NS.

Fourier Spectrum (μm)

10Fourier Spectrum (μm)

Fourier Spectrum (μm)(e) Time History data of segment 1 from 60 sec to 80.5 sec

0

10

-1

10

-2

10

-2

10

10

-1

10

0

Frequency (Hz)

10

1

UD.

0

10

-1

10

-2

-1

0

10

10

Frequency (Hz)

1

10

10

-1

10

0

10

Frequency (Hz)110(f) Fourier Transformation of Segment 2 in EW, NS and UD direction
Figure 2.7: Fourier Transformation of three segments at Uttara Phase-3 (North side).

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March 2012

H/V Ratio

H/V Ratio

0

10

EW
NS
RM

-1

10

10

1

10

0

10

-1

0

10

EW
NS
RM

-1

10

1

10

1

10

H/V Ratio

1

10

10

0

10

EW
NS
RM

-1

-1

10

0

10

1

10

-1

0

10

Segment 1

1

10Frequency (Hz)Frequency (Hz)10

Frequency (Hz)Segment 2

Segment 3(a) H/V Ratio of EW, NS and their mean at Segment 1, 2 and 3
10

1

10

0

1

10

1

0

10

10

H/V Ratio

H/V Ratio

H/V Ratio

10

EW1
EW2
EW3
NS1
NS2
NS3

-1
-1

10

10

0

Frequency (Hz)

1

10

10

seg.1
seg.2
seg.3
mean

-1

10

0

10

mean
mean+1/2σmean-1/2σ

-1

10

-1

10

0

Frequency (Hz)

10

1

-1

0

10

10

Frequency (Hz)110(b) Mean H/V ratio with Standard Deviation
Figure 2.8: Predominant Frequency and H/V ratio at Uttara Phase-3 (North side).

Figure 2.8 (a) shows the Horizontal to Vertical Spectral ratio (H/V) of segment 1, 2 and 3
in EW and NS directions, respectively. The square root of EW and NS direction H/V ratio
in segment 1, 2 and 3 is calculated. Then, mean of the square root H/V ratio value isplotted with standard deviation 0.5σ. 0.5σ standard deviation represents the deviation ofsix H/V ratio data from mean in three segments. Figure 2.8 (b) presents the mean H/Vratio with six segmental H/V ratio in EW and NS direction. In addition to this, threesegmental square root H/V ratio and their mean H/V Ratio is shown in Figure 2.8 (b).
The plotted data is smoothed with suitable log- window to understand clearly the
Predominant frequency (Hz) and Horizontal to vertical spectral ratio (H/V).

2.4.1

Stability of Microtremor Data

Microtremor is the combination of shear wave, Rayleigh wave and Love wave. The effectof different waves on microtremor data is significant. Therefore, stability check of
microtremor data is important to estimate dynamic properties of any site soil. To carry out
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this research velocity time history data have been recorded time ranging between morning
to midnight at 14 locations in West Palashi, BUET. The observation microtremor data
recording varies from 5 to 20 minutes. Ten minutes observation time has been taken in
most of the observation points. Three segments of 20.48 s time domain data have beenused to transform frequency domain spectrum. In order to get low noise data these
Fourier spectra have been filtered using rectangular windows. The mean of these threesegments of frequency domain data have been calculated using smoothing function withaverage smoothing point 5. Mean Fourier spectrum along EW, NS and UD directions
have been plotted in logarithmic windows from 0.1 Hz to 10 Hz along predominantfrequency and from 0.001µm to 1µm along Fourier amplitude spectrum, respectively.
From these observations, stability of time variation microtremor data has been comparedfrom Fourier spectrum. The horizontal to vertical spectral ratio has also been calculated inthese locations to analyze the stability of H/V ratio with Fourier spectrum. Both Fourier
spectrum and H/V ratio of fourteen observation points at different times have been
included in this section.
2.4.1.1

Stability of Amplitude of Fourier Spectrum

Frequency domain Fourier spectra of fourteen observation points have been demonstrated
from Figure 2.9 to 2.13 along EW, NS and UD, respectively. Instead of using all theobserved time records, three to four different times instants are selected from 24 hourobservation for fourteen sites, for investigation. Figure 2.9 shows the vertical andhorizontal Fourier spectra of microtremors observed at MT05, MT06 and MT07. The
mean peak value of Fourier spectra varies from 2.1 Hz to 3.1 Hz for both the horizontal
and vertical motions. Figure 2.9 (a) shows three time instants (13:07 PM, 16:20 PM and
01:06 AM) and their mean value. Figure 2.9 (b) shows three time instants (18:29 PM,
00:08 AM and 01:29 AM) where as Figure 2.9 (c) represents three time instants (11:34
AM, 16:55 PM and 19:41 PM). From figure 2.9, it can be concluded that Fourier spectra
along EW, NS and UD directions are stable at these observation points. The stable
Fourier spectra along vertical directions have been found around 3.0 Hz.
In Figure 2.10 Fourier spectra of microtremor observations at MT08, MT09 and MT10
have been illustrated along EW, NS and UD directions, respectively. The overall peakvalue of the Fourier spectra lies between 3.02 Hz and 3.84 Hz for both the horizontal andvertical motions. From Figure 2.10 (a), the horizontal motion of MT08 in the afternoon
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March 2012

(11:34 AM and 16:55 PM) has a peak from 3.34 Hz to 4.4 Hz and in night (00:01 AM
and 01:21 AM); it varies between 2.75 Hz and 2.95 Hz along EW direction. The peakalong NS direction in the afternoon varies between 2.29 Hz and 2.57 Hz whereas it lies
from 2.61 Hz to 2.94 Hz in night. The stable peak along vertical direction is 3.59 Hz inafternoon and it varies from 2.42 Hz to 3.02 Hz in night. The stable fourier spectra of MT
09 and MT 10 have been shown in Figure 2.10 (b) and Figure 2.10 (c). From Figure 2.10,
it can be concluded that Fourier amplitude spectrum are stable along EW, NS and UD
directions, respectively.
The frequency domain Fourier spectra at MT11, MT12 and MT13 are illustrated in Figure
2.11. The mean peak Fourier amplitude spectrum varies between 2.20 Hz and 3.74 Hz forboth the horizontal and vertical motions for all three locations. The Fourier spectra at MT
11 and MT 12 are almost stable. The amplitude of these sites is around 3 Hz. But, theFourier spectra at MT 13 are slightly different from MT 11 and MT 12. The mean peak ofFourier spectra at MT 13 varies from 2.72 Hz to 3.26 Hz. The peak Fourier spectra at
MT 13 lies between 0.13 µm and 0.37µm.
Figure 2.12 shows Fourier spectra of microtremor observations at MT15, MT16 andMT19 along EW, NS and UD directions, respectively. The mean peak amplitude ofspectra varies from 1.94 Hz to 3.77 Hz for both the horizontal and vertical motions for all
three locations. The mean peak Fourier amplitude has been found around 3.5 Hz along thevertical directions. The Fourier spectra at MT16 are more stable than other two locations
along EW, NS and UD directions, respectively.
0

0

10

0

10

-1

10

-2

10

13:07 PM (NS)16:20 PM (NS)
01:06 AM (NS)Mean (NS)

Fourier amplitude spectrum, µm

13:07 PM (EW)
16:20 PM (EW)
01:06 AM (EW)
Mean (EW)

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

-1

10

-2

10

-3

10

-3

10

10

-1

0

10

Frequency (Hz)10

1

13:07 AM (UD)
16:20 PM (UD)
01:06 AM (UD)Mean (UD)

-1

10

-2

10

-3

-1

0

10

10

Frequency (Hz)

10

1

10

-1

10

0

10

Frequency (Hz)110(a) MT05

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-1

10

-2

10

-3

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

10

18:29 PM (EW)
00:08 AM (EW)
01:29 AM (EW)
Mean (EW)010

18:29 PM (NS)OO:08 AM (NS)01:29 AM (NS)Mean (NS)

Fourier amplitude spectrum, µm

0

10

-1

10

-2

10

-3

10

10

-1

10

0

Frequency (Hz)18:29 PM (UD)00:08 AM (UD)
01:29 AM (UD)Mean (UD)

-1

10

-2

10

-3

-1

0

10

1

10

0

10

1

10

10

10

Frequency (Hz)

-1

0

10

1

10

Frequency (Hz)(b) MT06
0

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

11:34 AM (EW)
16:55 PM (EW)
19:41 PM (EW)
Mean (EW)

-1

10

-2

10

-1

10

-2

10

-3

-3

10

10

11:34 AM (NS)16:55 PM (NS)19:41 PM (NS)Mean (NS)

Fourier amplitude spectrum, µm

0

10

10
-1

10

0

10

Frequency (Hz)

1

10

0

11:34 AM (UD)
16:55 PM (UD)19:41 PM (UD)Mean (UD)

-1

10

-2

10

-3

-1

10

10

0

Frequency (Hz)

1

10

10

-1

10

10

0

Frequency (Hz)101(c) MT07

Figure 2.9 [(a), (b) and (c)]: Stability of Fourier Spectrum at different times along EW, NS
and UD directions at MT05, MT06 and MT07.
The Fourier spectra of MT22 and MT23 are shown in Figure 2.13. The peak value of thespectra lies between 2.48 Hz and 4.08 Hz for both the horizontal and vertical motions for
all three locations. Figure 2.13(a) shows the variation of Fourier spectra at MT22 at fourtime instants (12:48 PM, 15:53 PM, 11: 31 and 00:38 PM) along EW, NS and UD
directions, respectively. The variation of four time instants (12:48 PM, 15:53 PM, 11:46
PM and 00:46) of MT23 has been demonstrated in Figure 2.13 (b). From Figure 3.13, it
can be said that the Fourier spectra in night are stable.
From the Fourier spectra analysis of 14 sites, it can be said that the amplitude level of
Fourier spectra vary at different time instants of a day. The Fourier spectra at night are
more stable than other time instants within a day. In the most of the sites Fourier spectravary along EW and NS directions, respectively. It is not possible to estimate the dynamic
characteristics (Predominant frequency and Amplification) of these sites on the basis of
the amplitude level of Fourier spectra.
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0

10

-1

10

-2

10

11:24 AM (NS)16:55 PM (NS)12:01 PM (NS)12:21 PM (NS)Mean

Fourier amplitude spectrum, µm

11:24 AM (EW)
16:55 PM (EW)
00:01 AM (EW)
01:21 AM (EW)
Mean (EW)

Fourier amplitude spectrum, μm

Fourier amplitude spectrum, µm

0

10

0

10

-1

10

-2

10

11:24 AM (UD)
16:55 PM (UD)00:01 AM (UD)
01:21 AM (UD)Mean (UD)

-1

10

-2

10

-3

10

-3

10

-1

0

10

10

10

Frequency (Hz)

-1

0

10

1

-3

10

1

10

Frequency (Hz)

10

-1

0

10

1

10

10

Frequency (Hz)(a) MT08
0

10

-2

10

-3

10

13:07 PM (NS)16:20 PM (NS)20:30 PM (NS)Mean (NS)

Fourier amplitude spectrum, μm-1Fourier amplitude spectrum, μm

Fourier amplitude spectrum, μm

10

13:07 PM (EW)
16:20 PM (EW)
20:30 PM (EW)
Mean (EW)

10

0

0

10

-1

10

-2

10

-1

0

10

Frequency (Hz)

10

-2

10

-3

-1

10

1

-1

10

10

-3

10

10

13:07 PM (UD)
16:20 PM (UD)20:30 PM (UD)Mean (UD)100Frequency (Hz)

-1

0

10

1

10

10

1

10

Frequency (Hz)(b) MT09
0

0

10

-1

10

-2

10

-3

10

-1

0

10

10

Frequency (Hz)

1

10

0

10

12:53 PM (NS)16:53 PM (NS)19:52 PM (NS)Mean (NS)

10

-1

10

-2

10

-3

Fourier amplitude spectrum, μm

12:53 PM (EW)
16:15 PM (EW)
19:52 PM (EW)
Mean (EW)

Fourier amplitude spectrum, μm

Fourier amplitude spectrum, μm

10

10

-1

10

0

Frequency (Hz)1

10

12:53 PM (UD)
16:15 PM (UD)19:52 PM (UD)Mean (UD)

10

-1

10

-2

10

-3
-1

0

10

1

10

Frequency (Hz)10(c) MT10

Figure 2.10 [(a), (b) and (c)]: Stability of Fourier Spectrum at different times along EW, NS
and UD directions at MT08, MT09 and MT10.
0

-2

10

12:18 PM (NS)
17:19 PM (NS)20:10 PM (NS)Mean (NS)

Fourier amplitude spectrum, µm

-1

10

-1

10

-2

10

-3

-3

10

0

10

0

10

12:18 PM (EW)
17:19 PM (EW)
20:10 PM (EW)
Mean (EW)

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

10
-1

10

0

10

Frequency (Hz)1

10

12:18 PM (UD)
17:19 PM (UD)20:10 PM (UD)Mean (UD)

-1

10

-2

10

-3

-1

10

0

10

Frequency (Hz)

1

10

10

-1

10

0

10

Frequency (Hz)110(a) MT11

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1

0

0

10

0

10

10

11:08 AM (NS)17:37 PM (NS)00:40 AM (NS)01:28 AM (NS)Mean (NS)

Fourier amplitude spectrum, µm

11:08 AM (EW)
17:37 PM (EW)
00:40 AM (EW)
01:28 AM (EW)
Mean (EW)

Fourier amplitude spectrum, µm

H/V Ratio

10

-1

10

-2

10

-1

10

-2

10

-3

10

-1

10

0.1

1

-3

-1

0

10

10

Frequency (Hz)11:08 AM (UD)17:37 PM (UD)00:40 AM (UD)
01:28 AM (UD)AVERAGE (UD)

10

1

10

10

Frequency (Hz)

-1

0

10

1

10

10

Frequency (Hz)(b) MT12
0

0

0

10

-1

10

-2

10

-3

10

13:07 AM (NS)16:20 PM (NS)00:21 AM (NS)Mean (NS)

Fourier amplitude spectrum, µm

13:07 AM (EW)
16:20 PM (EW)
00:21 AM (EW)
Mean (EW)

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

-1

10

-1

0

10

Frequency (Hz)

10

-2

-2

10

10

-3

10

10

1

-1

10

10

-3

10

13:07 AM (UD)
16:20 PM (UD)00:21 AM (UD)Mean (UD)

-1

10

10

0

-1

1

0

10

10

Frequency (Hz)10

Frequency (Hz)110(c) MT13

Figure 2.11 [(a), (b) and (c)]: Stability of Fourier Spectrum at different times along EW, NS
and UD directions at MT11, MT12 and MT13.

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

15:12 PM (EW)
17:15 PM (EW)
00:33 AM (EW)
Mean (EW)

-1

10

-2

10

-3

0

10

0

15:12 PM (NS)
17:15 PM (NS)00:33 AM (NS)Mean (NS)

Fourier amplitude spectrum, µm

0

10

-1

10

-2

10

-1

0

10

10

Frequency (Hz)

-2

10

-3

10

1

10

-1

10

10

-3

10

15:12 PM (UD)
17:15 PM (UD)00:33 AM (UD)Mean (UD)

10

-1

10

0

Frequency (Hz)

10

-1

0

10

1

10

1

10

Frequency (Hz)(a) MT15
0

-2

10

-3

15:12 PM (NS)
17:15 PM (NS)00:27 AM (NS)00:56 AM (NS)Mean (NS)

Fourier amplitude spectrum, µm

-1

10

10

0

10

0

10

15:12 PM (EW)
17:15 PM (EW)
00:27 AM (EW)
00:56 AM (EW)
Mean (EW)

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

-1

10

-2

10

0

10

Frequency (Hz)

1

10

10

-1

10

-2

10

-3

10

-3

-1

10

15:12 PM (UD)
17:15 PM (UD)00:27 AM (UD)00:56 AM (UD)Mean (UD)

-1

10

0

10

Frequency (Hz)

10

1

-1

10

0

10

1

10

Frequency (Hz)(b) MT16
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0

0

10

-1

10

-2

10

-3

10

11:08 AM (NS)14:22 PM (NS)16:48 PM (NS)Mean

Fourier amplitude spectrum, μm

11:08 AM (EW)
14:22 PM (EW)
16:48 PM (EW)
Mean (EW)

Fourier amplitude spectrum, μm

Fourier amplitude spectrum, μm

10

-1

10

-2

10

-3

10

-1

0

10

10

1

10

10

Frequency (Hz)0

11:08 AM (UD)
14:22 PM (UD)
16:48 PM (UD)Mean (UD)

-1

10

-2

10

-3

-1

0

10

10

1

10

Frequency (Hz)

10

-1

0

10

1

10

10

Frequency (Hz)(c) MT19

Figure 2.12 [(a), (b) and (c)]: Stability of Fourier Spectrum at different times along EW, NS
and UD directions at MT15, MT16 and MT19.

0

0

10

-1

10

-2

10

0

10

12:48 PM (NS)15:53 PM (NS)11:31 PM (NS)00:38 AM (NS)Mean (NS)

10

-1

10

-2

10

-3

Fourier amplitude spectrum, µm

12:48 PM (EW)
15:53 PM (EW)
11:31 PM (EW)
00:38 AM (EW)
Mean (EW)

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

12:48 PM (UD)
15:53 PM (UD)
11:31 PM (UD)00:38 AM (UD)Mean (UD)

-1

10

-2

10

-3

10
-3

10

-1

0

10

10

Frequency (Hz)

-1

0

10

10

1

10

-1

0

10

Frequency (Hz)

1

10

10

Frequency (Hz)110(a) MT22
0

-1

10

-2

10

-3

0

10

12:48 PM (NS)15:53 PM (NS)11:46 PM (NS)00:46 AM (NS)Mean (NS)

Fourier amplitude spectrum, µm

10

0

10

12:48 AM (EW)
15:53 PM (EW)
11:46 PM (EW)
00:46 AM (EW)
Mean (EW)

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

-1

10

-2

10

-3

10

10

-1

10

0

10

Frequency (Hz)

1

-1

0

10

10

Frequency (Hz)1

10

12:48 PM (UD)
15:53 PM (UD)11:46 PM (UD)00:46 AM (UD)Mean (UD)

10

-1

10

-2

10

-3
-1

10

0

1

10

10

Frequency (Hz)(b) MT23
P37
P37
Figure 2.13 [(a) and (b)]: Stability of Fourier Spectrum at different times along EW, NS and
P37
P37
�� /�
���/�� at MT22 and MT23.
UD directions

��
� /�
� /�
��
P78
2.4.1.2 Stability
ofP78
Horizontal to Vertical Spectral Ratio
P78
P78
2.4…..
2.4…..
を次のページに移動
を次のページに移動

The
amplitude
ratio calculated in this study is defined by Nakamura (1989). Amplitude
2.4…..
2.4…..
を次のページに移動
を次のページに移動
P88
P88
ratios of Fourier amplitude spectra of EW and NS components, respectively, to that of the
P88
P88
� �
� �
����
��
= =�� ��as����= =�� �� ������
, ���
, ���
����������
����UD components, ����
and
, are
follows:
������ ����
��obtained
��
�� ��
����
�� ��
���
���

��
��
��
��
��
�� ��
���� ��
��
��= =
P95
P95

88

P95
P95

���
���

������
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���

��
��
����= =

� ��
� ��
���
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�� ��

���
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BNUS Annual Report-2011

P37P37

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ジに移動
ージに移動
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ICUS Report 59

P78P78�������
����
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are
== ��
=
��
��
��
=��
=Where,
=��
����
�,��
, ����, �and
����
��
��
��
��
��Fourier������
��2.4…..
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��
��
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��
��the
��
��
�� �� amplitude spectra in the EW, NS and vertical
2.4…..
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�����
��

� �

direction, respectively.
P88P88The Horizontal to Vertical spectral ratio along EW and NS directions are shown from
�

�

�

�

�� ��
Figure2.14
to��2.18.
����
��
����
��
����
=����
= In��Figure������=2.14,����, �����, ratios,
����
����
��and
����
���� of the Fourier������ = amplitude�� ���
����� ������ ���

spectra of two horizontal components, are shown for three different time instants (13:07
PM, 16:20 PM and 01:06 AM) of MTO5, MT06 and MT07, respectively. The

characteristics of the peak frequency of the amplitude ratios are different from those for
P95P95
Fourier spectra (Figure 2.9). The mean predominant frequency of two horizontal
�����
�����
����
������
directions at MT05 and MT06 are stable. The mean predominant frequency of two� ���� ��� � ��
����� ���� directions
��at MT05 is around 0.77 whereas this value is around 0.94 at MT05�= �= horizontal��along EW and NS directions, respectively. The mean peak amplitude ratio is around 1.25����������
��
���
����
�� �
��
at MT07.
Although the Fourier spectra are not stable with time, the amplitude ratios at

����
��
���
�����
����

different time instants along three directions within a day are stable at these sites.

�����
���
���

���
���
���

= ��
���
��
����
���
� ���
�� � ���� ������������� � �� �
� �
���
���
���
���
���
���
Figure 2.15 shows stability of H/V ratio data at different time instants at MT08, MT09
P98P98���������
MT10 along EW and NS components, respectively. The peak Fourier amplitude08����������� � �� � and
� �
�
�
���
���
��� �� ������� �����

� are around������
���
ratios of MT08,�which
1.20 Hz, are similar ���
amplitude ratios at– � –� �� � � � � = =�� �
�����
� ���
� � ��
��������
� to �the� Fourier
�
�
�
���
���
���
���
�����
�����
�MT10.
�The peak amplitude ratio of MT09 is around 1.20 Hz along EW component andaround 1.06 Hz along NS component, where the change of amplitude ratio of the spectra������� � � +�0.08+ 0.08������� �� �
������

������

������

������

at different time instants of a day is comparatively small.

Figure 2.16 represents Stability of H/V ratio data at different time instants at MT11,
P130P130
and MT13 along EW and NS components, respectively. The peak Fourier� MT12�= =� ��� ���� ����amplitude
��
ratios of MT10 varies between 0.78 Hz and 0.88 Hz where this value is around0.93 Hz at MT12. The peak amplitude ratio of MT13 is around 1.22 Hz at MT13 in both
Horizontal components.
The pattern of the amplitude spectra ratio at MT15, MT16 and MT19 are illustrated in
Figure 2.17. Figure 2.17(a) and Figure 2.17(b) show the of amplitude change of Fourier
spectra at three different time instants are comparatively small. The amplitude spectra
ratio of four different time instants (15:12 PM, 17:15 PM, 00:27 AM and 00:56 AM) andtheir mean value are stable (Figure 2.17 (b)).
Figure 2.18 shows the stability of H/V ratio data at four different time instants at MT22
and MT23 along EW and NS components, respectively. Figure 2.18 (a) represent theamplitude spectra ratio of MT22 is around 0.96 Hz along EW component and around 0.73
15489

March 2012

Hz along NS component. The peak amplitude ratio of MT23 lies between 0.98 Hz and1.32 Hz along the two horizontal directions. The change of amplitude spectra ratio atfour different time instants (12:48 PM, 15:53 PM, 11:31 PM and 00:38 AM) at MT 22
and four different time instants (12:48 PM, 15:53 PM, 11:46 PM and 00:46 AM) at MT
23 are stable.
From analysis of Fourier spectra ratio from Figure 2.14 to 2.18, it can be concluded thatthe change of amplitude ratio at different time instants of a day is comparatively small. In
addition to this, the amplitude ratio is less influenced by the source of vibration than the
Fourier spectrum of any direction and may reflect the particular charactersistics of the site.
Therefore, the Horizontal to Vertical spectra ratio has been found more reliable toestimate dynamic properties (Predominant frequency and Amplification) of any particular
soil.
1

1

10

13:07 AM (EW)
16:20 PM (EW)
01:06 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

13:07 AM (NS)16:20 PM (NS)
01:06 AM (NS)Mean (NS)

0

10

-1

-1

10

10

-1

0

10

10

-1

0

10

1

10

1

10

10

1

10

Frequency (Hz)Frequency (Hz)(a) MT05
1

1

10

18:29 PM (EW)
00:08 AM (EW)
01:29 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

-1

10

0

10

-1

-1

10

0

10

1

10

Frequency (Hz)90

18:29 PM (NS)00:08 AM (NS)01:29 AM (NS)Mean (NS)

155

10

0.1

Frequency (Hz)BNUS Annual Report-2011

ICUS Report 59(b) MT06
1

1

10

11:34 AM (EW)
16:55 PM (EW)
19:41 PM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

11:34 AM (NS)16:55 PM (NS)19:41 PM (NS)Mean (NS)

0

10

-1

10

-1

10

-1

0

10

10

Frequency (Hz)

10

1

10

-1

0

10

Frequency (Hz)110(c) MT07

Figure 2.14 [(a), (b) and (c)]: Stability of H/V ratio data at different times along EW and NS
direction at MT05, MT06 and MT07.
1

10

1

11:34 AM (EW)
16:55 PM (EW)
00:01 AM (EW)
01:21 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

0

10

-1

10

-1

10

11:34 AM (NS)16:55 PM (NS)00:01 AM (NS)01:21 AM (NS)Mean (NS)

-1

10

0

10

Frequency (Hz)

1

10

-1

10

0

10

Frequency (Hz)110(a) MT08

156

91

March 2012
1

1

10

13:07 PM (EW)
16:20 PM (EW)
20:30 PM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

13:07 PM (NS)16:20 PM (NS)20:30 PM (NS)Mean (NS)

0

10

-1

-1

10

10

-1

0

10

10

Frequency (Hz)

1

-1

0

10

10

1

10

10

0

10

Frequency (Hz)(b) MT09
1

1

10

12:53 PM (EW)
16:15 PM (EW)
19:52 PM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

-1

10

-1

0

10

0

10

10

1

10

10

12:53 PM (NS)16:25 PM (NS)19:52 PM (NS)Mean (NS)-1

10Frequency (Hz)-1

10Frequency (Hz)1(c) MT10

Figure 2.15 [(a), (b) and (c)]: Stability of H/V ratio data at different times along EW and NS

10

1

10

0

1

10

12:18 PM (EW)
17:19 PM (EW)
20:10 PM (EW)
Mean (EW)H/V Ratio

H/V Ratio

direction at MT08, MT09 and MT10.

