BNUS ANNUAL REPORT-2021

BANGLADESH
NETWORK OFFICE FORURBAN SAFETY
BUET, DHAKA, BANGLADESH
Edited By:

Mehedi Ahmed Ansaryy1.6

Bedrock UHS
Surface UHS using Vs30 based site coefficients
Surface UHS (Mean) based on nonlinear analysis
Surface UHS (Mean) based on equivalent-linear analysis

1.4

Spectral Acceleration (g)

1.2

1

0.8

0.6

0.4

0.2

0
0.02

0.03 0.04 0.05

0.07

0.1

0.2

0.3

0.4 0.5 0.6 0.7

1

2

3

4

Period (s)April 2022
1

CONTENTS
PART-I: SLOPE STABILITY ANALYSIS OF REFUGEE CAMPSTABILITY STRUCTURE USING BAMBOO AND SYNTHETIC
3
GEO-TEXTILE IN UKHIYA, COX'S BAZAR
PART-II: COMPARISON OF AXIAL LOAD CAPACITY OF PILESFROM THEORETICAL METHODS AND STATIC LOAD TESTS
30
PART-III: CAN RANA PLAZA HAPPEN AGAIN IN BANGLADESH 66
PART-IV: DYNAMIC RESPONSES OF REINFORCED SOIL MODEL
WALL ON SOFT CLAY FOUNDATION
87
PART-V: A STUDY ON RECENT EARTHQUAKES IN AND AROUNDBANGLADESH
117
PART-VI: SITE RESPONSE AND LIQUEFACTION SUSCEPTIBILITY
ESTIMATION OF A SITE IN NORTHERN PART OF BANGLADESH 128
PART-VII: SEISMIC SOIL-STRUCTURE-INTERACTION OF A TALLBUILDING ON PILE-RAFT FOUNDATION IN DHAKA CITY
151
PART-VIII: RECENT MAJOR FIRE OCCURRENCES IN
186
BANGLADESH
PART-IX: RECENT EARTHQUAKES AROUND BANGLADESH
191

2

PART-I

SLOPE STABILITY ANALYSIS OFREFUGEE CAMP STABILITY STRUCTURE
USING BAMBOO AND SYNTHETIC GEOTEXTILE IN UKHIYA, COX'S BAZARBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By:

Maiesha Tabassum
Mehedi Ahmed Ansary

3

1.1

GeneralThe south-eastern region of Bangladesh consists of many hilly tracks and coastal ridges
laying by the Bay of Bengal. The Cox's Bazar district of that zone has both the features
currently providing shelter for more than 1.1 million Rohingyas. Especially in the Ukhiya
Upazila of the district is confirmed to have at least 0.9 million Rohingyas. After that, the land
use of the zone has increased tremendously. For that, many retaining structures near the
Rohingya camps are built like dams, backfill protection, bamboo ring protection, etc. as the
lives of the people matter there as well as to facilitate their livelihood.
In the Palongkhali union, Ukhiya the earth retaining structures built were needed to beanalyzed for slope stability as different measures protect the structures and people to adifferent extent. Therefore, five samples were taken from the Balukhali Bazar area fromwhich one was from the block dam, two from the bridge dam, and the last two from theculvert dam with road protection.
So, Slope stability analysis of these measures taking samples from some of the locations by
doing both laboratory testing and software analysis for all the samples collected. With andwithout additional stability measures, the analysis is done checking the factor of safety
against stability. Thus, this chapter covers the geological site description, objective, andoutline of the research regarding the slope stability of protection measures of Ukhiya Upazila.

1.2

Geology of Study Area

Ukhiya Upazila of Cox's Bazar district with an area of 261.8 sq km is located between 21°08'
and 21°21' north latitudes and in between 92°03' and 92°12' east longitudes. Ramu Upazila
bounds it on the north, Teknaf Upazila on the south, the Arakan state of Myanmar, andNaikhongchhari Upazila on the east, the Bay of Bengal on the west.
The location of the collected samples was from Balukhali Bazar and Gundum in the
Kutupalong union of this Upazila. The region is hot and humid with some seasons oftemperate weather. The average rainfall of Ukhiya is 4285 mm with a maximum andminimum temperature of 32.8° C. and 16.1° C respectively on an annual basis. The only river
flowing through the Upazila is the Rejur canal flowing to the Bay of Bengal.
4

Most of the bedrocks of Cox's Bazar were formed in the Pleistocene and Pliocene age withDihing and Dupi Tila formation. Balukhali Bazar area is formed explicitly by Boka Bil
formation and Bhubon formation of the Neocene and Miocene age, respectively.
Dakhin Nhila structure lies under Teknaf Upazila near Ukhiya of Cox's Bazar district andbounded by latitude 20°52' to 21°07'N and longitude 92°08' to 92°18'E and is situated at theextreme southeast of Bangladesh territory. Hills and valleys striking N I7'W and S 17'E
represent it. The maximum elevation is about 266m above mean sea level. The northern pitch
is defined by low relief due to the saddle separating from the Inani anticline, whereas thesouthern slope abruptly merges with the bare land.
Dakhin Nhila anticline is an elongated, asymmetric, and box-like structure. It is acomplicated structure due to the presence of longitudinal and transverse faults. The oldest
exposed rock is Upper Bhuban that is about 545m thick. The exposed rock formations fromolder to younger are Upper Bhuban, Boka Bil, Topham, and Dupi Tila. Mostly argillaceous
sediments with little coverage of arenaceous deposits characterize the structure. The axis of
the frame runs along the NNW-SSE direction. Some portion of the western flank and younger
formation of the southern pitch has been eroded due to the Bay of Bengal.
This location stands nearly 3 to 4 meters above sea level. The dams from which the samples
were collected were more likely to have sandy clay to clay in most of the cases with one
sandy soil deposit for sample number four.
1.3

The objective of the research

The main objective of the research is as follows:a)

To determine the sub-soil profile of all five samples by determining the types andparameters of the representatives of the location by laboratory procedures.
b)

To discuss and select appropriate slope protection measures for the establishedstructures of the location.
c)

To analyze earth structures without any protection measures and decide if any

protection measure is needed5d)To utilize bamboo anti-slide pile for protective measure and check for the stability ofslopese)To study synthetic Geotextile as an alternate protective technique and compare

the two approaches against slope protection.

Figure 1.1: Geological Map of Ukhiya Upazilla
1.4

Scope of the Research

In this research, soil samples from five different locations of Ukhiya Upazila are collected
and analyzed for checking slope stability against the failure of any kind. The software,
GEO5, is used to measure the factor of safety against failure in only Bishop's simplified
method of analysis. A specific slip circle is provided for all the models with different soil
parameters as well as earth structure dimensions in the optimization model.
As there were no in-situ soil tests or boring done to get some parameters to the exact, theparameters found using laboratory procedures, might be distorted to some extent. Moreover,as only five samples were collected, also having limitations with slope protection techniques,
the actual proper treatment measure may not have been found out. Following other methods
6

for slope stability analysis also might have changed some outcomes for having different

principles.
Figure 1.2: Location of Sample Collection Map

Figure 1.3: Slope protection measure in the locations of Ukhiya (a)close-up view (b)full view7

2.1 Methodology
The slope stability analysis of the five soil samples collected from Ukhia Upazila is to be firsttested on the laboratory for gaining the parameters needed for the software analysis were
implying these data slope stability analysis is done. Keeping that in mind, as the soils were
disturbed and no bore-logs were collected, tests such as grain size analysis, specific gravity
test, standard proctor test and finally consolidated direct shear test are done for getting thevalue of dry density, saturated dry density, confined shear stress and the angle of internal
friction. After getting all these values and inputting them on slope stability software, GEO5
for further investigation slope stability analysis is done using Bishop's simplified method ofslices. The research was done considering different slopes, tread height and width and extra
pile height. The slip surface in the GEO5 software was taken to be circular not the polygonal
one following the Bishop's method of analysis. No groundwater table criteria or change inwater level height was considered for the examination. Taking the allowable Factor of Factorof safety 2.5 to 3 for both cases of bamboo and Geotextile, slope stability analysis iscompleted. However, in this chapter, only the laboratory testings are defined and discussed,
and the GEO5 analysis is described in the following chapter.

2.2 Laboratory Tests
For the collection of undisturbed samples from the site, the complete set of laboratory
investigation consisted of the following test procedures on all the samples:Grain size analysis


Sieve analysis

Hydrometer analysis

Specific Gravity TestStandard Proctor TestDirect Shear Test

These tests are discussed below after which the data collected from these tests are provided in
the upcoming sub-sections.

83.3.1 Grain Size Analysis
Grain size analysis provides the grain size distribution as the distribution of different grain
sizes affects the engineering properties of the soil. Sieve analysis provides the distribution ofcoarser particles, and hydrometer analysis significantly shows the distribution of finerparticles of the earth.
Figure 3.1: Opening of different sieves to be used
les was conducted to determine the distribution of larger-sized particles (usually retained on#200 sieve). The equipment required for the tests are #4, #8, #16, #30, #50, #100, #200 sieve;
Pan;

Lead;

Brush;

Container;Spoon;

Bowel; Balance and Sieve shaker.
3.3.1.2 Hydrometer Analysis
Hydrometer analysis is required for thedetermination of the grain size distributionof the more delicate portion of the soil thatpasses#200

sieve.

ASTM

152H

hydrometers are calibrated such that wheninserted in a soil-water suspension thereading on the hydrometer stem indicatesgrams of soil that are in 1000cc suspension
Figure 3.2: Hydrometer dipped in control cylinder
9
withsoaked specimen beside itcentre of the bulb following the Stokes law. The scale of the 152H reads -5 to +60 g/L
graduated/marked. The equipment needed is 152H Hydrometer; Hydrometer jar; Measuringcylinder / graduated jar; Car; Wash bottle; Stopwatch; Mechanical mixture & mixing pot;
Balance; Thermometer and Water bath.

3.3.2. Specific Gravity
As neither of the five soil samples
was highly organic, this test was
performed

todeterminetheSpecific Gravity of the soil passing
4.75 mm sieve by using a water
pycnometer. It is used in the phaserelationship and for determining
soil density. The code followed to
conduct the test was ASTM D
854-02: Standard Test Methods forSpecific Gravity of Soil Solids by
Water Pycnometer. The equipment

Figure 3.3: Apparatus used for determining specificneeded is Volumetric flask; Wash bottle; Funnel; Pipette; Can; Balance Burner/gas stove;
Vacuum pump; Oven and Thermometer.

3.3.3 Standard Proctor Test
Mechanical compaction is one of the most common and costeffective means of stabilizing soils. So, to determine the properamount of mixing water to use when compacting the earth in
the field and the resulting degree of denseness which can be
expected from compaction at this optimum water content.
Design specifications usually state the required density and
Figure 3.4: Apparatus used for Standard Proctor
10optimum water content which can improve strength, stiffness, resistance to shrinkage andimperviousness of the soil. Following the standard proctor test of compaction, with thespecification of ASTM D698, this test is only applicable for soils that have 30% or less bymass of particles retained on the 19.0 mm sieve. To complete the test, following instruments
are needed are Moisture sprayer; No 4 sieve; Rubber tripped pestle; Scoop; Straight edge andknife; Drying oven; Standard Proctor test mould and Standard Proctor Test hammer (5.5 lbs.)

3.3.4 Direct Shear Test
Following the standard, ASTM D-3080-03-Direct Shear Test of Soils Under Consolidated
Drained Conditions, a direct shear test of all the five samples is conducted. This test is
performed to determine the consolidated-drained shear strength of silty and sandy soil. The
shear strength of the ground is one of the most significant engineering properties of the earth
as it is necessary whenever a structure is dependent on the soil's shearing resistance. The
shear strength is required for engineering practical problems like determining the stability ofslopes or cuts, calculating the pressure exerted by the ground on a retaining wall and finding
the bearing capacity for foundations.
The direct shear test is one of the oldest strength tests for soils. In this laboratory, a direct
shear device will be used to determine the shear strength of a cohesionless soil (i.e., angle ofinternal friction (Φ)). From the plot of the shear stress versus the horizontal displacement, themaximum shear stress is obtained for a specific vertical confining stress. After the experimentis run several times for various vertical-confining stresses, a plot of the maximum shear
stresses versus the vertical (normal) confining stresses for each of the tests is produced. Fromthe plot, a straight-line approximation of the Mohr-Coulomb failure envelope curve can be
drawn, f may be determined, and, for cohesionless soils (c = 0), the shear strength can becomputed from the following equation:
S =σtanΦ

Where, S = Shear strengthσ = Shear stressΦ = Angle of internal friction

11

The necessary equipment for thetest is Direct Shear Device; Loadand deformation dial gauges;
Shear box; Balance; Verticalload;

Pressureplate;

Porousplate; Screw; Filter paper; Scale
Dish Stopwatch and Probe ring.

Figure 3.5: Different parts of a shear box
3.3.4.1 Sample preparation:For cohesive soil: Sample 1,2,3 and 5 were tested out to be cohesive soil with relative
higher amount of clay than that of sand. For preparing the sample, the new example isto be ready using optimum water content calculated from the standard proctor test
graphs. At first, nearly 10 lbs. of the model is to be taken on a tray, and optimum
water is added and mixed with the soil. Then the soil is to be set into three layers in astandard proctor mould to the top, and 25 blows in each layer are given. The soil isthen extruded out and cut into three equal cylinders to fill in the probe rings. Then
using three individual probing ring soil samples are moulded, and thus soil samples
for the shear test are prepared. In addition to that, the weight of the individual probe
rings and ring with soil are also calculated.

For cohesionless soil: Sample 4 was found out to be cohesionless as a higher numberof sandy particles was found during the grain size analysis. For preparing the sample,
a certain amount of soil sample is to be taken for filling three probing rings. Then
mixing with ample amount of water with hand and filling the ring with 5-7 blows of
wooden tamper in three layers to the top of the probing ring, cohesionless soil
samples are made.

12

3.3.4.2 Apparatus setup:
At first, the soil sample for testing was transferred into the shear box. For this, the bottom
plate and one porous plate was inserted into the shear box after which the upper frame wasinserted with the alignment pins. The placing one filter paper, the soil sample was extruded
from the ring to the box with the help of a wooden tamper. Then another filter paper wasplaced with the remaining porous plate on top, and the pressure plate was placed on top of
everything. In the next step, after placing the shear box in the shear device, all the gages were
adjusted and set to zero except the normal displacement dial gauge. Also, the hollow space inthe box was filled with water. The initial dial reading of normal displacement dial gauge wasrecorded. Then a normal vertical load of 10 kg was applied, and the alignment pins were
removed.

3.4 Data Collection
After the setup of all the tests, appropriate data need is needed to be collected for further
analysis in GEO5 software. The procedure and collected data re provided in the following
subsections
3.4.1 Sieve Analysis Data
After writing down the weight of each sieve along with the bottom pan, the weight of thegiven oven-dried soil sample is recorded. Cleaning all sieves and assembling them in theascending order of sieve numbers the soil sample is placed on the top sieve, and the cap isplaced on top. This sieve stack is placed in the mechanical sieve shaker then the sieve stack isshaken for 10-15 minutes. Then removing the stack, each sieve with its retained soil isweighed. The same is also done for the bottom pan with its refined soil. Placing the values inthe sieve analysis chart following gradation chart informed for all five samples.

13

.4.2 Hydrometer Analysis Data
For conducting the test, precisely 50 g of oven-dry, well-pulverized soil was measured. The
weight was recorded in the datasheet. The ground was placed in the mixing pot. 125 ml of
4% NaPO3 (sodium hexa meta phosphate) was mixed in the solution. Then the mixture wastransferred to a mixing pot, and tap water was added until the cup was two-thirds full. It was
mixed for 3 to 5 minutes in the mixing device. All the contents of the mixer pot weretransferred to the hydrometer jar being very careful not to lose any material. Tap water was
toFigure 3.6: Gradation chart of the samples obtained from Sieve Analysis

addedfill thecylinder to the 1000-ml mark. Also, the graduated cylinder was filled (later referred to aswater jar) to about 1000 ml mark with tap water. The palm of the left hand was put on the
open end of the hydrometer jar, and the soil water suspension was mixed by quickly
overturning the pot up and down several times. Then the hydrometer jar was placed on thetable. Care was taken so that the jar was not disturbed by any vibration. Immediately after
placing the hydrometer jar on the table, the Hydrometer was inserted in the soil watersuspension, the timer was started, and the readings were taken at elapsed times of 0.25, 0.5, 1,
and 2 minutes. After 2 minutes, the Hydrometer was removed from the soil water suspension,and it was placed in the water jar.

14

The suspension was remixed in the hydrometer jar. If the last set of four readings (at anelapsed time of 0.25, 0.5, 1 and 2 minutes) were almost the same as the previous set, thenthese readings were recorded in continue with next step otherwise previous steps wererepeated. Taking hydrometer readings were continued at elapsed times of 4, 8, 15, 30, 60
min., and 2, 4, 8, 16, and 24 hours. Between hydrometer readings, the Hydrometer was stored
in the water jar. The internal diameter of the hydrometer jar was measured after which thevolume of the hydrometer bulb was measured. Similar graph of per cent finer vs pa Figure

3.7: Gradation chart of the samples obtained from Hydrometer rticle size was plotted for all
the samples.
So, a final percentage of sand, silt and clay can be derived and attached below:
Sample Number

Amount of Sand (%)

Amount of Silt (%)

Amount of Clay (%)

01

1

81

18

02

41

53

6

03

41

46

13

04

89

10

1

05

45

47

8

15

3.4.3 Specific Gravity Test Data
Table 3.1: Percentage of sand, silt and clay for all samples from grain size analysis
Forcommencing the test, the volumetric flask was weighed in a dry state. The weight ofthe empty and clean pycnometer was determined and recorded. By measuring 50
gm of the oven‐dry soil sample, it was placed in the pycnometer, and about 2/3 ofpycnometer was filled with tap water. Then the model was kept soaking for 10
minutes. After heating the sample until the water in the soil‐water mixture starting
to boil, the vacuum was applied to the contents for 10 minutes during boiling ofwater in the mix to remove the entrapped air. Then stopping the vacuum andcarefully drawing the line from pycnometer, the pycnometer was filled with water tothe mark and kept for a day to bring it to the room temperature. On the following
day, the weight of the pycnometer filled with water and soil sample was recorded.
The emptying the pycnometer and filling with water to the mark, the weight of
pycnometer with water was determined. With a thermometer, the room temperature
was recorded as well. The using appropriate equation specific Gravity for eachsample was determined.
The value of the Specific Gravity of the five samples are as below:
Specific Gravity

Specific Gravity

Sample No.

(at room temperature)(at 20o C)

01

2.646

2.640

02

2.762

2.756

03

2.551

2.545

04

2.716

2.710

05

2.762

2.756

16

3.4.4 Standard Proctor Test Data
For starting the test, approximately 10lbs of the soil sample is taken, which is then pulverized
and ran through #4 sieve. After that, the weight of both the soil sample and compaction
mould with base (without the collar) are taken separately. Then computing the initial amountof water to be added, the water is measured out, added to the soil and mixed thoroughly withthe earth.
Therefore, assembling the compaction mould to the base, some soil is placed into the mould
and the ground is compacted in three layers with 25 blows in each layer with every fall heightof 12 inches. It was ensured that the drops were to be applied at a uniform rate not exceeding
1.5 seconds per drop. For filling the cylinder, the last compacted layer was made to extend
slightly above the collar joint. Then the collar was carefully removed, and the compacted soil
was trimmed to the top of the mould. After that, the mould with base and dirt was weighed
and extruding the sample, and soil moisture content samples were taken from top and bottomof the extruded compacted sample from which wet density and dry density of the soil is to befound. Then by plotting the graph of dry density vs moisture content, optimum moisture
content can be figured out.

Average Moisture Content vs. Dry Density Graph

Dry Ddensity

1.800
1.750

Sample 05

1.700

Sample 04

1.650

Sample 03
1.600
1.550
0.050

Sample 02
Sample 01
0.100

0.150

0.200

0.250

Average moisture content
The graphs from the standard proctor test of dry density vs water content of the five samples
are given below:According to these graphs, the optimum water content for each sample iscalculated as below:

17Sample No.

Optimum moisture content (%)

01

19.38

02

19.56

03

20.16

04

19.41

05

18.4

3.4.5 Direct Shear Test
An average vertical load of 10 kg was applied, and the alignment pins were removed.
After that, the soil was kept being fully consolidated, and we had to wait until thechange in standard displacement dial was unnoticeable. The time can take 30 mins to 2
hours depending on soil and load. When the typical displacement gauge dial wasconstant, motor speed was set for the required strain rate, and the machine was started.
Instantly starting the stopwatch, the shear load reading, regular displacement dialreading and horizontal displacement dial reading were recorded at 0, 0.25, 0.5, 0.75, 1,
1.25, 1.5, 1.75, 2 etc. minutes. A similar procedure was done for a vertical load of 20 kgs
and 40 kgs. For obtaining the result shear stress vs, shear displacement
graph is to be plotted from which peak shear stress for each case is to be taken, after
which shear stress vs typical stress graph is plotted from which values of cohesion, c and18

Shear Stress vs Shear Displacement
90
80

Shear stress kpa

70
60

40 kg
20 kg
10 kg

50
40
30
20
10
0
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Shear displacement x10^‐3 m

0.9

1

(e)

Figure 3.10: Shear Stress vs. Shear Displacement curve for (a)Sample 01 (b)Sample 02(c)Sample 03 (d)Sample 04 (e)Sample 05
The shear stress vs normal stress values for finding c and Φ values are as follows:

The final data obtained from this laboratory analysis for further software analysis is provided
below:
Sample No.

C
(kPa)

Φ
(degree)Density(KN/m3)

01
02
03
04
05

15
10.5
2.73
0
4.44

20.2
21.1
26.9
31
28.9

19.17
19.24
18.93
19.82
18.39

Saturated
Density(KN/m3)
19.42
19.67
19.95
20.31
18.66

Table 3.4: Parameters obtained from the direct shear test graphs
These data are directly put into the parameter values of the five soil samples for slope
stability analysis on GEO5 software using Bishop's simplified method.

19

Analysis and Discussion
The stability of any slope with or without stabilizing techniques is needed to be analyzed
using manual calculation or specific software. In this chapter, for our analysis of slopes withsynthetic geotextile and bamboo anti-slide pile, a software named GEO5 is going to be used.
It is a versatile yet straightforward software for geotechnical issues among which one of theprominent ones is slope stability analysis. In this software, slope with or without retaining
structures can be analyzed with various loads and groundwater table location after inputting
the soil data. So, in this chapter, the factor of safety of the slope is calculated using Bishop's
method and further discussed to check the stability.

4.2 Sub‐soil Profile
For our research, five samples were collected from Ukhia Upazila in Cox's Bazar district
from different types of dams already constructed. As no field data were collected, in theprevious chapter, all the data needed for further analysis were measured in a different
laboratory procedure. From those, the following information of the soil is gathered:

Sample
No.
01

02

03

04

05

Soil
SampleType
Clay SoilTop

SoilParticle
Percentage
Sand= 1%
Silt=81%
Clay=18%
Soft Clay Sand= 41%
Silt=53%
Clay=6%
Sandy Clay Sand= 41%
Silt=46%
Clay=13%
Sandy Soil Sand= 89%
Silt=10%
Clay=1%
Sandy Clay Sand= 45%
Silt=47%
Clay=8%C(kPa)

Φ(degree)Density(KN/m3)

15

20.2

19.17

Saturated
Density(KN/m3)
19.42

10.5

21.1

19.24

19.67

2.73

26.9

18.93

19.95

0

31

19.82

20.31

4.44

28.9

18.39

18.66

20

4.3 Factor of Safety Calculation
The factor of safety of the slopes are to be measured with Geotextile is the first phase as analternative of bamboo and further with bamboo anti-slide piles which were used in thelocation of dams from which the samples were collected. Changing the parameters for bothtechniques, analysis of the slopes was done assuming circular slip for both measures ofBishop's method in GEO5.
The factor of safety of the dams, assuming different height with three different slopes foreach height with no protective measure is given below:

SampleNo

Slope Ht.
(m)

FS without any protection
1V:1H

1.5V:1H

2V:1H

Table 4.1: Sub-soil parameters of the Soil Samples

1

2

3

4

5

10

1.18

1.07

1.13

12

1.08

0.96

1.03

14

1.45

1.01

0.9

10

1.03

0.87

0.89

12

0.95

0.8

0.81

14

1.34

0.89

0.73

10

0.77

0.56

0.48

12

0.74

0.54

0.46

14

0.92

0.71

0.45

10

0.12

0.12

0.12

12

0.12

0.12

0.12

14

0.13

0.12

0.12

10

0.92

0.7

1.33

12

0.88

0.84

0.58

14

1.35

1.18

0.84

Table 4.2: Factor of safety chart using all five samples with different
slope and slope height21

4.3.1 Factor of Safety check using Geo-textile
The kind of Geotextile used for the analysis was Monofilament polypropylene geotextile,which is a prominent kind of synthetic Geotextile available in Bangladesh. As its ultimate
tensile strength varies from 16 to 70 kN/m2, taking 16, 24 and 32 kN/m2 as the tensile
strength of that with a change in the slope of 1:1, 1:1.5 and 1:2 for heights of 10, 12 and 14
meters, slope stability analysis was done with no presence of excess load or groundwaterlevel.

Dam height 10 m
Tensilestrength(KN/m) 1H:1V 1H:1.5V 1H:2V
2.08

2.24

2.54

24

2.44

2.73

3.09

32

2.78

3.19

3.92

4.5

Factor of Safety

16

FoS vs. Tensile Strength of Geotextile(for 10 m Height of Sample 01)
4
3.5

1H:1V

3

1H:1.5V

2.5

1H:2V

2
1.5
1
16

24

32

Tensile Strength(Kn/m)

16

1.93

2.07

2.32

24

2.29

2.56

2.87

32

2.64

3.01

3.38

3.5

Factor of Safety

Tensilestrength(KN/m) 1H:1V 1H:1.5V 1H:2VFoS vs. Tensile Strength of Geotextile(for 10 m Height of Sample 02)
3
1H:1V

2.5

1H:1.5V
2

1H:2V

1.5
1
16

24

Tensile Strength(Kn/m)

32

22

FoS vs. Tensile Strength of Geotextile(for 10 m Height of Sample 03)
3

Factor of Safety

2.5
1H:1V

2

1H:1.5V
1.5

1H:2V

1
0.5
0
16

24

Tensile Strength(Kn/m)

32

FoS vs. Tensile Strength of Geotextile(for 10 m Height of Sample 04)
1.2

Factor of Safety

1
0.8

1H:1V

0.6

1H:1.5V

0.4

1H:2V

0.2
0
16

24

32

Tensile Strength(Kn/m)FoS vs. Tensile Strength of Geotextile(for 10 m Height of Sample 05)
3.5

Factor of Safety

3
2.5

1H:1V

2

1H:1.5V

1.5

1H:2V

1
0.5
0
16

24

32

Tensile Strength(Kn/m)

23

Dam Height 12 m
FoSvs.
vs.Tensile
TensileStrength
Strength ofofGeotextile
Geotextile
FoS(for1212m
mHeight
Heightof
ofSample
Sample01)
04)(forFactorofofSafety
SafetyFactor

2.5
3.5
23
1.5
2.5

1H:1V
1H:1V
1H:1.5V
1H:1.5V
1H:2V
1H:2V

1
2
0.5
1.5
0

FactorSafetyFactorof of
Safety

1

3.5
3
3
2.5

16

24

32

16

Tensile Strength(Kn/m)
24
Tensile Strength(Kn/m)

32

FoS vs. Tensile Strength of Geotextile
FoS vs. Tensile Strength of Geotextile(for 12 m Height of Sample 02)(for 12 m Height of Sample 05)
1H:1V

2.52

1H:1V
1H:1.5V2
1.5

1H:1.5V
1H:2V

1.51

1H:2V

0.5
1
0

16
16

24

32

Tensile Strength(Kn/m)
2432
Tensile Strength(Kn/m)FoS vs. Tensile Strength of Geotextile(for 12 m Height of Sample 03)
3.5

Factor of Safety

3
2.5

1H:1V

2

1H:1.5V

1.5

1H:2V

1
0.5
0
16

24

32

Tensile Strength(Kn/m)

24

Dam Height 14
FoS vs. Tensile Strength of Geotextile(for 14 m Height of Sample 02)
Factor of Safety

3
2.5

1H:1V
1H:1.5V

2

1H:2V

1.5
1
16

24

32

Tensile Strength(Kn/m)

Factor
Factor ofof Safety
Safety3.5

FoS vs.
vs. Tensile
Tensile Strength
Strength ofof Geotextile
Geotextile
FoS(for 1414 m
m Height
Height ofof Sample
Sample 03)
01)
(for

3
3
2.5
2.5 2

1H:1V

21.5
1
1.5
0.5
1 0

1H:1.5V
1H:1V
1H:2V
1H:1.5V
1H:2V
1616

24
24

Tensile Strength(Kn/m)
Tensile Strength(Kn/m)

32
32

FoS vs. Tensile Strength of Geotextile(for 14 m Height of Sample 04)
2.6

Factor of Safety

2.4
2.2
2

1H:1V

1.8

1H:1.5V

1.6

1H:2V

1.4
1.2
1
16

24

32

Tensile Strength(Kn/m)25

FoS vs. Tensile Strength of Geotextile(for 14 m Height of Sample 05)
3.5

Factor of Safety

3
2.5

1H:1V

2

1H:1.5V

1.5

1H:2V

1
0.5
0
16

24

32

Tensile Strength(Kn/m)

Figure 4.1: F.S vs Tensile strength graph using geotextile for different dam height and slope

4.3.2 Factor of Safety check using Bamboo as Anti‐slide pile
As for the focus of our research, bamboo used as an anti-slide pile for slope stabilization isdone in this sub-section. Using Arundinaria gigantia bamboo with variations of length of 1 m
to 4 m with 1 m increment and spacing of 10 cm to 30 cm with 10 cm increment, with theheight variation of 10m, 12m and 14 m, each with the change in the slope of 1:1, 1:1.5 and
1:2, slope stability analysis is done using Bishop's simplified method of accounting. No
surcharge load or groundwater table criteria were taken into consideration.