-1

12:18 PM (NS)
17:19 PM (NS)20:10 PM (NS)Mean (NS)

0

10

-1

10

10

-1

0

10

Frequency (Hz)

10

10

1

-1

10

0

10

Frequency (Hz)110(a) MT11

92

157

BNUS Annual Report-2011

ICUS Report 59
1

10

1

11:08 AM (EW)
17:37 PM (EW)
00:40 AM (EW)
01:28 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

0

10

-1

-1

10

11:08 AM (NS)17:37 PM (NS)00:40 AM (NS)01:28 AM (NS)Mean (NS)0.1

1Frequency (Hz)

10

10

-1

0

10

(b) MT12
1

10

1

10

13:07 AM (EW)
16:20 PM (EW)
00:21 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

1

10

Frequency (Hz)010

13:07 PM (NS)16:20 PM (NS)00:21 AM (NS)Mean (NS)

0

10

-1

10

-1

10

-1

0

10

10

Frequency (Hz)

-1

0

10

1

10

10

Frequency (Hz)110(c) MT13

Figure 2.16 [(a), (b) and (c)]: Stability of H/V ratio data at different times along EW and NS
direction at MT11, MT12 and MT13.
1

1

10

15:12 PM (EW)
17:15 PM (EW)
00:33 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

10

-1

15:12 PM (NS)
17:15 PM (NS)00:33 AM (NS)Mean (NS)

0

10

-1

10

-1

0

10

Frequency (Hz)

10

1

158

10

-1

10

0

10

Frequency (Hz)

1

10

93

March 2012(a) MT15
1

1

10

15:12 PM (EW)
17:15 PM (EW)
00:27 AM (EW)
00:56 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

-1
-1

0

10

0

10

10

Frequency (Hz)

10

1

0

1

10

10

Frequency (Hz)(b) MT16
1

10

11:08 AM (EW)
14:22 PM (EW)
16:48 PM (EW)
Mean (EW)

-1

10

-1

10

H/V Ratio

H/V Ratio

10

1

0

10

-1

10

10

15:12 PM (NS)
17:15 PM (NS)00:27 AM (NS)00:56 AM (NS)Mean (NS)11:08 AM (NS)14:22 PM (NS)16:48 PM (NS)Mean (NS)

0

10

-1

-1

0

10

10

1

10

Frequency (Hz)

10

-1

10

10

0

1

Frequency (Hz)(c) MT19

10

Figure 2.17 [(a), (b) and (c)]: Stability of H/V ratio data at different times along EW and NS
direction at MT15, MT16 and MT19.
1

1

10

12:48 PM (EW)
15:53 PM (EW)
11:31 PM (EW)
00:38 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

-1

-1

10

94

0

10

10

-1

10

12:48 PM (NS)15:53 PM (NS)11:31 PM (NS)00:38 AM (NS)Mean (NS)010Frequency (Hz)

1

10

159

-1

10

0

10

Frequency (Hz)1

10

BNUS Annual Report-2011

ICUS Report 59(a) MT22
1

1

10

12:48 PM (EW)
15:53 PM (EW)
11:46 PM (EW)
00:46 AM (EW)
Mean (EW)H/V Ratio

H/V Ratio

10

0

10

10

-1

12:48 PM (NS)15:53 PM (NS)11:46 PM (NS)00:46 AM (NS)Mean (NS)

0

10

-1

10

-1

10

0

10

1

10

Frequency (Hz)

-1

0

10

1

10

10

Frequency (Hz)(b) MT23

P37
P37
Figure2.18 [(a) and (b)]: Stability of H/V ratio data at different times along EW and NS
P37
�� /�P37
�� /��
�P37 direction at MT22 and MT23.
�� /��
P78 � /�P78
P37
�� /�� � �
2.4.2 P78
Resultant of H/V Ratio Curve
2.4…..
2.4….. を次のページに移動
P78を次のページに移動�� /��
P78
Microtremor
H/V ratio has been found along East-West and North-South direction,
2.4….. を次のページに移動
P88 2.4….. を次のページに移動 P88
P78
2.4….. To
を次のページに移動
respectively.
estimate Predominantfrequency and H/V ratio resultant of two direction
P88
���
���
���
���
�� isP88���� ��
��two=direction
��
���
��
�curve
= ��
��
����
�� =
�� ��
��, �ratio
�� ��
��
��RM,
�� = � RS ��� , ��� ���
spectrum
necessary.
Four
resultant
of
H/V
are
RMS,
��� 2.4…..
������
を次のページに移動
P88��
��
��
���
���
��
��
=
��
=
�
,
�
�
��
��
��
��The resultant�������� These��are follows:
��
���
���
and mean.
H/V ratiobe��
represented
in four��ways.
��� can��������� , ��� ��� ���� �������� ���� �����
��= P88
�� =
��
���
��
���� ���� ���� =���� =���� , ��� ��� ���� ����P95(a) Root multiplication, RM:

P95
RM = ���P95
�� � ����
P95
����� RMS:����� ��square,(b) Rootmean���� �������� � �� � �����=����� � ������� ��� �
RMS== � �� ����� ��� �
� ��
��
� �
��
��
���
�
��
���
=���
����
�
= � ��� RS:(c) ���
Root �square,
�
���
����
��
����
���
�
�
����
� ������ ��RS = ��
�������� � ����
��

��

��
�����
(d) Mean=������
����
��
�
�

���

���

P95 �� = ������� ��
����
Where,
������� =��������� , ��� ��� ����Horizontal
to Vertical Spectral����� �= ��
��

P95

Ratio
along East-West direction�� � ��� �= � �� ��
�

�

�

����
to Vertical Spectral� ����
����� ����� =�Horizontal
Ratio
along
North-South direction� ��������
��
����
���
��
�
�

= �

�
�
�����
� ����
P98
P98
P98
���� �����
�
�
�
�
P98
� ��� �� ������� �����
�
� ���
���
P98
�
�
The resultant
H/V ratio
2.21.
– �
� has
= been�� �shown��� � from– ���Figure 2.19
� to���
=Figure��� �� ���These� three��������� ������
���������������
���
�
��
�
�
graphsthecomparison
of
H/V
ratio
resultant
in
four
ways.
�
– represent=� � �� �����
�
���
���
�
��
���
�����
��
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���
��� ���
= ��� ����–� ���
�
���
–
�
���
���
����� =��������� ���
�����
����
���
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�
� ���
��� �� �����
�
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�
– ���
=
���
�
���
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���
���
�
���
�����
� 160
���
���

�
� ��
���

�
�� � ������ � �P98� ��
�
��
�
���
�
��
��� ���� ��� � � + 0.08
��� ����
�� + 0.08 ���� ����� ������� � � + 0.08 ��� � ��
� + 0.08
��� ���� �� + 0.08
��� ���� ��
P130
���

P130��
= P130 ��
����
P130

��

�

�

�� � ��� �

P130
���
���
��� � = ���+ 0.08����� �
�
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� ���
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95

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March 2012
1

H/V Ratio

10

0

10

RM
RMS
RS
MEAN

-1

10

-1

0

10

10

Frequency (Hz)1

10

Figure 2.19: Comparision of RM, RMS, RS and MEAN resultant H/V ratio of EW and
NS direction at Bashundhara, Block-D.
1

H/V Ratio

10

0

10

RM
RMS
RS
MEAN

-1

10

-1

10

0

10

Frequency (Hz)1

10

Figure 2.20: Comparision of RM, RMS, RS and MEAN resultant H/V ratio of EW and
NS direction at Board Bazar, Gazipur.

96

161

BNUS Annual Report-2011

ICUS Report 59
1

H/V Ratio

10

0

10

RM
RMS
RS
MEAN

-1

10

-1

10

0

10

Frequency (Hz)1

10

Figure 2.21: Comparision of RM, RMS, RS and MEAN resultant H/V ratio of EW and
NS direction at Uttar Khan.
Figure 2.19 shows comparison of RM, RMS, RS and MEAN resultant H/V ratio of EW
and NS direction at Bashundhara, Block-D. Figure 2.20 and 2.21 demonstrate comparisonof H/V ratio in Board Bazar, Gazipur and Uttar Khan, respectively. From Figure 2.19 to
Figure 2.21, it can be said that square root H/V ratio shows higher value than others. The
RM, RS and mean H/V ratio show almost similar value. For this study, Rootmultiplication H/V ratio has been analyzed to estimate predominant frequency and H/Vratio.
2.4.3 Window Effect on Microtremor data
Fourier transformation using various analysis windows has significant effect on
Horizontal to Vertical spectral ratio (H/V). The most common five types of analysis
windows are Rectangular, Hanning, Hamming, Welch and Blackman windows. Fast
Fourier transformation can be done in five time windows. The equations of five windows
are shown from Equation 2.2 to Equation 2.6. These equations are follows:
1)

Rectangular Window
W[n] = 1 for 0 ≤ n ≥ N and zero otherwise

2)

Welch Window:
162

(2.2)

97

���� � ������ ��� ����������� �����
�

� �

�����

�

�
�
� ����
�����

�

�

P98

���� �����
�

P98
3)

98

�
�

���� �����

�

March 2012��� ����
������ �����

= �

– � �

4)

�

�����

�

��
�� ����������� �����
��

�
== �

��

���
��
�����
�
� ��
����
� ���
��
�� �������
�

W[n] = 1 –– � � �

Hanning
Window:���� �����

����
����
�
���
�� �� ����

�W[n]==

��

Hamming Window

����
=
���

��
����
�����
��

�

���

��
��

��

�� � ��� �

�

���

�

���

���

���

���

���

��

��

��

���
�����
�����

==

��
��

���

��

�������� �����
+ 0.08 ��� � ���� � ��� �
��
���
���
P98
P98 ������������ �����
�����
P130
���
���
= ���
�� �����
����W[n]�+ 0.08–����
0.46=��0.54––������
���
��
�

���

���

���(2.3)
� �
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(2.4)
���
���

��
�� �
� ���
�����

��
��

���
���

=
�� ��
5) Blackman Window:
��
���
���
���
���
���
���
��� � � + 0.08P130
��� � �W[n] = 0.42 – 0.5 �������� �� ++ 0.08
0.08 ���
����� ��
(2.6)
���
���
���
���
���
���
�
= � �� ��
Where,��
130
P130P130number and N = Total number of data points
W[n] = Windows function, n = Index������ result of microtremor data of three segments at
�� ��Figure 2.22 to 2.25 show the analysis==
���� ����
������Bramangaon. Microtremor Time history
data of three segments has been Fourier���transformed using five windows. Figure 2.22 shows the analysis result of segment 1 in

five windows at Bramangaon. From Figure 2.22, rectangular window shows different
H/V ratio result than other four windows. The other four H/V curve gives almost similar
pattern. However, predominant frequency is same in all the five cases. Rectangular
window gives lower peak value of H/V ratio than other methods at segment 2 (Figure2.23). From Figure 2.24, the rectangular window shows similar predominant frequency
and H/V ratios to other windows. The mean H/V ratio and predominant frequent of fivemethods are represented in Figure 2.25. According to Figure 2.25, the pattern of H/V ratio
curve in rectangular window is similar to other four windows. From the analysis of mean
H/V ratio curve in five windows, it can be said that rectangular window is more suitable
than other windows to estimate predominant frequency and H/V ratio. Therefore,
rectangular window is selected to analyze the microtremor data in this study. This
rectangular windows is suitable than others to assess dynamic properties.

98

163

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���

(2.5)���
�����

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1

H/V Ratio

10

0

10

Rectangular
Hanning
Hamming
Welch
Blackman

-1

10

-1

0

10

10

Frequency (Hz)1

10

Figure 2.22: Five different windows effect on Microtremor data at segment 1 of

H/V Ratio

Bramangaon.
10

1

10

0

10

Rectangular
Hanning
Hamming
Welch
Blackman

-1
-1

10

0

10

Frequency (Hz)1

10

Figure 2.23: Five different windows effect on Microtremor data at segment 2 ofBramangaon.

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1

H/V Ratio

10

0

10

Rectangular
Hanning
Hamming
Welch
Blackman

-1

10

-1

0

10

10

Frequency (Hz)1

10

Figure 2.24: Five different windows effect on Microtremor data at segment 3 ofBramangaon.
1

H/V Ratio

10

0

10

Rectangular
Hanning
Hamming
Welch
Blackman

-1

10

-1

0

10

10

1

10

Frequency (Hz)Figure 2.25: Five different windows effect on mean microtremor data at Bramangaon.
2.4.4

100

Smoothing Effect on Microtremor Data

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Smoothing of microtremor data has significant effect to estimate predominant frequency
and H/V ratio of any particular site. In some microtremor measurement locations, it isdifficult to estimate dynamic properties. In that case, smoothing of data with suitablesmoothing point gives accurate data. Therefore, almost all the microtremor locations data
has been smoothed with suitable smoothing point. Generally, H/V ratio decreases andpredominant frequency changes with the increase of smoothing point. So, proper
justification is required before applying smoothing point on microtremor logarithmic
window. Figure 2.26 to 2.29 show four mean microtremor data with smoothing effect.
Different smoothing points have been applied to determine predominant frequency and
H/V ratio. Figure 2.26 shows that the peak H/V becomes decreases due to applying
different smoothing point. Figure 2.27, 2.28 and 2.29 illustrate the application of suitablesmoothing point to determine Predominant frequency and H/V ratio of soil. It is difficult
to determine predominant frequency and H/V ratio.
1

H/V Ratio

10

0

10

Original mean data
3 point
5 point
10 point
15 point
20 point

-1

10

-1

10

0

10

Frequency (Hz)1

10

Figure 2.26: Variation of predominant frequency and H/V ratio due to smoothing effect at
Bramangaon.

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1

H/V Ratio

10

0

10

Original mean data
2 point
3 point
5 point
10 point
15 point

-1

10

-1

0

10

10

1

10

Frequency (Hz)Figure 2.27: Variation of predominant frequency and H/V ratio due to smoothing effect at

H/V Ratio

Tongi, Ershadnagar.
10

1

10

0

Original mean data
2 point
3 point
5 point
10 point
15 point

-1

10

-1

10

0

10

Frequency (Hz)1

10

Figure 2.28: Variation of predominant frequency and H/V ratio due to smoothing effect at
Ashiyan city.

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1

H/V Ratio

10

0

10

Original mean data
3 point
5 point
10 point
15 point
20 point

-1

10

-1

0

10

10

1

10

Frequency (Hz)Figure 2.29: Variation of predominant frequency and H/V ratio due to smoothing effect at
Agargaon Trade Fair.
2.5

ANALYSIS RESULT

Field time history microtremor data of 132 locations within BUET campus and 45 sites inand around Dhaka city has been analyzed according to section 2.4. The mean H/V ratio
and standard deviation at 45 locations has been included in this chapter. The remains ofanalysis results of these locations are shown in APPENDIX-B. Microtremor analysis
results at 132 locations in soil and 45 buildings within BUET campus are presented in thischapter. But, details Figures are illustrated in APPENDIX-C and APPENDIX-D.
2.5.1

Microtremor Analysis Result in and around Dhaka City

Microtremor measurement has been carried out in 45 locations at latitude lies from2338΄15.10 to 2356΄46.54 and longitude lies from 9020΄24.92 to 9033΄50. Obtained

velocity records are converted from time domain to frequency domain to get the Fourier
Spectrum and it has been smoothed by using rectangular window with average smoothing
point 5.

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Table 2.16: Microtremor Test Location, Predominant Frequency and H/V ratio in andaround the Dhaka city
SerialNumberID

Location

Latitude1

SBH-01

National University

2356΄46.54

9022΄43.93

1.24

2.59

2

SBH-022356΄18

9023΄58

0.82

2.73

3

SBH-032355΄37

9023΄03

0.72

2.79

4

SBH-04

Board Bazaar,
Gazipur
Kaunia, Boro Bari,
Moddopara
Tongi, Ershadnagar

23°54'48"

90°24'11"

0.97

2.51

5

SBH-05

Tongi BSCIC area

23°53'37.18"

90°25'13.35"

0.95

2.73

6

SBH-06

Abdullahpur

2352΄31

9024΄01

1.32

2.33

7

Ijtema field (North
and East side)
Ijtema Field (Southand West side)
Ashulia Toll Plaza

2353΄31.13

9023΄53.39

1.17

3.37

2352΄59.96

9023΄37.91

0.86

3.26

9

SBH07(A)
SBH-07(B)
SBH-0823°53'25.40"

90°21'54.61"

1.14

1.75

10

SBH-9

Uttar Khan

23΄52΄30

9025΄28

1.09

2.09

11

SBH10(A)
SBH10(B)
SBH-11

Uttara Phase 3( North side)
Uttara Phase 3 (South
side)
Azampur School,
UttaraMirpur DOHS
(South side)2352΄22

9021΄40

1.18

3.16

2351΄15

9021΄16

0.97

4.47

2352΄03

9024΄04

3.65

2.73

2349΄59

9022΄42

1.54

2.46

Mirpur DOHS
2350΄11(North side)
Ashiyan city, Askona, 2350΄49
Dakkhin Khan
Purbachal-1,2345΄03
Randokpur Hazi bari,
Rupganj
Purbachal-2,2349΄33
American City
Purbachal Picnic
2351΄28
Park, Gazipur
Adjacent to Mirpur 2349΄04.14
Zoo
Field Ground, Pallabi
2349΄06

9022΄42

1.21

3.44

9025΄37

1.12

3.19

9031΄17

0.94

3.04

9033΄50

2.00

2.69

9031΄14

1.34

2.23

9020΄29.63

1.52

2.43

9022΄08

1.24

2.64

2348΄38

9025΄54

2.09

3.12

Block-D, Basundhara 2349΄00.49

9026΄12.95

1.57

4.71

Block-H, Basundhara9026΄34

2.52

2.94

8

12
13
14

SBH-12(A)

15

SBH-12(B)
SBH-1316
17

SBH14(A)1820

SBH14(B)
SBH14(C)
SBH-1521

SBH-1622

SBH-17(A)
SBH-17(B)
SBH-17
(C)

19

23
24

104

Block-B, Basundhara

2349΄19
169

Longitude Predominant H/V Ratio
Frequency(RM)

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SerialNumberID

Location

LatitudeLongitude Predominant H/V Ratio
Frequency(RM)

25

SBH-1823050΄33.61

90025΄11.22

0.64

3.70

26

SBH-19Civil Aviation
Quarter
Kuril Flyover

2349΄41.51

9026΄32.06

1.97

2.73

27

SBH-20Sarengbari, Mipur-2

2348΄03.24

9020΄47.10

0.59

2.84

28

SBH -21 Purachal, Uttar Badda

2346΄51

9026΄29

2.11

2.59

29

SBH-222346΄41.99

9020΄24.92

0.82

3.67

30

SBH-23

City Corporation,
Gabtoli
Adabor2346΄09.75

9021΄37.62 

3.35

2.26

31

SBH-242346΄10.56

9022΄42.73

0.86

2.12

32

SBH-252346΄04.98

9026΄03.22

0.95

2.76

33

SBH-262347΄57.17

9025΄41.61

1.32

3.83

34

SBH-27

Agargoan Trade Fairarea
Aftab Nagar Housing
Project
Umme Had Nagar,
Nadda
South Banasree2345΄07.17

9026΄45.36

1.39

3.86

35

SBH-28Basila Garden City

2345΄10.29

9020΄42.36

1.12

4.47

36

SBH-292344΄54

9021΄28

2.57

1.08

37

SBH-302343΄38.50

9022΄08.62

0.83

3.86

38

SBH-312342΄57.58

9022΄42.11

0.48

3.91

39

SBH-322342΄44.81"

9023΄26.51

1.21

4.78

40

SBH-33Royer Bazar
Boddhobumi
Kalunagar,
Hazaribagh
Rab-10, Plot,
Kamrangirchar
Sosan Ghat,
Kamrangirchar
Basundhara Riverview

2339΄10

9026΄09

1.05

3.51

41

SBH-34

Matuail, Demra

2343΄18.24

9028΄16.48

2.77

2.48

42

SBH-35

Jilmil Project, Equria2340΄33.40

9024΄08.42

1.00

3.26

43

SBH-36

Rajendapur

2339΄25

9022΄58

1.17

2.59

44

SBH-37

Bramangaon

2338΄15.10

9027΄37.35

1.08

3.55

45

SBH-38

Meradia, Uttar
Banasree2345΄43.57

9026΄19.67

1.26

2.84

Table 2.16 shows predominant frequency and square root of Horizontal to Vertical
spectral ratio (H/V) at 45 locations in and around the Dhaka city. The locations, latitude
and longitude of 45 locations are also demonstrated in Table 2.16. Figure B2.30
represents the comparison of predominant frequency and H/V ratio among these locations.
Details of predominant frequency, mean H/V ratio and standard deviation are illustrated
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from Figure B2.31 to Figure A2.75. The basic six H/V ratio, square root of H/V ratio in
three segments and their mean H/V ratio are also illustrated in APPENDIX-B.
Table 2.16 shows the predominant frequency and H/V ratio at 45 locations. Out of 45
microtremor observation locations, the maximum predominant frequency is 3.65 Hz,
where H/V ratio is 2.73, at Azampur School, Uttara (Lat. 2352΄03 and Long. 9024΄04).
The geology of this location is Upper Modhupur terrace (Figure 3.2) and Moderately
High Pleistocene terrace (Figure 2.3). Figure 2.30 shows the Horizontal to Vertical
spectral ratio (H/V) ranging between 1.81 and 3.74. The basic six H/V ratio in threesegments along EW and NS direction, H/V ratio of three segments and their mean value
are shown in Figure B2.43. On the other hand, the minimum predominant frequency is
0.48 Hz, where H/V ratio is 3.91, Rab-10, Plot, Kamrangirchar (Lat. 2342΄57.58andLong. 9022΄42.11). This location is classified as River Bar (Figure 3.2) and Moderately
Thick fill (Figure 3.3). Figure 2.31 demonstrates square root of Horizontal to Vertical
spectral ratio (H/V) ranging between 2.23 and 5.65.
From Table 2.16, the maximum Horizontal to Vertical spectral ratio (H/V) is 4.78 where
as predominant frequency is 1.22 Hz, at Sosan Ghat, Kamrangirchar (Lat. 2342΄44.81"and
Long. 9023΄26.51). The geology of this site is flood plain (Figure 2.2) and thick fill
(Figure 2.3). Figure 2.32 shows Horizontal to Vertical spectral ratio (H/V) ranging
between 4.07 and 5.71. The basic six H/V ratio in three segments along EW and NS
direction, H/V ratio of three segments and their mean value are shown in Figure B2.69.
The minimum Horizontal to Vertical spectral ratio (H/V) is 1.08 where as predominantfrequency is 2.57 Hz at Royer Bazar (Lat. 2344΄54and Long. 9021΄28). The geologyof this location is River Bar (Figure 2.2) and gently sloping Erosional terrace edge
(Figure 2.3). Figure 2.33 shows Horizontal to Vertical spectral ratio (H/V) ranging
between 0.87 and 1.28. The basic six H/V ratio in three segments along EW and NS
direction, H/V ratio of three segments and their mean value are illustrated in Figure B2.66.
Out of 45 locations, the overall predominant frequency is 1.25 Hz with standard deviation
0.014. On the other hand, the overall H/V ratio is 2.72 with standard deviation 0.177. The
predominant frequency of 45 locations has been classified into five types which are TypeI (0 – 0.49), Type II (0.50 – 0.99), Type III (1.0 – 1.99), Type IV (2.0 – 2.99) and TypeV (> 3.00).

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The classifications of predominant frequency at 45 locations are as follows:
Type I: SBH-31
Type II: SBH-02, SBH-03, SBH-04, SBH-05, SBH-07(B), SBH-10(B), SBH-14(A),SBH-18, SBH-20, SBH-22, SBH-24, SBH-25 and SBH-30.
Type III: SBH-01, SBH-06, SBH-07(A), SBH-08, SBH-09, SBH-10(A), SBH-12(A),SBH-12(B), SBH-13, SBH-14(C), SBH-15, SBH-16, SBH-17(B), SBH-19, SBH-26,
SBH-27, SBH-28, SBH-32, SBH-33, SBH-35, SBH-36, SBH-37 and SBH-38.
Type IV: SBH-14(B), SBH-17(A), SBH-17(C), SBH-21, SBH-29 and SBH-34.
Type V: SBH-11 and SBH-23.
From this classification of predominant frequency, it can be said that most of thelocations predominant frequency varies from 1.0 Hz to 1.99 Hz. These are classified as
Type III. This classifications show the second most common predominant frequency
ranging between 0.50 and 0.99. The number of locations predominant frequency ranging
between 2.0 and 2.99 is six. Only SBH-31 is classified as Type I predominant frequency.
On the other hand, Horizontal to Vertical spectral ratio (H/V) has been classified into fourtypes. Type I (0-0.99), Type II (1.0 – 1.99), Type III (2.0 – 2.99) and Type IV (>3.0).
The classifications of H/V ratio at 45 locations are as follows:
Type I: None
Type II: SBH-08, SBH-12(B), SBH-14(C), SBH-15, SBH-16, SBH-17(B), SBH-29 andSBH-39.
Type III: SBH-01, SBH-02, SBH-03, SBH-04, SBH-05, SBH-06, SBH-09, SBH-11,
SBH-12(A), SBH-14(B), SBH-17(A), SBH-17(C), SBH-19, SBH-20, SBH-21, SBH-23,
SBH-24, SBH-25, SBH-34, SBH-36 and SBH-38.
Type IV: SBH-07(A), SBH-07(B), SBH-10(A), SBH-10(B), SBH-13, SBH-14(A),SBH-18, SBH-22, SBH-26, SBH-27, SBH-28, SBH-30, SBH-31, SBH-32, SBH-33,
SBH-37 and SBH-39.
From the above classification of H/V ratio, the common H/V ratio is Type III in 45
locations. The second most common H/V ratio is Type IV. The number of locations H/Vratio ranging between 1.0 and 1.99 is eight.

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1

H/V Ratio

10

0

10

mean
mean+1/2σmean-1/2σ

-1

10

-1

0

10

1

10

10

Frequency (Hz)Figure 2.30: Predominant frequency and H/V ratio at Uttara Azampur.
1

H/V Ratio

10

20

mean
mean+1/2σmean-1/2σ

-1

10

-1

10

0

10

Frequency (Hz)1

10

Figure 2.31: Predominant frequency and H/V ratio at Rab-10 Plot, Kamrangirchar.

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1

H/V Ratio

10

0

10

mean
mean+1/2σmean-1/2σ

-1

10

-1

0

10

10

Frequency (Hz)1

10

Figure 2.32: Predominant frequency and H/V ratio at Sosan Ghat, Kamrangirchar.
1

H/V Ratio

10

0

10

mean
mean+1/2σmean-1/2σ

-1

10

-1

0

10

10

1

10

Frequency (Hz)Figure 2.33: Predominant frequency and H/V ratio at RoyerBazar.

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2.5.2

Microtremor Analysis Result within BUET Campus

The BUET campus is situated in latitude ranging from 23°43'16.58" N to 23°43'59.44" Nand longitude from 90°23'13.31"E to 90°23'43.56" E. Microtremor observation at 132
selected points in soil and 45 locations in building have been carried out in BUET campus.
The analysis results of these points are shown in this chapter and APPENDIX-C and
APPENDIX-D.
2.5.2.1

Soil Sites

Table 2.17 shows predominant frequency and RM value of H/V ratio of 132 locations.
Figure 2.34 demonstrates the observed microtremor locations at 132 selected locations.
The details analysis results at 132 points are illustrated in APPENDIX-C from Figure
C2.76 to Figure C2.207.
Out of 132 sites, the overall mean predominant frequency is 1.39 Hz where as standard
deviation is 0.289. On the other hand, the overall peak mean H/V ratio is 2.09 where as
standard deviation is 0.523.
Table 2.17 shows the predominant frequency and mean H/V ratio in 132 locations. Out of
132 microtremor observation locations, the maximum predominant frequency is around9.62 Hz where as H/V ratio is 2.43 at MT82. The geology of this site is Upper Modhupur
terrace (Figure 2.2) and Higher Pleistocene Terrace (Figure 2.3). Figure 2.35 (f) andC2.157 shows Horizontal to Vertical spectral ratio (H/V) ranging from 1.65 to 2.51. The
basic six H/V ratio in three segments along EW and NS direction, square root of H/Vratio of three segments and their mean value are also shown in Figure C2.157. On theother hand, the minimum predominant frequency is around 0.25 Hz where as H/V ratio is9.51 at MT72. This is the highest peak of H/V ratio in 132 selected locations in BUET
campus. Figure 2.35(e) and Figure C2.147 demonstrates Horizontal to Vertical spectral
ratio (H/V) ranging between 6.85 and 11.85. This lower predominant frequency andhigher amplification ratio show that this site is highly susceptible due to any seismic
hazard.

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The predominant frequency of 132 locations has also been classified into five types. TypeI (0 – 0.49), Type II (0.50 – 0.99), Type III (1.0 – 1.99), Type IV (2.0 – 2.99) and TypeV (> 3.00).
The classifications of predominant frequency at 45 locations are as follows:
Type I: MT 02, MT 14, MT 17, MT 36, MT 62, MT 67, MT 72, MT 76, MT 77, MT 78,
MT 80, MT 83, MT 84, MT 86, MT 108 and MT 120.
Type II: MT 03, MT 04, MT 05, MT 06, MT 11, MT 12, MT 15, MT 16, MT 18, MT 19,
MT 22, MT 23, MT 24, MT 29, MT 30, MT 35, MT 41, MT 47, MT 48, MT 51, MT 52,
MT 54, MT 56, MT 71, MT 79, MT 81, MT 85, MT 93, MT 99, MT 101, MT 103, MT
109 and MT 111.
Type III: MT 01, MT 07, MT 08, MT 09, MT 10, MT 13, MT 20, MT 21, MT 25, MT 26,
MT 33, MT 34, MT 37, MT 38, MT 39, MT 40, MT 43, MT 44, MT 45, MT 46, MT 49,
MT 50, MT 53, MT 58, MT 59, MT 60, MT 61, MT 63, MT 64, MT 65, MT 74, MT 87,
MT 88, MT 90, MT 98, MT 102, MT 104, MT 106, MT 107, MT 110, MT 112, MT 113,
MT 114, MT 115, MT 116, MT 121, MT 122, MT 128, MT 129, MT 130 and MT 132.
Type IV: MT 27, MT 28, MT 66, MT 89, MT 95, MT 105, MT 118, MT 119 and MT
123.
Type V: MT 31, MT 32, MT 42, MT 55, MT 57, MT 68, MT 69, MT 70, MT 73, MT 75,
MT 82, MT 91, MT 94, MT 96, MT 97, MT 100, MT 117, MT 124, MT 125, MT 126
and MT 131.
From this classification of predominant frequency, it can be said that most of thelocations predominant frequency ranging between 1.0 Hz and 1.99 Hz. These
predominant frequencies are classified as Type III. The second most common type of
predominant frequency is Type II. The number of locations predominant frequency
classified as Type V is 21. In addition to this, there are sixteen Type I locations.
On the other hand, Horizontal to Vertical spectral ratio (H/V) has been classified into fourtypes. Type I (0 - 0.99), Type II (1.0 - 1.99), Type III (2.0 - 2.99) and Type IV (>3.0).
The classifications of H/V ratio at 132 locations are as follows:
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Type I: None
Type II: MT 01, MT 09, MT 10, MT 19, MT 20, MT 27, MT 28, MT 38, MT 47, MT 52,
MT 58, MT 61, MT 66, MT 67, MT 68, MT 69, MT 70, MT 71, MT 73, MT 74, MT 75,
MT 76, MT 77, MT 78, MT 80, MT 85, MT 86, MT 90, MT 91, MT 94, MT 97, MT 100,
MT 104, MT 105, 108, MT 116, MT 117, MT 123, MT 124, MT 126, MT 127, MT 128
and MT 129.
Type III: MT 03, MT 04, MT 08, MT 11, MT 12, MT 13, MT 14, MT 15, MT 16, MT 17,
MT 18, MT 21, MT 22, MT 23, MT 24, MT 25, MT 29, MT 30, MT 31, MT 32, MT 33,
MT 34, MT 35, MT 37, MT 40, MT 41, MT 42, MT 43, MT 44, MT 45, MT 46, MT 48,
MT 49, MT 50, MT 51, MT 53, MT 54, MT 55, MT 56, MT 57, MT 59, MT 63, MT 64,
MT 65, MT 71, MT 79, MT 81, MT 82, MT 83, MT 87, MT 89, MT 92, MT 93, MT 95,
MT 96, MT 98, MT 99, MT 102, MT 106, MT 107, MT 110, MT 111, MT 112, MT 113,
MT 114, MT 115, MT 118, MT 119, MT 120, MT 121, MT 122, MT 125, MT 130, MT
131 and MT 132.
Type IV: MT 02, MT 05, MT 06, MT 07, MT 26, MT 36, MT 39, MT 60, MT 62, MT 72,
MT 84, MT 88, MT 101, MT 103 and MT 109.
According to the above classification of H/V ratio, most of the selected locations areclassified as Type III. There are seventy five Type III locations. Type II is the second
most predominant H/V ratio. There is no H/V ratio ranging between 0 and 0.99. The
number of locations H/V ratio greater than 3 is 15.
From Table 2.17, the minimum mean Horizontal to Vertical spectral ratio (H/V) is 1.24
where as predominant frequency is around 0.29 at MT 108. Figure 2.35(h) shows the
Horizontal to Vertical spectral ratio (H/V) ranging between 0.93 and 1.56. The basic six
H/V ratio in three segments along EW and NS direction, H/V ratio of three segments andtheir mean value are illustrated in Figure C2.183.

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Table 2.17: Microtremor Test Location, Predominant Frequency and H/V Ratio within at
132 selected locations in soil within BUET campus
SerialNumberID

Predominant H/V Ratio Serial
Frequency(RM)
NumberID

PredominantFrequency

H/V Ratio
(RM)

1

MT-01

1.59

1.72

2

MT-02

0.35

3.37

3

MT-03

0.94

2.88

4

MT-04

0.70

2.29

5

MT-05

0.73

4.20

6

MT-06

0.90

3.27

7

MT-07

1.23

3.0

8

MT-08

1.21

2.94

9

MT-09

1.13

1.89

10

MT-10

1.14

1.48

11

MT-11

0.82

2.33

12

MT-12

0.94

2.38

13

MT-13

1.27

2.12

14

MT-14

0.45

2.88

15

MT-15

1.03

2.53

16

MT-16

1.45

2.00

17

MT-17

0.45

2.38

18

MT-18

0.97

2.79

19

MT-19

0.98

1.89

20

MT-20

1.03

1.97

21

MT-21

1.31

2.46

22

MT-22

0.70

2.48

23

MT-23

0.93

2.31

24

MT-24

0.92

2.53

25

MT-25

1.13

2.48

26

MT-26

1.34

3.13

27

MT-27

2.26

1.65

28

MT-28

2.44

1.87

29

MT-29

1.23

2.73

30

MT-30

1.31

2.67

31

MT-31

3.65

2.12

32

MT-32

3.98

2.03

33

MT-33

1.37

2.14

34

MT-34

1.21

2.06

35

MT-35

0.57

2.88

36

MT-36

0.48

3.67

37

MT-37

1.24

2.31

38

MT-38

1.23

1.89

39

MT-39

1.24

3.74

40

MT-40

1.27

2.38

41

MT-41

0.65

2.03

42

MT-42

3.81

2.31

43

MT-43

1.35

2.79

44

MT-44

1.31

2.33

45

MT-45

1.07

2.29

46

MT-46

1.27

2.31

47

MT-47

0.66

1.41

48

MT-48

0.77

2.73

49

MT-49

1.24

2.59

50

MT-50

1.27

2.03

51

MT-51

0.82

2.00

52

MT-52

0.84

1.85

53

MT-53

1.15

2.70

54

MT-54

0.85

2.19

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114

SerialNumberID

Predominant H/V Ratio Serial
Frequency(RM)
NumberID

PredominantFrequency

H/V Ratio
(RM)

55

MT-55

3.02

2.00

56

MT-56

0.50

2.48

57

MT-57

7.31

2.17

58

MT-58

1.65

1.60

59

MT-59

1.30

2.45

60

MT-60

1.29

3.23

61

MT-61

1.27

1.74

62

MT-62

0.40

6.20

63

MT-63

1.29

2.97

64

MT-64

1.34

2.21

65

MT-65

1.24

2.14

66

MT-66

2.75

1.68

67

MT-67

0.39

1.98

68

MT-68

5.80

1.58

69

MT-69

7.06

1.41

70

MT-70

4.89

1.65

71

MT-71

0.80

2.14

72

MT-72

0.25

9.51

73

MT-73

3.13

1.75

74

MT-74

1.37

1.85

75

MT-75

4.89

1.59

76

MT-76

0.38

1.27

77

MT-77

0.34

1.94

78

MT-78

0.34

1.48

79

MT-79

0.83

2.51

80

MT-80

0.34

1.58

81

MT-81

0.96

2.03

82

MT-82

9.62

2.43

83

MT-83

0.44

2.43

84

MT-84

0.42

4.38

85

MT-85

0.94

1.98

86

MT-86

0.39

1.29

87

MT-87

0.82

2.38

88

MT-88

0.90

3.37

89

MT-89

1.28

2.35

90

MT-90

0.91

1.77

91

MT-91

3.72

1.65

92

MT-92

0.87

2.67

93

MT-93

0.74

2.70

94

MT-94

3.10

1.31

95

MT-95

2.75

2.19

96

MT-96

3.38

2.12

97

MT-97

4.45

1.95

98

MT-98

1.27

2.48

99

MT-99

0.64

2.33

100

MT-100

7.5

1.51

101

MT-101

0.92

3.19

102

MT-102

1.27

2.35

103

MT-103

0.52

4.97

104

MT-104

2.64

1.61

105

MT-105

2.54

1.35

106

MT-106

1.33

2.85

107

MT-107

1.32

2.82

108

MT-108

0.29

1.24

109

MT-109

0.54

3.70

110

MT-110

1.36

2.82

111

MT-111

0.98

2.48

112

MT-112

1.21

2.51

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SerialNumberID

ID

PredominantFrequency

H/V Ratio
(RM)

113

MT-113

1.03

2.35

114

MT-114

1.27

2.14

115

MT-115

1.16

2.10

116

MT-116

1.39

1.95

117

MT-117

6.11

1.61

118

MT-118

1.33

2.59

119

MT-119

1.27

2.33

120

MT-120

0.39

2.08

121

MT-121

1.27

2.82

122

MT-122

1.27

2.35

123

MT-123

2.68

1.89

124

MT-124

4.00

1.42

125

MT-125

4.85

2.33

126

MT-126

5.95

1.77

127

MT-127

6.11

1.95

128

MT-128

2.52

1.47

129

MT-129

1.80

1.31

130

MT-130

1.26

2.35

131

MT-131

4.65

2.21

132

MT-132

1.18

2.46

8
7

Predominant H/V Ratio Serial
Frequency(RM)
NumberPredominant Frequency
H/V Ratio (mean)
H/V Ratio (mean+1/2σ)
H/V Ratio (mean-1/2σ)

Numerical Value

6
5
4
3
2
1
0
1

2

3

4

5

6

7

8

9

10 11 12 13 14 15

Microtremor Test Location(a) Microtremor Test Location 1 to 15

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Predominant Frequency
H/V Ratio (mean)
H/V Ratio (mean+1/2σ)
H/V Ratio (mean-1/2σ)

7

Numerical Value

6
5
4
3
2
1
0
16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

43

44

45

Microtremor Test Location(b) Microtremor Test Location 16 to 30
8

Predominant Frequency
H/V Ratio (mean)
H/V Ratio (mean+1/2σ)
H/V Ratio (mean-1/2σ)

7

Numerical Value

6
5
4
3
2
1
0
31

32

33

34

35

36

37

38

39

40

41

42

Microtremor Test Location(c) Microtremor Test Location 31 to 45

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8

Predominant Frequency
H/V Ratio (mean)
H/V Ratio(mean+1/2σ)
H/V Ratio (mean-1/2σ)

7

Numerical Value

6
5
4
3
2
1
0
46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

73

74

75

Microtremor Test Location(d) Microtremor Test Location 46 to 60
12

Predominant Frequency
H/V Ratio (mean)
H/V Ratio (mean+1/2σ)
H/V Ratio (mean-1/2σ)

11
10
9

Numerical Value

8
7
6
5
4
3
2
1
0
61

62

63

64

65

66

67

68

69

70

71

72

Microtremor Test Location(e) Microtremor Test Location 61 to 75

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Predominant Frequency
H/V Ratio (mean)
H/V Ratio (mean+1/2σ)
H/V Ratio (mean-1/2σ)98Numerical Value

7
6
5
4
3
2
1
0
76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

Microtremor Test Location(f) Microtremor Test Location 76 to 90
8

Predominant Frequency
H/V Ratio (mean)
H/V Ratio (mean+1/2σ)
H/V Ratio (mean-1/2σ)

7

Numerical Value

6
5
4
3
2
1
0
91

92

93

94

95

96

97

98

99 100 101 102 103 104 105

Microtremor Test Location(g) Microtremor Test Location 91 to 105

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8

Predominant Frequency
H/V Ratio (mean)
H/V Ratio (mean+1/2σ
H/V Ratio (mean-1/2σ)

7

Numerical Value

6
5
4
3
2
1
0
106 107 108 109 110 111 112 113 114 115 116 117 118 119 120

Microtremor Test Location(h) Microtremor Test Location 106 to 120
8Predominant Frequency
H/V Ratio (mean)
H/V Ratio (mean+1/2σ)
H/V Ratio (mean-1/2σ)

7

Numerical Value

6
5
4
3
2
1
0
121

122

123

124

125

126

127

128

129

130

131

132

Microtremor Test Location(i) Microtremor Test Location 121 to 132
Figure 2.35 [(a), (b), (c), (d), (e), (f),(g),(h) and (i)]: Predominant frequency and H/Vratio at 132 selected locations in soil within BUET campus.
118

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2.5.2.2

Building Sites

Microtremor observations at 45 residential and academic buildings of BUET campus areshown in Figure 2.36 and google map in Figure 2.37. The Horizontal to Vertical spectra
ratio at building does not provide reliable dynamic characteristics. In that case Fourier
Spectrum provides better result of predominant frequency at building. Table 2.18 shows
the mean predominant frequency of Fourier spectrum in EW and NS directions at 45
buildings. Fourier spectra of 45 buildings along EW, NS and UD directions are shown in
APPENDIX-D from Figure D208 to D252. In some buildings, microtremor data isrecorded at different floors or different locations in the same floor. Out of 45 microtremor
observation in buildings, the maximum predominant frequency is 5.56 Hz along both EW
and NS directions in MTB10 at Controller of Examination Building. This is a four-storied
frame structure building with 324sqm floor area. There are no lift and shear wall in thisbuilding. The foundation of the building is individual footing. There are no structural
irregularities in building. But torsional irregularity, re-entrant corner and diaphragm
discontinuity exist.
The minimum predominant frequency is 2.00 Hz along EW and NS directions at MTB02
at the Eleven Story Tower Building. This is an eleven-storied frame structure with
673sqm floor area. There are three lift cores and a shear wall in the building. The
foundation of the building is pile-raft system. No structural irregularity exist in thisbuilding. But torsional irregularity, re-entrant corner and diaphragm discontinuity exist.
The predominant frequency of 45 building has also been classified into five types. Type I(0 – 0.49), Type II (0.50 – 0.99), Type III (1.0 – 1.99), Type IV (2.0 – 2.99) and Type V(> 3.00).
The classifications of predominant frequency along EW at 45 buildings are as follows:
Type I: None
Type II: None
Type III: None
Type IV: MT 01, MT 02, MT 03, MT 04 and MT 06.

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Type V: MT 05, MT 07, MT 08, MT 09, MT 10, MT 11, MT 12, MT 13, MT 14, MT 15,
MT 16, MT 17, MT 18, MT 19, MT 20, MT 21, MT 22, MT 23, MT 24, MT 25, MT 26,
MT 27, MT 28, MT 29, MT 30, MT 31, MT 32, MT 33, MT 34, MT 35, MT 36, MT 37,
MT 38, MT 39, MT 40, MT 41, MT 42, MT 43, MT 44 and MT 45.
In addition to this, classifications of predominant frequency along NS direction at 45
buildings are as follows:
Type I: None
Type II: None
Type III: None
Type IV: MT 02, MT 03, MT 04, MT 05, MT 06, MT 07, MT 13 and MT 45.
Type V: MT 01, MT 08, MT 09, MT 10, MT 11, MT 12, MT 14, MT 15, MT 16, MT 17,
MT 18, MT 19, MT 20, MT 21, MT 22, MT 23, MT 24, MT 25, MT 26, MT 27, MT 28,
MT 29, MT 30, MT 31, MT 32, MT 33, MT 34, MT 35, MT 36, MT 37, MT 38, MT 39,
MT 40, MT 41, MT 42, MT 43 and MT 44.

Table 2.18: Predominant period and frequency of fourty five BUET buildings (after
Russel et al., 2006)
Building
Name/Number

SerialNumber1
IFCDR Building

No. ofstory
4Predominant
Predominantperiod (sec)Frequency (Hz)
EW
NS
EW
NS
direction direction direction direction
0.38
0.30
2.63
3.33

Eleven Story Tower
2

Building

11

0.50

0.50

2.00

2.00

Civil Engineering
3

Building

7

0.50

0.40

2.00

2.50

4

EME Building

6

0.40

0.39

2.50

2.56

5

Library Building

4

0.26

0.37

3.85

2.70

6

Architectural Building

5

0.37

0.36

2.70

2.78

7

URP Building

5

0.33

0.38

3.03

2.63

8

ARI Building

6

0.26

0.30

3.85

3.33

13

0.27

0.30

3.70

3.33

New Academic
9

Building

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SerialNumber10

Building
Name/Number
Controller of
Examination Building

No. ofstory

Predominant
Predominantperiod (sec)Frequency (Hz)
EW
NS
EW
NS
direction direction direction direction

4

0.18

0.18

5.56

5.56

Engg. University
11

School Building

4

0.27

0.23

3.70

4.35

12

Titumir Hall

4

0.32

0.31

3.13

3.23

13

Sher-e-Bangla Hall

4

0.27

0.40

3.70

2.50

14

Dr. M.A. Rashid Hall

5

0.24

0.27

4.17

3.70

15

Ahsan-Ullah Hall

4

0.27

0.25

3.70

4.00

4

0.27

0.21

3.70

4.76

Shahid Smrity Hall
16

(Middle Building)
Shahid Smrity Hall

122

17

(North Building)

4

0.30

0.28

3.33

3.57

18

Register Building

2

0.20

0.20

5.00

5.00

19

#1

4

0.25

0.25

4.00

4.00

20

#2

4

0.25

0.26

4.00

3.85

21

#3

4

0.28

0.22

3.57

4.55

22

#4

5

0.33

0.29

3.03

3.45

23

#5

4

0.22

0.26

4.55

3.85

24

#6

4

0.23

0.27

4.35

3.70

25

#7

4

0.25

0.27

4.00

3.70

26

#8

4

0.32

0.28

3.13

3.57

27

#9

4

0.24

0.22

4.17

4.55

28

# 12

5

0.30

0.28

3.33

3.57

29

# 13

5

0.28

0.28

3.57

3.57

30

# 14

5

0.31

0.31

3.23

3.23

31

# 18

5

0.33

0.29

3.03

3.45

32

# 21

4

0.23

0.30

4.35

3.33

33

# 22

4

0.33

0.29

3.03

3.45

34

# 23

4

0.25

0.30

4.00

3.33

35

# 24

4

0.24

0.29

4.17

3.45

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SerialNumber36

Building
Name/Number

Predominant
Predominantperiod (sec)Frequency (Hz)
EW
NS
EW
NS
direction direction direction direction
0.25
0.30
4.00
3.33

# 25

No. of
story
4

37

# 26

4

0.25

0.30

4.00

3.33

38

# 27

4

0.23

0.29

4.35

3.45

39

# 28

5

0.33

0.28

3.03

3.57

40

# 30

4

0.26

0.24

3.85

4.17

41

# 43

5

0.29

0.25

3.45

4.00

42

# 45

5

0.27

0.29

3.70

3.45

43

# 46

5

0.30

0.26

3.33

3.85

44

# 47

6

0.32

0.32

3.13

3.13

45

# 62

6

0.39

0.34

2.56

2.94

122

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Figure 2.36: 45 microtremor observation points in various building of BUET campus.