Damn Height 10 m
For slope 1V:1H
Factor of Safety Vs. Length of Bamboo(Sample 01)

Factor of Safety



10
8
6
4

10 cm

2

20 cm

0

30 cm
1

2

3

4

Length of Bamboo Piles(m)26Factor of Safety Vs. Length of Bamboo(Sample 03)

Factor of Safety

10
8
6
4

10 cm

2

20 cm
30 cm

0
1

2

3

4

Length of Bamboo Piles(m)Factor of Safety Vs. Length of Bamboo(Sample 04)

Factor of Safety

10
8
6
10 cm

4

20 cm

2

30 cm

0
1

2

3

4

Length of Bamboo Piles(m)27Factor of Safety Vs. Length of Bamboo(Sample 05)

Factor of Safety

10

6
10 cm

4

20 cm

2

30 cm

0
1

2

3

4

Length of Bamboo Piles(m)For slope 1.5V:1H
Factor of Safety Vs. Length of Bamboo(Sample 01)

Factor of Safety

20
15
10

10 cm
20 cm

5

30 cm
0
1

2

3

4

Length of Bamboo Piles(m)Factor of Safety Vs. Length of Bamboo(Sample 02)

Factor of Safety








8

20
15
10

10 cm

5

20 cm
30 cm

0
1

2

3

4

Length of Bamboo Piles(m)28

4.4 Concluding Remarks
From the graphs of the factor of safety for both geotextile and bamboo anti-slide pile, achange of pattern of the trendline is seen for the provided parameters. From the laboratory
tests and slope stability analysis having software effectiveness of the two slope stability
measures were compared. The main concluding remarks of the study are:a) Five soil samples were collected from the Ukhiya Upazila, Cox's Bazar with no fieldtest conducted and provide for laboratory analysis from which it results that four ofthem are silty clay with one having high sand properties.
b) The leading cause of slope failure of the constructed structure is found to be landslideas the location is in a hilly area with an adjacent coastal zone with a high amount ofsalinity.
c) The residing location was provided with bamboo anti-slide piles in the form of
symmetric stairs for local availability of bamboo.
d) Synthetic Geotextile with comparison to bamboo anti-slide piles as is regarded as analternative to bamboo for using as a slope stability technique.
e) Analyzing the chart trends of both bamboo and synthetic Geotextile, it is visible thatthe charts show an upward trend for varying parameters for both the cases. However,some variations are seen for two samples for having different soil properties than thatof others in all cases.
f) Bamboo anti-slide piles show a higher factor of safety comparing with synthetic
Geotextile for all the five samples.
g) According to the cost and availability of material, the bamboo used initially as theanti-slide pile will always have a higher chance compared to the alternative ofsynthetic Geotextile.

29

PART-IICOMPARISON OF AXIAL LOADCAPACITY OF PILES FROMTHEORETICAL METHODS AND STATICLOAD TESTSBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Sandip Dey
Mehedi Ahmed Ansary30

1.1 Background
Piles are structural members that transmit the superstructure loads to deep soil layers. They
are preferred to be used as a foundation material when the shallow foundation is not practicalto use it. Piles and pile foundations have been in use since prehistoric times. The Roman
wooden piles are a classic example of this. Today piles can be made of wood, concrete, or
steel.
Soft soil is very common in many parts of Bangladesh which is not suitable for theconstruction of a shallow foundation. Pile foundation provides the best possible solution totransfer the load to the deeper harder layers of soil. In Bangladesh, driven piles are used inlarge numbers because of their various advantages over bored piles; like the high quality of
construction, idea of capacity during driving, etc. Recently large diameter cast in situ piles isalso used in large numbers for bridge structures and high-rise buildings.
Estimating pile capacity accurately is a difficult job even for the experienced geotechnicalengineer. There are many conventional methods for calculating pile capacity, but the
selection of each method requires knowledge of soil properties as well as the limitation orapplicability of any method in a regional boundary. Traditionally, pile capacity can beevaluated by using a bore log of the subsoil investigation report (Bowles 1997), and then,later it needs to be confirmed by the static load test. As per, static load testing of the driven
pile and bored cast in situ pile is very time-consuming and expensive as well as needs
constant supervision on operation processes. It is often very difficult to ensure the chances ofaccuracy and precision. Moreover, the test has several problems like transferring the load tothe pile due to frictional errors. Besides, a manual data collection system introduces humanerror possibilities. In these circumstances, a suitable alternative to static load test or crosschecking options were necessary for foundation engineers. Pile capacity determination is adifficult thing. Several different designs practices here in Bangladesh and internationallyexist, but seldom have they given the same computed capacity. Especially, determining theskin friction component is not an easy thing since the soil is not intact after the pile is driven
or drilled and loses its intact engineering property (strength). So far, the precise determinationof this value has not been possible. Thus, today design offices only believe a load test can
only give a reliable capacity of the pile at the time of the test. After installation, the design
values, i.e. the load-carrying capacities of piles are usually verified using different methods
such as pile loading test and dynamic analysis.
31

Scientific approaches to pile design have advanced enormously in recent decades and yet,still the most fundamental aspect of pile design - that of estimating capacity –relies heavily
upon empirical correlations.
Western researchers provided empirical methods based on extensive explorations andinvestigations for different types and conditions of soil. Meyerhof (1959) has arranged a
speculative relationship between the corrected standard penetration test data and the ultimate
axial capacity of driven pile. Also in 1976, he administered another formula for estimating
the capacity of bored cast in situ piles based on the behavior of pile in granular soil. Whereas
Vesic (1977) modified the bearing capacity factor that (Meyerhof 1976)provided for end
bearing of driven pile and bored pile in granular soil founded by the relationship between
rigidity modulus and angle of internal friction of soil. The American Petroleum Institute(API) provides a static analysis procedure design developed for offshore construction. These
projects almost exclusively use large diameter, open-end, steel pipe piles which are driven by
impact hammer to final penetration (American Petroleum Institute 2003). Recently, largediameter open-end pipe pile usage has increased significantly on transportation projects. Thishas heightened the need for more accurate nominal resistance estimates on these larger piles.
So the design method proposed by API has more significance on large diameter steel piles
rather than concrete piles. Tomlinson (1994) studied the behavior of driven piles in cohesive
soil specially and established fascinating improvements of the adhesion or sometimes called
the reduction factor previously provided by (Peck et al. 1974). As with any design method,the one should also confirm the appropriateness of selected coefficients in a given soil
condition with local correlations between static resistance calculations and load test results.
American navy in 1982 provided a guideline for offshore and onshore piles design named
NAVFAC DM 7.2 and modified in 1984.Also, AASHTO time to time updated their codeabout pile capacity determination. O’Neill and Reese (1988) studied the behavior of piles incohesive and cohesion less soil and established an acceptable theory for pile capacity
determination later in 2005 AASHTO adopted this theory to their code for bored cast in situ
piles.
The study focuses on some of the selected empirical (semi-empirical) and theoreticalmathematical models used here in Bangladesh and internationally. To compare the various
models, some of the thirty piles have been chosen from different projects all over Bangladesh
32including MRT (Mass Rapid Transit) project and Rajuk high rise building project. During theinvestigation, static load tests are performed to determine the pile capacity. The load tests are
performed on single piles.

The study focuses only on the capacity of a single pile under compressive loading. Of course,
seldom single piles are used; however, the capacity of group piles entirely depends on thecapacity of a single pile within a group. It should be noted that the pile group capacity is not
the intension of this study. A pile foundation is much more expensive than spread footingsand is likely to be more expensive than mat foundation. Therefore, great care should be
exercised in determining the soil properties at the site for the entire depth of possible pilepenetration so that it can be accurately detern1ined whether a pile foundation is needed at all
and, if so, the design can be optimized so that neither an excessive number nor excessive
lengths are specified. This purpose can be achieved in two ways:
1. By taking adequate field and laboratory test programs which will help the designer toestimate the soil properties more accurately to design the foundation more
economically.
2. By determining the ultimate carrying capacity of a pile by load test.
1.2 Scope and Objective of the Study
The scope of the project work includes
1) Literature survey the focus is to do an intensive literature survey about empirical andtheoretical based practices.
2) Analysis and evaluation
The focus is to compare the empirical and theoretical based mathematical models with pileload test and of the selected piles. The Major objectives of the study are as follows:i.

To compare the ultimate capacity of piles determined by theoretical methods and froma static load, test results in selected areas.

33

ii.

To compare among ultimate pile capacity using different semi-empirical methods for
Cast-in-situ and Driven Piles.

iii.

To establish a correlation between ultimate theoretical capacity [(Qtheory)] andcapacity determined from static load test [(Qtest)].

METHODOLOGY
The exact analysis of a pile theoretically is impossible because of the higher degree ofindeterminacy and unpredictable behaviors. The pile may be analyzed theoretically in many
ways considering the empirical relations and suggestions offered by numerous authors. This
chapter deals mainly with the collection of pile data, development of soil model for theestimation of ultimate pile capacity, and discuss the methodology to establish correlations
between ultimate pile capacity from static analysis and pile load tests, Figure 3.1 gives a
flowchart, which explains different components of this study.
3.2 Collection of Data
Sub-soil investigation reports and corresponding pile load test results have been collectedfrom twenty-two projects all over the country. Among these projects, from twelve projects
fifteen precast piles have been tested and from ten projects fifteen cast-in-situ piles have beentested. The tests are performed between 1997 to 2018 and funded by the Public Works
Department (PWD), Bangladesh, RAJUK, R&H Department, Bangladesh, and Dhaka Mass
Transit Company (MRT). Almost 70% pile load tests are carried out under the directsupervision of the Department of Civil Engineering, BUET, and the rest of the pile load test
carried out by Icon Engineering Services, Dhaka. The approximate geographical locations of
the projects are shown in Fig. 3.2. Although most of the data are obtained from BUET, PWD,
and Icon Engineering Services, Dhaka. The author felt the necessity of proper data archiving
under a central national Organization such as BUET for future research purposes.
.3 Idealization of Soil Data
Identical borehole locations and test piles have been identified. For the estimation of ultimate
pile capacity in the static method, the total soil strata have been divided into some reasonable34

layers with specified soil properties. For the convenience of soil modeling, non-plastic silt isassumed as cohesion less soil and plastic silt assumed as cohesive soil. Field SPT value
determined every one-meter interval. But for simplicity here average SPT value of every
layer has to be used.

The precast piles are indexed as PTP-1, 2, 3 etc. and the cast-in-situ

piles are indexed as CTP-1, 2, 3 etc. The soil models together with other relevant informationof the piles are presented in table 3.2 and 3.3 and Appendix A.
3.4 Analysis of Data
The principle approach used to calculate the pile's capacities to resist the compressive loads isthe static or soil mechanics approach. During the past years, more research work is done toexpress a method based on the practical soil mechanics theory. For example, the calculationof skin friction on a pile shaft was based on a simple relationship between the effective
overburden pressure, the drained angle of shearing resistance of the soil, and the coefficientof earth pressure at rest, but they realized through the results of the practical tests andresearches that the coefficient of earth pressure must be modified by a factor takes into
consideration the installation method of the pile.
In the same way, the calculation of the pile end bearing resistance was based on theundisturbed shearing resistance of the soil at the pile toe level, but they recognized theimportance of the pile settlement at the working load and methods have been evolved to
calculate this settlement, based on elastic theory and considering the transfer of load in shaft
friction from the pile to the soil. A pile is subjected to a progressively increasing compressive
load at a steady rate of application, the resulting load - settlement relationship plotted in Fig.
3.4. There is a straight-line relationship up to point A on the curve, this is means if the load
released at any stage up to point ‘A’ the deformation or settlement of the pile head will return
to its original condition. when the loading increased beyond point ‘A’ the relationship will
have changed from linear to a nonlinear relationship, and there will be yielding at the pile-soil
interface till reaching the maximum shaft friction 'point ‘B’. In case of load releasing at thisstage, the pile head will have reached to point ‘C’. and the distance ‘OC’ will be themovement required to mobilize the maximum pile shaft resistance, usually, this distance isequal to 0.3% to 1% of the pile diameter. The pile base resistance requires more downward
movement to full mobilization, point 'D', that movement is based on the pile diameter, and it
is ranged between 10% to 20% of the pile diameter after point 'D' the pile will move
downward without any increase in the load "failure point" in figure 3.4.
35

Figure 3.4: Load /settlement curve for the compressive load to failure on a pile
The exact calculation of the load-carrying capacity of a pile is a complex matter, which isbased partly on theoretical concepts but mostly on empirical methods based on experience.
The practice of calculating the ultimate load-carrying capacity of a pile based on theprinciples of soil mechanics differs greatly from the application of these principles to shallow
spread foundations.
The conditions, which govern the supporting capacity of the pile foundation, are quite
different. No matter whether the pile is installed by driving with a hammer, by jetting, byvibration, by jacking, screwing or drilling, the soil in contact with the pile face from which
the pile derives its support by skin friction and its resistance to lateral loads, is completely
disturbed by the method of installation. Similarly, the soil beneath the toe of a pile iscompressed or loosened to some extent which may affect significantly its end bearing
resistance. Changes take place in the conditions at the pile-soil interface over periods of days,
months, or years which materially affect the skin friction resistance of a pile.
3.4.1 Pile Load Capacity from Static Analysis
Static analysis methods estimate shaft and base resistances separately and differently. For
shaft resistance, in cohesive as well as non-cohesive soils, considerable uncertainty anddebate exist over the appropriate choice of the horizontal stress coefficient, Ks. Normally,
bearing capacity theory is applied to estimate base resistance in non-cohesive soils. However,
the theory involves a rather approximate Φ-Nq relationship coupled with the difficulty ofdetermining a reliable and representative in-situ value of the Φ angle and the assumption of a36

proper shear failure surface around the pile tip. This creates doubts about relying on the
bearing capacity theory in pile foundation design. Design guidelines based on static analysis
often recommend using the critical depth concept. However, the critical depth is an
idealization that has neither theoretical nor reliable experimental support and contradicts
physical laws. For static analysis, few selected methods have been used to predict theultimate capacity of driven and cast-in-situ bored piles. These methods are describedelaborately in chapter two. For analysis purposes, the saturated and dry unit weight of soil
obtained from the chart referred by Bowles (1977) is based on the SPT value of soil. For
calculating the effective stress and total stress using the unit weight of every layer of soil
individually and this value obtained from table 3.1 and figure 3.4. Different formulas havebeen used to compute the skin friction and end bearing of piles as per the early describedmethods. The Sum of the end bearing and skin friction of a single pile is the ultimate capacityof that pile. For a given soil condition different methods predict the different ultimate
capacity of the same piles due to the postulation criteria of the methods. This has been
discussed in chapter two and some of the points will be discussed in chapter four. Some of
the calculation sheet attached in Appendix-C.
3.4.2 Pile Load Capacity from Pile Load Tests
Different criteria for obtaining ultimate pile load capacity from pile load test results are
mentioned in chapter two. In this study, load settlement curves (sample curve is shown inAppendix-B) from pile load test results are used to find out the ultimate capacity of the pileby Davisson offset method, Indian Standard and BNBC Code. Davisson offset method isprobably the best known and widely used in North America and other regions worldwide
because it provides the lowest estimate of axial compression capacity from the actual loadsettlement curve and for this versatile use of the Davisson offset method influenced theauthor to take as the ultimate capacity of piles for analysis. The other two methods have to
use to show their validation. Generally, all three methods give almost nearly ultimate
capacity, but the settlement of piles differs from one method to another. In Appendix-A load
test results and corresponding settlement are presented. In chapter two we already discuss theload test methods and their theory. In some projects extrapolated load settlement curves for
Test and Services piles are used for this purpose to determine the failure load. The validity ofthe extrapolated load settlement curve has been justified with some of the known load
settlement curves. And it found the very little amount of error (+/-10%).
37

3.4.3 Data for Further Analysis
After obtaining ultimate capacities from both static and load test results, Table 4.2 iscompiled for precast piles and Table 4.1 is compiled for cast-in-situ piles. From the twentytwo projects, fifteen results for precast pile and fifteen results for cast-in-situ piles are
obtained. For all the pile load tests, settlement corresponding to the ultimate capacity of thepiles obtained from load settlement curves by the early mentioned methods and are shown in
Table 4.1 and 4.2.
3.5 Statistical Analysis
For comparison of the prediction of the pile’s bearing capacity estimation approaches andevaluation of their accuracy and efficiency, the Rank Index, RI was utilized. This index is
calculated as follows:
RI=R1+R2+R3+R4+R5
Where
R1 is the rank of the method based on the highest value of the coefficient of determination of
Qp/Qm, R2 and R3 are the methods rank based on statistical analysis using the arithmetic
mean and standard deviation, R4, and R5 is methods rank based on cumulative probability
analysis. The lower the RI, the more precise would be the method. Analyses of residual error,
the difference between observed and predicted values, can be used to evaluate method
performance by characterizing, i.e., systematic under or over-prediction. In this approach, theCoefficient of Determination (COD) or modeling efficiency is employed to check thecompatibility of predictions and measured values. COD is measured by equation 3.1.
COD=1

∑
∑

(3.1)

38

Figure 2 Geographical locations of pile load tests and soil borehole

Figure 3.6: Schematic arrangement of the static load test.

39

RESULTS AND DISCUSSIONSIn this study, the main focus is to determine the compressive load capacity of piles using
different existing methods of pile capacity estimation and compare with static load test. In
this chapter, pile capacity calculation was done based on the Meyerhof (1976), NAVFAC
DM 7.2 (1984), AASHTO (1986), O’Neil & Reese (1988), and Decourt (1995) methods forcast-in-situ bored piles and Drilled Shafts. And for calculation of capacity of driven piles
based on Meyerhof (1976), API RP 2A (1993), Tomlinson (1994), Norwegian Pile Guideline(2005) and Indian Standard (2010) methods. For the selected fifteen precast driven pile eightcast in situ bored pile and seven Drilled shaft capacities was predicted and later comparedwith static load test. The later part of the study uses compared data for capacity and correlatewith prediction and measured capacity for precast and cast in situ piles and Drilled shafts.
Based on these compared (prediction and measured capacity) data selection of best
theoretical methods for predicting the capacity of precast driven piles and cast in situ boredpiles and Drilled shafts.
4.2 Determination of Pile Capacity by Theoretical Methods
4.2.1 Precast driven pile
In this study, fifteen numbers of precast driven piles have been selected from different
projects all over Bangladesh in the time 1998 to 2018.By using the following methods theirultimate capacity has been measured. It has been discussed elaborately on the following
methods in chapter two for both cohesive and cohesion less soil. The methods are:

Meyerhof (1976)



API RP 2A (1993)

Tomlinson (1994)



Norwegian Pile Guideline (2005)

Indian Standard (2010)

Summary of the predicted ultimate capacity of fifteen Precast drivren piles shown in table 4.2
The detailed calculation of these fifteen driven piles is included in the Appendix.
4.2.2 Cast in Situ Bored Pile and Drilled Shaft
40

In this study, eight numbers of the cast in situ bored piles and seven numbers of drilled shaft
have been selected from different projects all over Bangladesh in the time 1998 to 2018.By
using the following methods their ultimate capacity has been measured. It has been discussed
elaborately about the following methods in chapter two for both cohesive and cohesionlesssoil. The methods are:

Meyerhof (1976)



NAVFAC DM 7.2 (1984)

AASHTO (1986)

O’neil & Reese (1988)

Decourt (1995)

Summary of the predicted ultimate capacity of eight casts in situ bored pilesand seven drilledshafts shown in table 4.1. The detailed calculation of these fifteen bored piles is included in
the Appendix.
4.3 Determination of Pile Capacity from Load Test by Different Standards and Methods
The load was applied to piles in stages up to 200% to 300% of the design load. Pile
settlement in mm against applied load in tons has been plotted for piles (Appendix-3). To
measure the ultimate vertical load-carrying capacity of the test piles the following methods
are followed. These are(i) Davisson's offset limit method- In Davisson's (1973) method, the failure load is defined as
the load corresponding to the movement which exceeds the elastic compression of the pile,when considered as a free column, by a value of O.I 5in. plus a factor depending upon the
diameter of the pile. This critical movement can be expressed as follows:
Sr= S + (0.15x25.4 + 0.008D)(4.1 )

Where, Sr is the movement of the pile head (in mm), D is the pile diameter or width (inmm),
and S is the elastic deformation of the total pile length (in mm). In this study to calculate theelastic compression of the pile the Modulus of Elasticity of the concrete (Ec) has been taken
as
Ec=57000

′

(4.2)
41

Where, Ultimate compressive strength of the concrete, fc' = 4000 psi(ii ) Indian Standards (IS) code (1979) recommends that the ultimate capacity of pi Ie issmaller of the following twoa) Load corresponding to a settlement equal to 10% of the pile diameterb) Load corresponding to a settlement of 12 mm
The same code states that the allowable pile capacity is smaller of the following:a) Two-thirds of the final load at which total settlement

is 12 mm.

b) Half of the final load at which total settlement is equal to 10% of the pile diameter.
(iv) The Bangladesh National Building Code (1993) recommends that the allowable load
capacity of the pile shall not be more than one half of that test load which produces apermanent not settlement (i.e. gross settlement less rebound) of not more than 0.00028
mm/kg of test load nor 20mm. The result of load tests on piles under this study is presented intable 4.1 andtable4.2. And compare of each pile with predicted theoretical capacities
presented in table 4.1 and table 4.2 Appendix.
4.3.1 Analysis of Load–Settlement Curves
As the load tests used in this study out of thirty piles (fifteen of the precast and fifteen of thecast in situ) ten numbers of piles (seven of bored piles) were not carried to failure which
would have facilitated determination of the precise value of the ultimate load capacity of thepiles, a method of extrapolation of load settlement curves has been used to estimate as nearlyas possible; the failure load from load settlement curves. The assumptions used in theextrapolation are;Load settlement curves follow the trend of a parabola after an initial straight portion. The
piles under this study predominantly end bearing with a low to moderate contribution offrictional resistance. Before applying the extrapolation method, a clear idea of the nature of
the load settlement curves of different types of piles is needed. The following discussions areprovided to fulfill the above objective. As cited by Peck et al. (1980) the results of typicalload tests are shown in fig. 4.1 in which the total load is plotted as a function of thesettlement of the pile head. Curve 'a' represents a pile that slipped or plunged suddenly when42the load reached a definite value termed as the ultimate pile load or pile capacity. The natureof the curve indicates that the pile under test is a friction pile with negligible end bearing.
Curve ‘b’ does not show a well-defined break as in curve "a" and continues to penetrate theground showing a predominant contribution of the end bearing. Curve 'c' on the other handtakes a parabolic shape after an initial straight portion showing both the contribution offriction and end bearing.

Figure 4.1: Typical results of load test on (a) friction pile, (b) end bearing pile and (c) pilederiving support from both end bearing and friction
Analysis of the bearing capacity of piles by static methods under this study in Chapter two
shows that the piles are predominantly base resistance but has a good contribution from thefriction since the embedded depth of the piles in layered soil. Thus, the piles of which theload test results are being discussed fall in the group 'c' as discussed in this section earlier.
4.3.2 Procedure of Extrapolationo Step-1: With a careful examination of the load settlement curve, the parabolic portionof the curve is selected.

43

o Step-2: The general equation of the curve is taken as y =ax2-+bx+e, where a, b, c areconstants. Taking any three points on this curve the constants can be detel1nined.
Therefore, the equation of the parabola is established.
o Step-3: With this equation the curve can be extrapolated up to the next load incrementin the load settlement plot.
o Step-4: Using any three points on the extrapolated curve, another equation of parabola
can be established. With this equation, the curve can be extrapolated up to the next
load increment in the load settlement curve. Following the above procedure, the load
settlement curves can be plotted up to a distinct break and using this curve estimates
can be made of ultimate pile capacity using recommendations and standards as forfull-scale load tests carried to failure. some of the extrapolated load settlement curve
shown in figure 4.2.

0

100

200

300

400

500

600

700

800

900

1000

1100

0
10
20
30
40
50
60
70
80
90
100

Figure 4.2 (a): Load settlement curve of CTP-12 (Postogola under Pass)

44

0

100

200

300

400

500

600

700

800

900

0
10
20
30
40
50
60

Figure 4.2(b): Settlement curve of CTP-15 (Shibpur Bridge, Tangail)Figure 4.2(a) and 4.2(b) shown that the extrapolated value is almost like the actual failureload. This gives a validation of extrapolation methods for the other eight pile’s load
settlement curves.
4.4 Statistical Analysis
For comparison of the prediction of the pile’s bearing capacity estimation approaches andevaluation of their accuracy and efficiency, the Rank Index, RI was utilized. This index is
calculated as follows:
RI=R1+R2+R3+R4+R5(4.3)

Where R1 is the rank of the method based on the highest value of the coefficient ofdetermination of Qp/Qm, R2 and R3 are the methods rank based on statistical analysis using
the arithmetic mean and standard deviation, R4, and R5 is methods rank based on cumulative
probability analysis. The lower the RI, the more precise would be the method. Fig. 4.3(a) and4.3(b), illustrates the variation of the predicted capacities with measured capacities fordifferent methods. According to this figure, the solid line in each diagram reveals perfect45

agreement between predicted and measured pile capacity passing the origin with a slope
equal to unity. Analyses of residual error, the difference between observed and predictedvalues, can be used to evaluate method performance by characterizing, i.e., systematic underor over-prediction. In this approach, the Coefficient of Determination (COD) or modelingefficiency is employed to check the compatibility of predictions and measured values.
CODismeasured by equation 4.4.
COD=1

∑

(4.4)

∑

Where,
QpiandQmiare the predicted and measured values, and Qmais the mean of the measured
values, respectively, and n is the number of samples. The COD provides a dimensionlessstatistic summary very similar to the coefficient of determination, R^2 from linear regression.
It has been similarly interpreted as the proportional reduction in variation of observed values
around the model expectation to variation around the observed mean value. Note
Qmrepresents the “worst-case” regression line (slope = 0) indicating a lower bound of 0 forR^2, but Loehle pointed out that no such lower bound exists for COD. In the case of 100%
accuracy in method predictions, the COD will be equal to one. The arithmetic average (μ) andstandard deviation (σ) of the Qp/Qm values were calculated and utilized as a second-ranking
criterion. The closer the arithmetic averages to one, the lower the methods prediction’s error.
Also, the closer the standard deviation to zero, the lower the scatter of the predictions.
The third approach employed to evaluate the accuracy of methods is the cumulative
probability measure. According to the cumulative probability approach, the ratio of thepredicted value (Qp) to the measured value (Qm) has been drawn versus cumulative
probability. For a series of numerals, Qp/Qm has been set ascending and indexed with 1 to n.
Then for each of the relative amounts, the cumulative probability factor has been calculated
as follows:
%

100

(4.5)

Where P is the cumulative probability factor, iis the index of the considered case, and n is thenumber of total cases. To determine the convergence or deviation tendency of the output ofprediction, the following criteria have been referred: The value of Qp/Qm at the cumulative46

probability of 50% is a measurement of the tendency to overestimate or underestimate thepile capacity. The closer to a ratio of unity, the better the agreement. To estimate the average
error the following equation can be used:
Qp
Qm %

1

The slope of the line through the data points is a measurement of the dispersion or standard
deviation. The flatter the line, the better the general agreement. Fig. 4.3 illustrates the
cumulative probability analysis in this research.

Cumulative Probability vs Qp/Qm of
CTP
10

Qp/Qm

Meyerhof
NAVFAC
1
0

20

40

60

80

AASHTO

100

O'neill & Reese
Decourt
0.1

Cumulative Probability

Figure 4.3(a): Cumulative probability for Drilled Shaft in different methods.

Cumulative Probability vs Qp/Qm of
CTP
10

Qp/Qm

meyerhof
Navfac
1
0

20

40

60

80

100

AASHTO
O'neil & Reese
Decourt

0.1

Cumulative Probability

47

Figure 4.3(b): Cumulative Probability graph for bored pile in different methods.

Cumulative Probability vs Capacity
Ratio

Qp/Qm

10

1
0

20

40

60

80

100

meyerofAPI
TOMLINSONNPGINDIAN STANDARD

0.1

Cumulative probability

Figure 4.3(c): Cumulative Probability graph for driven pile in different methods.
4.5 Establishment of Correlation
The establishment of a correlation between predicted capacity and measured capacity of PTP
and CTP for different theoretical and semi-empirical methods is the goal of this study. For
this purpose, Microsoft excel has been used here. A regression equation has been used tocompare capacities. The R2 values give this study the compatibility of these regression
equations. The value of R2 near to unity gives the most compatible equation. But it does not
represent the accuracy of the statics equation to predict the capacity for different methods.
This accuracy of the statics equation has been determined by a statistical analysis which has
been discussed earlier.
4.5.1 Precast Driven Pile
Meyerhof (1976) Method
Compare the predicted capacity from Meyerhof (1976) method with measured capacity fromload test for fifteen numbers of precast driven piles gives a regression equation, Qp=0.685Qm+24.98 with R2=0. 935. High value of R2 indicates a better correlation between
48

Ultimate Capacity Predicted from Meyerhof, Qp

1200
Qp = 0.6855Qm + 24.984
R² = 0.9352
1000

800

600

400

200

0
0

200

400

600

800

1000

1200

Ultimate Capacity Measured from Load Test, Qm

Figure 4.4(a): Correlation between Qp and Qm for Meyerhof methods

Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.3), it has been observed that a moderate RI(RI=15) ranked this method thirdamongst all other methods in precast driven piles. Also, this method predicts to underestimate
the ultimate capacity by 17.40%. Figure 4.3(c) justify this error. COD value of 0.824
indicates the good compatibility of the predicted theory. Limiting value of effective stressafter 10D for loose sand, 15D for mid dense sand, and 20D for dense to very dense sandrecommended by Das control the skin resistance as well as end-bearing capacity. It is one of
the major causes of underpredict the capacity.
API RP 2A (1993) Method
Compare the predicted capacity from API (1993) method with measured capacity from load
test for fifteen numbers of precast driven piles gives a regression equation, Qp =1.01Qm-31.95
with R2=0. 949. High value of R2 indicates a better correlation between

49

Ultimate Capacity Predicted from API,Qp

1200

1000

y = 1.01x ‐ 31.958
R² = 0.9499

800

600

400

200

0
0

200

400

600

800

1000

1200

Ultimate Capacity Measured from Load Test, Qm

Figure 4.4(b): Correlation between Qp and Qm for API methods
Predicted and measured capacity. From statistical analysis and cumulative probability(shown in table 4.3), it has been observed that the lowest RI(RI=10) ranked this method
second amongst all other methods in precast driven piles. Also, this method predicts tounderestimate the ultimate capacity by 9.60%. Figure 4.3(c) justify this error. COD value of
0.937 indicates very good compatibility of the predicted theory. No such limit for thedetermination of effective stress. For this large value of end bearing obtained for large
displacement piles. But API recommended limiting unit skin friction and limiting unit end
bearing keep the ultimate capacity justified with measured capacity.
Tomlinson (1994) Method
Compare the predicted capacity from Tomlinson (1994) method with measured capacity fromload test for fifteen numbers of precast driven piles gives a regression equation,
2

Qp

2

=0.752Qm+26.67 with R =0.919. High value of R indicates a better correlation between

50

Ultimate Capacity Predicted from TOMLINSON,Qp

1200

1000

y = 0.7523x + 26.67
R² = 0.9195

800

600

400

200

0
0

200

400

600

800

1000

1200

Ultimate Capacity Measured from Load Test, Qm

Figure 4.4(c): Correlation between Qp and Qm for Tomlinson methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.3), it has been observed that the lowest RI(RI=10) ranked this method first amongst
all other methods in precast driven piles. This is the best method to predict the ultimate
capacity of precast driven piles with 3.20% overestimation. Figure 4.3(c) justify this error.
The COD value of 0.868 indicates very good compatibility of the predicted theory. No such
limit for the determination of effective stress. For this large value of end bearing obtained forlarge displacement piles. But Peck recommended limiting unit end bearing (11mn/m2)
adopted by Tomlinson to keep the ultimate capacity justified with measured capacity.