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Figure 2.37: Google Map of BUET Campus.

125March 2012

COMPARISON OF MICROTREMOR DATA WITH
THEORETICAL ANALYSIS
3.1

GENERAL

The reliability of microtremor observation to estimate predominant frequency andamplification of any particular site has been illustrated in Chapter 2. These parameters may
be used to assess the response of site soil due to any seismic activities. Comparison of H/Vratio of microtremor observation with theoretical transfer function of site soil using the 1D
site response program SHAKE is important. This chapter provides comparison of these two
ratios for 42 locations of Dhaka city. In 14 locations shear-wave velocity are obtained
directly using PS-logging and SSMM method and in other 28 locations correlations are used
to obtain shear-wave velocity from SPT-N value. Resonance between site soil and building
within BUET campus as well as Nakamura’s seismic vulnerability index (Kg) for soils for 45
locations has also been estimated.

3.2

COMPARISON OF MICROTREMOR DATA WITH 1D RESPONSEANALYSIS USING THE PROGRAMME SHAKE

From the existing borelogs, SSMM and PS-loggings, soil model at each site has been
established for theoretical analysis. The transfer function of the shear wave (the surface
motion versus the incidental motion at depth) has been calculated using the soil models. For
the calculation of transfer function of shear-wave and a damping ratio of 2% has been used,assuming input motion at the outcrop.
Figure 3.1 and Figure 3.2 show the typical graphs for comparison of amplitude ratio between
the transfer function of shear wave and microtremor H/V ratio. The comparision of amplitude
ratio between transfer function and microtremor H/V ratio for fourty two sites in and aroundthe Dhaka city have been illustrated in Appendix-E. Characteristics transfer function curve
have been found from the 1D response analysis using the programme SHAKE. On the other
hand, microtremor H/V ratio curve has been found from the Horizontal to Vertical spectral
ratio (H/V) of Fourier spectra.
From the comparison of microtremor and transfer function, four types of characteristics
curves have been observed. These curves are classified as similar, dissimilar, right side
shifted and left side shifted compared to the microtremor H/V ratio curve. Among 42 models

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thirty five transfer function have been shifted in the right side of microtremor and only one
has been shifted in the left side. There are six sites where two curves have similar pattern.
The rest two sites have been found where no similarity between microtremor H/V ratio andtransfer function.
Figure E3.38 shows the comparison of amplitude ratio between microtremor and Transfer
Function at Rajendapur. The amplitude ratio of Transfer function is similar to microtremor
H/V ratio. However, peak of transfer function has been moved into right side slightly. The
amplitude ratio of both curves is around 2.65. The predominant frequency of microtremor
H/V ratio is 1.17 Hz whereas transfer function shows 2.5 Hz. Similar curves between transfer
function and microtremor have been found in nine locations which are shown in Figure E3.1,
E3.4, E3.5, E3.6, E3.11, E3.13, E3.17, E3.19 and Figure E3.24.
Figure E3.35 demonstrates that the peak amplitude ratio of transfer function has been moved
toward right side of microtremor at Bashundhara River view Project. But, the peak value oftransfer function is lower amplified than microtremor H/V ratio. The predominant frequencyof microtremor H/V ratio is 1.05 Hz where as transfer function shows this value is 1.85 Hz.
On the other hand, peak H/V ratio of microtremor is 3.51 wheras transfer function shows thisvalue 3.03. The similar types of right shifted and lower amplified locations of transfer
function have been found in Figure E3.2, E3.3, E3.7, E3.8, E3.10, E3.14, E3.15, E3.16, E3.17,
E3.21, E3.23, E3.26, E3.29, E3.30, E3.31, E3.33, E3.34, E3.42 and Figure E3.35.
Figure E3.20 shows that amplitude ratio of transfer function is higher than microtremor H/Vratio at Pallabi. The predominant frequency of microtremor is 1.24 Hz whereas the
predominant frequency of transfer function is 1.60 Hz. The amplitude ratio of microtremor is
2.64 wheras this value is 4 Hz in Transfer Function. The similar pattern of curves between
microtremor and Transfer function have been observed in Figure E3.9, E3.13, E3.18, E3.20,
E3.26 and Figure E3.41.
Figure E3.36 shows the left side shifted transfer function curve at Matuail, Demra. The peakvalue of H/V ratio of microtremor is similar to Transfer Function. The Predominantfrequency of transfer function is around 1.7 Hz whereas this value is 2.73 Hz in microtremor.
The peak value of amplitude ratio of transfer function is 2.48 where as microtremor shows
2.3.
The similar predominant frequency of microtremor and transfer function has been found innine locations. Figure E3.12 represents the similar predominant frequency between
microtremor and transfer function. The predominant frequency of microtremor and transfer
function is around 3.65 Hz. The peak amplitude ratio of microtremor is 2.73 wheras this127
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value is 1.90 in transfer function. The similar patterns of curve have been illustrated in Figure
E3.22.
The similar predominant frequency but higher amplification has been found in Figure E3.27
at Adabor. The predominant frequency in both curves is 3.35 Hz. The peak amplitude ratio of
microtremor is 2.26 Hz wheras this value is 2.9 in Transfer Function.
The dissimilarity between transfer function and microtremor H/v ratio has been found in
Figure E3.29 at Aftab Nagar Housing project. The transfer function curve is right shifted. The
predominant frequency and amplitude ratio of transfer function are 6 Hz and 2 where as thesevalue are 0.95 Hz and 2.76 in microtremor. Figure E3.37 demonstrates that amplitude ratio oftransfer function is right shifted at Jilmil Project. The predominant frequency and H/V ratioof microtremor are 1.0 Hz and 3.26. The predominant frequency and H/V ratio of transfer
function have been found 8.0 Hz and 3.0.
From these result, it can be said that although amplitude values of the ratios are close, thepredominant frequency for the two cases differs slightly. The reason of this difference is thatmicrotremor consists of different types of waves, but the theoretical transfer function is basedon shear-wave only. Rayleigh wave has significant effect on microtremor result. If thesewaves are dispersed from the microtremor, microtremor results may be more close to thetransfer function.
1

Amplitude Ratio

10

Microtremor
Transfer Function

0

10

-1

10

10

-1

10

0

1

10

Frequency (Hz)Figure 3.1: Amplitude ratios of microtremor and theoretical transfer function of shear
128

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BNUS Annual Report-2011

ICUS Report 59

Amplitude Ratio

wave at National University.
10

1

10

0

10

Microtremor
Transfer Function

-1
-1

0

10

10

1

10

Frequency (Hz)Figure 3.2: Amplitude ratios of microtremor and theoretical transfer function of shear
wave at Block-D, Bashundhara.
3.3

VULNERABILITY ASSESSMENT

Earthquake vulnerability of the 45 buildings within BUET campus is carried out frompredominant frequency obtained by the analysis of microtremor data. Microtremor
observation has been carried out at 132 selected free-field locations within BUET campus
which has been discussed in Chapter 2. The Horizontal to Vertical spectra ratio (H/V) of
these locations have been compared with the predominant frequency of building along EW
and NS direction, respectively. Fourier spectra of 45 buildings of BUET campus have beenshown in APPENDIX-D from Figure D208 to D252. The mean square root of H/V ratio(RM) obtained from microtremor observations of nearby soils have been compared with
Fourier spectra of microtremor observations at the top floor of the buildings. The occurrenceof resonance between building and soil has been discussed in article 3.3.1. The damage
assessment of consolidated soil using Nakamura’s Seismic Vulnerability Index (Kg) has been
included in article 3.3.2.

3.3.1

Resonance between Site Soil and Building

129
BNUS Annual Report-2011

= �

– � �

�
�
�����
� ����

������March 2012���� �����
�

P98

�

�
�

�� �����

�

��� �

���

���

�

�

�
���
relation:� = �� � ��� � ��
�
���
�����

��

P98

� + 0.08 ��� �

���

���
�

�
�

�� �����
����

P130 ��� �����
�
��
���
���
=
��
β
=
��� � � Resonance+ 0.08 ��� � criteria,
�
R
���
���
��

P130
�
= �
��

�

=�������
����� ��� �

�

���

���

��

��� �

���

���

�

�
���
���
� � be explained� = �� �using��� � the�� following
���simple
� �
The resonance criteria of building and soil – can
�
���
���
�����

�� �����– � ��

����� � ����

��

��� �

���

���

� + 0.08 ��� �

���

���

�

(3.1)

P130
�
= � �� = �Predominant
Where, βR = Coefficient for resonance occurrence,
frequency of building
�
��

�and
� �� = Predominant frequency of soil.

In equation (3.1), if βR becomes close to 1 (1±0.20), resonance may occur. The resonancebetween buildings and soil has been analyzed using this resonance criterion, βR, in both EW

and NS directions. Table 3.1 presents the predominant frequency of the buildings and theiradjacent soils and shows possibility of resonance to occur. Four buildings have been found as
vulnerable due to resonance occurrence. These buildings are Eleven Story Tower Building,
URP Building, Titumir Hall and Building # 1.

Table 3.1: Analysis of resonance criteria of 45 buildings at BUET campus
Building Name/
NumberSerial
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
130

IFCDR Building
Eleven Story Tower
Building
Civil Engineering
Building
EME Building
Library Building
Architectural
Building
URP Building
ARI Building
New Academic
Building
Controller of
Examination
Building
Engg. University
School Building
Titumir Hall
Sher-e-Bangla Hall

Predominant
PredominantFrequency of Building
Frequency of(Hz)site soil (Hz)EW
NS
direction
direction Resultant, RM

Remarks
on resonanceoccurrence

2.63

3.33

0.96

No

2.00

2.00

1.80

Yes

2.00
2.50
3.85

2.50
2.56
2.70

0.75
1.24
2.17

No
No
No

2.70
3.03
3.85

2.78
2.63
3.33

1.88
3.05
2.26

No
Yes
No

3.70

3.33

0.96

No

5.56

5.56

1.24

No

3.70
3.13
3.70

4.35
3.23
2.50

1.37
3.52
1.65

No
Yes
No

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ICUS Report 59

Building Name/
NumberSerial
No.
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45

Dr. M.A. RashidHall
Ahsan-Ullah Hall
Shahid Smrity
Hall(Middle
Building)
Shahid Smrity
Hall(North Building)
Register Building
#1
#2
#3
#4
#5
#6
#7
#8
#9
# 12
# 13
# 14
# 18
# 21
# 22
# 23
# 24
# 25
# 26
# 27
# 28
# 30
# 43
# 45
# 46
# 47
# 62

Predominant
PredominantFrequency of Building
Frequency of(Hz)site soil (Hz)EW
NS
direction
direction Resultant, RM

Remarks
on resonanceoccurrence
No

4.17
3.70

3.70
4.00

1.87
5.92

3.70

4.76

0.34

No

3.33
5.00
4.00
4.00
3.57
3.03
4.55
4.35
4.00
3.13
4.17
3.33
3.57
3.23
3.03
4.35
3.03
4.00
4.17
4.00
4.00
4.35
3.03
3.85
3.45
3.70
3.33
3.13
2.56

3.57
5.00
4.00
3.85
4.55
3.45
3.85
3.70
3.70
3.57
4.55
3.57
3.57
3.23
3.45
3.33
3.45
3.33
3.45
3.33
3.33
3.45
3.57
4.17
4.00
3.45
3.85
3.13
2.94

3.13
0.65
3.81
1.07
1.24
1.27
1.31
1.31
0.66
0.77
0.82
1.18
1.18
1.16
6.11
2.68
1.27
5.95
4.85
1.80
2.52
1.27
6.11
0.84
1.39
0.66
1.36
0.88
1.39

No
No
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No

No

131
BNUS Annual Report-2011

March 2012

3.3.2

Seismic Damage assessment of soil using Nakamura’s Technique

Seismic vulnerability index (Kg) is an index indicating the level of vulnerability of a layer ofsoil to deform. Therefore, this index is useful for the detection of areas that are weak zone
(unconsolidated sediment) at the time of occurrence of earthquakes. Some studies like
Daryono (2009) and Nakamura (2000) showed a good correlation between seismic
vulnerability index (Kg) and the distribution of earthquake disaster damage. This index is
obtained from the peak value of HVSR squared, divided by the value of the predominantfrequency. For this research area (Kg) values for 45 locations are shown in Table 3.2.
The seismic vulnerability index has been classified into four major types. These are Low (05), Moderate (6-10), High (11-20) and Very High (>20). Table 3.2 demonstrates the highest(Kg) value at Rab-10, Plot, Kamrangirchar. Most of the zones having higher Vulnerability
Index (Kg) are situated in reclaimed areas.
Table 3.2: Damage assessment of site soil using Nakamura’s empirical formula
SL.
No

Location

SBH01

National
University

SBH02

Board Bazaar,
Gazipur3

SBH03

Kaunia, BoroBari,
Moddopara

4

SBH04

Tongi,
Ershadnagar

1
2

132

ID

5

SBH05

6

SBH06

7

SBH07(A)8

SBH07 (B)

Tongi BSCIC
area

Abdullahpur
Ijtema field(North and East
side)
Ijtema Field(South andWest side)

Predominant Frequency,
Fg (Hz)
1.24

H/V
Ratio,
Ag
2.59

P132
Vulnerability
Index,
��=

���
��

5.41
P136

Remarks
Low tomoderate

0.82

2.73

γ = 1000 x10��
γ > 10.000 x 10��
9.09
Moderate

0.72

2.79

P148
10.81

0.97
0.95

2.51
2.73

Moderate tohigh� �∅��� � �� �� ����� �����
�
6.49
Moderate��� � �� �∅�� ���∅�� ������ � ��, �� � ��

1.32

2.33

7.85
Moderate� �������������� � �� � �� � � � � ��� �

1.17

3.37

9.71

Moderate

0.86

3.26

12.35

High

4.11

� ��� �Low

BNUS Annual Report-2011
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ICUS Report 59

SL.
No
9

ID
SBH08

Location
Ashulia Toll
Plaza

Predominant Frequency,
Fg (Hz)
1.14

H/V
Ratio,
Ag
1.75

P132
Vulnerability
Index,
�� =Remarks

���
��

2.69
P136

Low

10

SBH-9

Uttar Khan

1.09

2.09

γ > 10.000 x 10��γ = 1000 x10��
4.01
Low

11

SBH10(A)Uttara Phase 3( North side)

1.18

3.16

P148
8.46

12

SBH10(B)

Uttara Phase 3(South side)

4.43∅��� � �� �� ����� �����
Very
�
20.48
high

0.97

Moderate���� � �� ��∅�� ���∅�� ������ � ��, �� � ��

13

SBH11

Azampur
School, Uttara

14

SBH12 (A)

Mirpur DOHS
(South side)

1.54

2.46

2.04
Low
� �
������������� � �� � �� � � � � ��� �

15

SBH12 (B)

Mirpur DOHS
(North side)

1.21

3.44

9.78

Moderate

16

SBH13

1.12

3.19

9.08

Moderate

0.94

3.04

9.83

Moderate

2.00

2.69

3.62

Low

1.34

2.23

3.71

Low

1.52

2.43

3.88

Low

3.65

2.73

3.93

� ��� �Low

17

SBH14(A)18

SBH14(B)Ashiyan city,
Askona,
Dakkhin Khan
Purbachal-1,
Randokpur
Hazi bari,
Rupganj
Purbachal-2,
American City19

SBH14(C)

Purbachal
Picnic Park,
Gazipur20

SBH15

Adjacent toMirpur Zoo

21

SBH16

Field Ground,
Pallabi

1.24

2.64

5.62

22

SBH17 (A)Block-B,
Basundhara

Low tomoderate

2.09

3.12

4.66

Low

23

SBH17 (B)

Block-D,
Basundhara

1.57

4.71

14.13

High

133
BNUS Annual Report-2011

March 2012

SL.
No
24

SBH17 (C)

Location

Block-H,
Basundhara

2.52

H/V
Ratio,
Ag
2.94

P132
Vulnerability
Index,
�� =Remarks

���
��

3.43
P136

Low

25

SBH18

Civil Aviation
Quarter

0.64

3.70

γ > 10.000 x 10��γ = 1000 x10�� Very
21.39
high

26

SBH19

Kuril Flyover

1.97

2.73

P148
3.78

SBH20

Sarengbari,
Mipur-2

2.84∅��� � �� �� ����� �����
�
13.67
High

27

28

134

ID

Predominant Frequency,
Fg (Hz)

0.59

Low
�

��� � �� ��∅�� ���∅�� ������ � ��, �� � ��

SBH 21

Purachal, Uttar
Badda

2.11

29

SBH22

City
Corporation,
Gabtoli

0.82

3.67

3.18
Low
� �
������������� � �� � �� � � � � ��� �
16.42

� ��� �30

SBH23

Adabor

3.35

2.26

1.52

Low

31

SBH24

Agargoan
Trade Fair area

0.86

2.12

5.23

Low tomoderate

32

SBH25

Aftab Nagar
Housing
Project

0.95

2.76

8.02

Moderate

33

SBH26

Umme Had
Nagar, Nadda

1.32

3.83

11.11

Moderate

34

SBH27

South Banasree

1.39

3.86

10.72

Moderate to
high

35

SBH28

Basila Garden
City

1.12

4.47

17.84

High

36

SBH29

Royer Bazar
Boddhobumi

2.57

1.08

0.45

Low

37

SBH30

Kalunagar,
Hazaribagh

0.88

2.48

6.99

Moderate

38

SBH31

Rab-10, Plot,
Kamrangirchar

0.48

3.91

31.85

Very High

2.59

High

BNUS Annual Report-2011
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ICUS Report 59

SL.
No

ID

Location

Predominant Frequency,
Fg (Hz)

H/V
Ratio,Ag

P132
Vulnerability
Index,
��=

Remarks

���
��

39

SBH32

Sosan Ghat,
Kamrangirchar

40

SBH33

BasundharaRiver view

1.05

3.51

γ > 10.000 x 10��γ = 1000 x10��
11.73
High

SBH34

Matuail, Demra

2.77

2.48

P148
2.22

SBH35

Jilmil Project,
Equria

41

42

43

1.22

1.00

4.78

3.26

18.72
P136

High

Low
�

�

∅��� � �� �� ����� ����� , �� � ��
�
10.63
Moderate∅�� ���
to high��� � �� ���� � ��∅�� ���

SBH36

Rajendapur

44

SBH37

Bramangaon

1.08

3.55

5.73
Low
� �
������������� � �� � �� � � � � ��� �

45

SBH38

Meradia, Uttar
Banasree

1.26

2.84

6.40

1.17

2.59

11.67

� ��� �High

Moderate

Figure 3.3 shows the classification of vulnerability site at 45 locations using Nakamura’s
Vulnerability Index (Kg). Figure 4.3 demonstrates four major and two in between
vulnerability type. The number of low vulnerability type locations, which is 16, is the mostcommon among 45 locations. The second most predominant number of vulnerability type ismoderate type which varies between 6 and 10. The number of very high type vulnerable site
is 4.

135
BNUS Annual Report-2011

March 2012

RY
VE
H
G
HI

NUMBER

TO
H
G
HI
TE
RA
DE
O
M
W
LO
TO
D
O
M

Vulnerabolity Type

H
G
HI

TE
RA
DE
O
M

W
LO

0

5

10

15

20

25

30

35

Total Number of Microtremor Test Location

Figure 3.3: Damage assessment of 45 test locations using Nakamura’s Vulnerability Index
(Kg).

P132

To further ensure this, research on the acceleration of seismic waves in the basement need to

P132

���

�� = of seismic waves in thebe estimated. Vulnerability Index together with the acceleration
�
�

���

�
basement
has been suggested by Nakamura (2000) to calculate the value of shear strain (γ) of�= ��surface soil layers. Damaging earthquakes will occur when theP136
limits are exceeded due to theshear strain deformation surface layer of soil. Soil is plastic at γ = 1000 x10x ��, whereas
at γ >x 10��γ > 10.000
P136��
Only predominant frequency is not effective to
10.000will
x 10deform.
γ10.000= 1000xx10�� , theγ >groundclassify a site due to Nakamura’s vulnerability index. Both predominant frequency and H/V
P148
ratio are required to estimate vulnerability type.
� �
P148∅��� � �� �� ����� ����� , �� � ��∅��� ��� � ����� �����
� � �
�

�

CONCLUSIONS, �� � �� AND RECOMMENDATIONS∅�� ������ � �� �∅�� ���∅�� ������ � ��������� � ��4.1 � ��GENERAL∅�� ����� �������������� � ��� �� � spectral� �(H/V)��� �
The purpose of this research is to apply microtremor Horizontal
to vertical� ��� �� ������������ �� � for� site� soil� ��response�����
ratio� ��
techniqueanalysis in and around the Dhaka city. For this purpose� ��� �fourty five selected locations in and around Dhaka city as well as one hundred and thirty two

136

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BNUS Annual Report-2011

ICUS Report 59

points within BUET campus has been selected. The locations are selected on the basis ofdifferent geomorphic units.
After checking the stability of microtremor at different time instants microtremor observation
has been carried out. The dynamic properties of soil, which are predominant frequency andamplification, have been estimated from microtremor analysis. The variation of microtremor
H/V ratio due to various analysis windows have been carried out in this research.
The soil model using one dimensional response analysis using the programme SHAKE has
been executed for the investigated sites. To carry out this research shear wave velocity data
has been used as input for the programme SHAKE. Fourteen shear wave velocity data of theinvestigated site has been collected from the direct field test (PS logging and SSMM). The
shear wave velocity of other investigated locations has been estimated using empiricalcorrelation between SPT-N and shear-wave velocity. The comparision of amplitude ratio of
microtremor and transfer function has been presented in this research. It should be mentionedthat microtremor consists of different types of body and surface waves.
The resonance criteria between the site soil and buildings have been analyzed. Finally,
vulnerability of site soil using Nakamura’s (2000) technique has been carried out for thisresearch.