51

Norwegian Pile Guideline (2005) Method
Compare the predicted capacity from Norwegian Pile Guideline (2005) method withmeasured capacity from load test for fifteen numbers of precast driven piles gives aregression equation, Qp =0.725Qm-0.273 with R2=0. 944. High value of R2 indicates a better
correlation between

Ultimate Capacity Predicted from NPG,Qp

1200

1000

y = 0.7252x ‐ 0.2734
R² = 0.9444

800

600

400

200

0
0

200

400

600

800

1000

1200

Ultimate Capacity Measured from Load Test, Qm

Figure 4.4(d): Correlation between Qp and Qm for NPG methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.3), it has been observed that the highest RI(RI=21) ranked this method fifthamongst all other methods in precast driven piles. This is the worst conservative method topredict the ultimate capacity of precast driven piles with 23.10% underestimation. Figure
4.3(c) justify this error. COD value of 0.827 indicates the good compatibility of the predicted
theory. No such limit for the determination of effective stress. An effective stress method isused to calculate skin friction for cohesion less soil. The co-efficient of skin friction β is afunction of OCR. Largely driven piles give very high side resistance for higher β value andhighly effective stress value. But bearing capacity factor Nq is very conservative.

52

Indian Standard (2010) Method
Compare the predicted capacity from Indian Standard (2010) method with measured capacityfrom load test for fifteen numbers of precast driven piles gives a regression equation, Qp=0.659Qm+23.98 with R2=0. 972. Highest value of R2 indicates a better correlation between

Ultimate Capacity Predicted from Indian Standard,
Qp

1200

1000
y = 0.6593x + 23.986
R² = 0.9724
800

600

400

200

0
0

200

400

600

800

1000

1200

Ultimate Capacity Measured from Load Test, Qm

Figure 4.4(e): Correlation between Qp and Qm for Indian Standard methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.3), it has been observed that a high RI(RI=19) ranked this method fourth amongst
all other methods in precast driven piles. This is a very conservative method to predict theultimate capacity of precast driven piles with 20% underestimation. Figure 4.3(c) justify thiserror. COD value of 0.814 indicates the good compatibility of the predicted theory. IndianStandard(2010) adopted Terzaghi Bearing Capacity equation to calculate the end bearing
capacity of piles. Hence the length and shape of piles play an important role in thecomputation of capacity.

53

4.5.2 Cast in situ Bored Pile
Meyerhof (1976) Method
Compare the predicted capacity from Meyerhof (1976) method with measured capacity fromload test for eight numbers of the cast in situ bored piles gives a regression equation,
Qp=0.957Qm+50.32 with R2=0.555.Moderate value of R2 indicates a pretty good correlation
betweenUltimate capacity predictd from Meyerhof,Qp

600
y = 0.9573x + 50.317
R² = 0.5551

500

400

300

200

100

0
0

100

200

300

400

500

600

Ultimate capacity measured from load test,Qm
Meyerhof Method

Figure 4.5(a): Correlation between Qp and Qm for Meyerhof methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.4(A)), it has been observed that the lowest RI(RI=10) ranked this method second
amongst all other methods in bored piles. Also, this method predicts to overestimate theultimate capacity of9%. Figure 4.3(b) justify this error. This method to predict the capacity ofbored piles is based on SPT. In this method field, SPT has been used. But for calculating theside friction field SPT has been used other hand for computing end bearing overburdenpressure correction for SPT has been taken places. Also, Meyerhof limiting unit friction andlimiting end bearing has been considered. This is kept the predicted capacity in minor error.
NAVFAC (1984) Method
54Compare the predicted capacity from NAVFAC (1984) method with measured capacity fromload test for fifteen numbers of the cast in situ bored piles gives a regression equation,
Qp=0.995Qm+21.62 with R2=0.64.Moderate value of R2 indicates a pretty good correlation
betweenUltimate capacity predictd from NAVFAC,Qp

600
y = 0.995x + 21.625
R² = 0.6316

500

400

300

200

100

0
0

100

200
300
400
500
Ultimate capacity measured from load test,Qm
NAVFAC Method

600

Figure 4.5(b): Correlation between Qp and Qm for NAVFAC methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.4(A)), it has been observed that a lower RI(RI=6) ranked this method first amongst
all other methods in bored piles. Also, this method predicts to overestimate the ultimate
capacity of 1%. Figure 4.3(b) justify this error. COD value of 0.35 indicates the fairreliability of the predicted theory. This method predicts the capacity of bored piles in claybased on total stress and in sand based on effective stress. In sand high bearing capacity
factor for high SPT values gives the high capacity for long piles. But, limiting value of unit
toe resistance and unit side resistance keep the predicted capacity relevant with measured
capacity.

55

AASHTO (1986) Method
Compare the predicted capacity from AASHTO (1986) method with measured capacity fromload test for eight numbers of the cast in situ bored piles gives a regression equation,
Qp=1.22Qm+37.75 with R2=0.794.Higher value of R2 indicates a good correlation between

600

Ultimate capacity predictd from AASHTO,Qp

y = 1.2198x + 37.759
R² = 0.7943
500

400

300

200

100

0
0

100

200

300

400

500

600

Ultimate capacity measured from load test,Qm
AASHTO Method

Figure 4.5(c): Correlation between Qp and Qm for AASHTO methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.4(A)), it has been observed that a moderate RI(RI=17) ranked this method fourthamongst all other methods in bored piles. Also, this method predicts to overestimate theultimate capacity by 40%.Figure 4.3(b) justify this error. This method predicts the capacity ofbored piles in clay-based on total stress and in the sand based on effective stress. In sand side
friction factor β is the function of the depth of the pile. It has an upper value of 1.2 for shortlength pile and a lower value of 0.25 after 87.5 feet depth of piles. Piles of low depth predicthigh value compare with long length piles. In sand end bearing capacity depends on SPT
value. For high depth piles, it gives higher values.

56

O'neill & Reese (1988) Method
Compare the predicted capacity from O’Neill& Reese (1988) method with measured capacityfrom load test for eight numbers of the cast in situ bored piles gives a regression equation,
Qp=1.40Qm-56 with R2=0.763.Higher value of R2 indicates a good correlation between
Ultimate capacity predictd from O'neill and Reese,Qp

600
y = 1.4031x ‐ 56.063
R² = 0.7632
500

400

300

200

100

0
0

100

200

300

400

500

600

Ultimate capacity measured from load test,Qm
O'neill and Reese Method
Figure 4.5(e): Correlation between Qp and Qm for O’Neill and Reese methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.4(A)), it has been observed that a lower RI(RI=13) ranked this method thirdamongst all other methods in bored piles. Also, this method predicts to overestimate theultimate capacity by 24.60%.Figure 4.3(b) justifies this error. This method predicts thecapacity of bored piles in clay-based on total stress and in the sand based on effective stress.
In sand side friction factor β is the function of the coefficient of lateral earth pressurev(k).
This k is the function of pre consolidated stress and over consolidation ratio. With theincrease of depth of pile effective stress increase abruptly. This causes higher depth piles togive more side friction due to excess vertical stress. Piles of high depth predict high value
compare with short length piles. In sand end bearing capacity depends on SPT value. For
high depth piles, it gives higher values.

57Decourt (1995) Method
Compare the predicted capacity from Decourt's (1995) method with measured capacity fromload test for eight numbers of the cast in situ bored piles gives a regression equation,
Qp=1.89Qm+130.54 with R2=0.518.Moderate value of R2 indicates a pretty good correlation
betweenUltimate capacity predictd from Decourt,Qp

1200
1000
800
600
y = 1.8885x + 130.54
R² = 0.5186

400
200
0
0

200

400

600

800

1000

1200

Ultimate capacity measured from load test,Qm
Decourt Method

Figure 4.5(e): Correlation between Qp and Qm for Decourt methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.4(A), it has been observed that the highest RI(RI=23) ranked this method fifthamongst all other methods in bored piles. Also, this method predicts to overestimate theultimate capacity of134%.Figure 4.3(b) justify this error. COD value of -33.84 indicates very
poor reliability of the predicted theory. It is a SPT based empirical formula invents by
Decourt with numbers of the load test. This empirical formula gives justified values for skinfriction both clay and sand. But computation of end bearing capacity in the sand gives very
high values due to the overestimate of end bearing co-efficient.

58

4.5.3 Cast in Situ Drilled Shaft
Meyerhof (1976) Method
Compare the predicted capacity from Meyerhof (1976) method with measured capacity fromload test for seven numbers of the cast in situ drilled shafts gives a regression equation,
Qp=0.04Qm+1937 with R2=0.Value of R2 and other statistical data indicates the inability ofthis method to predict the capacity of drilled shaft.

Ultimate capacity predictd from Meyerhof,Qp5000
y = 0.0409x + 1937.1
R² = 0.004
4000

3000

2000

1000

0
0

1000

2000

3000

4000

5000

Ultimate capacity measured from load test,Qm
Meyerhof Method

Figure 4.6 (a): Correlation between Qp and Qm for Meyerhof methods

59

NAVFAC (1984) Method
Compare the predicted capacity from NAVFAC (1984) method with measured capacity fromload test for seven numbers of the cast in situ drilled shafts gives a regression equation,
Qp=0.006Qm+3231 with R2=0.Value of R2 and other statistical data indicates the inability ofthis method to predict the capacity of drilled shaft.

Ultimate capacity predictd from NAVFAC,Qp

5000

4000

3000

2000

1000

y = 0.0062x + 3231.2
R² = 5E‐05

0
0

1000

2000

3000

4000

5000

Ultimate capacity measured from load test,Qm
NAVFAC Method

Figure 4.6(b): Correlation between Qp and Qm for NAVFAC methods
This method predicts the capacity of bored piles in clay based on total stress and in sandbased on effective stress. In sand high bearing capacity factor for high SPT values gives theirrelevant capacity for long piles.

60

AASHTO (1986) Method
Compare the predicted capacity from AASHTO (1986) method with measured capacity fromload test for seven numbers of the cast in situ drilled shafts gives a regression equation,
Qp=0.228Qm+1764.6 with R2=0.13.Low value of R2 indicates a some correlation between

Ultimate capacity predictd from AASHTO,Qp

5000

4000
y = 0.2288x + 1764.6
R² = 0.1283
3000

2000

1000

0
0

1000

2000

3000

4000

5000

Ultimate capacity measured from load test,Qm
AASHTO Method

Figure 4.6(c): Correlation between Qp and Qm for AASHTO methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.4(B)), it has been observed that a lower RI(RI=7) ranked this method first amongst
all other methods in drilled shaft. Also, this method predicts to underestimate the ultimate
capacity by 3%. Figure 4.3(a) justify this error. COD value of 0.5 indicates a good reliabilityof the predicted theory.

61

O'neill & Reese (1988) Method
Compare the predicted capacity from O’Neill & Reese (1988) method with measured
capacity from load test for seven numbers of the cast in situ drilled shafts gives a regression
equation, Qp=0.347Qm+2234 with R2=0.1.Lower value of R2 indicates some correlation
betweenUltimate capacity predictd from O'neill andReese,Qp5000
y = 0.347x + 2234.1
R² = 0.0903

4000

3000

2000

1000

0
0

1000

2000

3000

4000

5000

Ultimate capacity measured from load test,Qm
O'neill and Reese Method

Figure 4.6(d): Correlation between Qp and Qm for O’Neill and Reese methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.4(B)), it has been observed that a lower RI(RI=15) ranked this method thirdamongst all other methods in drilled shafts. Also, this method predicts to overestimate theultimate capacity by 6%. Figure 4.3(a) justifies this error.

62

Decourt (1995) Method
Compare the predicted capacity from Decourt's (1995) method with measured capacity fromload test for seven numbers of the cast in situ drilled shafts gives a regression equation,

Ultimate capacity predictd from Decourt,Qp

Qp=0.087Qm+4356 with R2=0.01.Very low value of R2 indicates a poor correlation between
6000
5000
4000
3000
2000

y = 0.0873x + 4356.6
R² = 0.0106

1000
0
0

1000

2000

3000

4000

5000

6000

Ultimate capacity measured from load test,Qm
Decourt Method

Figure 4.6(e): Correlation between Qp and Qm for Decourt methods
Predicted and measured capacity. From statistical analysis and cumulative probability (shownin table 4.4(B)), it has been observed that the highest RI(RI=24) ranked this method fifthamongst all other methods in drilled shafts. Also, this method predicts to overestimate theultimate capacity of62%.Figure 4.3(a) justify this error. It is a SPT based empirical formulainvents by Decourt with numbers of the load test. This empirical formula gives justified
values for skin friction both clay and sand. But computation of end bearing capacity in thesand gives very high values due to the overestimate of end bearing co-efficient. Also, theuncorrected SPT value gives higher results for long piles.

63

CONCLUDING REMARKSIn this study sub-soil investigation report and corresponding pile load test results have beencollected from twenty-two projects all over the country. Among these projects, twelve
projects have been selected where fifteen precast piles have been tested and ten projects havebeen selected where fifteen cast-in-situ piles have been tested. The tests are performed
between 1997 to 2018 and funded by the Public Works Department (PWD), Bangladesh,RAJUK, R&H Department, Bangladesh, and Dhaka Mass Transit Company (MRT). Almost
70% pile load tests are carried out under the direct supervision of the Department of Civil
Engineering, BUET, and the rest of the pile load test carried out by Icon Engineering
Services, Dhaka. The findings of this study are as follows:
The length of fifteen cast in situ piles vary from 12 meters to 52 metershavingdiameters of
400 mm to 1200 mm. For convenience of analysis it has been divide in to two categories
named Bored pile and Drilled shaft. Ithasbeen observed that the long piles with large
diameter generally conservatively predict the capacity of piles than the short piles (shorter
than 18 m) for different statics methods except the Decourt(1995) method. It can beconcluded for bored piles that the long and larger diameter pile capacity are governed bysettlement rather than capacity.
Cast in situ piles larger than 600 m diameter considered as drilled shafts. No such good
regression equation found by analyzing the selected theoretical methods in this thesis. Only
AASHTO (1986) and O’neill and Reese (1988) gives some reliability to predict the ultimate
capacity. On the other hand, the length of fifteen precast piles vary from 7 meters to 30.5
meters having sizes of 175 mmX175mm to 400 mm X 400 mm. It has been found in thisstudy that the predicted pile capacity using all the methods are relatively conservative. Pile
driving energy plays an important role to increase the capacity of piles.
In this study, it has been observed that the Tomlinson (1994), API (1993) and Meyerhof(1976) methods provide the most reliable and justified correlation with predicted andmeasured capacity for the precast piles.
For the cast in situ bored piles, the AASHTO (1986), O;neill and Reese (1988) and NAVFAC(1984) methods provide the most reliable and justified correlation with predicted andmeasured capacity. For the cast in situ drilled shafts, the AASHTO (1986) and Onell andReese (1988) methods provide little reliable and justified correlation with predicted and64measured capacity. Other theoretical methods describe here are not suitable to predict thecapacity of drilled shafts. Drilled Shaft installation is a highly technological task. Duringboring of drilled shaft mud slurry has been used. This slurry creates a thin layer around theborehole of the drilled shaft. If this thin layer does not disappear during concreting it causes
to reduce the skin friction between soil and D.S. It lowers the measured capacity of the D.S.
In D.S construction first 5 feet of the soil formed cracks. This layer of cracked soil doesn't
exhibit any skin friction. This consideration ignored by most of the theory used in this thesis
except AASHTO and Reese et. al. Hence reduce the measured capacity compared withtheoretical capacity. Caving, necking, and construction faults in enormous scale reduce themeasured capacity of D.S. The above things didn't consider in the theoretical prediction. This
is why an insignificant correlation found.
It has also been observed that the methods for predicting the ultimate capacity of precast/driven piles give relatively more reliable and justified result with minimum error comparedwith the cast in situ/ bored piles. In all the cases a considerable correlation between the static
analysis of pile capacity and capacity of the pile from the static load test are found. This study
has supported the idea to put a higher degree of confidence to use the statics formulae to findout the ultimate capacity of the piles. The following correlations are proposed to obtain thepredicted capacity of different methods:
For Precast Piles

Meyerhof(1976) Qp=0.685Qm+24.98 with R2=0.935

API RP 2A(1993) Qp=1.01Qm-31.95 with R2=0.949

Tomlinson(1994) Qp=0.752Qm+26.67 with R2=0.919



Norwegian Pile Guideline (2005)Qp=0.725Qm-0.273 with R2=0.944

Indian Standard (2010) Qp=0.659Qm+23.98 with R2=0.972

For Cast-in-situ Piles (Bored Piles)

Meyerhof(1976) Qp=0.957Qm+50.317 with R2=0.555



NAVFAC DM 7.2(1984)Qp=0.995Qm+21.62 with R2=0.631



AASHTO(1986) Qp=1.219Qm+37.759 with R2=0.0.794

O’Neil&Reese(1988) Qp=1.403Qm-56.06 with R2=0.763
65PART-III

CAN RANA PLAZA HAPPEN AGAIN IN
BANGLADESHBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Uttama Barua
Mehedi Ahmed Ansary66

1. Introduction
In the world’s apparel sector, the Ready-Made Garment (RMG) industry in Bangladesh is theworld’s second-largest exporter which has also provided a primary source of livelihood forover four million workers (mostly women) and their family resulting in a significant
contribution to the country’s social and economic development (ILO 2017b). Despite suchremarkable achievement, the sector has been facing challenges to ensure workplace safety
and better working conditions for the millions of garment workers. Among others, building
collapse has been common in this sector. In 2005, the building of the Spectrum factorycollapsed causing the death of 64 garment workers and the injury of 84 (Miller 2012). In
2006, 22 workers died due to the collapse of the six-storied Phoenix Garments building(Ansary and Barua 2015). In 2012 due to the partial collapse of the Siams Superior Ltd.
factory building in Chittagong Export Processing Zone (CEPZ), five workers received minor
injuries (Solidarity Center 2019). In November 2012 at Ashulia’s Tazreen garments factoryin Dhaka, 112 people died due to a severe fire break out. In February 2013, at the factorybuilding of Envoy Garments Ltd. in Ashulia, Dhaka at least 100 garment workers were
injured in a stampede triggered by a false fire alarm and the consequent collapse of stairs
railing (Solidarity Center 2019). Just months after this accident, the nine-storied Rana Plaza
housing five RMG factories located in Savar, Dhaka collapsed on 24 April 2013. In 2005, theLocal Municipality (Savar) permitted the owner of Rana Plaza to construct a five-story
commercial building with one basement. Though the foundation of the building was for fivestory, later the owner was allowed to extend the building up to nine-story without considering
the structural design. Moreover, the building was converted from commercial to industrialuse, and power generators were placed on higher floors. As a result of such violations inbuilding construction, on 23 April 2013, a day before the fateful day, cracks developed onsome columns and the building jolted. After inspection, the industrial police requested thebuilding authorities to close the building and to suspend operations of the factories on thatday. However, the building owner and top-management of the garment factories ignored thewarning and forced the workers to work in the next morning on 24th April 2013 (Ansary andBarua 2015). As a consequence, the collapse of the building resulted in a high death toll of
1,134, and more than 2500 people were badly injured at the end of the rescue operation on 14
May 2013 (Solidarity Center 2019). It was the most fatal industrial accident in the RMG
sector in Bangladesh, and one of the deadliest industrial disasters in the world, which was theresult of the reluctant attitude of the stakeholders towards the compliance issues. This tragic

67

accident received global attention and brought forward diverse issues concerning millions ofstakeholders in the RMG sector of Bangladesh (Ansary and Barua 2015).
All these accidents represent poor workplace safety conditions in Bangladesh RMG factories.
After the Rana Plaza accident different diversified national and international initiatives havebeen taken to improve workplace safety conditions in this sector. Seven years after theaccident the question is now whether these initiatives could truly succeed to ensure
workplace safety or can accidents like the Rana Plaza collapse happen again. This paper aims
to explore the answer to this question by reviewing the initiatives and their progress toachieve workplace safety in the Bangladesh RMG industry with special attention to structuralsafety. The objectives of this research are threefold. Firstly, to review the process of ensuring
the structural safety; secondly, to review and understand the progress and the way forward in
the process; thirdly, to discuss the possibility of any such accidents in Bangladesh RMG
sector in light of the findings from first two objectives. This research has been carried out
through review of relevant literatures from different sources.
2. Initiatives after Rana Plaza collapse
Considering the potential of the RMG industry in Bangladesh and to ensure its safety andsustainability, several and diverse national and international commitments and initiatives
resulted as part of the reform and restructuring of the RMG sector after the Rana Plaza
accident (Khan and Wichterich 2015, Barua and Ansary 2017, Moazzem and Islam 2015,
RCC 2018b). As the National Initiative, a Joint Statement was signed by tripartite partners(GoB, RMG workers, and RMG employers) in May 2013. Afterward, as part of the National
Initiative, the National Tripartite Plan of Action (NTPA) on Fire Safety and Structural
Integrity in the RMG Sector of Bangladesh was formed in July 2013 merging the Joint
Statement with the NTPA on Fire Safety (outlined on March 2013 after Tazreen Fashion fire
accident) without altering the content (RCC 2018b). It included 25 commitments divided into
three categories: legislation and policy, administration, and practical activities. To ensure andmonitor its implementation the National Tripartite Committee (NTC) was established at thesame time under NTPA commitment. The committee is chaired by Labour Secretary andincludes Government agencies (Ministry of Labour and Employment, Department ofInspections for

Factories and Establishments (DIFE)), Employers’ Organizations(Bangladesh Employer's Federation (BEF), Bangladesh Garment Manufacturers & Exporters
Association (BGMEA) and Bangladesh Knitwear Manufacturers & Exporters Association(BKMEA)), and Workers’ Organizations (National Coordination Committee for Worker’s

68Education (NCCWE), and IndustriALL Bangladesh Council (IBC)) (Barua and Ansary 2017,
Moazzem and Islam 2015).
Based on NTPA, the European Union (EU), the Government of the People's Republic ofBangladesh (GoB), and the International Labour Organization (ILO) issued an agreement oftime-bound actions, “The Sustainability Compact: Compact for Continuous Improvements inLabour Rights and Factory Safety in the Ready-Made Garment and Knitwear Industry in
Bangladesh” in July 2013 to promote improved labour standards and responsible businessconduct in the RMG and knitwear industry in Bangladesh. A total of twenty-nine activities
were listed in the EU Sustainability Compact (Khan and Wichterich 2015, Barua and Ansary2017). Besides, the United States Trade Representative (USTR) requested GoB to implementa sixteen-point action plan within one year to reinstate Bangladesh’s GSP status in the US
market. The USTR Action Plan endorsed the EU Sustainability Compact particularly for
trade union-related activities (Moazzem and Islam 2015, Barua and Ansary 2017, RCC
2018b). To support the National Initiative, ILO Bangladesh launched the “Improving
Working Conditions in the Ready-Made Garment (RMG) Sector” programme in September
2013 with funding from Canada, the Netherlands, and the United Kingdom (RCC 2018g,
2020, ILO 2017a, b). The duration of this program is 22 October 2013 to 30 June 2023 (ILO
2017a).
In addition to these initiatives, two different factory inspection programmes were establishedto make the workplace safer in Bangladesh where ILO fulfils the role of neutral chair. They
are The Bangladesh Accord on Fire and Building Safety in Bangladesh (the Accord), and theAlliance for Bangladesh Worker Safety (the Alliance). The Accord was initiated by over 190
apparel companies from over 20 countries in Europe, North America, Asia, and Australia;
two global trade unions, IndustriALL and UNI Global; and eight Bangladeshi trade unions on
May 15, 2013. It is a five-year independent and legally binding agreement designed to build asafe and healthy Bangladeshi RMG Industry (Accord on Fire and Building Safety In
Bangladesh 2015). The Alliance officially launched its local operation in Dhaka on
December 9, 2013, which is also a five-year independent and legally binding agreement
initiated by a group of North American apparel companies and retailers and brands (26 North
American retailers and brands) to develop and launch the Bangladesh Worker Safety
Initiative (Alliance for Bangladesh, 2013). The targets and objectives of these initiatives are
the same, which is to improve the safety of workers in Bangladesh’s RMG sector (Alliancefor Bangladesh Worker Safety 2014a, Accord on Fire and Building Safety In Bangladesh2014). They share some common courses of action aiming at the improvement of workplace69

safety to safeguard the lives of over four million RMG workers and to retain the confidenceof global buyers following the Rana Plaza accident (Barua and Ansary 2017, Moazzem andIslam 2015, Alliance for Bangladesh Worker Safety 2018f).
Among the common actions considered in these initiatives, improving the structural safety of
RMG factory buildings to ensure a safe working environment is the focus of this research.
4. Actions regarding the structural safety of RMG factory buildings
All garment factories in Bangladesh need to meet accepted standards regarding theirstructural safety, for which they need to pass through a process to ensure and maintain safety(RCC 2018h). It is important because failure by any factory to comply may perpetuate unsafe
working conditions and put workers at risk (Alliance for Bangladesh Worker Safety 2018a).
The initiatives related to the structural safety in the RMG sector of Bangladesh comprised of
two phases, the first phase emphasizing on building safety assessments; and the second phasefocusing on ensuring factory safety through remediation (ILO 2017a, b). The Accord and theAlliance covered factories from which their members source garments and the remaining
factories were covered by the Bangladesh University of Engineering and Technology(BUET) and two private engineering firms TUV SUD Bangladesh (Pvt.) Ltd and Veritas
Engineering & Consultant on behalf of the National Initiative (RCC 2018g, 2020). In January
2014, the Chief Inspector of Factories and Establishment office was upgraded to the
Department of Inspection for Factories and Establishments (DIFE) under the Ministry ofLabour and Employment (MoLE) to support the structural safety actions (ILO 2017a, Barua
and Ansary 2017). The process to ensure structural safety in the Bangladesh RMG sector is
discussed below:
4.1 Building safety assessments
4.1.1 Inspection of factory buildings(a) Preliminary Inspection
All the factories are required to undergo preliminary inspections by qualified assessment
teams (RCC 2018h, ILO 2018). To undertake the initial structural assessment of factorybuildings with a common approach, “Guidelines for Assessment of Structural Integrity andFire and Safety” was developed by the technical experts from the BUET on behalf of the
NTC, the Accord, and the Alliance in 2013 (NTPA 2013). In 2014, Accord and Alliance incollaboration with local and international experts consolidated national rules and regulations
related to building integrity and prepared a comprehensive document consisting of a strict setof guidelines (Accord on Fire and Building Safety In Bangladesh 2014, Alliance for
Bangladesh Worker Safety 2014a). But, in case of insufficiency in local rules, the standards
70have been strengthened by taking support from international rules and guideline where
deemed necessary and practical (Alliance for Bangladesh Worker Safety 2018f, d, i, Accord
on Fire and Building Safety In Bangladesh 2014, Alliance for Bangladesh Worker Safety
2014a). In the process of standards development, the ILO played a vital role (Accord on Fireand Building Safety In Bangladesh 2014, Alliance for Bangladesh Worker Safety 2014a).
Alliance also developed an assessment protocol to conduct the initial assessment (Alliancefor Bangladesh Worker Safety 2014b).
The initial assessments for structures include basic capacity evaluation of critical members orcolumns or foundations through visual inspection (RCC 2018h, ILO 2018). Based on thefindings from the initial building assessments, the immediate threat of collapse of thebuilding from current building use is assumed considering that the condition of the column
ultimately represents the vulnerability of the buildings to collapse. Therefore, the working
stresses of key columns represented by the Factor of Safety (FOS) are calculated, which is theColumn Ultimate Strength, divided by the Column Working Stress. Based on the calculated
FOS, the factory buildings are classified into four color-coded classes indicating the level ofvulnerability (green, yellow, amber, and red where green is the safest and red is the mostvulnerable). The details of these colour coding procedures have been discussed in the
research of Ansary and Barua (2015). Such classification helps to prioritize further work
plans and provide factory owners with a technical understanding of the safety concerns(Alliance for Bangladesh Worker Safety 2018c, RCC 2018h).
(b) Detailed Engineering Assessment (DEA)
After the initial assessment, a Detailed Engineering Assessment (DEA) is carried out for all
the factory buildings. Considering the number of factory buildings and the detailing required
for DEA, it is not possible to carry out the DEA of all factory buildings at the same time.
Here the findings from the initial assessment help to set priority for conducting DEA. The
priority is given to the factory buildings which are found to have a potential structural
weakness after initial assessment (red and amber) or if there is insufficient information anddocumentation on the building structure to determine the safety of the structure (Accord on
Fire and Building Safety In Bangladesh 2018f, DIFE 2015a, Accord on Fire and Building
Safety In Bangladesh 2020b, RCC 2018h, Ansary and Barua 2015, ILO 2018). Later on,
DEA of factory buildings found to be safe during the initial assessment (yellow and green)
are also carried out because in some cases initial assessment may not depict true scenario
which can be verified or found out through DEA.

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To carry out the DEA, “DEA Guidelines” has been developed by DIFE (DIFE 2015a).
According to the guideline, the DEA should only be carried out by the qualified engineeringfirms by the RCC Structural Task Force. For approval, an engineering firm must have at least
three years of relevant experience, should be enlisted with the RAJUK, and must have two
Engineers (can include two structural engineers or one structural and one geotechnicalengineer). The Engineers should be suitably qualified to check, approve, and certify a DEA
Report. Therefore, according to the guideline, the Engineers must have Bachelor’s degree inCivil Engineering from a recognized university, should have a minimum of five years’
experience with both engineers having a combined 15 years of professional experience withproven skills and expertise in the relevant field; should have experience of at least three
DEAs or similar in a comparable area in the last two years, and having knowledge of theinstitutional context and RMG sector in Bangladesh should be considered as an advantage.
According to the DEA Guideline (DIFE 2015a), the DEA involves acquiring accurate as-built
information of the structure to use as input data for analysis and structural analysis of theperformance of the existing structure under the specified loading conditions (Accord on Fireand Building Safety In Bangladesh 2018f, 2020b, ILO 2018). The as-built drawing records
verified architectural drawings of each floor with use, newly developed structural as-built
drawings (plans and sections) accurately reflecting the structural system and all structuralelements, reinforcement details, overall and floor wise load plan, foundation details, etc. For
structural analysis, the existing loading on the structure is prepared including actual deadloads and live loads, as well as details and magnitude of the wind and seismic loading to be
adopted for the analysis. The assessment involves intrusive or destructive assessment, whichmeans partial removal or destruction of some structural elements for assessment, e.g. taking acore out of a concrete column, removing soil for lab testing, or removing finishes to see
hidden or covered details (DIFE 2015a, ILO 2018). For geotechnical investigation (ifrequired), sufficient on-site opening up is carried out to test or investigate the foundation
system, bearing levels, bearing capacities, and condition of a representative sample ofelements below ground for size, corrosion, and condition. Subsoil Investigation is carried out
to verify the existing foundation and check the adequacy
Irrespective of the state of the existing records, testing of the in-situ concrete is mandatory for
all DEAs to verify the concrete strength in the building. In this regard, several sample cores(minimum four) that are representative of the concrete under investigation are collected
ensuring proper witness and documentation. The number and locations of sample cores are
determined by the Engineer considering that concretes in different structures or constructed at72different times are likely to be of differing strength. If the cores are not ideal (i.e. low-quality
concrete, cores include aggregates larger than one-third the core diameter, or if there is thepotential that at least one of the cores may produce an erroneous result through a flaw in thecore or accidental damage) the Engineer considers the benefit of taking additional samples.
According to the guideline, the requirement is minimum four cores with minimum size 100
mm in diameter each. These test values are then used to calculate the equivalent compressive
strength for evaluating the strength capacity of the existing structure using in situ strengths
following ACI 562-13 (ACI 2013).
Some key signs during the preliminary inspection may indicate the deterioration of theapparent condition of the concrete structure, like cracking, spalling, discoloration, leaks,
damp patches, signs of reinforcement corrosion such as staining, delamination of the surface
or even exposed corroded reinforcement, and signs of previous repairs. Figure 1(a) shows flat
plate system structure and diagonal cracks on the ceiling in the cantilever portion and Figure1(b) shows the condition of a column of an RMG factory building observed during apreliminary inspection under the National Initiative representing the apparent condition of theconcrete structure. Even though the visible signs of the deterioration are not yet apparent, theEngineer may suspect it, particularly the corrosion of reinforcement. In these cases, theEngineer uses further lab tests to diagnose the cause of deterioration. Guidance on theselection of appropriate tests has not been prescribed in the Guideline, as the selection
depends largely on the nature of the concrete, the nature of the deterioration, and its
suspected cause. Moreover, multiple tests may have to be considered combining Engineering
judgment and visual inspection to gain a full understanding. The Engineer takes the decisionaccordingly. Some of the suggested tests are visual inspection with localized exposure of
reinforcement where required; carbonation depth measurement test to determine whether thealkalinity of the concrete has been neutralized to the depth of the reinforcing bars and hence
corrosion may be occurring; chloride profile testing to determine the presence of chlorides
which can accelerate the corrosion process; ultrasonic methods to measure the sound velocity
and reflections in concrete to give an indication of potential voids and unseen surfaces, etc.

73Figure 1(a): Flat plate system structure and diagonal cracks on the ceiling in the cantilever
portionFigure 1(b): Condition of a column
Figure 1: Apparent condition of the concrete structure of an RMG factory building observed
during a preliminary inspection under the National Initiative (Source: (National Initiative2020))
74

A structural model of the building is developed using an internationally recognized computer
analysis package, e.g. ETABS, STAAD pro, etc. The analysis based on the as-built drawing
considers the vertical and lateral stability of the structure. Based on the analysis results, theoverall performance of the structure is described indicating the elements which fail to satisfy
the requirements (if any). Then corrective measures are considered and the analysis is re-run.
This process is repeated until the satisfactory performance of all structural elements has been
demonstrated. The final analysis must show the structural adequacy of all the members.
Based on the findings from the DEA, the color-coded classification of the factory buildings
are again revised based on recalculated FOS (Ansary and Barua 2015). Some factorybuildings found to be green through initial assessment have been assessed as red after DEA,
which further justifies the conduction of DEA of all the RMG factory buildings.
(c) Review panel
Factory buildings found to be vulnerable (red) from initial inspection and/or the DEA are
instructed to be deactivated, evacuated, and stop production until the determination of its
safety for re-occupancy through corrective actions (Accord on Fire and Building Safety In
Bangladesh 2020b). Even after deactivation, the factory owners are supported as long as theyshow commitment to safety (Alliance for Bangladesh Worker Safety 2018c). When deemednecessary, the inspection results are submitted to the Review Panel (Accord on Fire andBuilding Safety In Bangladesh 2020b).
The review panel assesses the recommendation of the closure of a factory building (Accord
on Fire and Building Safety In Bangladesh 2020b). In May 2014, a Review Panel along witha review mechanism was established in Bangladesh through the Ministry of Labour and
Employment (MoLE) led NTPA under DIFE to handle urgent safety issues in these garment
factories which are considered to pose an imminent danger to workers' safety and make thedecision regarding the closure or non-closure of such factories (RCC 2018c, Accord on Fireand Building Safety In Bangladesh 2020a, b, Alliance for Bangladesh Worker Safety 2018e).
This panel is comprised of the DIFE, the Accord, the Alliance, BGMEA, and BKMEA withtechnical support from BUET, and consists of four Review Panel engineers: one representing
the Accord, one representing the Alliance, and two representing the BUET on behalf of GoB(RCC 2018c, Accord on Fire and Building Safety In Bangladesh 2020a, b, Alliance for
Bangladesh Worker Safety 2018e). When the Review Panel receives a report from one of thethree initiatives, it immediately convenes a visit to the concerned factory, and then aunanimous decision is taken by the Review Panel engineers ordering full or partial closure offactory operations as necessary. Once closed due to recommendation by the Review Panel,75the factory may be re-opened only after due remediation is completed and the Review Panelhas given its unanimous recommendation confirming improved structural integrity (Alliancefor Bangladesh Worker Safety 2018e).
4.1.2 Corrective Action Plan (CAP) development and approval
After the inspections, the reports are shared with the factory owners along with a list ofobservations and recommendations to improve the safety of the factory addressing the noncompliances (DIFE 2015b, Alliance for Bangladesh Worker Safety 2018d, f, Accord on Fireand Building Safety In Bangladesh 2020b). Based on the report, the factory owners or
managers have to develop a time-bound Corrective Action Plan (CAP) in conjunction withthe expert for technical guidance and support (DIFE 2015b, Accord on Fire and Building
Safety In Bangladesh 2020d). It contains detailed remedial actions corresponding to the noncompliances identified in the inspection with a clear timeline and a financial plan giving
priority to the most urgent non-compliant issues (Accord on Fire and Building Safety In
Bangladesh 2020b, ILO 2018). To guide the process, a CAP development guide has been
prepared by the DIFE (DIFE 2015b). The prepared CAP is submitted to the respective
responsible authority (the Accord, the Alliance, or the NTC respectively) for review andapproval (Alliance for Bangladesh Worker Safety 2018f, Accord on Fire and Building Safety
In Bangladesh 2020b, RCC 2018h).
4.2 Remediation
After CAP approval, the remediation phase begins which refers to the implementation of theapproved CAP (ILO 2018). This will create a greater workplace harmony, help to gain thetrust of buyers, and thereby ensure business continuity which may also lead to more workorders (ILO 2018). This will in turn enhance the image of the Bangladesh RMG industry as asafe source attracting more foreign direct investment (ILO 2018).
4.2.1 Remediation Coordination Cell (RCC)In May 2017, the Remediation Coordination Cell (RCC) was officially launched for the
Bangladesh RMG sector for managing the remediation process (of factories initially under
National Initiative and later other factories under Accord and Alliance), marking a major step
towards improving workplace safety in the Bangladesh RMG sector (RCC 2020, 2018b, a, g,
ILO 2018). It has been established through the collaboration of the GoB, BGMEA, and
BKMEA, in consultation with trade unions and international buyers, with technical support
from ILO, and with funding from Canada, the Netherlands, and the United Kingdom (RCC
2018g, 2020, ILO 2018). RCC is led by the DIFE comprising of four teams: the core body (toensure smooth operations and coordination among and between regulatory departments,)
76

field monitoring committee (to monitor remediation activities at field level), the task force (tomonitor the progress of remediation activities), and case handler and co-case handler (RCC
2018c).
4.2.2 Remediation process
Implementation of the remediation is the responsibility of the factory owners considering it as
an investment to ensure compliance (RCC 2018a, h). Such responsibilities may include
prioritization of remediation work; undertaking the steps as per CAP which may involve
careful planning, temporary relocation or closure of factory production to enable remedialactions to be carried out; engaging an enlisted private consultancy firm and in-house building
engineers to monitor progress; liaising with relevant engineers through a case handler under
the initiatives accordingly, and recording and reporting the progress made regularly (ILO
2018).
The remediation process in factories under National Initiatives is carried out based on the
Remediation Strategy for the RMG sector developed by the Ministry of Labour and
Employment (MOLE) and DIFE with the support of ILO and with inputs from international
engineering specialists (RCC 2020). The Accord and the Alliance follow their strategy for
remediation work (Accord on Fire and Building Safety In Bangladesh 2020b, Alliance for
Bangladesh Worker Safety 2018a). Factories begin remediation through the implementationof the approved CAP working with technical experts (Alliance for Bangladesh Worker Safety
2018f, Accord on Fire and Building Safety In Bangladesh 2020b). Among the developed
corrective actions, some can or need to be addressed immediately, but some can take a longer
time to complete (Alliance for Bangladesh Worker Safety 2018d). Thus the remediation work
continues until the factory addresses all non-compliances as per its CAP (Alliance for
Bangladesh Worker Safety 2018d). The progress of the remediation work is monitored andverified with the assessment report and the CAP through follow-up visits (Alliance for
Bangladesh Worker Safety 2018d, Accord on Fire and Building Safety In Bangladesh 2020b,
ILO 2018). After each follow-up visit, the CAPs are updated accordingly (Alliance for
Bangladesh Worker Safety 2018g, Accord on Fire and Building Safety In Bangladesh
2020d). When the remediation is marked to be completed, a third party final inspection isconducted to ensure the final closure of CAPs (Alliance for Bangladesh Worker Safety
2018f). After the successful implementation of the CAP, the factories receive remediation
completion approval (ILO 2018). On the contrary, if there is any disagreement with theresults of the final remediation assessment, then the case is referred to as the Remediation

77

Coordination Cell (RCC) Review Panel to respect the technical view and ensuringtransparency in decision-making (RCC 2018c).
The GoB is responsible for coordinating between the regulatory bodies as well as theremediation initiatives, and execute its legal mandate to ensure enforcement of national laws
(RCC 2018a). Thus, the Government is accountable for furthermore confirming transparency
and ensuring the availability of the remediation data (RCC 2018a). The BGMEA andBKMEA are responsible for supporting the remediation process by encouraging factoryowners to carry out required remediation work while also taking steps against any factory that
does not carry out remediation as required (RCC 2018a). Workers' organizations can help
monitor the process of remediation in factories and act as a channel through which workers
can convey any concerns in this regard (RCC 2018a).
4.3 Escalation process
In the whole process of assessment and remediation, the RMG factory owners have toparticipate fully maintaining compliance over time (Accord on Fire and Building Safety In
Bangladesh 2018d, Alliance for Bangladesh Worker Safety 2018a). They may fail to do so byrefusing to temporarily evacuate the factory as instructed; showing a lack of progress infinalizing or executing the CAPs within a reasonable timeframe; refusing to resolve worker
complaints on safety issues; showing a lack of cooperation; or conducting fraudulent acts
(Accord on Fire and Building Safety In Bangladesh 2018d, Alliance for Bangladesh Worker
Safety 2018a, RCC 2018b). In such cases, the factories are considered to be in severe andimminent danger. To take measures for such non-compliance within the legal framework, an
Escalation Protocol has been developed by RCC which contains the steps to be taken about
those factories (RCC 2018b). Similar methods are also followed by the Accord and theAlliance.
In such cases of non-compliance, the factory owners are given notice and warning leading totermination of the business relationship and other supports due to the continuation of
inadequate participation (Accord on Fire and Building Safety In Bangladesh 2018d, 2020d,
Alliance for Bangladesh Worker Safety 2018f, RCC 2018b). When a factory is madeineligible, an ineligibility statement and a letter of notification to workers informing them
about the status are generally issued (Accord on Fire and Building Safety In Bangladesh
2018e, RCC 2018b). Factories made ineligible or suspended are handed over to the DIFE,
along with the inspection reports and CAPs to address the ongoing safety concerns at thesefactories (Accord on Fire and Building Safety In Bangladesh 2018d, 2020d, RCC 2018b).

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Except for the cases of fraud or violence, the ineligible factories under the Accord and theAlliance may requalify for business after no less than 18 months from the date of ineligibility(Accord on Fire and Building Safety In Bangladesh 2018d, Alliance for Bangladesh Worker
Safety 2018f). For this purpose, the factories have to inform the relevant initiatives notifying
the completion of CAP and corresponding remediation and requesting for verification
inspection at their own cost (Accord on Fire and Building Safety In Bangladesh 2018d,
Alliance for Bangladesh Worker Safety 2018a). If these factories can demonstratesatisfactory preparation of an acceptable time-bound CAP and completion of all remediation
during the verification inspection, then they can requalify for business (Accord on Fire andBuilding Safety In Bangladesh 2018d, Alliance for Bangladesh Worker Safety 2018a).
Figure 2 illustrates the overall process flow to ensure structural safety in the Bangladesh
RMG sector.
4.4 Overall status determination at different steps of the process
Observing the factories in the whole process of assessment and remediation, the overall status
is determined to increase transparency and support progress (Alliance for Bangladesh Worker
Safety 2018a, RCC 2018g, Accord on Fire and Building Safety In Bangladesh 2020d). Suchstatus includes: completed (completed initial requirements of assessment and remediation);
participating or on track (progressing adequately with requirements); behind schedule orneeds intervention (falling behind on or refusing to follow requirements); critical (at risk ofbeing removed from compliant factory list based on lack of progress with requirements);
suspended or made ineligible (officially removed from compliant factory list based on lack ofprogress in one or more requirements) (Alliance for Bangladesh Worker Safety 2018a,
Accord on Fire and Building Safety In Bangladesh 2020d, 2018e, 2020a).

79

Figure 2: Overall process flow to ensure structural safety in the Bangladesh RMG sector
5. Progress of achieving structural safety of RMG factory buildings
To achieve the goal for structural safety by ensuring appropriate assessment and remediation,
all three initiatives emphasized capacity building. The DIFE appointed 60 engineers under agovernment-funded project to strengthen RCC, where the ILO is supporting RCC for
capacity building with a team of 54 members including 47 Engineers (RCC 2018b, f).
Additionally, DIFE is issuing certificates to firms and enlisting them who are eligible to carryout the activities accordingly to ensure correctness in the process. Till 2018, 26 structural
auditing firms have been listed for remediation works (RCC 2018e). The Accord invested inefforts to increase the Accord engineers’ capacity and experience with support frominternational structural engineering company (Accord on Fire and Building Safety In
Bangladesh 2020b).
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Table 1 shows the status of structural safety initiatives for RMG factory buildings in
Bangladesh including the status of inspection, suspension, and remediation. Except for new,unlisted and extended factories, initial inspection of all the RMG factories has been
completed under all the initiatives (Accord on Fire and Building Safety In Bangladesh 2020b,
Alliance for Bangladesh Worker Safety 2018f, RCC 2020). Many non-compliances withstandards were found in the factories under different initiatives through structural assessment(RCC 2018b). Among them, the main structural safety issues found include the highly
overstressed columns; cracks in beams and floor slabs; discrepancies between design
information and building structure; inadequate additional construction onto cantilevers;
absence of load plan or poor management of the existing load plan; undocumented
constructions and inconsistencies with the structural plan and design drawings; lack of design
check against lateral load; etc. (Accord on Fire and Building Safety In Bangladesh 2018f,
2020b, c). After completion of the inspection phase, the emphasis was switched to
remediation (ILO 2018).
From Table 1 it can be observed that, under the National Initiative, the progress ofremediation is not at the expected level due to inactiveness and deferral by factory owners(RCC 2018b). On the contrary, the Accord and the Alliance have completed remediation in
the vast majority of its affiliated factories, marking an enormous step forward in creating asafer industry for millions of workers indicating the real change in the sector (Accord on Fireand Building Safety In Bangladesh 2020b, Alliance for Bangladesh Worker Safety 2018f).
With time, the pace of remediation has been accelerated dramatically, and the rate ofsuspensions has slowed drastically indicating a strengthened foundation of safety across theindustry (Alliance for Bangladesh Worker Safety 2018f). Thus, both the Accord and theAlliance made a timely review of remediation activities and based on the progress put
necessary pressure for timely completion of remaining works.
Table 1: Status of structural safety initiatives for RMG factory buildings in Bangladesh
Status

AccordAlliance

National Initiative

Total inspected

1631

714

689

Suspended/Ineligible

183

180

-

Remediation completed

92%

94%

39%

Source: Adapted from (Accord on Fire and Building Safety In Bangladesh 2020b, Alliancefor Bangladesh Worker Safety 2018f, RCC 2020)
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Another important component of the structural safety initiatives is the public release of allinspection reports as well as periodic updates to each CAP of all factories throughout
Bangladesh in a single platform. The assessment reports and CAPs for the factories underAccord and the Alliance have been made public through their websites (Accord on Fire andBuilding Safety In Bangladesh 2018b, Alliance for Bangladesh Worker Safety 2018g).
Moreover, data sharing in a single platform has been done through RCC, though the reports
are not updated regularly (RCC 2018k, i, j).
6. Way forward
The assessment initiative has reached its target and the status of remediation is showing
significant progress in structural safety. But, due to limited capacity in terms of humanresources, technical issues, and database management, the process of remediation under the
National Initiative is getting hampered which is reflected by the lack of remediation progress.
Such lack of remediation completion may lead to continued risk of (partial) collapse of thefactory buildings. Therefore, the capacity of the National Initiative should be further
strengthened.
Many factories have not been included in the process due to the unwillingness of the factoryowners. Therefore, the co-operation of rented or shared building owners housing RMG
factories is necessary to make the structural safety initiative successful. Again, the list offactories provided by BGMEA and BKMEA is incomplete. There also remain many factories
which are not a member of any organizations such as BGMEA and BKMEA. Due to
exclusion from membership, these factories fall out of the programs and can no longer export
their products. Despite this fact, these factories are still operating for the local market andoften work as subcontractors for export-oriented factories. So, the list of factories needs to be
updated and verified including the remaining factories to ensure quick completion of theassessment. The safety concerns of backward linkage activities of RMG enterprises (e.g.
textiles, accessories, etc.) have also been excluded from monitoring and inspection which
also need to be taken into consideration.
Whatever the progress is, if accuracy in the whole process is not ensured then the target ofachieving structural safety in the Bangladesh RMG sector may remain unachievable leading
to more accidents like Rana Plaza. The RCC listed the common mistakes in the inspection
process for structural safety which includes general mistakes, mistakes in architectural andstructural drawings, common mistakes of structural DEA firms, and mistakes in the DEA

82

report (RCC 2018d). These mistakes may lead to inaccurate structural assessment andthereby misguide the remediation process. This in turn may fail to achieve the goal ofstructural safety in the RMG sector.
Another challenge is that CAP completion requires a great deal of time and investment,
where some remediation items are costly and burdensome to factory owners (Alliance for
Bangladesh Worker Safety 2018d, f). Despite this fact, such investments can mean the
difference between life and death for the workers (Alliance for Bangladesh Worker Safety
2018f). Thus, these measures are necessary to create a safer workplace and thereby build amore positive image of the Bangladesh RMG sector to ensure business continuity complying
with all relevant safety standards (Alliance for Bangladesh Worker Safety 2018d, ILO 2018).
On average, $250,000 to $350,000 per factory is required for remediation, and for this, manyfactories will require external financing which is difficult for the factory owners in
Bangladesh due to high-interest rates (Alliance for Bangladesh Worker Safety 2018h, ILO
2018).
To financially help the factory owners for remediation, special credit facilities at a lowinterest rate (4-7%) were established by several development partners including Japan
International Cooperation Agency (JICA), French Development Agency (AFD), German
Development Agency (GIZ), International Finance Corporation (IFC), KFW Development
Bank and United State Agency for International Development (USAID) (ILO 2019, 2018).
To facilitate these schemes, some workshops between and among factory owners, employers’organizations, commercial banks, and financing institutes have been organized by the ILO(ILO 2019). Moreover, several outreach activities have been organized jointly by the ILO and
Bangladesh Bank, and the DIFE targeting factory owners to orient them about the available
schemes and the remediation application process (ILO 2019). Furthermore, to improve theremediation finance application process taking feedback from the factory owners andbusiness associations, the “Support to Safety Retrofits and Environmental Upgrades in
Bangladesh RMG sector (SREUP)” programme has been launched with support from ILO
and jointly financed by AFD, EU, KFW and GIZ (ILO 2017a, b).
In addition to these facilities, the Alliance has created several opportunities for financial
support. A combined total of $100 million has been committed to being provided by theindividual Alliance members in this regard. To provide low-cost loans to factory owners withlower interest rates and longer payback periods, the Alliance partnered with the International
Finance Corporation (IFC) to provide financing to five local banks providing a total of $50
83

million and the Alliance has directly contributed $250,000 to fund its operation. To financethe smaller factories ineligible for the IFC program (already undergone an inspection andhave a CAP in place), the Alliance worked with the USAID Development Credit Authority(DCA) with $18 million workings with two local banks where the Alliance contributes $1.5
million to the risk-sharing facility (Alliance for Bangladesh Worker Safety 2018h). To
support the Accord factories a Factory Remediation Fund was established in 2017, which isavailable to all Accord-covered factories since July 2019, meeting certain criteria; e.g. musthave completed at least 75% of the initial remediation (Accord on Fire and Building Safety In
Bangladesh 2018a). The fund would contribute to cover 75% remediation costs, which would
be distributed in four instalments considering factory cooperation and Accord verifiedcompletion of the remediation commensurate with each preceding instalment (Accord on Fireand Building Safety In Bangladesh 2020b). Appropriate disbursement of the fund isnecessary to ensure that the fund is allocated at the right place as required.
After completing the five-year term in Bangladesh the Alliance has ceased operations in
December 2018 (Alliance for Bangladesh Worker Safety 2018b). In 2018, the BangladeshHigh Court issued a restraining order against the Accord prohibiting Accord activities in
Bangladesh beyond November 2018. In May 2019, a labour-brands-industry organization
named RMG Sustainability Council (RSC) was planned to be established to resolve the courtcase which was accepted by the High Court’s Appellate Court. As a result, the functions of
the Accord in Bangladesh were intended to be transitioned to the RSC after June 2020. The
purpose of this council is to ensure the sustainability of the process, which was intended to be
governed by a Board of Directors consisting of an equal number of representatives fromindustry, brands, and trade unions; and closely co-operating with and supporting theregulatory functions of the Government of Bangladesh. It was intended to inherit all
operations, staff, infrastructure, and functions of the Accord and to continue with factory
safety programs until May 2020 (Accord on Fire and Building Safety In Bangladesh 2020b).
However, completion of the remediation does not mean an end to the initiative (RCC 2018h).
These initiatives have led to important organizational learning for Bangladesh as well as forother apparel manufacturing countries. Therefore, to ensure the sustainability of the process
and the system after completion of these initiatives, the remediated factories will have tomaintain safety compliance and to ensure this regular inspection system of DIFE will be
continued (RCC 2018h). In this vision, the RCC will transition into a government-led
Industrial Safety Unit in the long run and will take over the responsibility for relevant
84

workplace safety issues and non-remediated factories once the Accord, Alliance, anddevelopment partner support end (RCC 2018a, c, ILO 2018). It will also identify and include
unlisted, newly established, expanded, and relocated factories in the safety process (ILO
2018). In this regard, the RCC will contribute to enhance the national regulators’ capacity
facilitating knowledge transfer from the Accord and the Alliance as well as enhancecollaboration between them in the long run (RCC 2018g, ILO 2018). It will also be tasked tomonitor workplace safety of all industrial sectors in Bangladesh (RCC 2018h, g, ILO 2018).
But the challenge remains in the successful transition in this regard.
7. Can RANA Plaza Happen Again in Bangladesh?
From the above discussion it can be said that even though the structural safety initiatives havelargely reached its target of inspection and remediation of factories, there is still a long way
forward to reach the goal of workplace safety in Bangladesh RMG factories. There are manysuccess stories. One of the many success stories is the case of Libas Textiles Ltd. Under the
Accord. After an initial inspection in 2014, the factory buildings were found to be unsafe andneeded to be evacuated and production temporarily suspended. In 2016, the factorycompleted its remediation accordingly (Accord on Fire and Building Safety In Bangladesh
2018c). But to achieve the ultimate goal, the way forwards will have to be addressed
accordingly.
There are many cases where factory owners are doing wrong deeds to get a positive reportfrom the assessment. We have one recent experience with two factories supposedly named
AL and PR, during the training of the DIFE inspectors regarding factory assessment andfollow up. These factories located at Dhaka have been assessed under the National initiativein December 2013. There are two buildings under the factories: one is a 6-storied and theother is an 8-storied building having a basement. The ground floor of the two buildings are
housing several shops and go-downs, the basement of the 8-storied building has been used as
the fabric store for one of the factories (factory AL). This factory is occupying both buildings
up to the 3rd floor (connected internally) and up to the 5th floor of the 6-storied building,while the other factory (factory PR) is occupying the 4th to 7th floor of the 8-storied building.
During the inspection in 2013, the 8-storied building was found safe having larger columns
and smaller spans. On the other hand, the 6-storied building was found unsafe having smallercolumns and larger cantilevers for which remediation measures were suggested accordingly.
In early 2015, factory AL moved under Accord. While applying for the Accord, the owner ofthe factory has only used the 8-storied building intentionally hiding the 6-storied building.
85Thus, the 6-storied building was never assessed by the Accord. During a recent visit to thefactory PR (which is still under National Initiative), the DIFE inspectors have found several
cracks in the top floor beams of the 6-storied factory. But when DIFE inspectors werechecking the factories, the owner of factory AL told them that the whole factory is underAccord and has been fully assessed.
This is just a case among many. If these conditions cannot be taken care of then, surely, Rana
Plaza can happen again. More researches are necessary in such cases to explore andunderstand different dimensions of the problems in the way of achieving structural integrityin the RMG sector in Bangladesh.