4.2

CONCLUSIONS

From the overall result and analysis of the study following findings may be summarized.
(a)Stability of microtremor data on ground

In order to check the stability of microtremor data fourteen different locations of BUET
campus have been selected to carry out microtremor observation from morning to midnight.
The stability of microtremor H/V ratio for site amplification has been discussed in chapter 2.
Fourier spectra depend on the source of vibration. This data does not show significant site
amplification. That’s why horizontal to vertical spectral ratio (H/V) of both East-West andNorth-South have been calculated. Microtremor H/V ratio do not show the source vibration
effect. Whatever the source is, the amplification result is similar for different time instants.
From this research, it can be concluded that Horizontal to Vertical spectral (H/V) ratio of
microtremor is effective for site response analysis. This technique is reliable for site soil
response compared to Fourier spectra.
137
BNUS Annual Report-2011

March 2012(b)

Resultant of EW and NS direction data

It is necessary to estimate the resultant H/V ratio because microtremor Horizontal to Vertical
spectral (H/V) ratio data is found in East-West and North-South direction. Four resultant H/Vratio data are available to estimate the dynamic characteristics which are RM (Rootmultiplication), RMS (Root square mean), RS (Root square) and Mean. In this research thevariations of four resultant H/V ratios have been carried out in three study locations(Bashundhara, Block-D; Board Bazar, Gazipur; Uttar Khan). From the observation it can beconcluded that RM of H/V ratio data is close to other three resultants. Therefore, Rootmultiplication of East-West and North-South data have been used for the estimation of
dynamic properties of soil.
(c)Various windows filtering technique

Five filtering windows are available for microtremor data analyses which are Rectangular,
Welch, Hamming, Hanning and Blackman window. For this research, time history
microtremor data at Bramangaon has been selected to be analyzed using five filtering
windows. From analysis of data in filtering windows it can be concluded that the peak H/Vratio is almost same in five windows. Rectangular window has been selected for microtremor
data analysis in this research.
(d) Smoothing effect on the microtremor data
Smoothing has significant effect on the of microtremor data. In this research six averagesmoothing points (2, 3, 5, 10, 15 and 20) have been applied on microtremor H/V ratio at four
study locations (Bramangaon, Tongi Ershad Nagar, Ashiyan city and Agargaon Trade fair).
From this research it can be concluded that suitable smoothing function helps to estimate
peak H/V ratio and predominant frequency easily. The peak of H/V ratio decreases if higher
average smoothing points is applied.
(e) H/V Ratio data in and around Dhaka city
Microtremor measurement has been carried out in 45 locations. Out of 45 locations, theoverall predominant frequency is 1.25 Hz with standard deviation 0.014. On the other hand,the overall H/V ratio is 2.72 with standard deviation 0.177. The maximum predominantfrequency is 3.65 Hz, where H/V ratio is 2.73 at Azampur School, Uttara. The Horizontal to
Vertical spectral ratio (H/V) lies between 1.81 and 3.74. On the other hand, the minimum
predominant frequency is 0.48 Hz, where H/V ratio is 3.91, Rab-10, Plot, Kamrangirchar.
138

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ICUS Report 59

The Horizontal to Vertical spectral ratio (H/V) lies between 2.23 and 5.65. The maximum
Horizontal to Vertical spectral ratio (H/V) is 4.78 where as predominant frequency is 1.22 Hz,
at Sosan Ghat, Kamrangirchar. The Horizontal to Vertical spectral ratio (H/V) lies between 4.07
and 5.71. The minimum Horizontal to Vertical spectral ratio (H/V) is 1.08 whereas
predominant frequency is 2.57 Hz at Royer Bazar. From this classification of predominantfrequency, it can be said that most of the locations predominant frequency varies from 1.0 Hz
to 1.99 Hz. These are classified as Type III. From the classification of H/V ratio, the mostcommon H/V ratio is Type III in 45 locations. The second most common H/V ratio is Type
IV. The number of locations having H/V ratio ranging between 1.0 and 1.99 is eight. No
location has been observed as Type I.
(f) Microtremor observation within BUET Campus
Microtremor observation at 132 selected points in soil has been carried out in BUET campus.
Out of 132 locations, the overall predominant frequency is 1.39 Hz where as standard
deviation is 0.289. On the other hand, the overall peak H/V ratio is 2.09 where as standard
deviation is 0.523. The maximum predominant frequency is around 9.62 Hz where as H/Vratio is 2.43 at MT82. The Horizontal to Vertical spectral ratio (H/V) varies from 1.65 to 2.51.
On the other hand, the minimum predominant frequency is around 0.25 Hz where as H/Vratio is 9.51 at MT72. This is the highest peak of H/V ratio in 132 selected locations within
BUET campus. The Horizontal to Vertical spectral ratio (H/V) lies between 6.85 and 11.85.
This lower predominant frequency and higher amplification ratio show that this location ishighly susceptible due to any seismic hazard. The minimum Horizontal to Vertical spectral
ratio (H/V) is 1.24 at MT 108. The Horizontal to Vertical spectral ratio (H/V) lies between
0.93 and 1.56.
From this classification of predominant frequency, it can be said that most of the locations
predominant frequency ranging between 1.0 Hz and 1.99 Hz. These predominant frequencies
are classified as Type III. The second most common type of predominant frequency is Type
II. The number of locations predominant frequency classified as Type V is 21. There are
sixteen Type I predominant frequency locations. From the classification of H/V ratio, mostof the selected locations are classified as Type III. There are seventy five Type III locations.
Type II is the second most predominant H/V ratio. There is no H/V ratio ranging between 0
and 0.99. The number of location H/V ratio greater than 3 is 15.
Microtremor observation on 45 buildings has been carried out within BUET campus. Fourier
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Spectrum provides better result of predominant frequency for buildings. Out of 45
microtremor observation in buildings, the maximum predominant frequency is 5.56 Hz along
both EW and NS directions at Controller of Examination Building. This is a four-storied
frame structure building with 324sqm floor area. There are no lift and shear wall in thisbuilding. The foundation of the building is individual footing. There are no structural
irregularities in building. But torsional irregularity, re-entrant corner and diaphragm
discontinuity exist.
The minimum predominant frequency is 2.00 Hz along EW and NS directions at Eleven
Story Tower Building. This is an eleven-storied frame structure with 673sqm floor area.
There are three lift cores and a shear wall in the building. The foundation of the building ispile-raft system. No structural irregularity exists in this building. But torsional irregularity,
re-entrant corner and diaphragm discontinuity exist. From this classification of predominantfrequency along EW direction, most of the locations predominant frequency is more than 3.0
Hz. These are classified as Type V. The second most common type of predominantfrequency is Type IV. The number of building predominant frequency ranging between 2.0
Hz and 2.99 Hz is 5. There is no predominant frequency of Type I, Type II and Type III.
Type V is the most common predominant frequency in 45 buildings of BUET campus along
NS direction. Type IV is the second most predominant frequency. There are no buildings of
predominant frequency ranging between 0 and 1.99.

(g)Comparison between microtremor H/V ratio and Transfer Function using the
program SHAKEThe comparison of amplitude ratio between transfer function and microtremor H/V ratio for
fourty two locations in and around the Dhaka city has been studied.
From the comparison between microtremor H/V ratio and transfer function using the
programme SHAKE four types of characteristics curves have been observed. These curves
are classified as similar, dissimilar, right side shifted and left side shifted compared to themicrotremor H/V ratio curve. Among 42 models predominant frequency of thirty five transfer
function have been shifted in the right side of microtremor and only one has been shifted in
the left side. Similar pattern amplitude ratio curves have been found in six locations. The rest
two locations have been found where no similarity between microtremor H/V ratio andtransfer function.
The same amplitude ratio but higher frequencies of transfer function have been found in ten
locations. The higher frequency but low amplified locations have been found in nineteen
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different locations. On the other hand, both higher frequency and higher amplified locationsof transfer function have been found in six locations. The similar predominant frequency but
lower amplified transfer function has been found in three locations. But, the same
predominant frequency but higher amplified location is Adabor. The dissimilar types ofpattern curve have been found in three locations.
From these results, it can be said that although amplitude values of the ratios are close, thepredominant frequency for the two cases differs slightly. The reason of this difference is thatmicrotremor consists of different types of waves, but the theoretical transfer function is basedon shear-wave only.
(h) Resonance between site soil and building
The resonance between the site soil and building has been analyzed using the H/V ratio of
soil and Fourier spectra of building in both EW and NS direction. It has been found that
resonance may occur at four BUET buildings. These buildings are Eleven Story Tower
Building, URP Building, Titumir Hall and Building # 1. For most of the building
predominant frequency is not close to the predominant frequency of soil. From the sub-soil
characteristics within BUET campus, it can be concluded that stiff soil with higher SPT value
exists in most of the investigated locations.

(i) Seismic Vulnerability Index (Kg) for soil
Seismic vulnerability index (Kg) is an index indicating the level of vulnerability of a layer ofsoil to deform. This index is useful for the detection of areas that are weak zone
(unconsolidated sediment) at the time of occurrence of earthquakes. The details result ofVulnerability Index (Kg) of the investigated areas in 45 locations has been illustrated in
section 4.3.2. The vulnerability index of fourty five locations in and around the Dhaka city
has been classified into four types which are low (0-5), moderate (6-10), high (11-20) andvery high (>20). From the analysis the highest (Kg) value has been found at Rab-10, Plot, andKamrangirchar. So, it can be concluded that this location is more weak zone that otherlocations. The seismic vulnerability index (Kg) for 45 sites varies between 0.45 and 31.85.
Sixteen sites have been classified as low vulnerable of soil layers. Five sites have been
identified as having moderate to high vulnerable of soil layers to deform.

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REFERENCES

Alam, M. K., Hasan, A.K.M. Shahidul, Khan, M. R. and Whitney, J. W. (1990). The
Geological Map of Bangladesh, the Geological Survey of Bangladesh in Collaboration
with United States Geological Survey.
Ansary, M. A., Yamazaki, F. and Katayama, T. (1996). Application of microtremor
measurements to the estimation of site amplification characteristics, Bulletin ofEarthquake Resistant Structure Research Center, IIS, University of Tokyo, No. 29, PP.
95-113.
Ansary, M. A., Rahman, S., Murad, E. M., Chowdhury, S. A. and Shuvra, D. P. (2010).
Proposed Time History and Response Spectrum for Dhaka, Chittagong and Sylhet
cities, Proceedings, 3rd International Earthquake Symposium, March 5-6, Dhaka,Bangladesh, PP. 349-356.
ASTM (2000). Annual Book of ASTM Standards, vol. 04.08: Soil and Rock (I). Standard No.
D 1586-99, Standard Test Method for Penetration Test and Split-Barrel Sampling ofSoils, West Conshohocken, PA, PP. 139-143.
Banglapedia (2006). National Encyclopedia of Bangladesh, Prepared by Asiatic Society of
Bangladesh, CD edition.
Bard, P. Y. (2004). Effects of surface geology on ground motion: Recent results andremaining issues, Proceedings of the 10th European Conference on Earthquake
Engineering, Vienna, Austria, August 28 – September 2, 1994, PP. 305-325.
Bilham, R., Gaur, V. K. and Molnar, P. (2001). Himalayan Seismic Hazard, SCIENCE, 293.
CDMP (2009). Ongoing Research Work, CDMP-UNDP Fault Map Delineation for
Bangladesh, 2009.
Curry, J. R. and Moore, D. G. (1974). Sedimentary and Tectonic processes in Bengal Deep
Sea Fan and Geosyncline, The geology of continental margins, Springer-Verlag, NewYork.
Daryono (2009). Eftek Tapek Lokal (Local site effect) di Graben Bantul Berdasarkan
Pengakuran Mikrotremor. International Conference Earth Science and Technology.
Yogjakarta.
Dimitriu, P. P., Papaioannou, Ch. and Theodulidis, N. P. (1998). EURO-SEISTEST strong
motion array near Thessaloniki, Northern Greece: a case study of site effects. Bulletinof seismological society of America, No. 3, PP. 862-873.

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Dravinski, M., Ding, G. and Wen, K. L. (1996). Analysis of spectral ratios for estimating
ground motion in deep basins, Bull. Seism. Soc. Am., 86, PP. 843-847.
Field, E. H. and Jacob, K. H. (1993). The Theoretical Response of Sedimentary Layers toAmbient Seismic Noise, Geophysical Research Letter, 20, PP. 2925-2928.
Field, E. H. and Jacob, K. H. (1995). A comparison and test of various site-response
estimation techniques, including three that are not reference-site dependent, Bulletin of
the Seismological Society of America, 85, PP. 1127-1143.
Field, E. H., Clement, A. C., Jacob, K. H., Aharonian, V., Hough, S. E., Friberg, P. A.,
Babaian, T. O., Karapetian, S. S., Hovanessian, S. M. and Abramian, H. A. (1995).
Earthquake site response study in Giumri (Formerly Leninakan), Armenian using
ambient noise observation. Bull. Seism. Soc. Am., 85, PP. 349-353.
Ghayamghamian, M. R. and Kawakami, H. (1997). Segmental cross-spectrum in microtremor
spectral ratio analysis. 7th International Conference on Structural Safety andReliability, Kyoto, November 1997, 24-28, PP. 1487-1494.
Geological Survey of Bangladesh, GSB (2008). Geomorphological Map of Dhaka city,
Preapared by GSB under the project of Comprehensive Disaster Management
Programme (CDMP).
Horike, M., Zhao, B. and Kawase, H. (2001). Comparison of site response characteristics
inferred from microtremors and earthquake shear waves, Bulletin of the SeismologicalSociety of America, 91, PP. 1526-1536.
Hossain, M. T. (2009). Estimation of Earthquake Induced Liquefaction Potential of Selectedareas of Dhaka City Based on Shear Wave Velocity, Thesis paper of Master of Sciencein Civil Engineering, November, 2009.
Huang, H. C. and Tseng, Y. S. (2002). Characteristics of soil liquefaction using H/V ofmicrotremors in Yuan-Lin area, Taiwan, TAO,Vol.13, No.3,325-338, September, 2002.
Kamal, A.S.M. Maksud and Midorikawa, S. (2003). GIS-based Landfill Mapping of Dhaka
City area, Bangladesh, Using Remote sensing data, Proceedings on the second
International Symposium on New Technologies for Urban Safety of Mega cities in
Asia, University of Tokyo, Japan.
Kanai, K., Tanaka, T. and Osada, K. (1954). Measurements of Micro-tremors 1. Bulletin
Earthquake Research Institute, Tokyo University, 32, PP. 199-210.
Khan, M. R. and Munimullah., compilers (1988). Stratigraphic lexicon of Bangldaesh:
Geology Survey of Bangladesh record, Vol. 5, pt. 1, PP. 61.
Khan, F. H. (1991). Geology of Bangladesh, University Press Limited, PP. 1-207.
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Konno, K. and Ohmachi, T. (1998). Ground motion characteristics estimated from spectral
ratio between horizontal and vertical components of microtremor», Bull. Seism. Soc.
Am., 88, N. 1, PP. 228-241.
Lachet, C. and Bard, P. Y. (1994). Numerical and theoretical investigations on thepossibilities and limitations of Nakamura’s technique, Journal of the Physics of the
Earth, 42, PP. 377-397.
Lermo, L. and Chavez-García, F. J. (1993). Site effect evaluation using spectral ratios with
only one station, Bull. Seism. Soc. Am., 83, PP. 1574-1594.
Lermo, J. and Chavez-Garcia, F. J. (1994). Are Microtremors Useful in Site Response
Evaluation? Bulletin of Seismological Society of America, 84, PP. 1350-1364.
Matin, M.A., Maroof Khan, M.A., Fariduddin, M., Boul. M.A., Taolad Hossain, M.M. andKononov, A.I. (1983). The Techtonic Map of Bangladesh-Past and Present, Vol-2, PP.
29-36.
Molnar, S., Cassidy, J. F. Monahan, P. A. and Dosso, S. E. (2007). Comparison ofgeophysical methods to determine shear-wave velocity, Proceedings of the Canadian
Conference on Earthquake Engineering, June 24-27th 2007, Ottawa, ON, Paper 1173.
Nakamura, Y. (1989). A Method for Dynamic Characteristics of Sub-surface Using
Microtremors on the Ground Surface, Quick Report of Railway Technical ResearchInstitute, 30, No. 1, PP. 25-33 (in Japanese).
Nakamura, Y. (2000). Clear identification of fundamental idea of Nakamura’s Technique andits applications, Proc. Of the 12th World Conference on Earthquake Engineering,
Auckland, New Zealand, PP. 2656-2664.
Ohmachi, T., Nakamura, Y. and Toshinawa, T. (1991). Ground motion characteristics in the
San Francisco Bay area detected by microtremor measurements, Proc. 2nd
International Conference on Recent Advances in Geotech. Earth. Eng. & Soil Dyn.
Saint Louis, Missouri, PP. 11-15 March: PP. 1643-1648.
Rodriguez, V. S. H. and Midorikawa, S. (2002). Applicability of the H/V Spectral Ratio of
Microtremors in Assessing Site Effects on Seismic Motion, Earthquake Engineeringand Structural Dynamics, 31, PP. 261-279.
Russel, S. Z. R., Yasin, M., Ansary, M. A., Saha, R., Kamruzzaman, M. and Noor, M. A.
(2006). Evaluation of the Seismic Vulnerability of Bangladeshi Building using NonDestructive Testing, an unpublished BNUS annual Report, Bangladesh Network Officefor Urban Safety, International Centre for Urban Safety Engineering, Institute ofIndustrial Science, The University of Tokyo.
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Sesoren, Atila (1984). Geological Interpretation of Landsat Imagery of Bangladesh Ganges
Delta, ITC Journal, PP. 229-232.
Suzuki, T., Adachi, Y. and Tanaka, M. (1995). Application of Microtremor measurements tothe estimation of earthquake ground motions in the Kushiro city during the KushiroOki earthquake of 15 January 1993, Earthquake Eng. Struc. Dyn. 24, PP. 595-613.
TC4 (1993). Manual for Zonation on Seismic geotechnical hazards, published by ISSMFE.

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PART-III

ESTIMATION OF SHEAR WAVE VELOCITY
USING 3D MICROTREMOR MEASUREMENTIN SYLHET CITYBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Estiak Ahmed Murad
Mehedi Ahmed Ansary

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Introduction:

Bangladesh is a small country situated at the south of The Himalayans. The Indian tectonic
plate and the Asian tectonic plate had a collision in The Himalayans region. In 2001, Bilham
et al. (2001) has shown the high possibility of large earthquake occurrence around theHimalayan region . Sylhet is one of the major cities of Bangladesh. There are several faults
near Sylhet where past earthquake history is available. Shillong Fault and Douki Fault areprominent within them. So, seismic activity near Sylhet is higher than any other region of
Bangladesh. According to Bangladesh National Building Code (BNBC) 1993 Sylhet issituated in the most vulnerable zone, “Zone-3” to Earthquake. Recently some studies havebeen taken to evaluate earthquake risk in some particular Educational Institutions. Several
kinds of Structural and Geotechnical data have been collected for this study. For evaluationof site amplification and response of soil and structure, Shear wave velocity of soil is the key
parameter. Shear wave velocity of soil has been determined using a Geophysical technique
named microtremor array method. This method was developed and used in several projects
like Network for Earthquake Engineering Simulation (NEES) funded by National Science
Foundation (NSF), USA , Site Effects Assessment Using Ambient Excitation (SESAME) in
Europe etc. In Bangladesh this method is a new one and this is the first time where it has been
used.

Methodology:

There are several methods of determining shear wave velocity from surface wave. SpectralAnalysis-of-Surface-Waves (SASW) was proposed by Nazarian and Stokoe in 1984. Later amore easy and convenient method, Multi Channel spectral analysis was developed andproposed by Park et al. Tokimatsu, 1995; Zywicki, 1999 etc. but all these methods has one
common disadvantages. There an energy source is required to create vibration. That energy
source usually makes too much noise and vibration. So, in urban area those methods areunacceptable some time. To recover those problems in 2001, Louie proposed another method,
Refraction Microtremor (ReMi) method. Ambient vibration is used in this method to get deep
profile of shear wave velocity of soil.
The steps to get shear wave velocity starts with data acquisition. At first the different array
type was proposed by different researchers. After Wathele (2005) an irregular array of
microtremor was used in this research.

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P132
�

��
Five numbers �of sensors
are used in each sites except Zindabazar High School. Due to some
=
�

P132

��

limitations, three sensors were used for data collection. To reduce the effect of noise and to

P132

��� reading has been taken.
detect low frequency vibration �
one=hour
�
P136
��
���
Using those dataatfirstSpectral
Auto
Correlation(SPAC)�=��� �x 10��γ = 1000 x10
γ > 10.000�

was used to determine thecorrelation between waves detected from different location at the same time. According to
P132P136
Aki ( 1957) special auto correlation
function
betweentwo sensors
��defined by the following
P136
γ > 10.000
x 10isγ = 1000
x10��
���P148 P132
equation.
γ > 10.000 x 10��γ = 1000 x10��
� =
� �
�
�
, �� � ��∅��� � ��� �� ����� ����� ……………………………………(1)
� �
�� =
P148
�

2

�

���
��

000 x10���
P136∅�� ������ ������ ���� � �� �γ =�1000
�P148
��
=∅���
�
x10
γ >����
10.000x 10,���� � ��∅������� �� �����
Here,
��
� � �
� �
����� �����
P136 two sensors,∅���� dataξ is the distance between
T is thetime,, �� � �� are the signals� �acquisition
�� �
� � �
����������
∅��
���
�
�
�
�
�
��
�
��� � ��
��
��
� x10
�
γ =of
1000
10.000x���
10� ��
�>respectively.
�������� �� γrecorded at the sensors
0P136
and
ξ �distance∅�� ���∅�� ���
γ > 10.000 x 10����� � �� ���� � ��P148
∅�� ��� x 10��γ = 1000 x10��γ�>�10.000�����������
If a narrow frequency band filteris���� ��of� frequency� � �� �the auto correlation ratios are� used� � ��� ��� � , � �������� �����
∅��� � �� ������������ ��� �� � � � ��� �
���following� �� � ��equation.
P148
calculated for all pairsof receivers� by the� ��� ��� � ����� �����
� � �
�

P132

�

�

∅�� ���

………………………..(2)�� � ��
∅������
�P148
� ����� �, ��� �� ����� ������ � � ∅�� ���, �� � ��� �
Akai (1957) has shown that,for ∅��
a�givensensorξ the�����distance, �� �
�� azimuthal average of∅���� �inter����������� �� � � ��������������
���
�
��
�
�
��
���
�
��
�
�
�
��
�
�
�
∅�� ���
���� ��� ��� ���� � �� has the shape of Bessel ∅��function.
That can be shown as,∅�� ���∅�� ������ � �� ��� ���� � ��∅������
����������
�
�
�
�
��
���
�
��
…………………………….(3)������ ��� ������� � �� � � � � ��� �� ��� �� �����������
��� of� ���� order� � and� � ��� � is the dispersion curve. Than using
Here, J0 is the Bessel function
the�first� �� �
��those correlation dispersion curve has been developed. There was Possibility of different
dispersion curves, so a theoretical dispersion curve has been used to find the dispersion curvefor the site. Theoretical dispersion curve was developed for Sylhet from soil data achieved byComprehensive Disaster Management Program (CDMP). In the computation of theoreticaldispersion curve in GPDC program is based on Eigenvalue problem by Thomson (1950) and
Haskell (1953).

For the computation the assumptions are, the soil layers are perfectly

horizontal and isotropic, they are extended upto infinity horizontal distance. It can be shownby a figure given by Wathelet (2005),

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Fig 1: Schematic one dimensional soil model Wathelet (2005), .
For sylhet the soil property used are given below:
Thickness(m)Vp (m/s)Vs (m/s)density (kg/m3)

16

20

210

1600

24

800

400

1800

0

2000

1000

2200

The bottom most layer of thickness 0 m is actually the half space. Here 0 m thickness is given
just because GPDC program considers the half space by reading 0 value in thickness.
The dispersion curve found is given below.
Than the inversion of those dispersion curve was done by using Neighbourhood Algorithm
by Dinver ( A software developed by Marc Wathele (2005). In the inversion process theassumptions were, Shear wave velocity increases with depth of the layer and poison ratio issame for soil from any depth. There were less attention to the poison’s ratio of soil layers
because the poison ratio does not has a significant role in forward computation of dispersion
curve from soil layer ( Wathelet, 2005) . But it is necessary to relate shear wave velocity with
p-wave velocity.

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Collected Data:
Location of data collection are showed in the following figure.

Fig 2: the dispersion curve for Sylhet.
Fig 3 : Location of Data Collection from Sylhet.
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At Aided School, the playground was used for data collection. Two kind of array has beenused in that case. Array formations are given below.

Fig 4 : Array formation at Aided school play ground.
At Gindabazar Govt. Primary School due to the limitation of enough free space, only one
longitudinal array has been used.

Fig 5: Array formation of Zindabazar Govt. Primary School.
At Raza G. C. High School, the play ground has been used. The array formation is given
below.

Fig 6: Array formation of Raza G.C. High School play ground .
At Taltola fire service office, the field adjacent office has been used. Two array has beenused there. Array formations are given below.

Fig 7: Array formation of Taltola Fire service office.

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Fig 8: Upashar array formation.

Results:

After using all steps described in the methodology section, the shear wave velocity profiles
found are presented below.

(a)

(b)

Fig 9: Dispersion Curve for Rayleigh wave of Aided School (From cross array).
(a) All curves with misfit 0 to 1., (b) Curve with minimum misfit, ( Misfit = 0.0176) .

Depth
0
1.44
2.87
4.83
13.83
15.27
28.44
66.43

152

to
to
to
to
to
to
to
to

1.44
2.87
4.83
13.83
15.27
28.44
66.43
70

Vs
(m/s)
168.38201.27205.97215.37220
323.43579.51
991.45Vs (avg)

203
217
323
579
991

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Fig 10: Shear wave velocity profile of Aided School (From cross array).