86

PART-IV

DYNAMIC RESPONSES OF REINFORCED
SOIL MODEL WALL ON
SOFT CLAY FOUNDATIONBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Ripon Hore
Mehedi Ahmed Ansary87

INTRODUCTION
Seismic influence on soil structures played an important role in the area of earthquake
geotechnical engineering and was found considerable development in the recent past. Two
aspects of model testing were given importance, namely a rigid box, and a laminar box. A
laminar box is a sophisticated container than a rigid box which can enhance the accuracy inassessing the ground behavior. In this research, a wrap reinforced soil wall was fabricated onclay soil enclosed by a laminar box and subjected to sinusoidal input motions through theshake table. Moreover, the spacing between the reinforcements and relative density of thebackfill were kept constant in all shaking table tests. Based on shaking table tests, this paper
attempts to investigate the effect of the frequency and acceleration of the base sinusoidal
motion, surcharge pressure, pore water pressure and the number of layers on theaccelerations, horizontal face displacements and soil pressures in wrap-faced retaining walls
under simulated seismic conditions. Wrap faced reinforced soil retaining wall on soft clay ispopular in all over the world because wrap faced layer consumes less space in both sides of
the wall, which is economic and less susceptible to dynamic loading.
According to worldwide experiences, the reinforced soil walls show a flexible
behavior and considerable deformation under seismic loads (Edgar et al. 1989; Collin et al.
1992; Ho and Rowe 1996; White and Holtz 1997; Tatsuoka et al. 1995, 1997; Ling et al.
2001). Reinforced soil walls exhibit better performance level when compared to conventional
retaining walls under seismic load (Roessing and Sitar 1998). Moreover, the cost of
constructions of reinforced soil wall is less than a conventional retaining wall as stated by
Latha and Krishna (2006). Many researchers (e.g., Murata et al. 1994; Matsuo et al. 1998;
Bathurst et al. 2002; Nimbalkar et al. 2006) studied full scale rigid retaining walls andsegmental retaining walls (Nova-Roessig and Sitar 1999; Huang et al. 2003; Ling et al. 2005;
Huang and Wu 2006). The practice of wrap-faced reinforced soil increased rapidly
worldwide due to its better seismic performance. In spite of its importance, very few studies(e.g., Sakaguchi et al. 1992; Koerner 1999; Perez and Holtz 2004; Benjamim et al. 2007) areavailable in this regard.
Richardson and Lee (1975) attempted first small-scale shaking table tests on
reinforced soil walls with metallic reinforcement. Sakaguchi et al. (1992) and Sakaguchi(1996) carried out shaking table tests on 1.5m high reinforced model walls and discussed theinfluence of various parameters. Parameters like relative density of soil, frequency and88amplitude of the motion, reinforcement’s types, and spacing between the reinforcements,
tensile strength and soil interaction, friction angle between reinforcements, facing material,
surcharge pressure and others have influence on deformations of the reinforced soil walls
under seismic load (Roessing and Sitar 1998; Paulsen 2002). The seismic performance ofreinforced soil walls using different reinforcing materials and facing systems were inspected
through experimentations and numerical analyses conducted under various conditions(Richardson et al. 1977; Ling et al. 1997; Matsuo et al. 1998; Koseki et al. 2006; Shahri et al.
2010).
Several shaking table studies were carried out on wrap-faced reinforced soil retaining
walls to gain insight into their behavior under dynamic loads was conducted by Latha andKrishna (2006; 2008), Krishna and Latha (2007), Sabermahani et al. (2009) and Esmaeilabadi
et al. (2014). Moreover, a series of laboratory shaking table tests were performed forobserving the performance of unreinforced and reinforced soil slopes by Srilatha et al. (2013;2014) and Latha and Nandhi (2014). Two different slope angles and reinforcement were usedin their tests. A reduced-scale shake table test investigating the seismic response of slurrywall and sandy soil was presented by Xiao et al. (2014). Moreover, shaking table tests were
performed effectively to investigate the behavior of excess pore water pressure in different
soft soil-foundations of soil-structure interaction (SSI) system (Zhang, et al. 2009). The
performance of geo-cell retaining walls inside a laminar box under seismic shaking
conditions was described by Latha and Manju (2016). Moreover, a series of shaking table
tests on 0.9 m high reinforced-soil wall models with different steel strip lengths were
performed by Yazdandoust (2017).
This study focuses on the seismic design of roadway or railway embankment on soft
clay soil. A scale model testing platform was developed for a single degree of freedom
shaking table tests that symbolize the dynamic free-field conditions of clayey soil where awrapped geotextile-sand retaining wall was erected on clay soil subjected to seismic loading.
A total of 90 shaking table tests were carried out on this model embankment. In order toexplore the possible influence of the impact on the soil, the test implements repeated loading
and unloading process. The effects of frequency, amplitude, surcharge, pore water pressureand displacement along the different elevations were observed in this study.
OBJECTIVE AND SCOPE

89

The objectives of this study were to (a) observe the behavior of wrap-faced reinforced soil
wall under harmonic sinusoidal input motions, (b) fix a suitable scaling for constructing adummy embankment, (c) conduct a series of shaking tests effectively, (d) observe the seismic
response of the scale model embankment due to alterations in frequency, surcharge andacceleration of base shaking and (e) determine the layer by layer response of soil wall due tothese shaking. The specific purpose of the study was to evaluate the seismic response of aconstructed embankment model regarding the input of sinusoidal motions.
TESTING EQUIPMENTS AND TESTING MATERIALS
Equipment Used in This Study
Shaking Table
A computer-controlled servo-hydraulic single degree of freedom shaking table facility wasused to simulate the horizontal shaking action, associated with seismic and other vibration
conditions. The testing platform was made of a 2 m by 2 m size steel base with a 1500 kg of
payload capacity as shown in Figure 1. Shaking was provided by a digitally controlled servohydraulic actuator with an acceleration capacity of 0.05g to 2g and a frequency range of
0.05Hz to 50 Hz having a maximum amplitude of ±200 mm. The total operating system wascontrolled in a dedicated room.
Laminar Box
The ideal container is one that gives a seismic response of the soil model identical to thatobtained in the prototype. In this study, embankment with soft clayey soil model wasconstructed in a laminar box to reduce boundary effects. The fabricated laminar shear box
consists of 24 hollow aluminum layers of frames. Each layer consists of an inner frame withan inside dimension of 915 mm × 1220 mm × 1220 mm. The gap between the successive
layers is 2 mm, and the base layer is rigidly connected to the solid aluminum base plate (915mm x 1220 mm x 15 mm).
The Layers
Each layer consists of a rectangular frame with an internal dimension of 1220 mm × 920 mm
× 50 mm. Transfer ball bearings were used to minimize the friction between the layers. Ball90

bearings consist of one main ball, with a diameter of 12 mm, placed in a hemispherical space
filled with fine balls.
Base Plate and Saturation and Drainage Systems
The lowest layer is fixed on a steel base, rigidly fixed on a steel plate having the same
dimension of laminar layers. The base has some space for watering and dewatering via four
valves. The area of water entry into to the model is covered with porous stone. This
arrangement facilitates both the saturation and drainage of the samples.
MembraneA 2 mm thick rubber membrane, as shown in Figure 2, was placed inside the laminar box forthe hydraulic cut-off system and for the protection of the ball bearings. The significance ofusing this fabric was that it is designed to fold or unfold as sand moves against it rather thanto stretch like a conformist silicone rubber membrane.
Portable Pluviator
Many researchers (e.g., Fretti et al. 1995, Zhao et al. 2006, Choi et al. 2010) attempted indeveloping methods to control uniformity and to achieve desired relative density (Dr) of sandspecimen (Miura and Toki 1982, Rad and Tumey 1987, Lo Presti et al. 1993, Choi et al.
2010, Dave and Dasaka 2012, Srinivasan et al. 2016, Gade et al. 2016). Among thesetechniques, air pluviation method is preferred because of its advantage to reconstituteuniform sand bed for laboratory testing.
In this study, a portable traveling pluviator developed by Hossain and Ansary (2018),
was used to maintain the corresponding relative density of sand layer at 64%. Components ofthe pluviator are shown in Figure 3. The physical model was prepared with two soil layers—
clayey soil as the lower layer and sandy soil as the upper layer.
Materials Used in This Study
Clayey Soil
The clayey soil sample was collected at a depth of 1.5 m below the existing ground levelfrom a location within BUET, Dhaka city, Bangladesh. This sample was at first oven-dried;91

subsequently, the dry lumps were powdered gently by using a wooden hammer; and finallysieved through #200 standard sieve to obtain clean clayey soil powder. The particle size
distribution of the clean clayey soil is presented in Figure 4. The specific gravity Gs of thesoil was determined, from the laboratory test, to be 2.64. X-ray diffraction tests (XRD) was
performed, at a scanning speed of 8° (2θ) min-1 by using Ni-filtered CuKα radiation to
identify the mineral composition of clayey soil. XRD test results are summarized in Table 1.
A careful examination of these data reveals that the predominant mineralogical compositionof the clayey soil was Kaolinite (75%), followed by Illite (25%). An Atterberg limit test was
performed on five representative samples. Average liquid limit (LL) and plastic limit (PL)was established to be 41% and 16%, respectively. The soil was defined as Lean Clay (CL), as
per USCS classification.
Reconstituted Clayey Soil
Burland (1990) demonstrated that the essential engineering properties of reconstituted clay—
shear strength and compressibility—provides a basis to interpret the corresponding propertiesof the in-situ natural clay soil (regardless of it being normally consolidated or overconsolidated). Consequently, in this study, clayey soil was reconstituted by thoroughly
mixing the oven-dried clayey soil powder with an initial water content equal to the LL—aprocedure described by Burland (1990). The thorough mixing of the slurry was attained withthe aid of a ‘Hobart’ rotary mixer. With this slurry, a 610 mm (24 inches) thick reconstituted
clayey soil layer was constructed in the laminar shear box; and then consolidated under theundrained isotropic condition at loads: 15kPa, 20kPa, 25kPa, 30kPa, 40kPa, 60kPa, 80kPa
and 100kPa, respectively. The consolidation process was observed through the settlement ofclayey soil versus time graph, plotted with the aid of calibrated mechanical dial gauges,
instrumented on either side of the laminar shear box. The average settlement curve is shownin Figure 5. This curve shows progressive soil structure collapse, a kind of time dependent
bond weakening in the soil. Moreover, pore water pressure dissipates slowly then due toquicker dissipation settlement increases.
UU triaxial test is suitable for saturated clay, silt, peat in both undisturbed andremolded or reconstituted sample for providing the actual field conditions. UU triaxial test
was performed on the collected soil sample with a shear rate of 1.5 mm/min for each test. The
applied confining stresses for the reconstituted clayey soil samples were 50 kPa and 100 kPa.
The obtained value of undrained shear strength (Su) is 28 kPa.
92

Sandy Soil
Sand was utilized in the construction of the 0.4 m (16'') high reinforced soil zone and backfill
soil. The representative sample was oven dried and sieved through ASTM standard sieves(Passing sieve #4 and retaining on #200) to investigate the properties. The resulting particle
size distribution is shown in Figure 6. The coefficient of uniformity (Cu) and the coefficientof curvature (Cc) was 2.19 and 0.68, respectively. Tthe result indicates a poorly graded,medium to fine sand (SP). Fineness modulus of the sand was 2.7. Other physical parameterssuch as specific gravity (Gs) and maximum dry density (ɤd) had been determined to be 2.65
and 16.6 kN/m3, respectively. The portable traveling pluviator was operated to maintain atarget relative density of 64% for the sand layer. This was achieved by ensuring that sandfalls from the pluviator at a predetermined constant height for each layer laterally andlongitudinally. Strength parameters were determined using the direct shear test. The test
establishes an internal angle of friction φ of 33°.
Reinforcement
The non-woven polypropylene multifilament geotextile (DF50) was used in reinforcing thesand. Table 2 summarizes the properties of the geotextile. Universal tensile testing machine
was used for determining the tensile properties of geotextile. 500 mm × 200 mm sizedgeotextile sample was taken for this test and the gauge length was 100 mm. Three samples
were collected for X and Y direction. Elongation of specimens with increasing load wasmeasured. The load-elongation response of the geotextile was obtained from the wide-width
tensile strength test in both X and Y directions. The average initial modulus (Ei) and secant
modulus (Es) in both directions (X and Y) were 40 KN/m, 141 KN/m, and 47kN/m, 123
KN/m, respectively.
EXPERIMENTAL PROCEDURE
Model Geometry
Height of Clayey Soil Layer
The present study was conducted with a thickness of 610 mm (24 inches) clayey soil layer
foundation above which a 50 mm (2 inches) sand blanket was provided as shown in Figure 7.
This clayey soil layer reflects the height limitation of the laminar box and the total weight of93

the model. Approximately 1 m2 geotextile was placed between the clayey soil foundation andsand blanket. The toe boundary of the wall was horizontally free sliding since the wall wasconstructed on the surface of the foundation. The height of the clayey soil layer of 610 mm(24 inches) was made in three 200 mm (8 inches) stages. Considering the prototype to model
scale being N=10 and scale factor 1/N, the height of the prototype was 6 m (20 ft).
Wall Height and Layers
Wall height is a significant factor governing scale effects and the reaction of the model incontrast with the prototype. Better results were found with the higher height of the sand wall.
The average height of traditional walls usually ranges from 4.5 to 5 m (Sabermahani et al.
2009). A 400 mm (16 inches) high model with a scale factor of 10 was fabricated for thecurrent study. Many shake table tests, on the different height of the sand wall, such as 1.5 m(Sakaguchi et al. 1992; Sakaguchi 1996), 1 m (Matsuo et al. 1998; El-Emam and Bathurst2007), 0.6 m (Krishna and Latha 2007), and 0.33 m (Richardson and Lee 1975) were
performed in the past. The schematic geometry of the experimental model for this study isshown in Figure 7. The sand wall consists of 4 layers and each layer was 100 mm (4 inches)
thick. A concrete block as a surcharge load was placed at the top of the upper layer of thewall after the full construction of four layers.
Facing Type
Wrap-around type wall facing was used with flexible geotextile as shown in Figure 8. Hence,it allowed free movement of the reinforcing enclosure and had no interaction with the rigid
bottom. As per Koerner (1999), each individual facing was formed by wrapping each layer
with soft flexible geotextile element. The extended geotextile was anchored by partial burial
at the end by backfill material.
Sensor Arrangement
The accelerations and lateral displacement were measured using accelerometers anddisplacement transducers (LVDT sensors), respectively at different locations within theclayey soil layer, geotextile wrapped face wall and backfill soil. Six accelerometers (A1, A2,
A3, A4, A5, and A6), two pore water pressure sensors (P1 and P2), four strain gauges(Sg1,Sg2, Sg3 and Sg4), and three linear variable differential transformers (LVDT1,LVDT2

94

and LVDT3) were used in this model test. All the sensors were positioned at predefined
locations during the layer by layer construction of the physical model. One accelerometer,
A1, was fixed to the shake table to record the base acceleration. The other fiveaccelerometers A2, A3, A4, A5, and A6 were placed at elevations 457 mm (18 inches),
710mm (28 inches), 810 mm (32 inches), 915mm (36 inches), and 1015mm (40 inches) mm,
respectively, from the base as shown in Figure 7. A3, A4, A5, and A6 were positioned at aconstant distance of 100 mm (4 inches) from the middle of each sand slice. Two pore waterpressure sensors; P1 and P2, where P1 was set at the base of the clayey soil layer and P2 waspositioned at elevation 457 mm (18 inches) from the base is shown in Figure 7. The porewater pressure sensor (P2) was placed at a height of 457 mm (18 inches) from the base.
However, it was placed to maintain 254 mm (10 inches) horizontal distance from the left faceof the laminar box. Strain gauges were attached with geotextile layers. Sg1 was placed at thebottom of the first layer which was just above the sand blanket. However, the other threestrain gauges Sg2, Sg3 and Sg4 were placed at elevation 100 mm (4 inches), 200 mm (8inches), 300 mm (12 inches), respectively from the top surface of the sand blanket as
depicted in Figure 7. Three displacement transducers (LVDT1, LVDT2, and LVDT3) wereplaced at elevations 150 mm (6 inches), 250 mm (10 inches) and 350 mm (14 inches),
respectively from the top of the sand blanket to measure horizontal displacement of thegeotextile facings of the top three layers. LVDTs were positioned in place using a hanging Tshaped bracket rigidly connected to the laminar box frame.
Surcharge Load and Relative Density
A portable pluviator was used in this study to achieve a uniform density of the backfill
material as described by Hossain and Ansary (2018). 64% relative density of the backfill soil
was achieved by maintaining 200 mm height of fall. The sand which was used for backfill
material had been passed ASTM standard sieve number 4 (4.75 mm) and was retained at 200
number sieve (0.075 mm).
Three different surcharge loads 0.7 kPa, 1.12 kPa and 1.72 kPa were employed in thisstudy. The surcharge load was made in the form of a concrete slab. 0.1g, 0.2g, 0.3g, 0.4g and
0.5g acceleration based sinusoidal waves were applied to the model for each surcharge loadand corresponding measurements were made using the different sensors described before.
Prototype-Model Similitude
95

The reliability of model tests depends on whether the model can represent the real behaviorof the prototype system. Model size in this study was fixed according to the facilities
available for this test. Precise scaling of soil walls and reinforcement properties is needed forconsidering the stress-dependent behavior of the soil and boundary conditions.
The model is scaled to achieve similitude with the prototype wall. It is not possible topredict the accurate behavior of the prototype with compared to the reinforced model wallusing 1g shaking table test (Krishna and Latha 2007, Latha and Krishna 2008 and
Sabermahani et al. 2009). The exponent of confining pressure (α) was assumed to be 0.5 forsand (Kokusho 1980, Yu and Richart, 1984). Considering limitations due to the dimensionsof the model container and the capacity of shaking table, the prototype to model scale ratio(N) usedwas 10 as presented in Table 3.
Fundamental Frequency
As physical models are shorter versions of prototype walls, the frequency of induced input
motions is recommended to scale accurately to produce similar effects to those ofearthquakes on prototype walls. It is an essential phase in the seismic design to determine thenatural frequencies of the structure.
Reinforced-soil retaining walls of typical heights (i.e., H > 10 m) and backfill material
are generally considered as short-period structures as addressed by Sabermahani et al. (2009).
The response of the wall to ground motion is dominated by the fundamental frequency of thestructure (Hatami and Bathurst, 2000). The resonant frequen cy of the walls also changes
significantly with the height of the wall (Latha and Krishna, 2008).The fundamental
frequency of wall model was calculated based on impact test performed before the firstshaking of actual tests. The fundamental frequency of the soil embankment model wasaround 16 Hz. Wall response is critically dependent on the base frequency of the structure,
the range of the applied frequencies were kept in a range distant from the fundamental
frequency of the walls to avoid resonance which was addressed by Kramer (1996) andBathurst and Hatami (1998).
Input Motions

96Harmonic sinusoidal type of base acceleration was designated for this current parametricstudy. This harmonic sinusoidal base acceleration is more aggressive than an archetypal
earthquake with the same predominant frequency and amplitude which was observed bydifferent researchers in the past (Bathurst and Hatami 1998; Matsuo et al. 1998; El-Emamand Bathurst 2007).
Keeping in mind the fundamental frequency of the embankment modelwere subjectedto 1Hz, 3Hz, 5Hz, 10Hz, 12Hz, and 15 Hz frequencies as input motions. The frequency range
used in the present study was less than the natural frequency of the system and hence themodels were not subjected to resonance. Since frequencies of 2–3 Hz are representative oftypical predominant frequencies of medium to high frequency earthquakes (Bathurst andHatami, 1998), the rest of the frequency ranges were used to evaluate the seismic behavior
patterns of the existing embankment models. Based on the scale factor of frequency presented
in Table 3, these values are respectively corresponding 0.18Hz, 0.54Hz, 0.90Hz, 1.8Hz,
2.16Hz and 2.7 Hz frequencies for the prototype. Moreover, the statement is relevant only if
the exponent of confining pressure for soil stiffness α is kept equal to 0.5.
A few researchers experimented with base accelerations of low amplitude, such as
0.1g to 0.2g (Krishna and Latha 2007; Latha and Manju 2016; Helwany et al. 2017) and somewere with high amplitude, such as 0.3g to 0.5g (Sabermahani et al., 2009; Edinçliler andToksoy, 2017). In this current research embankment model was subjected to several different
excitations from 0.1g (low amplitude) to 0.5g (high amplitude) peak base accelerations, eachbeing employed after completion of the previous motion. The duration of each shaking was
decided to be kept for at least 5 seconds. Exactly 90 numbers of harmonic sinusoidal shaking
were used for this research as presented in Table 4. All the shaking tests were applied to the
newly constructed individual embankment models. A specific base acceleration was achieved
through changes in input amplitude for each frequency (1Hz, 3Hz, 5Hz, 10Hz, 12Hz, and 15
Hz) and surcharge pressures (0.70 kPa, 1.12 kPa, and 1.72kPa).
RESULTS AND DISCUSSION
Results were obtained from several shaking table tests on the embankment model as
discussed earlier. The parameters varied in tests were base acceleration, frequency, andsurcharge pressure. The base acceleration was kept as 0.1g, 0.2g, 0.3g, 0.4g, and 0.5g indifferent tests as shown in Figure 9. The range of frequency was varied from 1 Hz to 15 Hz.
97The surcharge pressure was kept as 0.70 kPa, 1.12 kPa and 1.72 kPa. The thickness of thesoft clayey soil layer was 610 mm. Reinforced-soil wall was constructed using sand upon theclayey soil layer in equal lifts (Sv) of 100 mm to achieve a total wall height (H) of 400 mm.
The height of clayey soil and reinforced sand wall together including the sand blanket (50mm thick) had been taken as the full model height (M) which was 1060 mm. The length (L)of the geotextile reinforcement at the interface of the sand layers was kept the same in all
tests as 510 mm. The model wall was subjected to 5 to 75 cycles of sinusoidal shaking for
obtaining 5 seconds of data.
Acceleration Response
Typical time-acceleration histories of the shake table tests ST1, ST7, ST13, ST19 and ST25
with 0.7 kPa surcharge and 0.1g, 0.2g, 0.3g, 0.4g, and 0.5g base acceleration and 1 Hz
frequency of base sinusoidal motion at same elevation are shown in Figures 9a to 9e.
Acceleration amplification is the proportion of maximum peak to peak acceleration value inthe soil to that of the corresponding value of the base motion. The acceleration amplification
profile along the height of the wall for various inputs of base motion after each test of 5 to 75
cycles of sinusoidal motion is presented in Figures 10a to 10f. However, to compare theacceleration amplification within the reinforced sand wall, the elevation (z) was represented
in non-dimensional shape subsequent to normalizing by the full reinforced sand wall height(H=400 mm) as can be seen from Figures 10a to 10c. On the other hand, to compare theacceleration amplification between clayey soil layer and reinforced sand wall, the elevation(z) was represented in non-dimensional shape subsequent to normalizing by the height ofclayey soil and reinforced sand wall together (M=1060 mm) as can be seen from Figures 10d
to 10f. Maximum acceleration amplification was observed almost at the top of the wall in all
the tests. This observation was in consensus with the results of physical tests reported by
Telekeset al. (1994), Murata et al. (1994) and El-Emam and Bathurst (2005).
Effect of Base Acceleration on Acceleration Amplification in Reinforced Sand Wall
The acceleration amplifications along the height of the wall for different base accelerations of
0.1g, 0.2g, 0.3g, 0.4g and 0.5g from ST2, ST8, ST14, ST20, and ST26 tests, respectively,
which was conducted at 3 Hz frequency and 0.7 kPa surcharge pressure is presented in Figure
10a. Acceleration amplifications were found to be higher with increased base accelerations.
After analyzing all the test results, it was observed that acceleration amplifications at the top98

of the wall for 0.1g and 0.2g base accelerations were close to 1.11, whereas it was 1.19, 1.29
and 2.01 for 0.3g, 0.4g, and 0.5g base acceleration, respectively. The present study was also
compared with the study of Krishna and Latha (2007) as shown in Figure 10a. The
acceleration amplification along the height of the wall for different base accelerations of 0.1g,
0.15g and 0.2g from T4, T6 and T7 model tests (Krishna and Latha, 2007) was comparedwith the present study. In that study, tests were conducted at 2 Hz frequency, 0.5 kPa
surcharge, and four layers of reinforcement (total reinforced wall height of 600 mm, eachlayer thickness was 150 mm). Acceleration amplifications were increased with increased baseaccelerations for all the curves. However, acceleration amplifications at the top of the wall,for 0.15g and 0.2g base accelerations, were very close to 1.70. At the top of the wall, thevalue of acceleration amplifications was 1.42 for 0.1g base acceleration. The pattern ofamplification for the current study and the study of Krishna and Latha (2007) are almost
same. The only difference are observed at the lower part of the curves, where for the current
study, amplification values are relatively high since there is a soft clay layer at the bottom of
the reinforced sand wall.
Effect of Surcharge on Acceleration Amplification in Reinforced Sand Wall
Acceleration response against different surcharge pressures was presented from tests ST1,
ST31 and ST61 as depicted in Figure 10b. These tests were conducted with 0.7 kPa, 1.12 kPa
and 1.72 kPa surcharge pressures at 1 Hz frequency and 0.1g base acceleration. Accelerations
at the top of the wall were inversely proportional to the surcharge pressures for all the tests. It
is observed from the figure that the acceleration amplification values were 1.85, 1.64 and1.42 for 0.7 kPa, 1.12 kPa and, 1.72 kPa surcharge pressures, respectively. Comparison of thepresent study with the study of Krishna and Latha (2007) is also shown in Figure 10b. The
acceleration amplifications for 1 Hz frequency and 0.1g base acceleration along the height of
the wall for surcharge pressures of 0.5 kPa, 1.0 kPa and 2.0 kPa from T1, T2, and T3 model
tests of Krishna and Latha (2007) was compared with the present study. Accelerations at the
top of the wall were inversely proportional to the surcharge pressures, with amplification
values of 1.63, 1.47 and 1.37 for 0.5 kPa, 1.0 kPa, and 2.0 kPa surcharge pressures,
respectively. The pattern of amplification for the current study and the study of Krishna andLatha (2007) are almost same.
Effect of Frequency on Acceleration Amplification in Reinforced Sand Wall

99

The effect of frequency on the acceleration response along the height of the wall for tests
ST1, ST2, ST3, ST4, ST5 and ST6 with frequencies of 1Hz, 3Hz, 5Hz, 10Hz, 12Hz and 15
Hz which were conducted at 0.1g base acceleration and 0.7 kPa surcharge pressure is shownin Figure 10c. From the figure, it is observed that the acceleration response against frequency
variation is not directly proportional. In fact, within the range of tests conducted accelerations
were amplified less for 1Hz, 3Hz and 5 Hz and more for 10Hz and 12Hz frequencies
compared with that of 15 Hz frequency at all elevations. Moreover, accelerations at
normalized elevations of 0.125, 0.375, 0.625 and 0.875 were amplified closer or slightly
more than 1 for the frequency 1 Hz. The differences in acceleration amplifications for various
frequencies were increased with increase in wall height. At a normalized height of 0.875, for
1Hz, 3Hz, 5Hz, 10Hz, 12Hz, and 15 Hz frequency, the values of acceleration amplification
were 1.04, 1.24, 1.46, 3.26, 2.47, and 1.80, respectively. Moreover, the acceleration
amplification values were 0.94, 0.99, 1.05, 1.51, 1.38 and 1.24 for 1Hz, 3Hz, 5Hz, 10Hz,
12Hz, and 15 Hz, respectively at a normalized height of 0.125. These observations highlightthe role of the fundamental (resonance) frequency of the system and the proximity of the baseexcitation frequency (Kramer, 1996). Figure 10c also compares the present study with thestudy of Krishna and Latha (2007). The acceleration amplifications along the height of thewall for different frequency of 1Hz, 2Hz and 3 Hz from T1, T4, and T5 model tests ofKrishna and Latha (2007) was compared with the present study. These three tests wereconducted with the base acceleration of 0.1g and 0.5 kPa surcharge on the test wall with four
layers of reinforcement. The pattern of amplification for the current study and the study of
Krishna and Latha (2007) for 1 Hz to 3 Hz frequency are almost same.
Comparison of Acceleration Response between Reinforced Sand Wall and Clayey Soil
Layer
To compare the acceleration amplification between clayey soil layer and geotextile wrap
faced sand wall, the height of clayey soil and reinforced sand wall together (M) had beentaken as the full model height, which is 1060 mm. The acceleration amplifications along theheight of the wall for different base accelerations of 0.1g, 0.2g, 0.3g, 0.4g and 0.5g from ST2,
ST8, ST14, ST20 and ST26 tests, respectively, which were conducted at 3 Hz frequency and0.7 kPa surcharge is shown in Figure 10d. From this figure, it is observed that in the clayeysoil layer at a normalized elevation of z/M=0.43, the acceleration amplifications wereincreased with increased base accelerations. It is also observed that in clayey soil layer at
100z/M=0.43, acceleration amplifies less with compared to the top of the wall (z/M=0.95). At the
top of the wall acceleration amplification ranged from 1.11 to 2.01 which were greater thanamplification of 1.05 to 1.23 at z/M=0.43.
It is observed that in clayey soil layer at z/M=0.43, for 0.7 kPa, 1.12kPa and 1.72 kPa
surcharge pressures at 1 Hz frequency and 0.1g base acceleration (from ST1, ST31, and ST61
tests), the acceleration amplitude was 0.99, 0.92, and 0.84, respectively. Moreover, at the topof the wall, for 0.7kPa, 1.12kPa and 1.72 kPa surcharge pressures, the acceleration amplitude
values were 1.68, 1.49, and 1.29, respectively as presented in Figure 10e. Accelerations at the
top of the wall were inversely proportional to the surcharge pressures for all the tests, which
is logical.
In clayey soil layer at the normalized elevation of 0.43, the acceleration amplitude
values were 0.89, 1.07, 0.96, 1.42, 1.21 and 1.18 for 1, 3, 5, 10, 12, and 15 Hz frequencies(from ST1, ST2, ST3, ST4, ST5, and ST6 tests), respectively. However, at the top of the wall(z/M=0.95), for 1 Hz, 3 Hz, 5 Hz, 10 Hz, 12 Hz, and 15 Hz frequencies, the acceleration
amplitude values were 0.95, 1.11, 1.17, 3.26, 2.27, and 1.74, respectively as shown in Figure
10f. The highest acceleration amplitude at top of the wall is for a base input frequency of 10
Hz as can be seen from Figure 10f. From the figure, it is observed that the acceleration
response against frequency variation is not directly proportional.
Displacement Response
Horizontal face displacement along the height of the wall was monitored using three LVDTs
positioned as shown in Figure 7. The displaced face profiles from various tests after 5 to 75
cycles of sinusoidal motion are presented in Figures 11a to 11c. Here elevation (z) andhorizontal displacements (δh) are presented in non-dimensional from after normalizing themby the height of the wall (H=400 mm).
Figure 11a depicts the normalized displacement profile for different baseaccelerations of 0.1g, 0.2g, 0.3g, 0.4g and 0.5g from tests ST66, ST72, ST78, ST84, andST90 (as shown in Table 4), respectively. From the figure, it is observed that the normalized
displacements were relatively high at higher base accelerations at the normalized elevation ofz/H= 0.875. This phenomenon had similarity to the test results of Sakaguchi et al. (1992) andKrishna and Latha (2007). A maximum horizontal displacement of 2.11% of the total wall101

height (H), for 0.5g, was observed compared with 1.96% for 0.1g base accelerations. No
significant change of displacements had occurred at z/H= 0.375 and z/H= 0.625 compared toat z/H= 0.875.
The normalized displacement profile for tests ST2, ST32, and ST62 after 5 to 75
cycles of base motion, which were conducted at 0.1g base acceleration and 3Hz frequency,
were providing an insight into the effect of different surcharge loadings of 0.7kPa, 1.12kPa
and 1.72 kPa as shown in Figure 11b. It was observed that the displacement response against
surcharge variation was inversely proportional at all elevations. Moreover, this observation
was concurrent with the test performed by Krishna and Latha (2007). The maximum
displacement of the wall was (δh/H=2.00%) at a surcharge pressure of 0.7 kPa, whereas it
was decreased to (δh/H=1.92%) at a surcharge pressure of 1.72 kPa.
According to the Figure 11c, it can be said that, the displacement response against
frequency variation was not directly proportional. The normalized displacement profile
observed for tests ST1, ST2, ST3, ST4, ST5, and ST6 with frequencies 1 Hz, 3 Hz, 5 Hz, 10
Hz, 12 Hz, and 15 Hz, respectively, which were conducted at 0.1g base acceleration and 0.7
kPa surcharge pressure as presented in Figure 11c. The displacement had occurred more atz/H=0.875 from the range of tests were conducted. The maximum displacement of 2.04%
was observed for 12 Hz frequency at z/H=0.875.
Pore Pressure Response
Typical pore water pressure variations obtained from the tests are presented in Figures 12a,
12b and 12c. The height of clayey soil layer (S) was taken as 610 mm in the case of porewater pressure. The variations of the pore water pressure from model tests ST65, ST71,
ST77, ST83, and ST89 with base accelerations 0.1g, 0.2g, 0.3g, 0.4g, and 0.5g, respectively
for 15Hz frequency and surcharge load of 1.72 kPa is shown in Figure 12a. The pore waterpressure response against base acceleration variation was directly proportional as can be seenfrom the figure. The maximum pore water pressure was 0.38 kPa at a base acceleration of
0.5g. The maximum pore water pressure for model tests ST66, ST72, ST78, ST84, and ST90
was0.06kPa, 0.09 kPa, 0.17 kPa, 0.26 kPa, and 0.38 kPa, respectively.
Variations of the pore pressure from model tests ST24, ST54 and ST84 with ofsurcharge 0.7 kPa, 1.12 kPa and 1.72, kPa, respectively for 15Hz frequency and base102

acceleration of 0.4g is presented in Figure 12b. From the figure, it is observed that pore waterpressure response against surcharge variation was inversely proportional at all elevations. The
maximum pore water pressure was 0.37 kPa at a surcharge load of 0.7 kPa. The maximum
pore water pressure for model tests ST24, ST54 and ST84 were 0.37 kPa, 0.33 kPa, and 0.26
kPa, respectively.
The effect of frequency for a given base acceleration and surcharge load on porewater pressure for tests ST1, ST2, ST3, ST4, ST5, and ST6 with the frequency of 1 Hz, 3 Hz,
5Hz, 10Hz, 12Hz and 15Hz for 0.1g base accelerations and 0.7 kPa surcharge is shown in
Figure 12c. From the figure, it is observed that pore water pressures response against
frequency variation is not directly proportional. In fact, pore water pressures increased lessfor 1 Hz, 3 Hz and 5 Hz and more for 10 Hz, 12 Hz frequencies compared with that of 15 Hz
frequencies at all elevations. The highest pore water pressure was 0.105 kPa at 10 Hz
frequency.
SUMMARY AND CONCLUSIONSA series of shaking table studies were carried out on a 1/10 scale model wrap-faced
reinforced soil wall to obtain apparent insight into their behavior under harmonic sinusoidal
input motions. It was observed that the seismic response of the scale model embankment wassignificantly affected by changing frequency, and acceleration of base shaking and surchargeloads.. Accelerations were amplified both for sand and clayey soil layers, at higher elevations
and with high base acceleration. Aaccelerations were also amplified with low surchargepressures. It was observed that the acceleration amplification response against frequency
variation was not directly proportional. However, the face deformations were high for highbase acceleration at the top of the reinforcing layer and impact was relatively low at the otherlayers. In general, the face deformations were high for low surcharge pressures. It was also
observed that the frequency had an inverse impact on face deformations. Pore water pressure
gets intensified with increased base acceleration. Increase in surcharge pressure shaking
results in a decrease in pore water pressure and the difference being more at higher
elevations. These results are helpful to observe the dynamic behavior of the wrap faced soil
retaining wall resting on the soft clay layer which is helpful for the design process of this typeof retaining walls considering the seismic environment of Bangladesh.

103

Figure 1: Testing platform

Figure 2: Membrane is being attached inside the laminar box

104Figure 3: Portable pluviator for construction of the model wall

Figure 4: Grain size distribution of clayey soil

105

Figure 5: Average settlement curve

Figure 6: Grain size distribution of sand106Figure 7: Schematic illustration of physical model with configuration and instrumentation

Figure 8: Finished wrap-faced wall

107

0.3

0.4
Z/H=0 (A1) (ST1)

Z/H=0 (A1) (ST7)0.2

Acceleration (g)Acceleration (g)

0.2
0.1

0

-0.1

0

-0.2
-0.2

-0.3
0

1

2

3

4

5

6

-0.4

7

0

Time (s)

1

2

3

(a)

5

6

7

(b)

0.6

0.8

Z/H=0 (A1) (ST13)

Z/H=0 (A1) (ST19)

0.4

Acceleration (g)

0.3

0

0

-0.4

-0.3

-0.8

-0.6
0

1

2

3

4

5

6

7

0

8

1

2

3

4

5

6

7

8

Time(s)Time (s)

(c)

(d)
1

Z/H=0 (A1) (ST25)

0.5

Acceleration (g)Acceleration (g)4Time (s)

0

-0.5

-1
0

1

2

3

4

5

6

7

Time (s)(e)
Figure 9: Input time-acceleration curves (0.1g to 0.5g) at frequency 1 Hz

108

1

Normalised Elevation, z/H

0.8

0.6
Test no. Acc.
ST2
0.1g
ST8
0.2g
ST14 0.3g
ST20 0.4g
ST26 0.5g
T4(Lata) 0.10g
T6(Lata) 0.15g
T7(Lata) 0.20g

0.4

0.2

0
0

0.5

1
1.5
Acceleration Amplification

2

2.5

Figure 10a: Effect of base acceleration on acceleration amplification
1

Normalised Elevation, z/H

0.8

0.6

0.4

Test no. Surch.
ST1
0.7 kPa
ST31 1.12 kPa
ST61 1.72 kPa
T1(Lata) 0.5 kPa
T2(Lata) 1 kPa
T3(Lata) 2 kPa

0.2

0
0

0.5

1
1.5
Acceleration Amplification

2

2.5

Figure 10b: Effect of surcharge on acceleration amplification109

1
Test no. Freq.
ST1
1Hz
ST2
3Hz
ST3
5Hz
ST4
10Hz
ST5
12Hz
ST6
15Hz
T1(Lata) 1Hz
T4(Lata) 2Hz
T5(Lata) 3Hz

Norrmalised Elevation, z/H

0.8

0.6

0.4

0.2

0
0

0.5

1

1.5
2
Acceleration Amplification

2.5

3

3.5

Figure 10c: Effect of frequency on acceleration amplification
1

Normalised Elevation, z/M

0.8

0.6

0.4
Test no. Acc.
ST2
0.1g
ST8
0.2g
ST14 0.3g
ST20 0.4g
ST26 0.5g

0.2

0
0

0.5

1
1.5
Acceleration Amplification

2

2.5

Figure 10d: Effect of base acceleration on acceleration amplification (considering total heightof the model including the clay layer for normalization, M=1060 mm)

110

1

Normalised Elevation, z/H

0.8

0.6

0.4
Test no. Surch.
ST1
0.7 kPa
ST31
1.12 kPa
ST61
1.72 kPa

0.2

0
0

0.5

1
Acceleration Amplification

1.5

2

Figure 10e: Effect of surcharge on acceleration amplification (considering total height of themodel including the clay layer for normalization, M=1060 mm)
1

Normalised Elevation, z/H

0.8

0.6

0.4

Test no. Freq.
ST1
1Hz
ST2
3Hz
ST3
5Hz
ST4
10Hz
ST5
12Hz
ST6
15Hz

0.2

0
0

0.5

1

1.5
2
Acceleration Amplification

2.5

3

3.5

Figure 10f: Effect of frequency on acceleration amplification (considering total height of themodel including the clay layer for normalization, M=1060 mm)

111

1
0.9

Normalised Elevation, z/H

0.8
0.7
0.6
0.5
0.4

Test no.
ST66
ST72
ST78
ST84
ST90

0.3
0.2
0.1
0
1.85

1.9

1.95
2
2.05
Normalised face Displacement, h/H (%)

Acc.
0.1g
0.2g
0.3g
0.4g
0.5g

2.1

2.15

Figure 11a: Effect of base acceleration on displacement profile
1
0.9

Normalised Elevation, z/H

0.8
0.7
0.6
0.5
0.4
0.3

Test no. Surch.
ST2
0.7 kPa
ST32
1.12 kPa
ST62
1.72 kPa

0.2
0.1
0
1.75

1.8

1.85
1.9
1.95
Normalised face Displacement, h/H (%)

2

2.05

Figure 11b: Effect of surcharge on displacement profile

112

1
0.9

Normalised Elevation, z/H

0.8
0.7
0.6
0.5
Test no. Freq.
ST1
1 Hz
ST2
3 Hz
ST3
5 Hz
ST4
10 Hz
ST5
12 Hz
ST6
15 Hz

0.4
0.3
0.2
0.1
0
1.7

1.75

1.8
1.85
1.9
1.95
Normalised face Displacement, h/H (%)

2

2.05

Figure 11c: Effect of frequency on displacement profile
1
0.9

Normalised Elevation, z/H

0.8
0.7
0.6
0.5
0.4
Test no.
ST65
ST71
ST77
ST83
ST89

0.3
0.2
0.1

Acc.
0.1g
0.2g
0.3g
0.4g
0.5g

0
0

0.05

0.1

0.15
0.2
Pore Water Pressure (kPa)

0.25

0.3

0.35

Figure 12a: Effect of base acceleration on pore water pressure

113

1
0.9

Normalised Elevation, z/H

0.8
0.7
0.6
0.5
0.4
0.3
Test no. Surch.
ST24
0.7 kPa
ST54
1.12 kPa
ST84
1.72 kPa

0.2
0.1
0
0

0.05

0.1

0.15
0.2
0.25
Pore Water Pressure (kPa)

0.3

0.35

0.4

Figure 12b: Effect of surcharge on pore water pressure1
0.9

Normalised Elevation, z/H

0.8
0.7
0.6
0.5
0.4

Test no. Freq.
ST1
1 Hz
ST2
3 Hz
ST3
5 Hz
ST4
10 Hz
ST5
12 Hz
ST6
15 Hz

0.3
0.2
0.1
0
0

0.05
0.1
Pore Water Pressure (kPa)

0.15

Figure 12c: Effect of frequency on pore water pressure114

Table 1: Brief description of XRD test
Compound Name

Percent (%) by atomic weight

SiO2

67.1747

Al2O3

15.8718

Fe2O3

7.7982

K2O

3.8247MgO

1.9221TiO2

1.4624CaO

0.7423Na2O

0.6149P2O5

0.1960SO3

0.1568MnO

0.0960

ZrO2

0.0439Cr2O3

0.0339Rb2O

0.0246

ZnO

0.0205

SrO

0.0171115

Table 2: Geotextile specification
No.

Details

DF 50

1.

Reinforcement typeMechanically bonded needle punched

2.

Yarn material (staple Fibre)

Polypropylene

3.

Mass/unit area (gsm)

322

4.

Aperture Size , O95 (μm)

130

5.

Thickness (mm)

2.54

6.

Ultimate Tensile Strength (kN/m)

15.5

7.

Ultimate Tensile Strength at 2% strain (kN/m)

15.97

8.

Ultimate Tensile Strength at 5% strain (kN/m)

16.57

Table 3: Scale factors of selected engineering variables (Prototype-Model Similitude)
Description

Parameter

Scale factor

Scale factor

Scale factor

M/P

P/M

Acceleration

a

1

1

1

Density

ρ

1

1

1

Length

L

1/N

0.10

10

Stress

Σ

1/N

0.10

10

Straing

1/N1-α

0.32

3.125

Stiffness

G

1/Nα

0.32

3.125

d

2-α

0.031

32.25

1-α/2

5.62

0.18

1/N

3

0.001

1000

2

0.01

100

Displacement
Frequency
Force

f
F

1/N
N

Force/L

F/L

1/N

Shear Wave velocity

Vs

1/Nα/2

0.56

1.785

Time

t

1/N1-α/2

0.178

5.62

*P-Prototype; M-Model

116

PART-V

A STUDY ON RECENT EARTHQUAKES IN
AND AROUND BANGLADESHBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: ASM Fahad Hossain
Mehedi Ahmed Ansary117

INTRODUCTION:
An earthquake is a sudden shaking movement of the surface of the earth that is known as a quake, trembler ortremor. Earthquakes can range in size from those that are so weak that they cannot be felt to those violent
enough to toss people around and destroy whole cities. The seismicity or seismic activity of an area refers to thefrequency, type and size of earthquakes experienced over a period of time. Bangladesh is consistently ranked
one of the most vulnerable countries to natural disasters, but this is primarily because of the frequent occurrenceof tropical cyclones, floods, heat waves and other weather-related disasters, combined with the massive
population living in vulnerable conditions. Bangladesh is situated in a modestly dangerous domain and thedensity of population here and the infrastructural condition are been constantly a matter of worry here. As there
is no technology developed to predict the time of occurring, makes earthquake a far devastating one. Recent
earthquake in several parts of the world and the destruction occurred, clearly showing that Bangladesh
has to take necessary steps to face the earthquake at any time in future.
Bangladesh is surrounded mostly by India and a few by Myanmar and she lies where three tectonic platesEurasia, India, and Burma meet making her one of the most tectonically active regions in the world. In the past
200 years, Bangladesh has experienced many devastating as well as mild earthquakes. After the independence in
1971, Bangladesh has been shaken up by more than 250 earthquakes and some of those were greater than 6.0
magnitude. But the risks cannot be ignored. The 1897 Great Indian Earthquake with a magnitude of 8.7, which
is one of the strongest earthquake in the world killed 1542 and affected almost the whole of Bangladesh(Oldham, 1899). Recently, Bilham et al. (2001) pointed out that, there is a very high possibility that a huge
earthquake will occur around the Himalayan region based on the difference between energy accumulation in thisregion and historical earthquake occurrence. The population increase around this region is the last 50 times thanthe population of 1897 and city like Dhaka has population exceeding several millions. It is a cause for great
concern that the next great earthquake may occur in this region at any time. So that detailed seismic response
analysis of his area is necessary. Also observation of recent earthquake record is needed. If we observe the rateof noticeable earthquake is increasing year wise. In April 2015 Nepal earthquake (also known as the Gorkha
earthquake) killed nearly 9,000 people and injured nearly 22,000. It occurred at 11:56 Nepal Standard Time on
25 April 2015, with a magnitude of 7.8Mw or 8.1Ms and a maximum Mercalli Intensity of VIII (Severe). The
2009 Bhutan earthquake occurred on 21 September at 14:53 BTT (08:53 UTC) in the eastern region of Bhutan
with moment magnitude of 6.1. The tremors were felt as far as Tibet. At least eleven people are reported to havebeen killed and seven in Bhutan.

SEISMOLOGY OF BANGLADESH:
Bangladesh is located close to the boundary of two active plates (Indian plate in the west and Eurasian plate in
the east and north) the country has always been under threat of an earthquake that might be so catastrophic itwill kill people in less than a minute. Bangladesh is surrounded by a number of tectonic blocks responsible formany earthquakes in the past. Calcutta, Assam, Tripura are the three very earthquake prone regions that are
joined to Bangladesh in the borders in the Northern, Western and North-Eastern part respectively. If we consider
the tectonics and geology, five major faults are significant for the occurrences of devastating earthquakes:

118

1.

Bogra Fault Zone2.

Tripura Fault Zone

3.

Shilong Plateau

4.

Dauki Fault Zone

5.

Assam Fault Zone

Bogra fault is a normal or gravity fault. It is very close to the Bogra town and Jamuna River. It was active in
Palaeogene andNeogene times. Movement along the Bogra fault led to the depositionof a large amount of
sedimentary pile within the Bogragraben.Tripura is one of the states of India surrounded by Bangladesh andtwo other states Mizoram and Assam of India. The area is surrounded by Koplili fault; Kaladan fault etc. whichhave produced many earthquakes. The Tripura Naga orogenic belt is a zone of highly faulted tertiary deposits
which has witnessed earthquakes of moderate magnitudes.Shillong plateau is characterized as a seismically
active and geologically complex region located on the collision boundary betweenIndian and Eurasian plate in
the Meghalaya state of India. The general altitude of the Plateau is about 1,500 m. The plateau is composed of
the Precambrian Metamorphic rocks and the Tertiary and Quaternary deposits are limited on the southernfoothills of the Shillong Plateau indicating the successive uplift of the Shillong Plateau and the process started
from the Pliocene time. Dauki fault zone is a 300 km long north dipping reverse fault along the MeghalayaBangladesh border and inferred to go through the southern margin of Shillong plateau. It has a major role indeforming the surrounding areas. The Dauki fault is believed to be active in the past. Though it is inactive in the
recenttimes still it is considered as one of the major threats for Bangladesh forthe occurrence of devastating
earthquakes.Figure 1 shows stechtonic framework of Bangladesh.

Figure 1: Tectonic Framework of Bangladesh (Banglapedia, 2015)

119Dhaka city, the soul of Bangladesh is highly vulnerable to the earthquake disaster due to high density of
population, unplanned infrastructure and close proximity with India and Myanmar's active seismic area, poor
economic condition, poor emergency preparation and recovery capability.Bangladeshwas divided into four mainearthquake zones in BNBC 2014 (Figure 2) where four zones have PGA values varied to 0.12, 0.20, 0.28 and
0.36. Figure 2 shows the seismic zoning map of Bangladesh. A seismicity map of Bangladeshis also shown in
Figure 3.

Figure 2: Earthquake zones of Bangladesh (BNBC 2014)

Figure 3: Seismicity Map of Bangladesh (M. A. Ansary)120

RECENT EARTHQUAKE RECORD (MAGNITUDE AND FOCAL DEPTH):
The magnitude, focal depth and locations of five year’s earthquake having Richter magnitude more than 3 thatwas felt from 2015 to 2019 (up to October) near Bangladesh are represented in the table 1 to table 5 below.

GRAPHICAL REPRESENTATION OF EARTHQUAKE RECORD ACCORDING TO MAGNITUDE
AND YEAR:
From the earthquake records of five years shown above, two maps were prepared according to magnitude andearthquake occurrence year. They are shown in figure 4 and figure 5. From the magnitude graph it was seen
that, earthquake with magnitude of 5 to 7.9 occurred at Nepal, magnitude of 3 to 4.9 were happened at thenorthern outside of Bangladesh that means at the area between Bangladesh and Bhutan. At the eastern outside of
Bangladesh that means the portion between Bangladesh and Myanmar, the values were within 4 to 5.9. From theyear wise graph it was seen that, considerable earthquake records were at the northern outside of Bangladesh atlast year 2019 that indicates a major earthquake may happen here from the stored energy and can make adevastating effect.

Figure 4: Earthquake Magnitude in and around Bangladesh from 2015 to 2019121

Figure 5: Earthquake occurrence in and around Bangladesh from 2015 to 2019
COMPARISON BETWEEN MAGNITUDE AND FOCAL DEPTH OF DIFFERENT EARTHQUAKEIN VARIOUS DATES:
Some comparisons between magnitude and focal depth of different earthquake in 2019 (up to October), 2018,2017, 2016 and 2015 are shown in figure 6 and figure 7. It was seen that Earthquake with more than 3 Ricter
magnitudes was occurred in all five years in February, April, August and September. January and December
have comparatively less earthquake record. Focal depth was higher in 2016 related to others in April August.

Figure 6: Comparison between magnitudes of different earthquake from 2015 to 2019122

Figure 7: Comparison between focal depths of different earthquake from 2015 to 2019

All data of magnitude vs focal depth of earthquake record shown in this article of five years were plotted in agraph and an equation was developed from the straight line graph. The straight line graph is shown in figure 8
and the equation is given below.

Focal Depth (KM)

(Y = 2.416X + 14.54) (R² = 0.005)
160
140
120
100
80
60
40
20
0

y = 2.416x + 14.543
R² = 0.0052
0

.

2

4

6

8

10

Magnitude

Figure 8: Focal Depth vs Magnitude of different earthquakes from 2015 to 2019
EFFECT OF SOME MAJOR RECENT EARTHQUAKE:
The primary effects of earthquakes are ground shaking, ground rupture, landslides, tsunamis, and liquefaction.
Fires are probably the single most important secondary effect of earthquakes. Some major effects occurred fromrecent earthquake around Bangladesh are described below:►Nepal experienced a major earthquake on 25 April 2015, which has a magnitude of Mw 7.8 earthquake with
an epicenter 77 km (48 miles) northwest of Kathmandu, which devastated large parts of the country. The quake
hit at 11:56 am local time (06:11 GMT) according to US Geological Survey (USGS).The main shock of 25
April and several other aftershocks including that of 12 May caused the death of about 9,000 people, injury to
22,000, and loss and damage equivalent to USD 7 billion. Figure 9 shows the devastating effect of Nepal
Earthquake.

123

Figure 9: Nepal Earthquake 2015 (todayonline.com and theguardian.com)►The 2016 Imphal earthquake struck northeast India in the state of Manipur on January 4 with a moment
magnitude of 6.7 and a maximum Mercalli intensity of VII (Very strong). Its epicenter was located in the
Tamenglong district; about 30 km west of Imphal. At least eleven people were killed, 200 others were injured
and numerous buildings were damaged, as shown in figure 10. The quake was also strongly felt in Bangladesh.
It was also extensively felt in eastern and north-eastern India.The earthquake, which hit at 4:35 a.m. on 4
January local time (23:05 UTC, 3 January), was centered in an isolated area. Imphal has a population of morethan 250,000.

Figure 10: Imphal Earthquake 2016(indianexpress.com)►A magnitude 6.8 earthquake struck Myanmar 25 km (16 mi) west of Chauk on 24 August 2016 with amaximum Mercalli intensity of VI (Strong). It struck at 5:04 pm local time (10:34 UTC), and was centered in an
isolated area. The estimated depth was 84.1 km. Tremors from the earthquake were felt in Yangon, in theeastern cities of Patna, Guwahati, and Kolkata in India, in Bangkok in Thailand and in Dhaka, the capital of
Bangladesh.According to reports, several temples in the nearby ancient city of Bagan were damaged and four
people were reported dead, as shown in figure 11.

Figure 11: Mawlaik, Myanmar Earthquake 2016 (asiasociety.org and bangkokpost.com)

124►A magnitude 5.7 earthquake struck India 20 km (12 mi) east north-east of Ambassa in the state of Tripura on
3 January 2017 with a maximum observed intensity of 6-7 EMS. It struck at 2:39 pm local time (09:09 UTC),and was centered in an isolated area. The estimated depth was 32.0 km. One person died and five others were
injured in India. At least 50 houses were damaged due to landslides that occurred in Dhalai district, while roads
were blocked after trees were uprooted. According to the Tripura State Disaster Management Authority, at least
6,727 buildings were damaged in Tripura in the districts of Dhalai and Unakoti, as shown in figure 12. Shaking
was felt in many parts of north-eastern India including as far as Kolkata. The tremor was also felt in neighboring
Bangladesh, where two people died and three others were injured.

Figure 12:Ambassa, India Earthquake 2017 (financialexpress.comand livemint.com)►A strong 6.1-magnitude earthquake struck Arunachal Pradesh the US Geological Survey said.The epicenter ofthe shallow earthquake was about 40 kilometers (25 miles) southeast of Along, and 180 kilometers southwest of
the state capital Itanagar.The devastating effect is shown in figure 13.

Figure 13: Along, Arunachal Pradesh, India Earthquake 2019(hindustantimes.com and cnbctv18.com)
EFFECTS AND DAMAGES IN BANGLADESH DUE TO NEPAL EARTHQUAKE 2015:
On April 25 the earthquake jolted the Dhaka, Chittagong, Barisal, Rajshahi, Dinajpur, Rangpur, Kushtia anddifferent parts of the Bangladesh. According to disaster management and relief ministry eighteen districts of
Bangladesh have been affected in this earthquake, which were felt in almost all corners of the country.
Department of Disaster Management (DDM) has received further feedback from local level officials in total 19
Districts [5] .In Dhaka, residents of high-rise buildings were seen running down in panic as apartments started
shaking. According to the ministry’s disaster Response Centre, four people died in as many districts. It said atleast 200 people were injured during evacuation and 17 buildings had either tilted or cracked (bdnews24.com).

125

Figure 14 shows people frightened and come out of their offices when the strong motion was felt. Figure 15
shows one building has tilted over another one. Seismograph recording of earthquake in Bogra, Jamuna Bridge
and Ruppur are shown in Figure 16.

Figure 14: Many people come out of their offices when a strong earthquake was felt in Dhaka and elsewhere(The Daily Star)

Figure 15: One building has tilted over another one (bdnews24)
BograEQ.xls

JMB-WESTEQ.xls

0

10

20

30

40

50

60

70

Time

80

90

RUPPUREQ.xls

25042015-1214PM

100

110

120

130

140

Bogra.grf

25042015-001354PM

15
13.5
12
10.5
9
7.5
6
4.5
3
1.5
0
-1.5
-3
-4.5
-6
-7.5
-9
-10.5
-12
-13.5
-15

20
15
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EW-A (cm/s2)

EW-A (cm/s2)

EW-A (cm/s2)

25042015-1318PM
15
13.5
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10.5
9
7.5
6
4.5
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1.5
0
-1.5
-3
-4.5
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-10.5
-12
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-15

5
0
-5
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-20

0

10

20

30

40

50

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70

Time

80

90

100

110

120

130

140

0

20

40

60

Time

80

100

Jamuna.grf

120
Ruppur.grf

Figure 16: Seismograph Recording in Bogra, Jamuna Bridge and Ruppur (M. A. Ansary)
CONCLUSION:
Bangladesh is consistently ranked one of the most vulnerable countries to natural disasters, but this is primarily
because of the frequent occurrence of tropical cyclones, earthquake, floods, heat waves and other weatherrelated disasters, combined with the massive population living in vulnerable conditions. From the above data
indicate that the earthquake occurred in Bangladesh was not so devastating. But it actually does not show thereal picture of the risk of Bangladesh about the earthquakes. In this article, only the magnitude and focal depth126

of five years of earthquakes in and around Bangladesh were represented. From the findings from the research, it
can be easily noticed that the northern and eastern side of Bangladesh is very much vulnerable that may cause
major earthquakes anytime with a great loss of life and property and also the recent earthquake occurrence rateis increasing. The topographical position and the historical quakes obviously demonstrate that the administrationof Bangladesh should put much stress on seismic tremors and how to limit its harm. Dhaka is situated at highhazard zone for seismic tremor and a phenomenal human fiasco may happen in the city whenever for even a
moderate to substantial tremor. The disaster management system of Bangladesh should be more developed tominimize the loss during earthquake. The building codes should be followed by the citizens and the government
should try to increase the awareness about the safety rules of earthquakes among the mass people.