(a)

(b)

Fig 11: Dispersion Curve for Rayleigh wave of Aided School (From long array).

(a) All curves with misfit 0 to 1., (b) Curve with minimum misfit, ( Misfit = 0.0176) .

Depth
0
10.04
22.48
43.39

to
to
to
to

Vs (m/s)
10.04
22.48
43.39
45.52

200.09234
469.43974.03Vs(average)
200
234
469
974

Fig 12: Shear wave velocity profile of Aided School (From long array).

BNUS Annual Report-2011153

March 2012

(a)

(b)

Fig 13: Dispersion Curve for Rayleigh wave of Raza GC School (From long array).
(a) All curves with misfit 0 to 1., (b) Curve with minimum misfit,(Misfit = 0.022) .

0
9.89
22.04
44.26

Depth
to
to
to
to

9.89
22.04
44.26
46.52

Vs (m/s)
211.07260.37645.76
991.60Vs avg
211
260
646
992

Fig 14: Shear wave velocity profile of Raza GC School (From long array).

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(a)

(b)

Fig 15: Dispersion Curve for Rayleigh wave of (From cross array).

(a) All curves with misfit 0 to 1., (b) Curve with minimum misfit,(Misfit = 0.02)

0
11.58
20.61
45.07
58.95

Depth
to
to
to
to
to

11.58
20.61
45.07
58.95
61.96

Vs (m/s)
214.76227.81484.51768.06974.73

Vs avg
215
228
485
768
975

Fig 16: Shear wave velocity profile of Upashar (From cross array).

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(a)

(b)

Fig 17: Dispersion Curve for Rayleigh wave of Taltola Fire service (From long array).
(a) All curves with misfit 0 to 1., (b) Curve with minimum misfit,(Misfit = 0.015)

0
1.11
2.34
6.12
17.03
31.45
33.56
56.76

Depth
to
1.11
to
2.34
to
6.12
to
17.03
to
31.45
to
33.56
to
56.76
to
59.66

Vs (m/s)
162.28191.53211.03223.22318.28622.97884.621021.12

Vs avg
209

318
623
885
1021

Fig 10: Shear wave velocity profile of Taltola Fire service (From long array).

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Dispersion
Dispersion
Dispersion
curve
curve
from
curve
from
ambient
ambient
from ambient
vibration
vibration
vibration
Theoretical
Theoretical
Theoretical
Dispersion
Dispersion
Dispersion
curve
curve curve(a)(a)(a)(b)(b)(b)

FigFig
18:18:
Dispersion
Fig
Dispersion
18: Dispersion
Curve
Curve
for
Curve
for
Rayleigh
Rayleighfor Rayleigh
wave
wave
of of
wave
Zindabazar
Zindabazarof Zindabazar
High
High
SchoolSchoolHigh School(a)(a)
AllAllcurves(a)curvesAllwithcurveswith
misfitmisfitwith
0 tomisfit
0 1.,
to 1.,
(b)
0(b)
to
Curve
1.,
Curve
(b)
with
Curve
with
minimum
minimumwith minimum
misfit,(Misfit
misfit,(Misfit
misfit,(Misfit= 0.017= 0.017).= ).
0.017 ).

Depth
Depth Depth Vs Vs
(m/s)
(m/s)
Vs (m/s)
0 to 1.46
1.46
to
1.46
195.31195.31
0 0to
195.31
1.46 to1.46
to 13.54
13.54
to
13.54
217.52217.52
1.46
217.52
13.54 to13.54
to 23.97
23.97
to
23.97
293.07293.07
13.54
293.0723.97 to23.97
to 30.01
30.01
to
30.01
419.71419.71
23.97
419.7130.01 to30.01
to 30.84
30.84
to
30.84
435.26435.26
30.01
435.2630.84 to30.84
to 60.96
60.96
to
60.96
728.54728.54
30.84
728.5460.96 to60.96
to 88.96
88.96
to
88.96
933.71933.71
60.96
933.7188.96 to88.96
to 97.93
97.93
to
97.93
971.48971.48
88.96
971.48Vs Vs
avgavgVs avg
206206 206
293293427427293
427

729729934934971971

729
934
971

FigFig
19:19:
Shear
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Shear
19:
wave
Shear
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velocity
velocity
wave velocity
profileprofileofprofileofZindabazar
Zindabazarof Zindabazar
High
High
SchoolSchoolHigh(From
School
(From
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(From
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array).
array).
long array).

Conclusion
Conclusion
Conclusion
Microtremor
Microtremor
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array
array
methodarray
methodmethodis isananapproximate
isapproximate
an approximate
methodmethodmethodwhich
which
iswhichishighlyhighlyis susceptible
highlysusceptible
susceptible
to to
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some
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factors
likefactors
like
array
array
like
formation,arrayformation,formation,
noise
noise
in noiseincollected
collected
in collected
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data,
thethedata,
theoreticaltheoretical
the theoreticaldispersion
dispersion
dispersion
curve
curve
and
curve
and
thetheand theparameterization.
parameterization.
parameterization.
The
The
noise
noise
The
was
noise
was
very
very
was
high
high
very
in in
most
high
most
of
in of
most
thethecases.
ofcases.
theLongcases.
Long
time
Long
time
readingreadingtime wasreading
was
taken
taken
was taken
to toreducereducetothe
reducetheeffecteffecttheofeffectofnoise.
noise.
ofThenoise.
The
shear
shear
The
wave
shear
wave
velocitywave
velocity
velocity
profilesprofilesprofiles
found
found
are
found
are
averageaverageare average
soil
soil
profileprofilesoil profile
157
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BNUS
AnnualReport-2011
AnnualReport-2011
Report-2011

March 2012of all the soil profiles below each sensor. So just because of the positioning of the sensors
gave close but different soil profile in the same field. The theoretical dispersion curve wasmade by using judgment on some soil profiles found by seismic downhole method. In theparameterization phase, the poison ratio and density of the soil strata kept same for all depth,
but according to Wathele (2005) the effect of poison ratio and density are insignificant. So it
will not lead to a profile much different from real case. Another fact is, the profiles are foundby using misfit less than 0.05. So there is probability of variation of real shear wave velocity
from the shown profile.

Reference
Aki, K. (1957). Space and time spectra of stationary stochastic waves, with special reference
to microtremors, Bull. Earthq. Res. Inst. 35, 415{456.
Bilham, R., V.K. Gaur and P. Molnar (2001). Himalayan Seismic Hazard, SCIENCE, 293.
Haskell, N. A. (1953). The dispersion of surface waves on multilayered media, Bull. Seism.
Soc. Am. 43, 17{34.
Louie, J. N. (2001). “Faster, better: shear-wave velocity to 100 meters depth from refraction
microtremor arrays.” Bulletin of the Seismological Society of American, 91(2), 347-364.
Nazarian, S., and Stokoe, K. H., II (1984). “In situ shear wave velocities from Spectral
Analysis of Surface Waves.”

Proceedings of the 8th World Conference on Earthquake

Engineering, Prentice-Hall, Inc., Englewood Cliffs, New Jersey, Vol. III, 31-38.
Park, C.B., Miller, R.D., Xia, J. (1999). “Multichannel analysis of surface waves.”
Geophysics, 64, 800-808.
Thomson, W. T. (1950). Transmission of elastic waves through a stratied solid medium,
Journal of Applied Physics 21, 89{93Tokimatsu, K. (1995). “Geotechnical site characterization using surface waves.” Proceedingsof 1st International Conference on Earthquake Geotechnical Engineering, IS-Tokyo '95,
Balkema, Rotterdam, 1333-1368.
Wathelet, M. (2005). “Array recordings of ambient vibrations: surface-wave inversion.” Ph.D.
dissertation, Universite de Liege.
Zywicki, D.J. (1999). “Advanced signal processing methods applied to engineering analysisof seismic surface waves.” Ph.D. dissertation, Georgia Institute of Technology.

158

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PART-IV

STRONG MOTION RECORDINGS DURINGSEPTEMBER 18, 2011 SIKKIM EARTHQUAKEBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Mehedi Ahmed Ansary
Md. Shamsur Rahman

BNUS Annual Report-2011

ICUS Report 59

1. INTRODUCTION
The 4.8 km long Jamuna Multipurpose Bridge connects the eastern and western parts of
Bangladesh. Being the only road and rail link between the two regions, the bridge bears
immense economic and strategic importance for the whole country. But the bridge is locatedin a seismically active region that can be subjected to moderately strong earthquakes from anumber of sources and special earthquake protection devices have been used in the bridge.
The bridge has been designed for a peak ground acceleration of 0.2g due to a 7.0 magnitude
earthquake in the Bogra fault zone, which is about 25 to 40 kms from the west end of thebridge, based on study by Bolt (1987).
Jamuna Multipurpose Bridge Authority (JMBA) took necessary steps for the installation ofseismic instruments on and around the Jamuna Bridge. JMBA employed Bangladesh
University of Engineering & Technology (BUET) as the technical consultant for this project.
The Installation of the seismic instruments on the bridge structure and six other free-field(ground) stations was completed by Kinemetrics, Inc. USA on July 10, 2003 (BUET, 2003).
The Operating and Monitoring Phase of the project started on July 11, 2003.
In this report the September 18, 2011 Sikkim earthquake recorded by the earthquake
monitoring system are presented.

2. EARTHQUAKE DATA ANALYSIS
The report gives the complete processed data of the three components of motion at the eight
free-field stations which recorded the earthquake. The data processing, which includes
necessary corrections and filtering, has been carried out using softwares SMA (Kinemetrics,
2001) and Origin 6.0. The earthquake data has been formatted using USGS format. The
acceleration, velocity and displacement time histories have been evaluated.

3. EARTHQUAKE PARAMETERS
The 6.9 Moment magnitude earthquake hit Sikkim on 18th September 2011 with its epicenter
located at 27.72°N, 88.06°E, near India-Nepal border, about 68 km NW of Gangtok and at a
focal depth of 19.7 km as reported by USGS. Three aftershocks of magnitude 5.7, 5.1 and 4.6
were also felt in Sikkim within 30 minutes of the earthquake.
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March 2012

The region is known for seismic activity between the Main Boundary Thrust (MBT) and theMain Central Thrust (MCT). Maximum observed shaking intensity during this earthquake
was VIII on MSK scale. About 100 deaths are reported in India with the maximum of at least
60 in the state of Sikkim and total loss of property was about 15 Million US Dollar.

Figure 1 Earthquake and strong motion (accelerometer) locations

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ICUS Report 59

4. GROUND MOTION DUE TO EARTHQUAKE
Figure 2 to 24 show the time history (acceleration) data of Bogra, Comilla, Haji Camp,
Khagrachari, Kurigram, Meherpur, Natore, Netrokona in EW, NS and UD directions. Table 1
gives a list of peak values of accelerations, velocities and displacements of all the free-fieldstations due to the 2011 Sikkim earthquake. The maximum recorded acceleration due to thisearthquake is 33.55 cm/s2 in Kurigram, the maximum velocity is 3.46 cm/s in Kurigram andthe maximum displacement is 1.62 cm in Netrokona.
Table 1: Summary of Peak Ground Motion Acceleration in Free Field Stations
Station ID

Bogra

ComillaHaji Camp

Khagrachari

Kurigram

Direction

Peak Ground Motion
2

Acceleration (cm/s )Velocity (cm/s)

Displacement (mm)

EW

21.49

2.00

0.54

NS

-21.57

-1.41

0.32

UD

10.67

0.68

-0.16

EW

-5.56

0.28

0.022

NS

-5.47

0.28

-0.017

UD

2.27

0.08

0.007

EW

7.95

1.198

-0.340NS

5.27-0.842-0.324UD

2.45-0.348-0.125

EW

6.81

0.467

-0.093

NS

-4.91

0.413

0.089

UD

1.84

-0.2150.038

EW-33.55-3.16-0.904

NS

29.87

3.46

0.565

UD

31.81

1.39

-0.320BNUS Annual Report-2011161

March 2012

MeherpurNatoreNetrokona

Note.

162

EW

-12.711.72-0.585NS-11.591.95-0.614

UD

5.73

-0.29

-0.125EW-17.34

1.58

0.589

NS

17.68

1.46

0.413

UD

-

-

-

EW

14.63

-2.89

1.623

NS

12.19

2.18

0.793

UD

-4.56

0.79

0.405

EW represents East-West direction,
NS represents North-South direction,
UD represents Vertical direction

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Displacement(cm) Velocity (cm/s) Acceleration(cm/s2)

ICUS Report 59

Shikim EQ:September 18,2011 Plot: EW-direction

30
20
10
0
-10
-20
-30
2

0

20

40

60

80

0

20

40

60

80

0

20

40

60

80

1
0
-1
-2
0.6
0.3
0.0
-0.3
-0.6

Time (sec)

Displacement(cm) Velocity (cm/s) Acceleration(cm/s)

Figure 2 Recorded earthquake ground motion in Bogra, EW-direction

Shikim EQ:September 18,2011 Plot: NS-direction

20
10
0
-10
-20
3.0

0

20

40

60

80

0

20

40

60

80

0

20

40

60

80

1.5
0.0
-1.5
-3.0
0.8
0.4
0.0
-0.4
-0.8

Time (sec)Figure 3 Recorded earthquake ground motion in Bogra, NS-direction

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March 2012

Displacement(cm) Velocity (cm/s) Acceleration(cm/s)

Shikim EQ:September 18,2011 Plot: UD-direction
12
6
0
-6
-12
0

20

40

60

80

0

20

40

60

80

0

20

40

60

80

0.4
0.0
-0.4
-0.8
0.2
0.1
0.0
-0.1
-0.2

Time (sec)

Velocity (cm/s) Acceleration(cm/s2)

Figure 4 Recorded earthquake ground motion in Bogra, UD-direction

Comilla Plot: EW-direction

8
4
0
-4
-8
0.4

0

4

8

12

16

0

4

8

12

16

0

4

8

12

16

0.2
0.0

Displacement(cm)

-0.2
-0.4

0.015
0.010
0.005
0.000
-0.005-0.010-0.015

X Axis Title

Figure 5 Recorded earthquake ground motion in Comilla, EW-direction

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Comilla Plot: NS-direction2

Velocity (cm/s) Acceleration(cm/s )ICUS Report 59

6
3
0
-3
-6

Displacement(cm)

0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3

0.015
0.010
0.005
0.000
-0.005-0.010-0.015

0

4

8

12

16

0

4

8

12

16

0

4

8

12

16

Time (sec)

Displacement(cm) Velocity (cm/s)
2
Acceleration(cm/s )Figure 6 Recorded earthquake ground motion in Comilla, NS-direction

Comilla Plot: UD-direction
3.0
1.5
0.0
-1.5
-3.0

0.15
0.10
0.05
0.00
-0.05
-0.10
-0.15

0.015
0.010
0.005
0.000
-0.005-0.010-0.015

0

4

8

12

16

0

4

8

12

16

0

4

8

12

16

Time (sec)Figure 7 Recorded earthquake ground motion in Comilla, UD-direction

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March 2012

Shikim EQ:September 18,2011 Plot: EW-direction
8
4
0
-4
-8
2

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

1
0
-1
-2

1.0
0.5
0.0

-0.5
-1.0

Time (sec)

Displacement(cm) Velocity (cm/s) Acceleration(cm/s2)

Figure 8 Recorded earthquake ground motion in Hazi Camp, EW-direction
Shikim EQ:September 18,2011 Plot: NS-direction
6
3
0
-3
-6

1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
1.0

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

0.5
0.0

-0.5
-1.0

Time (sec)Figure 9 Recorded earthquake ground motion in Hazi Camp, NS-direction

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ICUS Report 59

Shikim EQ:September 18,2011 Plot: UD-direction

6
4
2
0
-2
-4
-6

1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
1.0

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

0.5
0.0

-0.5
-1.0

Time (sec

Shikim EQ:September 18,2011 Plot: EW-direction

Displacement(cm) Velocity (cm/s)

2

Acceleration(cm/s )Figure 10 Recorded earthquake ground motion in Hazi Camp, UD-direction

8
4
0
-4
-8
1.0

0

4

8

12

16

0

4

8

12

16

0

4

8

12

16

0.5
0.0

-0.5
-1.0
0.5

0.0

-0.5

Time (sec)Figure 11 Recorded earthquake ground motion in Khagrachari, EW-direction

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March 2012

Shikim EQ:September 18,2011 Plot: NS-direction
6
3
0
-3
-6

1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
0.5

0

4

8

12

16

0

4

8

12

16

0

4

8

12

16

0.0

-0.5

Time (sec)

Displacement(cm)2

Velocity (cm/s) Acceleration(cm/s )Figure 12 Recorded earthquake ground motion in Khagrachari, NS-direction

Shikim EQ:September 18,2011 Plot: UD-direction
3.0
1.5
0.0
-1.5
-3.0
0.5 0

4

8

12

16

0

4

8

12

16

0

4

8

12

16

0.0

-0.5
0.05

0.00

-0.05

Time (sec)Figure 13 Recorded earthquake ground motion in Khagrachari, UD-direction

168

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Shikim EQ:September 18,2011 Plot: EW-direction
40
20
0
-20
-40
4

0

20

40

60

80

100

0

20

40

60

80

100

0

20

40

60

80

100

2
0
-2
-4
1.0
0.5
0.0

-0.5
-1.0

Time (sec)2

Displacement(cm) Velocity (cm/s) Acceleration(cm/s )Figure 14 Recorded earthquake ground motion in Kurigram, EW-direction

Shikim EQ:September 18,2011 Plot: NS-direction

40
20
0
-20
-40
4

0

20

40

60

80

100

0

20

40

60

80

100

0

20

40

60

80

100

2
0
-2
-4
0.8
0.4
0.0
-0.4
-0.8

Time (sec)Figure 15 Recorded earthquake ground motion in Kurigram, NS-direction

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Displacement(cm) Velocity (cm/s) Acceleration(cm/s )March 2012

Shikim EQ:September 18,2011 Plot: UD-direction

40
20
0
-20
-40
2

0

20

40

60

80

100

0

20

40

60

80

100

0

20

40

60

80

100

1
0
-1
-2
0.4
0.2
0.0

-0.2
-0.4

Time (sec)

Displacement(cm) Velocity (cm/s) Acceleration(cm/s2)

Figure 16 Recorded earthquake ground motion in Kurigram, UD-direction

Shikim EQ:September 18,2011 Plot: EW-direction

16
8
0
-8
-16
2

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

1
0
-1
-2
0.8
0.4
0.0

-0.4
-0.8

Time (sec)Figure 17 Recorded earthquake ground motion in Meherpur, EW-direction

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Displacement(cm) Velocity (cm/s) Acceleration(cm/s )ICUS Report 59

Shikim EQ:September 18,2011 Plot: NS-direction
12
6
0
-6
-12
3
2
1
0
-1
-2
-3
1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

Time (sec)2
Displacement(cm) Velocity (cm/s) Acceleration(cm/s )Figure 18 Recorded earthquake ground motion in Meherpur, NS-direction

Shikim EQ:September 18,2011 Plot: UD-direction
6
4
2
0
-2
-4
-6
0.50

0

10

20

30

40

0

10

20

30

40

0

10

20

30

40

0.25
0.00
-0.25
-0.50
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3

Time (sec)Figure 19 Recorded earthquake ground motion in Meherpur, UD-direction

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March 2012

Shikim EQ:September 18,2011 Plot: EW-direction
20
10
0
-10
-20
2

0

20

40

60

80

100

120

0

20

40

60

80

100

120

0

20

40

60

80

100

120

1
0
-1
-2
0.8
0.4
0.0
-0.4
-0.8

Time (sec)

Displacement(cm) Velocity (cm/s) Acceleration(cm/s2)

Figure 20 Recorded earthquake ground motion in Natore, EW-direction

Shikim EQ:September 18,2011 Plot: NS-direction

22
11
0
-11
-22
2

0

20

40

60

80

100

120

0

20

40

60

80

100

120

0

20

40

60

80

100

120

1
0
-1
-2
0.4
0.2
0.0
-0.2
-0.4

Time (sec)Figure 21 Recorded earthquake ground motion in Natore, NS-direction

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Acceleration(cm/s )ICUS Report 59

Shikim EQ:September 18,2011 Plot: EW-direction
16
12
8
4
0
-4
-8
-12
-16

Displacement(cm) Velocity (cm/s)

4

0

20

40

60

80

0

20

40

60

80

0

20

40

60

80

2
0
-2
-4
2
1
0
-1
-2

Time (sec)Figure 22 Recorded earthquake ground motion in Netrokona, EW-direction

Displacement(cm)2

Velocity (cm/s) Acceleration(cm/s )Shikim EQ:September 18,2011 Plot: NS-direction
16
8
0
-8
-16
3
2
1
0
-1
-2
-3

1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5

0

20

40

60

80

0

20

40

60

80

0

20

40

60

80

Time (sec)Figure 23 Recorded earthquake ground motion in Netrokona, NS-direction

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Displacement(cm)

Velocity (cm/s) Acceleration(cm/s2)

March 2012
Shikim EQ:September 18,2011 Plot: UD-direction
6
4
2
0
-2
-4
-6

0.9
0.6
0.3
0.0
-0.3
-0.6
-0.9

0.45
0.30
0.15
0.00
-0.15
-0.30
-0.45

0

20

40

60

80

0

20

40

60

80

0

20

40

60

80

Time (sec)Figure 24 Recorded earthquake ground motion in Netrokona, UD-direction

REFERENCE
1. Bolt, B.A (1987) ‘Site Specific Seismicity Study of seismic Intensity and Ground Motion
Parameter for Proposed Jamuna Bridge, Bangladesh’ Report prepared for seismic design of
Jamuna Bridge.
2. BUET (2003) ‘Final Report: Installation Phase, Jamuna Multipurpose Bridge Seismic
Instrumentation Project’, report submitted to JMBA.
3. KMI Strong Motion Analyst, Version 2.4, copyright 1998-2001, Kinemetrics, Inc. 222,
Vista Avenue, Pasadena, California, USA 91107.

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PART-V

APPLICATION OF NON-DESTRUCTIVETESTING TECHNIQUES FOR STRUCTURAL
SAFETY EVALUATION IN BANGLADESHBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Ram Krishna MazumderMehedi Ahmed Ansary

BNUS Annual Report-2011

ICUS Report 59

1. INTRODUCTION
Assessment of an existing structure is a difficult task. The construction of a structure is neverexactly as per a designer’s specification and a number of defects and uncertainties crop up
during the construction. Moreover, the quality of the materials deteriorated with time and theassessment of an existing structure becomes a time dependent problem.
The problem of assessment of an existing structure involves not only the current status of thestructure but also its exploration in the life of the structure with or without repairs. There arethree sources of deficiency in structures:a.

Defect arising from the original design, such as under estimation of loads as per oldstandards or practices, inadequate section or reinforcement anchorage and detailing.
b.

Defects arising from original construction, such as under strength of concrete, poor

compaction, poor construction joints, improper placing of reinforcement and honeycombing.
c.

Deterioration since the completion of the construction due to reinforcement corrosion,

alkali-aggregate reaction, etc.
If the design documents are available, the first type of deficiency can be assessed with asatisfactory level of confidence. A number of techniques have been developed to detect theother two types of deficiency. Almost all of them depend on indirect measurement and have a
low reliability (Singh, 2011). Further the variation of test result is large and interpretation of
results requires experience and skills. However, modern NDT techniques have a much morereliability to condition assessment of buildings before taking up repair and upgrading work.
In Bangladesh, most of the houses are non-engineered constructions, which are mainly load
bearing buildings. In urban areas, there are many RC frame buildings which have been
constructed without any consideration to resist earthquake forces or without using current
codal practice on Earthquake Resistance Design. For such type of seismically deficientbuildings, a quick NDT assessment could be a good approach for safety measurement ofbuildings within considerable cost.
2. NON-DESTRUCTIVE TESTING EQUIPMENT
2.1 Ferroscan
Ferroscan is portable, non-destructive steel reinforcement detection system using
electromagnetic pulse. It can reduce costly effort to drill, cut or physically break concretesurface to find out the bar. Ferroscan has been used for determining the position, depth anddiameter of rebar in existing structure. This is a portable, quick and simple-to-operate system
carrying out structural analyses quickly and exactly in a non-destructive manner. This also
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determines coverage over the entire surface of a structure. The key elements of the system are
the scanner and the monitor. After scanning a structure data has been transferred to themonitor. Collected data can be analyzed by monitor or in a PC using PS 200 software’s.
Maximum depth of scanning is 180 mm (at 36 mm rebar diameter) where rebar diameter
range 6 - 36 mm. Accuracy of depth measurement for rebar is ±1 mm, depending on depth
range and scan mode used. Three types of scanning can be checked out by using Ferroscan
device. Line scan is simple way to detect position and depth of rebar where Image scan
provides detail information (diameter of bar, concrete cover, location etc.) with scanned
image (2 ft x 2 ft grid) of any structure. Block scan is a combination of a set of image scan for
a comparatively large area (Rahman et. al, 2010). Figure 1 shows monitor and scanningdevice.