127

PART-VI

SITE RESPONSE AND LIQUEFACTIONSUSCEPTIBILITY ESTIMATION OF A SITE
IN NORTHERN PART OF BANGLADESHBANGLADESH NETWORK OFFICE FORURBAN SAFETY (BNUS), BUET, DHAKA

Prepared By: Nusrat Jahan
Mehedi Ahmed Ansary128

INTRODUCTION
For important sites like ports, power plants, etc, estimation of liquefaction potential isimportant owing to the existence of some important infrastructures. Resistance of soil toliquefaction has turned into an essential condition to be estimated before any major
construction during recent times. Liquefaction is the alteration of the previously secure coarse
aggregate of soils becoming a liquid mass owing to the enhancement of pore water pressure.
According to Marcuson (1978), liquefaction is mainly observed in areas where the soil
mainly consists of the sandy type and the water table is situated near the ground level. The
cyclic random loading of a seismic event is the source for water pressure inside the soil pores
to enhance, which causes the soil mass to perform as a fluid. The 1964 Alaska, USA, andNiigata, Japan earthquakes are the major examples where liquefaction played the main role inincreasing the damage level of those two events (Kramer, 1996; Youd, 2014). After these two
events, liquefaction becomes an important factor to be assessed before any new important
construction takes place. Also, a wide-ranging investigation has been done recently in thisfield to avoid any such catastrophic damages in the future (He et al, 2020; Jamali andTolooiyan, 2020; Karanjekar and Pachpor, 2020; Thokchom et al, 2018; Zhang et al., 2015;
Zhang and Goh, 2016; Zhang et al., 2021). In addition, there are numerous studies for site
response analysis (Chandran and Anbazhagan, 2020; Groholski et al., 2016; Kaklamanos etal., 2015; Rahman et al., 2021) being carried out recently. The findings of many researchers(Ansary, 2003; Ansary and Sharfuddin, 2002; Ansary and Arefin, 2020; Rahman et al., 2021)
advocate that important cities of Bangladesh have been struck by numerous historical large
earthquakes, that is why the current study is important.
In this research, the solar power plant site in a neighborhood in Gaibandha town, Bangladesh
has been considered. The site is located beside the Brahmaputra River in the North-Westernpart of Bangladesh. The soil of the site is mainly composed of loose to medium dense silty
fine sand up to a depth of 25m.
In this study, through 1D site response analysis, PGA values at the surface have been
estimated and later used for determining liquefaction potential index at the site. Although,many reseaches have been carried out to estimate liquefaction potential of different sites asmentioned above, there are almost no research where 1D site response analysis (using
equivalent nonlinear, nonlinear and average shear-wave velocity based on top 30m) has been129

specifically carried out to obtain the PGA value at the site for liquefaction potential
estimation.
EXISTING FAULTS AROUND BANGLADESH
Raoof et al. (2017) has developed 3-D seismic velocity structures for the adjoining areas of
Bangladesh to gain knowledge about the geodynamic processes of this region. This study
gives useful information about the site condition. The Indian plate is under-thrusting theHimalayas at low angles at the Main Boundary Thrust (MBT) along the entire ~2500 km long
Himalayan belt (Molnar et al., 1973; Baranowski et al., 1984). It is subducting at dip angles~30°–50° at the Indo-Burmese arc with the Benioff zone down to depths ~150–200 km, as
observed from the intermediate-depth seismicity (Satyabala, 1998, 2003; Li et al., 2008).
Several researchers suggested that subduction along the Indo-Burmese arc has slowed down
or may have stopped, and the Indian plate is dragged to the north, which is partly
accommodated by the long Sagaing fault in central Burma (Le Dain et al., 1984; Chen and
Molnar, 1990). The Sagaing is a fault in the plate boundary. Its sinistral movement shows apart of the junction of Burma and India plates.
The major faults that have an impact on the study area are: The Indus-Tsangpo Suture (ITS),
the Main Boundary Thrust (MBT), the Main Central Thrust (MCT), and the Main Frontal
Thrust (MFT) (see Figure 1). These are the major Himalayan crustal discontinuities spanningthe length of the northern border of the northeast Indian region (Yin and Harrison, 2000; Yin,
2006).
SEISMIC HAZARD ASSESSMENT
Seismic Data Processing
A homogeneous seismic database is a vital instrument in any assessment of earthquake
hazards. An earthquake database that involves pre-1900 (all historical), and post-1900 (thatoccurred after 1900) events need to be compiled. Organizing lists of seismic events in a
database that covers the studied region; requires collecting data from the various publishedcatalogs, literature, and those provided by national and international agencies.
The earthquake catalog has been assembled from the International Seismological Centre(ISC) UK and the United States Geological Survey (USGS) event data. The maximum
130seismic magnitude for this study has been estimated from this catalog. The developed catalog
has been homogenized to obtain a unified magnitude value MW. This has been carried out
applying conversion relations for magnitude provided by Scordilis (2006) and Kolathayar andThallak (2012). The past earthquakes from the period 1760 to 2020 have been selected using
the cut-off value of magnitude MW ≥ 3, the events are presented in Figure 2.
In probabilistic seismic hazard analysis, it is generally considered that the seismic
occurrences follow a Poisson distribution (Kadirioğlu et al., 2018). For this purpose, adeclustering algorithm to remove aftershock and foreshock from the original catalog is used.
Numerous declustering processes have been suggested over the years such as Gardner andKnopoff (1974), and Reasenberg (1985) algorithms with different space-time windows.
These methods are implemented in the software ZMAP (Wiemer, 2001). In the present study,
the Gardener and Knopoff (1974) algorithm has been applied for declustering. Afterdeclustering, 1038 seismic events have been compiled for the above-mentioned period. This
study assumed equal weightage to all faults considered. Linear, as well as smoothed point
source models, have been considered to estimate the PGA values (Kolathayar et al., 2012).
Figure 3 presents the study location together with the in-situ test locations.
Ground Motion Prediction Equations
Ground motion prediction equation (GMPE) is a relation among ground motion, magnitude,
distance, and other relevant parameters. Through these equations, ground motion at any
location can be estimated if magnitude, distance, and other parameters are known. GMPEs
pertinent to the current tectonic region with shallow earthquakes such as Abrahamson andSilva (1997), Iyengar and Raghukanth (2004), Amiri et al. (2007), and Tabassum and Ansary,(2020) have been used in this study to determine PGA at the bedrock. Equation (1) presents
the GMPE developed by Tabassum and Ansary, (2020) for rock type soil based on 273
earthquake data from 2005 to 2017 for Bangladesh and North-East Indian region, where
PGAh is the horizontal acceleration which depends on magnitude (M) and hypocentral
distance (r). σ is the standard error.
log PGAh = 0.80532 + 0.00029*r + 0.36134*M – 0.92616*log r ± 0.3705 σ (1)131Finally, for the assessment of liquefaction at the study site, PGA value needs to be
determined at the surface. For this purpose, DEEPSOIL software has been used here to obtain
the PGA value.
METHODOLOGY FOR SITE RESPONSE AND LIQUEFACTION ASSESSMENT
Figure 4 shows the flow chart of the total methodology employed in this study. The
properties for dynamic analysis of soils, such as accelerogram of earthquakes, shear wave
velocity (Vs), material damping, and shear modulus reduction curves are necessary toestimate site amplification parameters through site response analysis. Other soil parameters,for example, internal friction angle, over-consolidation ratio, plasticity index, and unit weight
are also required for this purpose. This information is gathered from 66 borehole locations
and one PS-Log location (near BH-23) of the study site as shown in Figure 3 to carry out thesite response analysis.
SPT and Shear-wave Velocity Profile
Figure 5 presents a typical cross-sectional profile of the study site. Generally, the top 10m is
composed of very loose to loose silty fine sand, from 10m to 30m, the soil consists of
medium dense silty fine sand, from 30m to 80m, the soil consists of dense silty fine sand andbeyond 80m, the soil consists of dense silty fine sand with gravel. Appendix-A presents the
SPT contours at various depths of the study site.
The shear wave velocity (Vs) information from the study location has been compiled fromthe ground level up to a depth of 120 m (Figure 6). The data has been determined utilizing asuspension PS-log system. In nearby Jamuna Railway Bridge and Rooppur Nuclear Power
Plant sites, the bedrock (when the shear-wave velocity is larger than 760 m/s) is located at
150 m below the ground level. So, the bedrock for this site is also assumed to be at 150m
depth.
Material damping and shear modulus reduction relations
For the site response analysis, the dynamic parameters of shallow ground layers are
significant. These are illustrated by the damping ratio and shear modulus reduction curves toassess the soil condition under cyclic loading. Due to the unavailability of these curves for the
study site, the suggestion of many researchers (Kumar et al., 2014; Chandran and132

Anbazhagan, 2020) to utilize the existing standard curves may be followed. Several damping
ratios and shear modulus reduction relations can be found in different available literature(such as Seed and Idriss, 1970; Sun et al., 1988; Darendeli, 2001) to estimate the dynamic
parameters of numerous soil patterns. According to different researchers (Darendeli, 2001;
Bajaj and Anbazhagan, 2019), effective confining pressure, loading frequency, plasticity
index, loading cycle numbers, strain, and soil type are the main essential properties that affectthe damping ratio and shear modulus reduction. In the study site, the soil layer from theground level up to 120 m deep is mostly consisting of sandy soils (Figure 6). According toHashash et al. (2010) for sandy deposits, the damping ratio and shear modulus reduction
relations recommended by Darendeli (2001) are preferred to analyze the site assessment by
nonlinear means. Hence, the material damping and normalized shear modulus reduction
relations suggested by Darendeli (2001) are applied to estimate the sandy deposits nonlinear
characteristics of the study site (Figure 7).
Bedrock and surface hazard spectra
According to the BNBC (2020), site classes are defined as follows: type SA, when
Vs30>760m/s; type SB when Vs30 varies between 360m/s and 760m/s; type SC when Vs30
varies between 180m/s and 360m/s; type SD, when Vs30<180m/s. The normalized design
acceleration response spectrum proposed in BNBC (2020) for ground condition (Vs > 760m/s) [soil type SA] has been considered in this study as shown in Figure 8a. This spectrum
for soil type SA has been multiplied by PGA for a return period of 475 years (in this case, it
is 0.23g) to obtain the target spectrum, which is here referred to as the hazard spectra at the
bedrock (UHS). In this particular site, the mean shear-wave velocity for the initial 30m of asoil column is 183 m/s (using Figure 6), which falls in the soil type C (SC) category. The
normalized design acceleration response spectrum for soil type SC as per BNBC (2020) has
been multiplied by 0.23g to obtain the surface UHS. Both these UHSs are shown in Figure
8b.
Earthquake acceleration time history and spectral matching
Recently, Bangladesh has set up a seismic network all over the country (Ansary and Arefin,2020). Although this network has recorded several weak ground motions, so far no strong
ground motion has been recorded by this system. Strong ground motions having the time
history data expressed in terms of acceleration are needed for site assessment. For this133

purpose, freely available six worldwide data are used: the 1940 Imperial Valley USA (USGS
station 5115), the 1989 Loma Prieta USA (090 CDMG station 47381), the 1994 Northridge
USA (090 CDMG station 24278), the 1995 Kobe Japan (Kakogawa CUE90), the 1999
Kocaeli Turkey (Yarimca, KOERI330) and the 1999 Chi-chi Taiwan (TCU045) earthquakes.
Also, four strong ground motion time histories have been generated using synthetic
accelerogram following the algorithm suggested by Halldorsson and Papageorgiou, (2005).
The spectral acceleration of the earthquake and synthetic accelerograms are fitted to thetarget bedrock response spectra to generate time history data compatible with the target
spectra (Figure 9a and 9b). The matching of spectra has been done by using the
SEISMOSOFT software to adapt the time history data by fitting its spectral acceleration withthe target response spectrum (Figures 9 and 10). The spectral response of 6 earthquakes and 4synthetic acceleration time histories are fitted with the target spectra for a return period of
475 years (Figures 11 and 12). The time versus acceleration data of the fitted spectral
acceleration curve has been applied for the site assessment (see Figure 10).
One-dimensional site assessment
DEEPSOIL software resulted from the research of Hashash et al. (2010) has been used tocarry out one-dimensional nonlinear and equivalent-linear site assessment analysis. The
Equivalent Linear (EL) model employs an iterative procedure in the selection of the shear
modulus and damping ratio soil properties as pioneered in program SHAKE. These properties
can be defined by discrete points or by defining the soil parameters that define the backbone
curve of one of the nonlinear models. Non-linear (NL) analysis solves the equations of
motions in time domain using the Newmark β method (implicit) or the Heun’s Method(explicit). The available soil models are: General Quadratic/ Hyperbolic Model (GQ/H),
Pressure-Dependent Modified Kondner Zelasko (MKZ), Discrete Points (Equivalent Linear)and User-Defined (UMAT). The analysis can be performed with or without porewaterpressure generation.
The soil model for response analysis requires material damping and shear modulus reduction
relation in normalized form. The relations suggested by Darendeli (2001) have been utilized
in this research. To utilize the relationships of Darendeli(2001), the following soil

parameters are needed: vertical stress under the effective condition in the initial state, initial134coefficient of lateral earth pressure, loading frequency, loading cycle numbers, OCR ratio,
and plasticity index (Figure 7).
DEEPSOIL has numerous soil models to carry out the site assessment analysis as mentioned
earlier. In the current study, the model suggested by Groholski et al. (2016) has been applied
to match material damping and modulus reduction relations of the materials of the soilcolumn with the benchmark relations of Darendeli (2001) for certain shear strength. Thismodel consists of a non-Masing reloading-unloading hysteretic setup based on the general
quadratic/hyperbolic model (GQ/H). The effective shear strength condition has been applied
for all calculations by considering the water table at the top of the surface. According to
Groholski et al. (2016), the GQ/H form can depict the relatively big shear stress-strain
characteristics of the materials to precisely approximate the motion of the ground at thesurface for relatively big strains. Viscous damping term which has been frequencyindependent has been utilized for nonlinear response assessment in the time domain. During
response analysis, the accelerogram of the matched bedrock spectral acceleration has been
applied for the motion of the ground at the bottom of the soil column.
Liquefaction assessment techniques
Several methods have been built up to evaluate the liquefaction susceptibility of soils. This
paper focuses on the following methods to estimate liquefaction potential: Seed-Idriss
simplified procedure (Seed and Idriss, 1971), Japanese Code of Bridge Design (Tatsuoka etal., 1980), Japanese Code of Bridge Design based on the Chinese criterion (Ishihara, 1993),
and Chinese Code for Seismic Design of Buildings method (GB50011-2010) (as outlined on
Sun et al., 2015). These methods are Standard Penetration Test (SPT) based liquefaction
assessment methods where empirically determined curves—utilizing Cyclic Stress Ratio(CSR) and Cyclic Resistance Ratio (CRR)—are employed to predict liquefaction and noliquefaction occurrence. Appendix-B presents the description of these three methods. Afterthe detailed assessment, liquefaction severity is evaluated based on liquefaction potential
index (LPI), similar to that suggested by (Iwasaki et al., 1978; Iwasaki et al., 1981, 1984).
Iwasaki et al. (1984) has classified the LPI in three levels: (a) LPI < 5, implies ‘Low
liquefaction potential; b) 5 ≤ LPI ≤ 15, implies ‘High’ liquefaction potential and c) LPI > 15,
implies ‘Very High’ liquefaction potential.
RESULTS AND DISCUSSIONS
135

Development of surface hazard spectra
The hazard spectra at the surface (UHS) of the study site have been developed utilizing thethree site assessment methods: site coefficients based on Vs30, equivalent-linear, andnonlinear (Figure 13). The spectral acceleration of the hazard spectra at the surface at
different periods are at all times bigger than that of the hazard spectra at the bedrock for
Vs30-based site coefficients, whereas the spectral acceleration of hazard spectra at thesurface are smaller at relatively low periods (from 0.06 s to 0.20 s) and bigger at large periods(0.20 s and 4 s) in comparison with the spectral accelerations of the hazard spectra at the
bedrock during equivalent-linear response assessment. Similarly, the spectral acceleration of
the hazard spectra at the surface is smaller at low periods (from 0.02 s to 0.35 s) and larger atlarge periods (0.35 s and 4 s) in comparison with the spectral accelerations of the hazard
spectra at the bedrock during nonlinear response assessment. The period of the highest
acceleration has moved towards the larger periods during the equivalent-linear and nonlinear
models for the Vs30 dependent assessment.
The equivalent-linear model-based hazard spectrum (UHS) is in general larger than the
nonlinear-based model. The period of the highest acceleration is almost equal for both cases.
The Vs30 dependent UHS is not suitable to represent the characteristics of the alluvial
deposits of sufficient thickness of the site well since the bedrock is located at a depth ofaround 150m. Kaklamanos et al. (2015) have commented that the equivalent-linear model
happens to be erroneous at a shear strain of around 0.1 to 0.4%. Also, they mentioned that thenonlinear model can better predict the motion at the ground surface at large shear strain. The
obtained biggest shear strain is larger than 0.1% in the majority of the layers throughout site
response analysis. Hence, for thick sedimentary deposits, the nonlinear site assessment issuitable for the determination of UHS at the surface. The average obtained PGA value at thesurface for a return period of 475 years is around 0.27g using the nonlinear assessment
technique.
Liquefaction susceptibility estimation
In this study, the liquefaction susceptibility at each layer of 1.5m intervals where SPT-N
value exists and liquefaction potential index (LPI) values have been estimated for 66
boreholes located all over the site up to a depth of 20m. The locations where borehole data
are not present, LPI have been estimated by the Kriging method. LPI estimation has been136

made for the three methods Seed and Idriss (1971) method (later amended by Youd andIdriss, 2001), Japanese method (Tatsuoka et al., 1980), and Chinese method (Sun et al., 2015)
for two cases: (a) A lower bound value of PGA=0.19g (for 23% probability of exceedance in
50 years or a return period of 200 years) and Mw = 7.5 and (b) an upper bound value of
PGA=0.27g (estimated through nonlinear site assessment for a return period of 475 years)
and Mw = 8.15 which has been estimated with the help of past seismic data. Figure 14 shows
the factor of safety versus depth plot at BH-01 for the three methods for PGA=0.19g and
Mw=7.5 (lower bound case). Tables 1 and 2 have presented LPI values for the three methods
and for lower and upper bound cases. To show LPI contours, the three levels of hazard as
described by Iwasaki et al. (1984), have been utilized as shown in Figure 15 for the lower
bound case. The LPI plot of the upper bound case has not been shown here since all thevalues exceed 15.
It is apparent from the results of the LPI values that the site is mainly composed of inferior
quality soil. There is a high probability that sand boils and lateral spreading may occur at thesite during a seismic event. This may become decisive for essential structures within the
power plant site. From the findings of the current study, it may be concluded that structureswith a shallow foundation for this site may be recommended only if the entire soil up to adepth of 20m is fully improved by suitable ground improvement techniques. Alternatively,
the length of the pile greater than 20m below EGL may be recommended along with ground
improvement of the top 5m of the loose sand soil zone. In this research, borehole data of 66
locations with SPT have been utilized for a relatively small area. A large number of boreholes
for a relatively small area of the site would generally produce dependable results in theassessment of LPI.
CONCLUSIONS
During the whole design lifecycle, the assessment of the Liquefaction Potential Index (LPI) is
important for the development of a power plant site in inferior quality soils for the proper
working condition of the facility. The PGA value at the bedrock level has been evaluatedutilizing past seismic data, seismo-tectonic details, and suitable GMPE relations. To
approximate the time history at the surface in a site where the loose soil deposits of larger
than 30 m thick are located on top of the bedrock, 1D nonlinear site assessment is needed. A
nonlinear site assessment using DEEPSOIL has been performed to estimate the site
amplification and consequently to obtain the surface level PGA at the site. The LPI of the137power plant site has been assessed utilizing the SPT-N value data at 66 locations of the site
applying three methods and two sets of PGA values and magnitudes up to a depth of 20m.
The soil of the entire power plant site is highly vulnerable to liquefaction up to a depth ofabout 20 m. For this reason, two alternative foundation solutions are recommended for thissite. The first one is providing a shallow foundation above an improved ground up to a depthof 20m or providing 20m deep piles. Also, the LPI contours will be helpful for future
development in the vicinity of the current site.

Figure 1 Tectonic map of the area. Abbreviations: ITS: Indus–Tsangpo–Suture, MCT: Main
Central Thrust, MBT: Main Boundary Thrust, MFT: Main Frontal Thrust, LHT: Lohit Thrust,
TDS: Tidding Suture, MMT: Mishmi Thrust, EBT: Eastern Boundary Thrust, DKPF:
Dhansiri–Kopili Fault, NGT: Naga Thrust, DST: Disang Thrust, SHF: Sylhet Fault, JMF:
Jamuna Fault, DPT: Dapsi Thrust, DBF: Dhubri Fault, DDF: Dudhnoi Fault, KSF: Kulsi
Fault, OF Oldham Fault, DKF: Dauki Fault, BMDL: Bomdila lineament (after Raoof et al
2017)

138

Figure 2 Earthquakes in and around 300 km radius from the solar power plant. The
magnitude is low when marked by yellow color and high when marked by red color.

139

Figure 3 Plant area showing borehole locations

140

Select a Site
Obtain Necessary Soil
Parameters from SPT,PSLOG and other tests

Develop the Soil
Model for the Site

Using Vs30 of the site
Select Suitable
Response Spectrum
from BNBC

Select Target Response
Spectrum (TRS) for
Rock (SA) from BNBC()

Gather all the Earthquake
Data within a Radius of
300 km from the Site
Using Different Available
Sources

Determination of thePGA value at the Bedrock
Level for a Return Periodof 475 years throughPSHA at the Site Using
Suitable GMPEs

Select at least 10 Earthquakes (6Real & 4 Synthetic) and Match themwith TRS for Rock to obtain 10 Input
Motions for the Soil Model based on
the PGA Value obtained for RockU i PSHA
Use Nonlinear (NL) and
Equivalent Nonlinear (EL)methods (DEEPSOIL
Software) to generate Surface
PGA and Response Spectrum

Compare Response
Spectrum obtained from
Vs30, NL and EL methods
at the Surface

Use Surface PGA obtained
from NL method for
Liquefaction Analysis
Using Different Methods

Figure 4 Flow chart of the methodology used in this study141

Shear-wave Velocity, Vs (m/s)
0

100 200 300 400 500 600 700

0-25Depth (m)

-50

-75

-100

-125

Figure 6 Shear wave velocity (Vs) profile at location BH-23 of the plant site

142

1

Reference Curve

Curve Fit
FittingCurve
0.8

G/Gmax

0.6

0.4

0.2

0
0.0001

0.001

0.01

0.1

1

10

0.1

1

10

Strain (%)
25

Damping ratio (%)

20

15

10

5

0
0.0001

0.001

0.01

Shear Strain (%)

Figure 7 Sample of normalized shear modulus reduction and material damping curves
where the reference curves are taken from Darendeli (2001)

143

(a)
0.8

Bedrock UHS
Surface UHS using Vs30 based site coefficients

Spectral Acceleration (g)

0.6

0.4

0.2

0
0.02

0.03 0.04 0.05

0.07

0.1

0.2

0.3

0.4 0.5 0.6 0.7

1

2

3

4

Period (s)(b)
Figure 8 (a) Normalized design acceleration response spectrum for different site classes(after BNBC, 2020) and (b) UHS for a return period 475 years for soil class SA and SC

144

3.2

TargetInitialMatched

2.8

Spectral Acceleration (g)

2.4

2

1.6

1.2

0.8

0.4

0
0.02

0.03

0.04 0.05

0.07

0.1

0.2

0.3

0.4 0.5 0.6 0.7

1

2

3

4

Period (s)

(a)

0.8

TargetMatchedSpectral Acceleration (g)

0.6

0.4

0.2

0
0.02

0.03 0.04 0.05

0.07

0.1

0.2

0.3

0.4 0.5 0.6 0.7

1

2

3

4

Period (s)(b)
Figure 9 Spectral matching of the response spectrum of (a) the earthquake time history and(b) synthetic accelerogram with target response spectra for a return period 475 years. Initial is
the response spectrum of the earthquake time history (orange), and green is the matched
response spectra with target response spectra (black) of bedrock ground condition

145

(a)
0.4

ActualMatched

Acceleration (g)

0.3
0.2
0.1
0

-0.1
-0.2
-0.3
-0.4
0

5

10

15

20

25

30

35

Time (s)

y

(b)

p

0.3

Synthetic
Matched

Acceleration (g)

0.2
0.1
0

-0.1
-0.2
-0.3
0

5

10

15

20

25

30

35

40

45

Time (s)Figure 10 Initial earthquake time history (solid black line) from the database and matched
time history (dashed green line) for a return period 475 years at bedrock ground condition

146

3

Target Response Spectrum
ChichiImperial Valley
Kobe
Kocaeli
Loma Prieta
Northridge

Spectral Acceleration (g)

2.5

2

1.5

1

0.5

0
0.02

0.03 0.04 0.05

0.07

0.1

0.2

0.3

0.4 0.5 0.6 0.7

1

2

3

4

Period (s)Figure 11 Response spectra of 6 time histories from real earthquakes with target response
spectrum for a return period 475 years at the site
0.8

TargetChiChiImperialValley
Kobe
Koca
LomaPrieta
Northridge
Synthetic 1
Synthetic 2
Synthetic 3
Synthetic 4

Spectral Acceleration (g)

0.6

0.4

0.2

0
0.02

0.03 0.04 0.05

0.07

0.1

0.2

0.3

0.4 0.5 0.6 0.7

1

2

3

4

Period (s)Figure 12 Matched response spectra of 10 time histories with target response spectrum for a
return period 475 years at the site
147

y
1.6

Bedrock UHS
Surface UHS using Vs30 based site coefficients
Surface UHS (Mean) based on nonlinear analysis
Surface UHS (Mean) based on equivalent-linear analysis

1.4

Spectral Acceleration (g)

1.2

1

0.8

0.6

0.4

0.2

0
0.02

0.03 0.04 0.05

0.07

0.1

0.2

0.3

0.4 0.5 0.6 0.7

1

2

3

Period (s)Figure 13 Uniform hazard spectra (UHS) at ground surface using Vs30-based site
coefficients and UHS at ground surface using equivalent-linear, and nonlinear groundresponse analysis at the site for a return period 475 years

148

4Factor of Safety (FL)
0

2

4

6

0

2

4

Depth from EGL (m)6
Simplified Idriss
8

Chinese Criterion

10Japanese Code of
Bridge Design

12

14

16

18

20

Figure 14 Factor of safety versus depth plot at BH-01 of the three methods for PGA=0.19g
and Mw=7.5

149

Figure 15 LPI contour of the site for PGA=0.19g and Mw=7.5

150

PART-VII

SEISMIC SOIL-STRUCTURE-INTERACTION
OF A TALL BUILDING ON PILE-RAFT
FOUNDATION IN DHAKA CITYBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Md. Mahadi Hasan
Mehedi Ahmed Ansary151

INTRODUCTION

One of the most common challenges that civil engineers face is the problem of seismic-soilstructure-interaction (SSSI) when the buildings are located in potential earthquake areas.
The seismic soil–structure interaction (SSSI) plays an important role to the response of thatstructure. The foundation is a part of a structure system in which the gravity load and live
load from the structure are applied to. However, the seismic load comes from some depths ofthe earth and transfers the load to the structure via foundation. This demands the survival ofstructure even if they occur a few times in hundred years, suddenly without prediction.
The main components of the seismic response of building include displacement, and drift ofeach floor, foundation rocking and also the recorded acceleration at any point in models.
This can produce the response spectrums. All of these parameters need to satisfy certain
requirements from design codes.
In order to determine the seismic response of structures, the assumption that the structure isfixed at its base has been made frequently in practice. In general, this assumption canbe acceptable if the ground under the structure is stiff enough (similar to structure foundedon solid rock). However, when the soil under the structure is soft, two modifications factors
need to be considered to determine the seismic response. First of all, the imposed motion to
the structure is different from free field motion due to the presence of the structure andfoundation. Secondly, additional dynamic deformations are induced within the structure dueto the soft soil underneath. According to Kramer (1996), soil-structure-interaction (SSI) is
the process in which response of the soil influences the motion of the structure and also
response of the structure influences the motion of the soil.

Bangladesh is the largest delta on the earth and its land is formed by the alluvial soils. Here,it is hardly possible to find the solid rock stratum. Soil profiles established for Dhaka
Metropolitan area, in general, showed soft to very stiff cohesive layers at the top strata up to
depth of 20 ft to 60 ft (Bashar, 2000). The surface deposits are usually soft clay. In
seismically active regions, building structures with unfavorable geotechnical conditions are
sometime inevitable. To accommodate fast growing population with rapid urbanization it
has become essential to construct tall buildings or skyscraper. In Dhaka city, such152skyscrapers on pile mat foundation are in the planning. The critical nature of these structures
requires a better understanding of their performance under strong seismic shaking. It has
been found from investigation of some recent earthquakes (e.g., Christchurch earthquake of
New Zealand in 2011 and Tohoku-Oki earthquake of Japan in 2011) that the aspect of the
fixed-base assumption is often misleading (Bilotta et al. 2015; Bagheri et al. 2018; Berger et
al. 2012; Sotiriadis et al. 2017). This increases the possibility of unsafe designs, especiallyfor ignoring seismic soil-pile-structure interaction (SSPSI) impacts upon the super structures
resting on soft soils. Impacts of SSPSI on super structure responses have been studied bymany researchers during the last two decades and frequent analytical formulations have been
conducted to solve the complex practical problems based on linear and elastic soil structureinteraction (Stewart et al. 1999; Galal et al. 2008; Khalil et al. 2007; Tabatabaiefar et al.
2010). In particular, considering the effects of SSPSI on structure founded on soft soil,
lateral displacements and inter-story drifts of unbraced frames may be significantly
amplified, thus compromising the building integrity and safety. However, the realistic
simulation of SSPSI is mostly dependent on the behavior of soil nonlinearity which iscomplex and time-consuming process (Bolisetti et al. 2018; Luo et al. 2016; Mucciacciaro etal. 2018; Wang, 2012; Maheshwari et al. 2011; Bourgeois et al. 2012; Hokmabadi et al.
2014; Carbonari et al. 2014). Under the light of above discussion, it becomes essential toinvestigate the impact of SSPSI for the structure to be built in high seismic zone considering
nonlinear behavior of soil beneath the structure.
This study aims to numerically analyze a tall building resting on pile-mat foundation forstudying seismic soil-pile-structure interaction (SSPSI) effects in Dhaka soil under different
earthquakes. The study will throw light on the effects of considering seismic soil-pilestructure interaction (SSPSI) on the design parameters of a tall building for Dhaka soil
conditions. The results are expected to give some guidelines whether SSI effects should beconsidered while designing tall buildings/skyscrapers on pile-mat foundations in Dhaka city.

1.2 Objectives
The main objectives of this research work are follows:i.

To develop a suitable numerical model for studying seismic soil-pile-structure153interaction (SSPSI) effects for a tall building resting on pile-mat foundation
using time-history analysis.
ii.

To study modal shapes and natural frequencies of the tall building resting on
pile mat foundation in Dhaka soil considering SSPSI effects and ignoring SSPSI
effects.

iii.

To compare principal design parameters of a tall building on Dhaka soil
considering SSPSI effects and ignoring SSPSI effects. The lateral displacements
and inter-story drifts criteria are vital indicators of performance of tall building
during an earthquake, these become more important for skyscrapers.

iv.

Studying the deformation of pile under seismic loadingv.

To study the settlement of the raft foundation and piled raft foundation restingon Dhaka soil by static analysis

1.3 Outline of Methodology
In this research, a numerical simulation has been carried out for a tall building resting on
piled raft foundation using a geotechnical software midas GTS NX to quantitatively assess
the effects of soil-pile-structure interaction subjected to seismic loads. Key steps regarding
this work are stated below:
1. Experimental work performed in the University of Sydney Lab has been verified
through numerical analysis using midas GTS NX software.
2. Accordingly, the performance of a tall building model consists of 42 stories with 4basements has been evaluated by equivalent linear static analysis according to
BNBC-2020.
3. After satisfying linear static analysis according to the code, the building has been
analyzed for seismic soil- pile-structure interaction using finite element method.
4. The analyses has been performed for both fixed-base model and flexible base model
resting on soil continuum.
5. Typical Dhaka soil stratigraphy has been used for three-dimensional continuum soilmodel.
6. All the structural members of the frame has been modeled using a beam element. The
general shell element and eight nodded solid brick elements will be used for floorslabs and soils respectively to the numerical model.
154

7. Implicit unconditionally stable time integration scheme has been used considering
three earthquakes as a dynamic load.
8. Finally, the lateral displacements and inter-story drifts of the numerical model has
been ascertained.
Flow chart of the methodology is shown in Figure 1.1 below.