Figure 1: Hilti PS 200 Monitor and Scanner device
2.2 Rebar Detector
Rebar Detector has been used to determine the exact location of rebar in existing structure.
The Profoscope is a versatile, fully-integrated rebar detector and cover meter with a uniquereal-time rebar visualization allowing the user to actually see the location of the rebar beneaththe concrete surface to a maximum depth of 180 mm. This is coupled with rebar-proximity
indicators and optical and acoustical locating aids. Rebar diameter can also be estimatedwithin the specified testing range. The Profoscope combines these unique features in acompact, light device that allows the user to operate this rebar detector with one hand making
the task of locating rebars a simple and efficient process. In addition, Proceq’s rebar detector
convinces through its intuitive user interface making rebar detection easy. Figure 2(a) showsa Profoscope Rebar detector.

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2.3 Rebound Hammer
A simple equipment known as Rebound Hammer or Schmidt Hammer is used determine asurface hardness in order to establish the theoretical relationship between the strength of
concrete and the rebound number of the hammer. The details of the equipment are shown in
Figure 2b, 2c. Surface hardness measured during the test give an idea about the soundness
and quality of cover concrete. Locations having very low rebound numbers indicate weaksurface concrete and may be affected by corrosion.

Figure 2: a) Profoscope Rebar Detector, b) Schmidt Hammer and c) Different parts ofSchmidt Hammer
2.4 Ultrasonic Pulse Velocity (UPV) Instrument
The ultrasonic pulse velocity method is used to determine material strength and quality, basedon the relation-ship to material density and elasticity. The test equipment has provisions forgenerating ultrasonic pulse, transmitting it to concrete, receiving and amplifying the pulse
and measuring and displaying the pulse travel time. Good acoustic coupling between thetransducers and concrete is to be established for correct measurement of the speed (IAEA,
2002). The instrument uses transducers as transmitters and receivers to calculate pulse
velocity by measuring transmission time. This flexible unit can measure via directtransmission, semi-direct transmission, indirect or surface transmission to accommodate thedemands of virtually any test site. Figure 3 shows UPV instrument and its observation.

Direct transmission

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Tico - Ultrasonic Device

Semi-direct transmission

Principal of measurement

Indirect or surface transmission

Figure 3: Ultrasonic concrete testing instruments and its observation
2.5 Microtremor Instrument
Microtremor measurement has been done with five component of sensor. At each site,
microtremor ground motions were measured for 5 minutes. Each accelerometer recorded datain three direction two horizontal (N-S and E-W components) and one vertical direction (updown). For free field near to building, First Fourier Transform (FFT) has been done in orderto calculate H/V spectral ratio for microtremors. At the top and ground floors of the bothbuildings, horizontal X- and Y-component microtremor motions, which are in longitudinal
and transverse directions of the buildings, were observed. Figure 4 shows Microtremor
testing equipments.

Figure 4: Test equipments used in microtremor measurements.
2.6 Ground Penetrating Radar
Ground Penetrating Radar (GPR) is a technique of obtaining sub-surface images using
electromagnetic radiation. The energy radiated by the antenna of the system penetrates thesurface, and is either absorbed or reflected back at any discontinuities. GPR is valuable for inlocating defects and voids in concrete structures, determining embedded reinforcement andother subsurface details. The StructureScan Standard system provides a nondestructive means
to accurately inspect concrete structures. This StructureScan Standard used to safely locate
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embedment within concrete structures prior to drilling, cutting or coring. Reach depths of 018 inches with confidence using a 1600 MHz antenna, survey cart and SIR–3000 control unit.
This is generally used to locate metallic and non-metallic targets in walls, floors. Figure 5
shows GPR control units and a 1.6 GHz antenna for structure scan.

Figure 5: 1.6 GHz Antenna and Control Unit of GPR by Geophysical Survey System Inc.
(GSSI)
3. STUDY AREA
In the last two years, these Non-Destructive Testing equipments have been used in different
parts of Bangladesh. Important buildings of Chittagong hill tracts region (Khagrachari,Rangamati and Bandarban districts), new and old buildings in Dhaka and an electrical power
plant building in Kushtia and two school buildings in Sylhet have been covered. BasicallyUnreinforced Masonry (URM) and Reinforced Concrete (RC) frame structure has been tested
for structural safety. Figure 6 shows conducted NDT location in Bangladesh.

Figure 6: Locations of NDT conducted in Bangladesh

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4. METHODOLOGY OF EVALUATION
Location and spacing requirements of column transverse reinforcement and beam stirrup
have been checked by using Ferroscan and Rebar Detector. Existing beam and column havebeen scanned by those two equipments. Reinforcement configuration has been compared withseismic specification provided in ACI 318. Figure 7 and Figure 8 give reinforcement
requirement for column where Figure 9 provides reinforcement requirement for beam (ACI,2008). Slabs also scanned to check the existing reinforcement location as per design.
To measure the elastic properties or strength of concrete, Rebound hammer was used in allcolumns located at the ground floor of the surveyed building. Schmidt hammer was also used
for some of the beams at ground floor. The quality of concrete may be interpreted as shownin the Table 1(GoI-UNDP, 2007).
Table 1: Average Rebound number and quality of concrete
Average Rebound number

Quality of Score>40

Very good hard layer

30 to 40

Good layer

20 to 30

Fair

< 20

Poor concrete0DelaminatedFigure 7: Column transverse reinforcement spacing requirements.

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Figure 8: Transverse Reinforcement in Columns.

Figure 9: Transverse Reinforcement for Beams.
Using this ultrasonic method, the ultrasonic instrument determines, indirectly, the modulus ofelasticity and concrete strength. The instrument is typically used on site to assess uniformlyof concrete and to locate cracks, voids, cavities, and defects due to fire and frost. The qualityof concrete may be interpreted from the Table 2(GoI-UNDP, 2007).
Table 2: UPV value and concrete quality
UPV value in m/sec (V)Concrete quality

V > 4000.0

Very goodV = 3500 - 4000

Good, but may be porousV = 3000 - 3500

Poor

V = 2500 - 3000

Very poor

V = 2000 - 2500

Very poor and low integrity

V < 2000 and reading fluctuating

No integrity, large voids suspected

Microtremor instruments measures predominant ambient frequency of the structures and soil.
If predominant frequency of both structure and soil are close to each other, there will be
more likelihood to damage during an earthquake.

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GPR 1.6 GHz antenna can identify the rebar position in a structure by generating radar pulse.
Semi-automatic mapping of deterioration zones within concrete structures can be identify
using special RADAN software.
5. RESULTS
Among 65 buildings only 7 buildings are masonry, rest of all are reinforced concretebuildings. Considered masonry structures are situated at Dhaka and only microtremor test are
performed for these masonry buildings in order to check the resonance criteria. Other NDTequipments have been used for all RC buildings.
Ferroscan and Rebar Detector have been used alternatively for RC buildings. Identified
reinforcement spacings have been verified with ACI 318 guideline for seismic consideration.
According to priority basis on structural configuration, at least three columns have beenscanned for each building in different storey level. From 57 buildings, only 12 buildings
comply with seismic provision for column middle part as per ACI 318 where 45 buildings
didn’t satisfy. For end portion of column, only 9 buildings are satisfied as per ACI 318. Beamreinforcement configuration also justified with ACI 318 provision. From 54 scanned cases,
19 cases have been satisfied for middle part of beam. Other hand, only 2 beams are satisfied
for end portion check from 11 cases. Reinforcement identification of end portion hasn’t been
performed for most of the beams due to insufficient space. Scanned image of slabs have been
generate using image scan mode by Ferroscan. Figure 10 and Figure 11 show typical image
scan result and reinforcement position in structural elements respectively.
Schmidt hammer has been used for 55 buildings. Average of 10 impacts has been considered
for each concrete surface. From the assessment it has been found that column rebound value
is below 30 for 36 buildings. So, concrete conditions of those 36 buildings are fair to poor(see Table 1). Average rebound number more than 40 have been found for only 2 buildings,
where 17 buildings have score greater than 30. Figure 12 shows impact data in Hammerlink
software.

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11.0"

11.0"

1'-4.0"

4.5"

7.0"

9.0"

8.0"

7.0"

8.5"

9.0"

7.0"

8.0"

9.0"

7.0"

8.0"

9.0"

1'-0.0"

6.5"

5.0"

Figure 10: Typical image scan for column (left) and slab

Figure 11: Identified reinforcement position in column and beam.

Figure 12: Impacts data analyzed in Hammerlink software.
Ultrasonic equipment has been used in three hill tract districts. Among 44 ultrasonic results, 2buildings have very poor and low integrity, 4 buildings have very poor to poor condition, 21
buildings have good to very good condition (see Table 2).
Microtremor has been used for 21 buildings in Dhaka, Sylhet and Kushtia. First Fourier
Transform (FFT) indicates that only 3 masonry buildings have likelihood to significant
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damage during an earthquake. From other 14 RC buildings, 4 buildings have a highpossibility to resonance during earthquake where 10 buildings have a moderate to low risk forresonance. Predominant frequency can be found from FFT (in Figure 13).
NS
EW
V

8

9

NS
EW
V

8
7

Amplitude

Amplitude

6

4

6
5
4
3

2

2
1

0
0

10

Frequency

20

0

0

10

20

Frequency

Figure 13: Typical FFT analysis for free field and roof of structure
A raft founded basement has been scanned by GPR. 3D data has been collected in order toinvestigate deterioration zones within concrete structures. After RADAN analysis, nodeterioration has been found. Figure 14 shows 3D model of raft basement

Figure 14: 3D data set showing rebar mat.
6. CONCLUSIONS
The importance and need for NDT assessment and evaluation of safety of existing buildings
have been highlighted in this paper. Safety evaluation forms the basis for designing andcarrying out strengthening of buildings to satisfy the safety and performance standards as per
the extant building codes. An overview of the procedures and different investigations
including tests involved in condition assessment and evaluation of safety is presented. It canbe seen that detailed visual inspection and Non Destructive Testing (NDT) plays an
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important role in condition assessment of existing buildings. It may be emphasized here thata great deal of expertise is required for interpretation of field observations and test results tomake a proper assessment of the condition as well as for analyzing and evaluating safety.
References
American Concrete Institute (ACI) -318 (2008), “Building Code Requirements for Structural
Concrete”.
GoI-UNDP Disaster Risk Management Programme, Government of India (2007),“Condition Assessment of Buildings for Repair and Upgrading Report”.
International Atomic Energy Agency (IAEA) (2002), “Guidebook on Non-Destructive
Testing of Concrete Structures”, Training Course Series No. 17.
Rahman, M. S., Islam, B. and Ansary, M. A.. (2010), “Diagnosis of the Seismic
Vulnerability of Buildings at Dhaka Using Non-Destructive Testing”, 9th Proceedings of
New Technologies for Urban Safety of Mega Cities in Asia, Kobe, Japan.
Singh, Y. (2011), “Seismic Vulnerability Assessment of Existing Buildings”, Earthquake
Risk Mitigation Training Manual, SAARC Disaster Management Center, L-18.

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PART-VI

VULNERABILITY EVALUATION FORZINDABAZAR GOVERNMENT PRIMARYSCHOOL, SYLHET, BANGLADESHBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: K .M. Khaleduzzaman Nayan
Istiak Ahmed Murad
Mehedi Ahmed Ansary

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1. General

The devastating social and economic impacts of recent earthquakes in urban areas haveresulted in an increased awareness of the potential seismic hazard and the corresponding
vulnerability of the built environment. Greater effort has been given to reasonably estimates,
predictions and mitigation of the risks associated with these potential losses.
This report is based on engineering judgment arrived at from the site visit, review of available
architectural drawings, and non-destructive test carried out at site. All possible efforts havebeen made to provide accurate and authoritative seismic vulnerability assessment of thebuilding in the given circumstances of information provided by the client and limited numberof field-tests. Therefore, neither BNUS nor any of its employees make any warranty,
expressed or implied, nor assumes any responsibility for the accuracy, completeness, orusefulness of the statement made in this report in case the starting information does not standcorrect.

2. Basic Information
Building Name
Locality
Estd.
Shape in Elevation
Plan view
Comments
Populations
Mass irregularity
Tall Unhooked Component
Height of Ground Floor
HazardZindabazar Government Primary School
Zindabazar, Sylhet
1999
RegularRectangular
One side of 2ndfloor is not constructed
Day:220/250, Night: 2
Presence
Light
10 ft
Earthquake, Fire

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3. Turkish Score
3.1.

Level 1 Score
Turkish Level 1 Score

Number of
Story
3
VSM
∑VSM X
VS

Zon
e
I
90

Zon
e
II
120

1
90

Zone
III

Soft
Story

Heavy
Overhang

Apparent Quality

Short
ColumnPoundin
g

140

-15

-10

-10

-5

-2

0

0

0

0

1

0

0

0

0

0

0

-10

0

0

Remarks

Where,PS = Performance Score
VSM=Vulnerability Score Modifiers

Topography
Effects

PS

0
80

Light

(Ref: Sucuglu et. al. 2003)

4. Building plan:

Figure 1 Building plan showing the location of tested column

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5. Seismic Load Calculation
5.1.
Lump Load Calculation Table
S.N.

Load calculation for 1st Lump
Item
WeightWeightFraction
Taken
0.5
0.5
1.0
0.5
0.5
1.0
1.0

KN
1
2
3
4
5
6
7
8

GF Column
1F column
Beam
GF wall
1F wallParapet Wallslab
Dead load

254.7
254.7
191.8
422.9
430.1
1.7
192.6
1748.5

1
2
3
4
5
6
7
8

Load calculation for 2nd Lump
Item
WeightFraction
KN
Taken
1F Column
254.7
0.5
2F column
127.3
0.5
Beam
191.8
1.0
1F wall
430.1
0.5
2F wall258.9
0.5
Parapet Wall
1.7
1.0
slab
192.6
1.0
Dead load
1457.1

S.N.

Load calculation for 3rdLump
Item
Weight

S.N.

KN
1
2
3
4
5
6
7
8

2F Column
3F column
Beam
2F wall
3F wallParapet Wall
Slab
Dead load

127.3
0.0
95.9
258.9
0.0
1.7
96.3
580.2

KN
127.3
127.3
191.8
211.5
215.0
1.7
192.6

Weight
KN
127.3
63.7
191.8
215.0
129.5
1.7
192.6

WeightFraction
Taken
1.0
0.5
1.0
0.5
0.5
1.0
1.0

KN
127.3
0.0
95.9
129.5
0.0
1.7
96.3

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6. Base Shear Calculation
No. of Stories = 3
Building Structural Type = RCStoreyHt (Level)012Each st.Ht(m)
3.05
3.05
3.05

Total StoreyHt (hn) =Ct =T=
S (Site Class) =Response reduction factor,R=
C=
Seismic Zone =Z=
Importance factor, I =Seismic Weight,W =Base Shear, V =Ft =V‐Ft =

9.15
0.073
0.38
2.0

Lump load(floor)
level
3
2
1

weightwi
(KN)

580.2
1457.1
1748.5

5.0
2.75
3
0.25
1
3785.8
520.5
0.00
520.5

Height hi
(m)

9.15
6.10
3.05
Sum=

Wihi
5308.98888.55332.819530.2

Ht. from
GL(m)
3.05
6.10
9.15
m
second
S4

KN
KN
KN
KN

Qi
141.4994
236.9105142.1372

Storey Shear
Vi( KN)141.499407
378.40992
520.547122@2 Storey Shear@1 Storey Shear@0 Storey Shear(Ref: Bangladesh National Building Code, 1993)

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7. Ferro-Scan Test
7.1.

2D Image Scan

In Figure 1 circle indicates the scanned column. The results of the test are shown below.

Column(Short side)

Column(Long side)

Inbuilt spacing of the stirr ups

Cross section of the column found from Ferroscan observation
Figure 2: Image Scan results for different structural components
7.2.

Line Scan

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Table 6: Transverse Reinforcement Requirements - Rectangular hoop check reinforcement
for Column (C1-1F)
Transverse Reinforcement Requirements - Rectangular hoop reinforcement for Column (C11F)xy
L0 ≥Column Dimension
11
21
Larger of C1 or C2
21 in
Column Height (Clear Span)
9.5ft
Clear Span/6
19 in
114
in
18"
18 in
Longitudinal Bar Used
Diameter , D
Max. Value between tie (in aplane), hx
End Strip Length
Middle Strip length

16
0.63

mm
in

6
19
76

in
in
in

Spacing Recommended for End Strip :S≤
0.25 X Smaller of C1
or C2
6 X Longitudinal Bar
Diameter, D
Sx = 4+[(14-hx|)/3]

2.7
5 in
3.7
5 in
66.
6 in

Spacing Recommended for Middle Strip
S
3.75
in
S≤
Existing Spacing
10in6"
6 X Longitudinal Bar
RemarkDiameter, D
Not Satisfied

6 in
3.7
5 in

S
Existing Spacing
Remark

2.75

in

5.5
Not
Satisfiedin

Clear Cover
Cover depth ≥Existing min Depth

38.1 mm
51 mm

RemarkSatisfied(Ref: American Concrete Institute, 2002)

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8. 8.Microtremor
Microtremor
Observations
Observations
FigureFigure3 3shows
showsindividual
individualtime
timehistories
historiesforforX,X,Y YandandZ Zcomponents
componentsforfora building.
a building.Figure
Figure4 4showsshowsFFT
FFTofofthose
thosetime
timehistories.
histories.Table
Table5 5presents
presentsthethepredominantpredominantfrequency
frequencyofofthethebuildings
buildings
inin
both
both
directions.
directions.
8

4

4

0

0

-8 -8
0 0
8 8

Velocity (µm/s)

Velocity (µm/s)

-4 -4

4

4

0

0

-4 -4
-8 -8
0 0
8 8
4

4

0

0

-4 -4
-8 -8
0 0

6 6
4 4
2 2
0 0
-2 -2
-4 -4
-6 -6
0 0
6 6
4 4
2 2
0 0
-2 -2
-4 -4
-6 -6
0 0
6 6
4 4
2 2
0 0
-2 -2
-4 -4
-6 -6
0 0

Y-direction
Y-direction
3

3

6

6

9

9

12 12

15 15

18 18

21 21

6

9

9

12 12

15 15

18 18

21 21

6

9

9

12 12

15 15

18 18

21 21

X-direction
X-direction
33

6

Velocity (µm/s)
Velocity (µm/s)

8Z-direction
Z-direction
3

3

6

Time
Time
(s) (s)Y-direction
Y-direction
3

3

6

6

9

9

12 12

15 15

18 18

21 21

6

6

9

9

12 12

15 15

18 18

21 21

6

6

9

9

12 12

15 15

18 18

21 21

X-direction
X-direction
3

3

Z-direction
Z-direction
3

3

Time
Time
(s) (s)FigureFigure
3:3:
Time
Time
History
History
ofof
soil
soil
and
and
buildingbuilding
0.200.20

10 10

1

Amplitude (μm)
Amplitude (μm)

H/V Ratio
H/V Ratio

0.150.15

Zindabazar
Zindabazar
GPS
GPS
ch-4
ch-4
(Y-direction)(Y-direction)
ch-5
ch-5
(X-direction)(X-direction)

0.100.10

10.050.05

Zindabazar
Zindabazar
PS PS
H/VH/V
Ratio
Ratio
CH1/CH3
CH1/CH3(15 (15
point
point
smoothing)smoothing)
CH2/CH3
CH2/CH3(15 (15
point
point
smoothing)smoothing)
0.1 0.1
0.1 0.1

110.000.00
10 10

Frquency
Frquency
(Hz)
(Hz)

5

5

10 10

15 15

20 20

Frequency
Frequency
(Hz)
(Hz)

FigureFigure
4:4:
Fourier
Fourier
Spectrum
Spectrum
ofof
soil
soil
and
and
buildingbuilding
AtAt
Zindabazar
Zindabazar
Govt.
Govt.
Primary
Primary
SchoolSchooldue
due
toto
thethelimitation
limitation
ofof
free
free
space,
space,
only
only
one
one
longitudinallongitudinal
array
array
asas
shown
shown
inin
FigureFigure
5 has
5 has
been
been
used
used
toto
estimate
estimateshear-wave
shear-wave
velocity.
velocity.

Fig
Fig
5:5:
Array
Array
formationformation
ofof
Zindabazar
Zindabazar
Govt.
Govt.
Primary
Primary
School.
School.

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Depth
0
to
1.46
1.46
to
13.54
13.54 to23.97
23.97 to30.01
30.01 to30.84
30.84 to60.96
60.96 to
88.96
88.96 to97.93

Vs (m/s)
195.31217.52293.07419.71435.26728.54933.71
971.48Average Vs
206
293
427
729
934
971

Figure 6: Shear wave velocity profile of Zindabazar High School (From long array).
9. ETABS MODEL

Computer model for the school buildings have been developed. In Figure 7, first mode of
ETABS model and periods for different modes for Zindabazar Government Primary School
have been shown. It can be seen that first mode from the computer model is 0.21 s which islonger than the actual period obtained from the microtremor observation (0.12 s). This is dueto the presence of different walls located in the actual building whereas in the model no walls
exist. Also we have run another model using cross bracing insist of wall which shows almost
the same period (0.13 s) for the model.

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Mode
1
2
3
4
5
6
7
8
9
10
11
12

Period0.205682
0.193634
0.160071
0.079141
0.073774
0.063269
0.049727
0.045960.044678
0.037971
0.037200.028681

Figure 7: First mode of ETABS model and periods for different modes for Zindabazar School
10. Photographs

Perspective View

Beam-Column Joint at GF

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195March 2012

Unhooked Component

Image Scan Survey

Side view of the structure

No Structure in circular portion

11. Conclusions and Recommendations
The columns of the buildings have inadequate reinforcement from the point of view ofearthquake loadings. The columns may be retrofitted either by using ferrocement column
jacketing or using FRP wrappings, which also need to be connected with the foundation of
the building.
The predominant period of the building is 0.12 sec (8 Hz) and the predominant period of thesoil is 0.50 sec (2 Hz), so there is no chance of resonance between the soil and building’s
vibration.

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PART-VII

GEOPHYSICAL INVESTIGATION AT MEGHNADHONAGODA IRRIGATION PROJECT (MDIP)USING GROUND PENETRATING RADAR MET
HOD

BANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Ram Krishna MazumderMehedi Ahmed Ansary

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1. INTRODUCTION
The project is located at 19 km North of Chandpur Town and 40 km South East of Dhaka
near the confluence of the Padma & the Meghna River. MDIP comprises the gross area of
17584 ha in Matlab Upazilla of Chandpur district is bounded on the North and the West by
the mighty Meghna and on the East and the South by the Dhonagoda River.
The Project is encircled by a 60.7 km of flood embankment completed in 1987. Aftercompletion of the embankment, severe seepage and boiling were observed along thecountryside of the embankment during floods. The embankment was breached during 1987
and 1988 floods causing severe damages. During the flood of 2004, a breach at Nandalalpur
occurred but no damage could be caused as the Bangladesh Water Development Board(BWDB) authorities repaired the breach quickly with the help of local people. Furthermore,sliding of the slope of embankments occurred on the countryside at about 60 places, seepage
problems developed at about 25 km length and boiling occurred at about 120 locations.
Figure 1 shows the embankment location and the affected points. The damages were severe
and it remained as a threat to future performance of the embankment during floods (Ansary etal., 2009).
To strengthening the embankment, currently BWDB authorities are injecting cement grouting
up to 5 m to 12 m below the surface. This paper presents the geophysical study which was
carried out to evaluate the performance of the embankment after the cement grouting wascompleted.

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Figure 1: Location of Meghna Dhonagoda Irrigation Project (MDIP) and erosion points(right)2. SUBSOIL INVESTIGATION
The field investigation at the embankment site consisted of drilling of boreholes, recording
density or stiffness characteristics of soil layers by carrying out Standard Penetration Tests(SPT), collection of sufficient numbers of disturbed and undisturbed tube samples. Also
portable seismograph was used to support the result obtained from SPT-N values. A total of
fifty six boreholes at eleven sites were drilled vertically at this site using wash boring
technique. The depth of boreholes below the ground surface varied from 10 m to 17 m. In
general five boreholes were drilled at each site across an embankment section.
2.1 Soil Sampling
Disturbed and undisturbed samples were collected from the boreholes. A split-spoon sampler
was used to obtain the disturbed samples in conjunction with the Standard Penetration Test.
Undisturbed samples were also retrieved from cohesive layers of the boreholes by pushingconventional 76 mm external diameter thin-walled Shelby tubes following the procedure
outlined in ASTM D1587. The locations of disturbed and undisturbed samples obtained fromthe boreholes are shown in the bore logs. The drilling of the fifty six boreholes at the projectsite, including collection of disturbed and undisturbed tube samples and performance ofStandard Penetration Test (SPT) were carried out by the Groundwater Hydrology Division of
BWDB.
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2.2 Soil Profile and Parameters across Embankment Alignment

A typical soil profile across the embankment is shown in Figure 2.
Particle size distribution was obtained following procedures mentioned in ASTM D422,
ASTM C136 and ASTM D1140 on samples from different boreholes and from different
depths. Particle size characteristics (d10, d15, d30, d50, d60, d85, percentage of non plastic fines,
Cu, Cc) are also presented tabular form. A summary of the amount of fine material (% finer
than #200 sieves i.e. 0.074 mm) in soils at different depths and in different locations tested(Ansary et al., 2009).
As has been mentioned earlier the subsoil consisted mostly of cohesionless soil andundisturbed samples could not be retrieved from the boreholes. It therefore became apparent
that shear strength parameters for this layer has to be interpreted from the field-N values
based on appropriate corrections and available empirical relations. Since the soil mineralogy
and grain characteristics could be different from those for which correlations is available, it
was decided to perform laboratory shear strength tests on samples reconstituted fromdisturbed samples at different densities in order to achieve possible highest and lowest rangeof strength parameter (Ansary et al., 2009)..

Figure 2: Typical Soil Profile across MDIP embankment (after Ansary et al., 2009)
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Direct shear tests were performed on reconstituted (near to field density as depicted fromSPT) disturbed soil samples from several location and depth to obtain the angle of internal
friction, and cohesion intercept, c of the sub-soil. The tests were performed on air dry soil.
Specimens were tested under three different normal stresses (45 kPa, 90 kPa, and 180 kPa)
and the strength parameters were determined from the failure envelope with various physicalproperties of the soil encountered. For the soils tested apparent cohesion, c was found to be
negligible and in the range of 0-16 kN/m. The angle of internal friction, the soils is in therange of 26.7 to 35.8. It can be seen that the range of void ratio (e) of the soil is 0.81 to 1.13
corresponding to porosities (n) of 0.45 to 0.53 respectively. The experimental results indicatethat the soils of the site are predominantly fine sand existing in a loose to medium dense state.
Constant head permeability test was carried out on specimen prepared by mixing soils fromdifferent boreholes and depths. For better representation of field conditions the flow of water
was allowed upward through the specimen by using a special constant head permeameter.
The boiling phenomenon was simulated for the field conditions using this apparatus. The
gradient was found to be lower than the theoretical value of 1.0. The permeability of the soil
was also estimated using Allen Hazens well known empirical formula of k=Cd210 using therange of C values of 100 to 150 (Lees and Chuaqui, 2004).
3. GPR PRINCIPLE
Geophysical exploration is a non-destructive, cost effective way to help locate andcharacterize features beneath the ground at many sites; GPR is one of the better techniques
for this search in the shallow subsurface. GPR is a near-surface geophysical technique thatcan provide high resolution images of the dielectric properties about 20 meters of the earth. It
is a very useful technique which employ the radio waves typically 16 to 2000 MHz frequency
range, to study structure and features buried in the ground, groundwater, subsurface faulting,and underground cavities (natural or man).
A trigger pulse is generated in the control unit at a normal repetition rate of about 100 kHz.
The trigger pulse is sent through the control cable to the transmitter electronics in the antenna.
In the transducer, each trigger pulse is transformed into a bipolar pulse with higher amplitude
than the trigger pulse. The pulse shape varies with the electronics and the antenna. The
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transmit pulse then propagates along the antenna and is radiated into the subsurface. The sizeof the antenna and electrical properties of the subsurface determine the frequency of the
propagating energy. In the subsurface, reflections occur at boundaries where there is adielectric contrast. The reflected portion of the signal travels back to the antenna. The
receiver in the antenna detects the returning signal and sends it back to the control unit. In thecontrol unit the signal is processed and displayed. The output of the graphic recorder or the
display on the video is a representation of the analog signal. Horizontal axis is distance along
the surface and vertical axis is two-way travel time of the radar pulse in nanoseconds (ns).
The signal amplitude determines the shade of grey on the paper or the color on the video
display.
The penetration depth is controlled by the GPR centre frequency, the electrical conductivity
and the attenuation of the subsurface deposits. In low-loss (i.e., resistive) deposits a low
centre frequency achieves a large penetration depth whereas a high centre frequency results ina lower penetration depth. Figure 3 shows the fundamental principal of GPR.

Figure 3: Fundamental principal of GPR
3.1 Modal propagation Theory
Modal propagation within a layer waveguide (of permittivity ε2) refers to lossless propagationand is especially dispersive when the layer thickness is close to or less than an in-situ
wavelength λ¸ (Arcone et al., 1998). In a two layer dielectric ground, lossless (nonleaky)modes occur when the confining layers (e.g. air above, for which ε1=1 and dry sand ε3 below)
have lower permittivities than the waveguide. In this case, a refraction will occur in the lower
layer at the critical angle, and dispersive modes will develop in the upper layer (Figure 2).
Depending on waveguide thickness d and ε2, higher order modes will develop which havephase fronts that propagate at speeds determined by discrete angles (measured from vertical)
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greater than the critical angle. The lowest order mode is always the strongest and mostimportant. The modes are determined by the modal equation (Budden, 1961) for eithertransverse electric (TE) or transverse magnetic (TM) waves, such that
R01R12 exp (i2k2d cosθ) = 1
Where R01 and R12 are the TE or TM reflection coefficients for the upper and lower layerinterfaces, respectively; k2=k0√ε2 is the propagation function for the refracting layer; and θ isthe modal angle of a particular frequency with respect to vertical. The quantity k0=2πf/c,
where f is frequency in Hz and c=30 cm/ns. The phase velocity of any particular frequency is
vph=c/√ε2sin θFor our case of parallel and facing antennas, we consider only TE waves. In this case allmodes have a minimal cutoff frequency where phase and group velocities equal the velocity
within an adjacent, refracting layer and a higher frequency at which minimum group velocity
occurs and energy is theoretically maximized. This latter phenomenon is known as the Airyphase (Grant and West, 1965). For given values of d and the permittivities of each layer,
several modes might exist, each of which can support all frequencies above their own
particular cutoff frequency.
Modal propagation losses are caused by transmission through the waveguide interfaces,
intrinsic attenuation within the medium itself, and geometric wavefront spreading. Interface
transmission losses and intrinsic attenuation, such as caused by conduction currents or
scattering, may be expressed through a complex, equivalent propagation angle θ + ίγ, forwhich the phase velocity then becomes
vph=c/√ε2sinθ coshγ

If ε1>ε2, then transmission leakage into the lower layer can produce values of γ near unity andattenuation rates can approach several tens of decibels per meter. For the case of ourrefractive waveguide, however, real energy loss occurs strictly through medium attenuation
mechanisms. Apparent energy loss at any particular frequency occurs from the dispersive
process itself.
For geometric spreading losses we consider that the amplitudes of modes, refractions, andany kind of lateral surface wave decay in proportion to r2, where r is the range separation

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between transmitter and receiver antennas. The range is both several wavelengths from thesource and much greater than the surface layer depth. We assume this range dependency
because very thin layers (in terms of γ) support nearly interfacial waves; interfacial waves
along homogeneous ground follow this behavior (Annan, 1973), and so do seismic refractions(O’Brien, 1967). Furthermore, the low-frequency wave velocity that developed in our surface
waveguide emulates refraction along the lower interface (Steven et. al., 2003)
4. FIELD TECHNICS
We used the Geophysical Survey Systems, Inc. (GSSI) model SIR-3000 control unit to set
radar parameters and record data to hard disk. We used separate transmitter and receiverresistively loaded antennas with bandwidths nominally centered near dominant frequencies of
100 MHz (GSSI model 3207).
4.1 Reflection profiling
In reflection profiling mode the antennas are kept at constant separation, while they are
moved along a profile (Figure 4). The electromagnetic pulses are transmitted at fixed time or
distance interval. The signal is recorded and displayed immediately on a computer screen as
GPR profiles, in which the vertical axis is two-way travel time in nanoseconds (ns) and thehorizontal axis is distance along the measured profile. The GPR data are either collectedalong a single profile or in a grid of profiles to obtain 2D or pseudo 3D information on
structures in the ground. The GPR data can also be acquired along lines so densely spacedthat the line spacing equals the stepwise along the line. This leads to a 3D data cube, wheredata also can be displayed as time or depth slices. Study was conducted using bi-static highrange profiling mode at distance interval according to Figure 4.

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Figure 4: Diagram of the transmit (Tx) and receive (Rx) antennas, airwave, waveguidedispersive modes, and refraction (Top). 100-MHz antennas with fiber optic circuitry to
trigger the receiver and antennas on the study line (bottom).
4.2 Common Depth Point
A common depth point dataset, CDP, is also called a velocity sounding, since the technique iscommonly used for signal velocity establishment. In CDP mode the antennae separation isincreased for each recording, while they are kept over a common midpoint (Figure 5a). A
CDP plot contains the direct wave transmitted in the air above the ground, the direct wave
transmitted in the ground and waves reflected from interfaces in the ground, where thedielectric properties change (Figure 5b). Refracted waves are seldom present in CDP
soundings. This is related to the fact that the electromagnetic wave velocity decreases withdepth together with increasing water content with depth.
5. RESULT ANALYSIS AND DISCUSSION
The test area of this study consisted of 75m along embankment foot and formed a 2-D sectionof underground stratum structure. Figure 6 displays the GPR section for distance on groundsurface, at 0 m~40m. From the Figures, a clear surface of reflection can be observed along
ground surface at underground depth of 6m, which shows different electrical properties ofstratum above and below the reflection interface. This reflection interface is almost parallel tothe ground level.

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Figure 5: Principles of GPR in CDP mode. a) In CDP mode a set of a transmitting antenna (Tx) and a
receiving antenna (Rx) are moved away from each other. The six first antenna positions are shownwith the path of the reflected wave from the first reflector. b) Sketch of the path of the most common
waves that is present in a CDP.

Groundwater table is present just below the 3m. Figure 6 implies that cement grouting has
been successfully injected about 6m below the surface. The reflection signal is also verystrong at 13m depth, which shows that the property of this layer differs a lot from the layers
above and below it. Figure 7 shows the wiggle shape. This figure indicates that the strong
signal of reflection below 6m depth is caused by rich content of underground water. Figure 8
shows the data collection in CDP mode. This data is used to estimate velocity of the soil withrespect to depth profile.

Figure 6: GPR Section at a distance of 0m~40m from ground surface (different color).

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Figure 7: GPR Section in wiggle mode at a distance of 0m~75m from ground surface

Figure 8: Multifold data are normally acquired or sorted in CDP gathers as represents in ray path form
(left). An optimum stacking velocity versus travel time can be extracted which permits coherent
summation of multifold survey data as well as a velocity depth function such as shown (right).

4. CONCLUSIONSIn this study, a 100 MHz frequency GPR antenna was used at Meghna Dhonagoda Irrigation
Project (MDIP) site to evaluate the remedial measures undertaken using cement grouting
technique at the river side in two affected embankment points. Common Depth Point (CDP)
and bi-static high range reflection profiling was used for data collection. The collected data
indicated that a water table did exist at a depth of 3m which was substantiated by thepiezometer located at the investigated points. Also the collected GPR data indicated that thesoil up to a depth of 6m might have improved by cement grouting technique.
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REFERENCES
Ansary, M. A., Yasin, S. J. M., Siddque, A., Abedin, M.Z. and Safiullah, A. M. M., (2009),
Soil Investigation of Meghna Dhonagoda Irrigation Project (MDIP) Embankment,
Proceedings of the Bangladesh Geotechnical Society’s Conference in 2009 in Dhaka,Bangladesh.
Annan, A. P., (1973), Radio interferometry depth sounding: Part I-Theoretical discussion,
Geophysics, Vol. 38, pp. 557–580.
Arcone, S. A., Lawson,D. E., Delaney,A. J., Strasser, J.C., and Strasser, J. D., (1998),
Ground-penetrating radar reflection profiling of ground water and bedrock in an area of
discontinuous permafrost. Geophysics, Vol 63, pp. 558-669.
ASTM (2006), American Society for Testing and Materials Standards, Vol. 04.08.
Budden, K. G., (1961), The wave-guide mode theory of wave propagation, Prentice-Hall, Inc.
BWDB (2007), Cross Section of Flood Embankment at Boring Points of MDIP, Memo.
No.PMO-JMREMP/ S-83/ 632, Project Director, JMREMP, Bangladesh Water Development
Board, July 2007.
Grant, F. S., and West, G. F., (1965), Interpretation theory in applied geophysics, McGrawHill Book Co.
Lees, D. & Chuqui, M. (2004), Soil Grouting: Means, Methods and Design, Grouting 2003,
pp. 1347-1359.
O’Brien, P. N. S., (1967), The use of amplitudes in seismic refraction survey, in Musgrave, A.
W., Ed., Seismic refraction prospecting: Soc. Expl. Geophys, pp. 85-118.
Steven, A. A., Paige, R. P. and Lanbo, L., (2003), Propagation of a ground penetrating radar(GPR) pulse in a thin-surface waveguide, Geophysics, Vol. 68, No. 6 P. 1922–1933.

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PART-VIII

TRAINING COURSES, SEMINARS AND
WORKSHOPS

BANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Mehedi Ahmed Ansary

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BNUS Participates in Earthquake Risk Mitigation Training
Earthquake Risk Mitigation training program organized by Centre of Excellence in Disaster
Mitigation & Management and Department of Earthquake Engineering, Indian Institute ofTechnology Roorkee (IITR). This two week training course conducted on Earthquake risk
mitigation from 6th-17th June 2011 at IIT Roorkee Greater Noida Extension Center, New Delhi,
India. This program is founded by SAARC Disaster Management Center (SDMC). A total of 27
participants representing SAARC member countries attended the training course. The main
objective of the training course was to impart training to the participants to assess the earthquake
hazard, vulnerability of buildings; mitigation measures to be undertaken for minimizing theearthquake effects; sharing knowledge on best practices in earthquake resistant design,
construction and mitigation measures. Research Engineer Ram Krishna Mazumder from
Bangladesh Network Office for Urban Safety (BNUS) has been participated in this training
course which focused on Earthquake Risk and Mitigation.
The training program was inaugurated by Padmashree Dr. A. S. Arya, Former National Seismic
Advisor, Government of India. Dr. S. C. Saxena, Director, IIT Roorkee welcomed theparticipants and Dr. O. P. Mishra Director/Officer-in-Charge SDMC elaborated history, genesis,
vision and mission of SDMC, various training programs conducted by the center in collaboration
with specialized agencies for the benefit of SAARC region.

Figure: Ram Krishna Mazumder from BNUS presenting country presentations on Bangladesh
The training programme was divided into 32 sessions covering Seismic Hazard and Vulnerability
Assessment; Secondary Seismic Hazards; Earthquake – Resistant Design and Construction and
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other related aspects of the Earthquake risk mitigation by several experts as resource persons
affiliated with IIT Roorkee, National Institute of Disaster Management (NIDM) India, SDMC,
Dhaka University Bangladesh, Taylor Devices India Pvt Ltd. The participants were also madefield visits to New Delhi, Agra for on-spot observation of the mitigation measures executed forminimizing the effects of earthquake. The facilities available to the trainees included hands-onexercises on aspects of earthquake risk mitigation. The session dedicated to country presentations
enabled the trainees to be in tune with the recent developments in the related fields in the region.
The trainees could also get a chance to evaluate themselves about the lessons learnt from thetraining through an evaluation test.
Dr. O. P. Mishra, Officer-in-charge, SDMC, distributed the certificates to the participants at theend of the training. In his valedictory speech he elaborated on the role played by SDMC in the
rapidly evolving field of disaster mitigation and management. Dr. D. K. Paul, coordinator of the
training presented the course completion report.

Figure: Participants and Program co-ordinators of Earthquake Risk Mitigation training at Roorkee,
India.

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Report on Training of Architect and Engineers on Earthquake Safe Construction

Jointly Organized by
Bangladesh Network Office for Urban Safety (BNUS), BUET
Institute of Architect Bangladesh (IAB)
National alliance for Risk Reduction and Response Initiatives (NARRI)Key Contents

Earthquake and Geotechnical Issues
Structural Issues regarding earthquake

No of Participants

27 (Twenty Seven)

Level of Participants B. Sc Engineer (Architecture)
Date
Venue

January 12-13, 2012
Hotel Rigs Inn, House 9, Road 23/1, Gulshan 1, Dhaka

Type of training

Non-residential

Facilitated by

Prof Dr. Mehedi Ahmed Ansary
Prof. Dr. Raquib Ahsan

Focus Area
Introduction to Key Issues Involved in Seismic Design
Characteristics of Earthquake important for building design and nature of seismic hazard
Selection and assessment of sites in earthquake hazard area
Basic ways in which earthquake-induced ground motion affects buildingWays in which fundamental architectural design decisions influence building seismic
performance
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Report on Training of Engineers on Earthquake Safe Construction

Jointly Organized by
Bangladesh Network Office for Urban Safety (BNUS), BUET
National alliance for Risk Reduction and Response Initiatives (NARRI)Key Contents

Earthquake and Geotechnical Issues
Structural Issues regarding earthquake

No of Participants

40

Level of Participants B. Sc Engineer
Date

December 29-31, 2011

Venue

Hotel Supreme, Sylhet

Type of training

Non-residential

Facilitated by

Prof Dr. Mehedi Ahmed Ansary
Prof. Dr. Raquib Ahsan
Engr. Mehedi Hasan

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Report on Training of Masons and Bar Binders on Earthquake Safe Construction

Jointly Organized by
Bangladesh Network Office for Urban Safety (BNUS), BUET
National alliance for Risk Reduction and Response Initiatives (NARRI)Key Contents
Structural Issues regarding earthquake
No of Participants

90

Level of Participants Masons and Bar Binders
Date

December, January and February

Venue

SylhetType of training

Non-residential

Facilitated by

Diploma Engr. Mintu Deb
Mason Matiar Rahman Sheikh

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SURVEY REPORT ON BURNT BUILDING AT OLD DHAKA
BNUS conducted a survey on two back to back fires in Ward 65 in Old Dhaka. The fires
occurred in 15th and 16th January 2012 in Islambag and Lalbag areas. The first incident
occurred in a plastic warehouse near the Eidgah ground in West Islambag at around 10:45
PM stated with gas stove. Eventually the fire became so devastating that it burnt three housesaround the warehouse. Fire service came after 30 minutes of fire occurrence and controlled
the fire at 12:30 AM. Total economic loss of this hazard is Tk. 0.3 Million.
The next day again at the same time another fire occurred in Shahid Nagar area at Lalbag
around 10:30 PM. In this case fire originated from a tin shed house. Around 100 shanties,
five shops and a printing press were caught by fire. Ten units of Fire Service and Civil
Defense (FSCD) from Lalbagh, Polashi, Sadarghat and the headquarters rushed to the spot
and managed to extinguish the blazes around 12:40 AM. A man was injured during fire.
Some photographs of the Islambag fire are as follow:

Burnt household objects

Burnt household objects

Burnt household objects

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2 feet wide staircase within the burnt building

Electric pole near the burnt building

Nearby building affected by fire

4 feet wide road in front of the burnt building

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INTERVIEW WITH OFFICIALS RELATED WITH STANDING ORDER ON
DISASTER
BNUS and ICUS jointly conducted a number of interviews with some officials related with
the Standing Order on Disaster (SoD) of Bangladesh from 4th January 2011 to 10th January
2011. They covered four government organizations including Disaster management Bureau(DMB), Comprehensive Disaster Management Programme (CDMP) Phase II, Fire Service
and Civil Defense Directorate (FSCD) and Cycle Preparedness Programme (CPP). An
international NGO Oxfam GB was also visited to know the gap between the planning andimplementation of SoD.

Figure 1: BNUS and ICUS Officials in front of BNUS Office in BUET, Dhaka

DMB is directly related with the planning, implementing and monitoring of SoD. Two
important personnels of DMB including the Director General Mr. Ahsan Zakir and theCommunication Media Specialist Mr. Syed Ashraf are interviewed. The government of
Bangladesh introduced its Standing Orders on Disaster (SoD) which specify the functions ofeach concerned Government Ministry, Division, Department and Agencies. The SoD is thecompilation of all the disaster codes in Bangladesh. Cyclone codes of 1070, drought codes of1979 and flood codes of 1985 are gathered together to form the first version of SoD in 1998
which was published in Bangla. In 1999, the SoD was translated into English and published.
In 2000 and 2002 Bangladesh experienced two big floods and some big earthquakes occurredin the neighboring countries of this country. So there was a need to revise the SoD toincorporate earthquake. The revision process stared in 2004. But it was running slowly until
Cyclone Sidr hit Bangladesh in 2007. The DMB formed a committee to manage the revision
process. The committee incorporated more functions for each organization related withdisaster management. Then they called a validation workshop and invited all the DM
organizations to participate in the workshop. After the validation made by the DM
organizations about their responsibilities in DM, the DMB committee made a number of216

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corrections and finalized the revised SoD. The revised SoD was published in 2010 in English
version. The DMB mainly involves in planning of the SoD rather than implementation.
FSCD and Oxfam GB involve directly in the implementation process. FSCD is a service
oriented emergency government organization under Ministry of Home Affairs of Bangladesh
which responds first and remains alert for 24 hours a day for the management of any kind offire and disaster. Its main mission is to provide service support to reduce mortality rate during
fire or any disaster, ensure first aid to the victim, provide ambulance service to the patient,organize training, demonstration and consultancy to prevent fire incident and arrange civil
defense measures. Director (Operation and Maintenance) Major Mohammad Mahbub, Staff
Officer Mr. Akram and Staff Officer Md. Abul Bashar of FSCD are interviewed to know theactivities of BFSCD in the implementation process of SoD. FSCD involves in fire fighting,rescue operation and preparedness of disaster. Recently they are organizing several training
program to instruct 62000 community volunteers throughout the country. They also conduct
fire drill, simulation drill and evacuation drill frequently specially in high rise buildings andslum.

Figure 2: Community Volunteer Training Program

Figure 3: Demonstration Training Program

Figure 4: Fire Drill Program

Figure 5: Simulation Drill Program

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Two officials of CPP including Assistant Director Mr. Hasanul Amin and Coordinator of
Signal Mr. Abdul Hamid were interviewed to know how CPP responses in case of any
cyclone after implementation of the SoD and the revised SoD. The CPP plays an importantrole in the dissemination of cyclone warning, evacuation, rescue, first aid and emergency
relief work including mobilization of people toward cyclone shelters through its volunteers in
the coastal districts. Currently, CPP has 203 paid employees, 49215 volunteers including
32810 male and 16405 female and 3281 Units covering 321 Unions, 37 Upazilas, 7 Zones
and 13 District. Due to global warming, CPP has increased its preparedness and awarenessbuilding functions for the community people living in the coastal area of Bangladesh. CPP
command area is expanded in more 5 Upazilas of Khulna, Bagerhat and Satkhira districts
with the financial help of Comprehensive Disaster Management Program (CDMP) Phase I.
Comprehensive Disaster Management Programme (CDMP) Phase II was also visited to know
its involvement in the planning and implementation of SoD. Disaster Response Management
Specialist Mr. Abdul Latif Khan, Communication Specialist Shaila Shahid and Project
Coordinator (Inter Ministerial) Officer Md. Eusuf Ali were interviewed.
Apart from these government organizations, some international NGOs are currently working
in DM sector. Six international NGOs viz. Action Aid, Concern Universal, Concern
Worldwide, Islamic Relief Worldwide, Oxfam GB and Bangladesh government haveestablished a consortium named National Alliance for Risk Reduction and Response
Initiatives (NARRI). Among these NGOs, Oxfam GB was visited and the ProgrammeManager Manish Kumar Agrawal was the key interviewee.

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