Verifying experimental
work performed in the
University of Sydney lab
through numericalanalysis using a software
midas GTS NX

Adopted a tallbuilding (42storied with 4
basements) fromPEER report
2011/05

Performing
LSA
following
BNBC2020 tosatisfy themembersize

Staticanalysisconsidering
SSI
for Dhaka
soil

Soil
profile-01

Soilprofile-02

Ignoring
SSI(fixedsupport)Raft foundation
Raft on pilefoundation
Raft foundation
Raft on pilefoundation
El Centro EQ
Kobe EQ
Northridge EQ

Dynamic
analysis

Note:* Considering SSI means Flexible base condition* Ignoring SSI means Fixed base condition

Considering
SSI(Raft on pilefoundation)

Figure 1.1: Flowchart of the study

155

El Centro
EQ
Soil
profile-01

Kobe EQ
Northridge
EQNUMERICAL MODEL DEVELOPED IN THE CURRENT STUDY
4.1 Introduction
In order to conduct a fully coupled analysis of the entire soil-pile-structure system, a threedimensional numerical soil-structure model has been developed in this study which treats the
behaviors of the soil and the structure with equal rigor. Adopting direct method of analysis,
the numerical model can perform nonlinear time-history dynamic analysis to simulate
realistic dynamic behavior of the soil and the structure under seismic excitations.
In this study, a three-dimensional ﬁnite element analysis using a commercial software calledmidas GTS NX is performed for a tall building (42 stories with 4 basement) with soil
continuum. It should be noted that there are some rigorous approaches to model soil behavior
under cyclic loads such as isotropic kinematic constitutive models (Gajo and Muir Wood,1999), incrementally nonlinear models (Darve et al., 1995), or hypoplastic models (Chambon
et al., 1994). However, the modulus reduction approach is the most common approach tomodel the soil for dynamic analysis of soil-structure systems, and is employed in this study
All the structural members of the frame will be modeled using a beam element. The generalshell element and solid elements will be used for floor slabs and soils respectively to thenumerical model.
This program can simulate behavior of different types of structures and materials by elements
which can be adjusted to fit the geometry of the model. Each element behaves according to aprescribed constitutive model in response to the applied forces or boundary restraints.
In this chapter, different components of the developed numerical model including soil
elements, pile elements, structural elements, interface elements, boundary conditions, anddynamic loading are explained.
4.2 Parametric StudyIn this study both static and dynamic SSI are studied for a tall building which is considered tobe resting on Dhaka soil. Two types of soil profiles are considered which will be discussed in
section 4.4. For static SSI, equivalent linear static analysis has been performed for both soil
profile-01 and soil profile-02 with mat foundation and mat on pile foundation.
For dynamic SSI, nonlinear time history analysis has been performed for soil profile-01 with
mat on pile foundation considering design based earthquake (DBE) for three different events
156

(El Centro, Kobe and Northridge). Table 4.1 summarizes the parametric study.
Table 4.1: Summarization of parametric study
Loads

ProfileEarthquake

Soil-01
StaticEquivalent static

Z=0.13

Soil-02
El Centro
Dynamic Soil-01

Kobe
Northridge

Z=0.17Z=0.148
Z=0.147
Z=0.123
Z=0.134
Z=0.12

FoundationMat
Mat on PileMat
Mat on Pile

Mat on Pile

Model ID
Flexible Base (S1)
Flexible Base (S2)
Flexible Base (S3)
Flexible Base (S4)
Fixed Base (D1)
Flexible Base (D2)
Fixed Base (D3)
Flexible Base (D4)
Fixed Base (D5)
Flexible Base (D6)

4.3 Characteristic of Building Structure
In this study, a tall concrete building is selected from a case study of Tall Buildings Initiative(Moehle et al., 2011). The building consists of 4 (four) stories below ground and 42 (fortytwo) stories above ground and a pent house at top of the structure. Story heights of floors
below ground, ground to 2nd floor, typical floor from 2nd to 42nd, roof and pent house of thebuilding are to be 10.5 ft, 13.67 ft, 10.5 ft, 11.5 ft, and 20 ft respectively. Slab thickness
varies for different stories. Colum size, building core wall and compressive strength of
concrete vary for different elements of the structure which are shown in table 4.1 and 4.2.
Reinforcement, yield strength of 60 ksi, is used. Beam depth for the selected structure isconsidered to be 30 inch. Shear wall of 16-inch thickness is chosen. Figure 4.2 presents
typical plan view of a subterranean level and figure 4.3 shows typical plan view of stories
from level-2 to roof. Figure 4.4 and figure 4.5 display elevation of grid-3 and shear wall andbasement wall respectively. Detail geometric data of the building is provided below.

4.3.1 General Building Properties
General building properties of the adopted building are shown below:
Number of Stories

42 above ground plus Pent-house157

4 below ground

Story Height

10.5(3.20 m) at levels below Ground13.67(4.17 m) from Ground to 2nd floor
10.5 (3.20 m) Typical from 2nd floor to 42ndfloor
11.5(3.50 m) Roof20 (6.10 m) Pent-house

Slab Construction

10(254 mm) thick reinforced concrete at
Basement levels
12(304 mm) thick reinforced concrete at
Ground floor8 (203 mm) thick concrete typical above
Ground10 thick reinforced concrete at RoofBeam Depth30 (typical)(762 mm)

Basement Walls

16 thick(406 mm)158

Figure 4.1: 3D View of the structure159

Figure 4.2: Typical plan view (bottom  ground floor)

Figure 4.3: Typical plan view (Level 2  Roof)160

Figure 4.4: Elevation of grid -3

161

Figure 4.5: Core wall and Basement Wall

162

Table 4.2: Column properties and section
Frame A and F

Frame 2 and 5

Frame C5

Story

ColumnDimensionfc (ksi)

ColumnDimensionfc (ksi)

ColumnDimensionfc (ksi)

Base to GF
GF to 10F
10 to 15F
15F to 25F
25F to 42F36"  36"36"  36"36"  36"36"  36"36"  36"

10
8
6
5
5

42"  42"42"  42"42"  42"36"  36"36"  36"

10
8
6
5
5

46"  46"46"  46"46"  46"46"  46"46"  46"

10
8
6
5
5

Table 4.3: Building core wall thickness and material strength

Story
Base to 20 th
20 th Floor to Roof

Thickness(inch)
24
18

f’c (ksi)

fy
(ksi)

6
5

60

4.3.2 Effective Stiffness of the Structural Members
The stiffness assumptions are listed in Table 4.3 When non-linear behavior of elements ismodeled, stiffness modifiers are applied to the assumed “elastic” portion of the forcedisplacement relationship.
Table 4.4: Effective stiffness of crack section

Structural ElementsCore Walls
Basement Walls
Coupling Beams
Ground Level and Basement slabs

Effective stiffness
Flexural (EIg)
Shear (GAg)
0.6
1.0
0.8
0.8
0.2
1.0
0.25
0.5

Moment Frame Beams

0.35

1.0

Moment Frame Columns

0.7

1.0

Note:
Modulus of elasticity is based on the following equations:Ec  57000 √ f cfor f’c ≤ 6000 psi
Ec  40000 √ f c1106for f’c > 6000 psi (per ACI 363R-92)
4.3.3 Gravity Load Consideration
In addition to the self-weight of the structure, the loads listed in Table 4.5 are used for the163

calculation of superimposed dead load and live loads.
Table 4.5: Load criteria of the building

Use

Location

Parking
Retail Area
Residential
MechanicalRoof

4 stories below ground
Ground Level inside area
2nd floor to 42nd floor
At roof floor only
Roof floor

Superimposed dead load
(psf)
30
110
28
100 kip
28

Live Load (psf)
50
100
40
25
20

4.4 Characteristics of the Adopted Dhaka Soil
This section provided a detail overview on characteristics of soil profiles.
4.4.1 Subsoil Stratigraphy
A case study has been performed to investigate the variation of the soil properties with depth
and to establish approximate correlation among different geotechnical properties of the
subsoil of the Dhaka Metropolitan Area (Bashar, M.A., 2000). About 300 sub-soil
investigation reports consisting of 674 boreholes data were collected from the different
drilling companies, consulting firms and other organizations in order to develop thegeneralized soil profiles of Dhaka Metropolitan area. In order to verify the existing soil data, anumber of test bore holes were drilled up to a depth of 100 ft. From the investigation, four
longitudinal soil profiles and five cross soil profiles have been established for Dhaka
Metropolitan area. Soil profiles established for Dhaka Metropolitan area, in general, showed
soft to very stiff cohesive layers at the top strata up to a depth of 20 ft to 60 ft. At large
depths, the soil layers have been found to consist of medium dense to very dense sandy soils.
In some areas of the eastern region of Dhaka Metropolitan, however, cohesive layers up to adepth of 100 ft have been encountered. These areas include Uttarhan, Dakkhinkhan, Saterkul
and Daina. Based on the case study, two soil profiles, namely soil profile-01 and soil profile02, have been adopted and soil properties except modulus of elasticity have been taken fromthe case study. The value of modulus of elasticity is calculated using an equation developed
by Bowel (El-kasaby, 1991).
For Clay, Es = 500 Cu, Cu= 166 N (psf)
For Sand, Es = 1200 (N+6) (kpa)
The SPT values (N), cohesion (c), and friction angle (φ) of different layers of Dhaka soil were164

obtained from the Geotechnical Subsoil Investigation Report of the well-known drillingcompany Engineering and Research Associates (ERA). Soil profiles are described below.

Soil Profile-01: Combination of Cohesive and Non-Cohesive Soil.
According to the case study performed by Bashar (2000), profile-01 represents soil strata ofmost of the Dhaka metropolitan area. In profile-01, cohesive soil up to a depth of around 12
m from top level is found with stiffness variation from very soft clay to stiff clay. Non
cohesive soil is usually found after stiff clay layer and usually is seen to have variation ofrelative stiffness from medium dense to dense. Figure 4.6 shows a simplified subsoil
stratigraphy of soil profile-01 of Dhaka city.

Soil Profile 02: Cohesive Soil
According to the case study performed by Bashar (2000), profile-02 symbolizes soil strata
found rarely in Dhaka metropolitan area where this profile consists of cohesive soil.
In profile-02, cohesive soil is found from top level to bottom. The stiffness variation of soil
profile-02 from very soft clay to stiff clay. Non cohesive soil is not found in profile-02 after a
stiff clay layer as like profile-01. Figure 4.7 presents a simplified subsoil stratigraphy of soil
profile-02 consisting of cohesive soil only.

165

10 ft

10 ft

10 ft

10 ft

20 ft

330 ftVery soft clayγ = 115.6 lb/ft3
E = 8.8E+4 psf
c = 313.3 psf
φ=0
ν = 0.4

Mohr-Columb
plasticity model

Soft clayγ = 122 lb/ft3
E = 2.6E+5 psf
c = 522 psf
φ=0
ν = 0.4

Medium stiff clayγ = 125.3 lb/ft3
E = 6.05E+5 psf
c = 731 psf
φ=0
ν = 0.35

Stiff clayγ = 128.5 lb/ft3
E = 1.02E+6 psf Mohr-Columb
plasticity modelc = 1211.4 psf
φ=0
ν = 0.3

Medium dense sand

γ = 128.5 lb/ft3
E = 7.3E+5 psf
c = 0 psf
φ = 30ºν = 0.3

Dense sand

γ = 128.5 lb/ft3
E = 2.5E+6 psf Mohr-Columb
plasticity modelc = 0 psf
φ = 40ºν = 0.3

Figure 4.6: Simplified Subsoil Stratigraphy‐01

166

Mohr-Columb
plasticity model

Mohr-Columb
plasticity model

Mohr-Columb
plasticity model

10

10 ft

10 ft

10 ft

20 ft

330 ftMohr-Columb
plasticity model

Very soft clayγ = 115.6 lb/ft3
E = 8.8E+4 psf
c = 313.3 psf
φ=0
ν = 0.4

Soft clayγ = 122 lb/ft3
E = 2.6E+5 psf
c = 522 psf
φ=0
ν = 0.4

Mohr-Columb
plasticity
d lMedium stiff clayγ = 125.3 lb/ft3 Mohr-Columb
E = 6.05E+5 psf plasticity modelc = 731 psf
φ=0
ν = 0.35

Stiff clayγ = 128.5 lb/ft3 Mohr-Columb
E = 1.02E+6 psf plasticity modelc = 1211.4 psf
φ=0
ν = 0.3

Very stiff clayγ = 128.5 lb/ft3 Mohr-Columb
E = 1.67E+6 psf plasticity modelc = 3341.6 psf
φ=0
ν = 0.3

Hardclay

γ = 128.5 lb/ft3
E = 2.6E+6 psf
c = 5221.4 psf
φ=0
ν = 0.25

Figure 4.7: Simplified Subsoil Stratigraphy‐02

167

Mohr-Columb
plasticity model4.4.2 Dynamic Soil Properties
The non-linearity of soil during an earthquake plays an important role in the dynamic
response of soil-structure systems. The equivalent linear method has been used for many
years to calculate wave propagation (and response spectra) in soil and rock at sites subjected
to seismic excitations. In the equivalent linear method adopted in this study, a linear analysis
is carried out with some assumed initial values for the damping ratio and shear modulus invarious regions of the model was performed by midas GTS NX software. Then the maximum
cyclic shear strain is recorded for each element and used to determine the new values for
damping and modulus by referring to the backbone curves relating the damping ratio andsecant modulus to the amplitude of shear strain. Some empirical scaling factors are usually
utilized when relating these strains to the model strains, and then these new values for thedamping ratio and shear modulus are used in the next stage of the numerical analysis. The
whole process is repeated several times, until there is no further change in the properties andthe structural response.
At this stage, “strain compatible” values of damping and modulus are recorded, and thesimulation using these values is deemed to be the best possible prediction of the real behavior.
As described by Seed and Idriss (1969), the equivalent linear method uses linear properties
for each element because they remain constant under the influence of seismic excitations;those values are estimated from the mean level of dynamic motion, as explained before, butsince trial and error utilizing nonlinear backbone curves to find the “strain compatible” valuesof damping and modulus is used, soil non-linearity was captured by this method. Dynamic
soil properties are obtained only for soil profile 01 because this profile represents most of the
Dhaka Metropolitan area. Figure 4.8 to Figure 4.10 shows dynamic soil properties of the soil
profile 01. Soils exhibit nonlinear behavior in shear. The secant shear modulus decreases withincreasing strain amplitude as shown in Figure 4.9 and Figure 4.10. Shear modulus at small
strains, at which soil behavior is linear, is referred to as small-strain shear modulus, Go. The
relationship between shear modulus and strain amplitude is typically characterized by anormalized modulus reduction curve as shown in Figure 4.9 and Figure 4.10. The nonlinearity
in the stress-strain relationship results in an increase in energy dissipation and, therefore, anincrease in material damping ratio with increasing strain amplitude as presented in Figure 4.9
and Figure 4.10.
168Damping Ratio

Shear wave velocity vs (ft/s2)
0

500

0.0

1000

0

0.1

Very Soft Clay

Very Soft Clay

Soft Clay

Soft Clay
20

20

Medium Stiff
Clay

Medium Stiff
Clay

Stiff Clay

Stiff Clay
40

40

Medium Dense
Sand

Medium Dense
Sand60

Deptth (ft)60

Deptth (ft)

0.2

0

80

80

Dense Sand

Dense Sand
100

100

120

120

140

140

(a)

(b)

Figure 4.8: Dynamic soil properties (a) shear wave velocity, (b) damping ratio

169

Damping

1.2

0.3

1

0.25

0.8

0.2

0.6

0.15

0.4

0.1

0.2

0.05

0
0.0001

Damping(%)

G/G0

Stiffness decrease rate (G/Go)

0
0.001

0.01
0.1
Shear Strain (%)

1

10

Figure 4.9: Backbone curve of stiffness decrease rate and damping to shear strain for sandDamping

1.2

0.3

1

0.25

0.8

0.2

0.6

0.15

0.4

0.1

0.2

0.05

0
0.0001

Damping(%)

G/G0

Stiffness decrease rate (G/Go)

0
0.001

0.01
0.1
Shear Strain (%)

1

10

Figure 4.10: Backbone curve of stiffness decrease rate and damping to shear strain for clay170

4.5 Characteristics of the Foundation
Loads from super structure to the foundation for this study are obtained considering threeelements of the super-structure, namely shear wall, columns within super structure andcolumns within sub structure. Load intensity below core structure, covering loads from shear
wall and columns within super structure, is greater than the podium structure. To meet thedemand of load distribution from structure two types of piles are selected. Piles of 36-inch
diameter and of 150 ft in length are considered below core structure, whereas piles of 24-inch
diameter and of 60 ft in length are considered below podium structure. Load capacity of 36inch diameter pile is found to be 2000 kip for soil profile- 01, where for 24-inch diameter pileload capacity is found to be 330 kips for the same soil profile. Number of piles of 36-inch and24-inch dimeters are considered to be 81 and 72 respectively. Table 4.6 summarizes loads on
foundation from super structure and pile capacity, diameter and number of piles.
Table 4.6: Summarization of loads from super structure and pile capacity, diameter andnumber of pile

Elements
Shear wall
Columns within Super
Structure
Columns within Sub
Structure

Loads
Kips
(kN)
100528(447171)93433(415610)22213(98808)Pile
Capacity
kips
(kN)

Pile
(Dia)
inch
(mm)

Pile
Lengthft(mm)

No of Pile
(Considered)

2000(8896)

36
(914)

150
(45720)81

330(1468)

24
(609)

60
(18288)72

Figure 4.11 represents arrangement of piles under mat. 36-inch diameter piles are provided in
middle part of the structure where load intensity is greater and where the load intensity issmaller than the central structure, 24-inch diameter piles are used. Figure 4.12 shows the 3Dview of pile arrangements under mat and Figure 4.13 shows the 3-D view of mat above the
pile.

171

Figure 4.11: Arrangements of piles

Figure 4.12: 3‐D view of piles under mat

Figure 4.13: 3‐D view of mat

Structural model adopted for this study is shown in figure 4.14 with mat on pile foundation.

172

Figure 4.14: 3‐D view of the super structure and sub structure

4.6 Earthquake Parameters
Three major earthquakes, namely El Centro, Kobe and Northridge, chosen to stimulate thenumerical model for this study. Lists of earthquake motion, actual magnitude and peakground accelerations are seen in Table 4.7. Earthquake induced ground motions have different
characteristics regarding site conditions, intensity and frequency content. It is realistic to scale
down specifications of actual ground motion for dynamic analysis. Actual records of peak173

ground acceleration of three different earthquakes are scaled down by spectral matching inthis study.
Table 4.7: Lists of earthquakes motion used for numerical analysis

Earthquake

Record Description

Magnitude( Richter)

Actual PeakGroundAcceleration

El Centro

Imperial Valley, May 1940

7.2

0.35g

Kobe

Kobe, January 1995

6.9

0.80g

Northridge

Sylmar County Hospital,
January 1994

6.6

0.89g

Based on the average shear wave velocity and SPT value, the site class of soil profile-01 is
determined to be “SC” as per BNBC 2020. (Table 4.8)
Table 4.8: Site classification based on soil properties for profile‐01
Depth fromGL(ft)
From
To
0
10
10
20
20
30
30
40
40
50
50
60
60
85
85
110
110
135
135
160
160
185
185
210
210
235
235
260
260
285
285
310
310
335
335
360
Sum

Thickness (ft)
(h)
10
10
10
10
10
10
25
25
25
25
25
25
25
25
25
25
25
25
360.00

174

N

h/N

2
3
7
12
21
21
40
40
40
50
50
50
50
50
50
50
50
50

5.00
3.33
1.43
0.83
0.48
0.48
0.63
0.63
0.63
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.50
17.92

Average N=

20.09

Site ClassSC

4.7 Response Spectrum for Soil Profile ‐01 as per BNBC 2020
The design basis earthquake (DBE) ground motion is selected at a ground shaking level thatis 2/3 of the maximum considered earthquake (MCE) ground motion. The spectral
acceleration of soil profile -01 for DBE are shown in Figure 4.15.
Parameters for determining the spectral acceleration are illustrated below.
Long Period, TL=

4Site Coefficient , Fa =1.15

Site Coefficient , Fv =1.725

Spectral Response Acceleration, Ss =0.5

Spectral Response Acceleration, S1 =

0.2

To =

0.12 sec

Spectral Response Acceleration, SDS =

0.383

Ts =

0.6 sec

Spectral Response Acceleration, SD1 =

0.23

TL =

4 sec

sec

SA V S T (BNBC 2020)_DBE
SPECTRAL ACCELERATION (SA)_DBE

0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

TIME PERIOD (T)Figure 4.15: Spectral acceleration for soil profile‐01 as per BNBC 2020
Fig. 4.16 shows the simulation output of three acceleration records in the form of response
spectrum curve and the target response spectrum for the site class SC of Dhaka soil. The
average of these three spectrums is scaled by a factor, which is the ratio of the area under175spectrum curve between the matched and target spectrum along 0.2T to 1.5T.

Matched Accelerograms
0.4

Target Spectrum
Kobe

Acceleration (g)0.3

Northridge
0.2

El centro

0.1

0
0

1

2

3

4

Periods (sec)Figure 4.16: Matched accelerograms of three earthquake with code based target spectrum
The matched spectrums are then used to generate new time history accelerograms. These
newly generated accelerograms are then utilized to analyze for fixed base model.
However the accelerograms for flexible base model are not same as the fixed base model. In
the case of generating accelerograms for flexible base model, the effects of soil factor must be
nullified. As the matching spectrums have met the requirement, the adopted acceleration
records can be used in dynamic time history analysis for fixed base model and flexible basemodel.
Matched Accelerograms for fixed base model

Matched Accelerograms divided by soil factor

New Matched Accelerograms for flexible base
Figure 4.17: Flow chart of conversion of accelerograms from fixed base model to flexible
base model

Matched Acceleration, velocity and displacement of three earthquake for fixed base modeland flexible base model are illustrated in Figure 4.17 to Figure 4.34

176

Kobe (Flexible Base)

0.2

0.2

0.15

0.15

0.1

0.1

Accelaration (g)Accelaration (g)Kobe (Fixed Base)

0.05
0
-0.05

0.05
0

-0.05

-0.1

-0.1

-0.15
-0.2

-0.15
0

10

20

30

40

0

40

Time (sec)Time (sec)Figure 4.18: Acceleration vs Time of Kobe EQ for fixed basemodel

Figure 4.19: Acceleration vs Time of Kobe EQ for
flexible base model

Kobe (Fixed Base)

Kobe (Flexible Base)

20

20

15

15

Velocity (cm/s)

10Velocity (cm/s)

20

5
0
-5

10
5
0
-5

-10

-10

-15
-20

-15
0

10

20

30

40

0

Time (sec)Figure 4.20: Velocity vs Time of Kobe EQ for fixed base model

20

40Time (sec)Figure 4.21: Velocity vs Time of Kobe EQ for flexible
base model

177

Kobe (Flexible Base)
6

4

4

2

2

Displacement (cm)Displacement (cm)

Kobe (Fixed base)
6

0
-2
-4

0
-2
-4

-6
0

10

20

30

-6

40

0

20

Time (sec)Time (sec)Figure 4.22: Displacement vs Time of Kobe EQ for fixed basemodel

Figure 4.23: Displacement vs Time of Kobe EQ for
flexible base modelNorthridge (Fixed Base)

Northridge (Flexible Base)

0.15

0.15

0.1

0.1

Accelaration (g)Accelaration (g)

40

0.05
0
-0.05

0.05
0

-0.05

-0.1

-0.1

-0.15

-0.15
0

10

20

30

40

0

Time (sec)Figure 4.24: Acceleration vs Time of Northridge EQ for fixedbase model

10

20

30

40

Time (sec)Figure 4.25: Acceleration vs Time of Northridge EQ for
flexible base model

178

Northridge (Flexible Base)
20

15

15

10

10

Velocity (cm/s)

Velocity (cm/s)

Northridge (Fixed Base)
20

5
0
-5

5
0
-5

-10

-10

-15

-15

-20

-20
0

10

20

30

40

0

10

Time (sec)30

40Time (sec)Figure 4.26: Velocity vs Time of Northridge EQ for fixed basemodel

Figure 4.27: Velocity vs Time of Northridge EQ for
flexible base modelNorthridge (Fixed Base)

Northridge (Flexible Base)

4

4

3

3

Displacement (cm)2

Displacement (cm)

20

1
0
-1
-2
-3

2
1
0
-1
-2
-3

-4
-5

-4
0

10

20

30

0

40

Time (sec)Figure 4.28: Displacement vs Time of Northridge EQ for fixedbase model

10

20

30

40

Time (sec)Figure 4.29: Displacement vs Time of Northridge EQ for
flexible base model179

El Centro (Fixed Base)

El centro (Flexible Base)

0.2

0.2

0.15

0.15

Accelaration (g)Accelaration (g)

0.1
0.05

0.1

0.05

0

-0.05

0

-0.1

-0.05

-0.15

-0.1

-0.2
0

10

20

30

-0.15

40

0

Time (sec)

20

30

40

Time (sec)Figure 4.30: Acceleration vs Time of El Centro EQ for fixedbase model

Figure 4.31: Acceleration vs Time of El Centro EQ for
flexible base model

El centro (Fixed Base)

El centro (Flexible Base)

20

20

15

15

10

10

Velocity (cm/s)

Velocity (cm/s)

10

5
0
-5

5
0
-5

-10

-10

-15

-15

-20

-20
0

10

20

30

40

0

Time (sec)Figure 4.32: Velocity vs Time of El Centro EQ for fixed base
model

20

40

Time (sec)Figure 4.33: Velocity vs Time of El Centro EQ for flexible
base model180

El centro (Fixed Base)

64

Displacement (cm)4

Displacement (cm)El centro (Flexible Base)

6

2
0
-2
-4

2
0
-2
-4

-6

-6
0

10

20

30

40

0

10

Time (sec)

20

30

40

Time (sec)Figure 4.34: Displacement vs Time of El Centro EQ for fixedbase model

Figure 4.35: Displacement vs Time of El Centro EQ for
flexible base model

After matching the accelerograms with code base spectrum the maximum acceleration of
three earthquakes.(1) Kobe, (2) Northridge, (3) El Centro are illustrate in figure 4.35. For
three earthquakes, the maximum acceleration value of the flexible base model was found tobe lower than that of the fixed base model. Since the soil factor (S) is not taken into account,the maximum acceleration of the flexible base model is lower.
Fixed Base Model

Flexible Base Model

Maximum Accelaration (g)

0.18
0.17
0.16
0.15
0.14
0.13
0.12
0.11
0.1
Kobe

Northridge
Matched Accelerograms

Figure 4.36: Maximum acceleration of three earthquakes.

181

El centro

4.8 Boundary Conditions
Two different sets of boundary conditions are employed for static and dynamic analyses.
Detail descriptions of boundary conditions are written below.
4.9.1 Boundary Conditions for Static Analysis
Gravity loading was applied in the static analysis; thus, the bottom boundary was fixed in all
directions, while all the four side boundaries were fixed in the horizontal direction only. In
this study, rigid boundary condition is adopted to simulate the bedrock at the bottom of thesoil medium for static analysis. Support condition of soil medium along two side of xdirection are constrained for Ux and soil medium along two side of y-direction are
constrained for Uy.
4.9.2 Boundary Conditions for Dynamic Analysis
In the dynamic analysis, however, as mentioned by Semblat (2011), the boundaries at thesides of the model must account for free-field motion. As shown in Figure 4.36, the free-field
elements, consisting of dashpots in the normal and shear directions, transfer the free-fieldmotion from the free-field grids to the main grid of the 3D numerical model. Moreover, theviscous boundaries consisting of independent viscous dampers were coupled to the free-field
grids to eliminate the reflection from outgoing waves by applying resistant tractions in thenormal and tangential directions. The applied resistant tractions in the viscous boundaries,
governed by the equations proposed by Lysmer and Kuhlemeyer (1969), are expressed asfollows:
tn = - Cp Vn
ts = - Cs Vs
Where tn and ts = tractions in the normal and shear directions, respectively;ρ = density of the medium;Cp and Cs = velocities of the p-wave and s-wave, separately; andVn and Vs = normal and shear components of the velocity in the near-boundary material.
The viscous boundary may not perfectly absorb the outgoing waves when 30° (Han et al.
182

2016). Therefore, to minimize the adverse effect of the waves reflected from the artificial
boundaries, according to Syed and Maheshwari (2014), horizontal distance between the sideboundaries along the earthquake shaking direction was set to be consid- erably larger than thefoundation width as presented in Figure 4.37, Furthermore, a rigid boundary condition,utilized to simulate the strong bedrock and the significant impedance difference between thesoil deposit and the strong bedrock, was applied to the bottom of the model during the seismic
analysis, following the suggestion made by Maheshwari and Sarkar (2011).

Free Field Boundary

Direction of Earthquake
Figure 4.37: Boundary condition of the soil model

4.10 Size of the Numerical Model
Rayhani and El Naggar (2008), after undertaking comprehensive numerical modelling andcentrifuge model tests, concluded that the horizontal distance of the soil lateral boundaries
should be at least five times the width of the structure in order to avoid reflection of outward
propagating waves back into the model. The boundary condition of the soil model is shown in
Figure 4.37. In this study, the bedrock depth of 377 ft is adopted. The horizontal distance ofthe soil lateral boundaries is assumed to be 984 ft.

183

377ft

984 ft
984 ftFigure 4.38: Boundary condition of the soil model

4.11 Summary
In this chapter, the 3D numerical model using midas GTS NX have been used to investigate
the influence of SSPSI on the behavior of superstructures under seismic loads. The developed
numerical model performs SSPSI analysis in a fully coupled manner, without resorting to
independent calculations of site or superstructure response, or application of pile groupinteraction factors. The main feature of the developed numerical model is incorporating thenonlinear behavior of soil together with linear behavior of structural elements simultaneously
throughout the three-dimensional numerical analysis.
In this study, a three-dimensional ﬁnite element analysis using midas GTS NX is performed
for a tall building (42 stories with 4 basement) with soil continuum.
Two types of typical Dhaka soil profiles are considered. For static SSI, equivalent linear static
analysis has been performed for both soil profile-01 and soil profile-02 with mat foundationand mat on pile foundation.

184

For dynamic SSI, nonlinear time history analysis has been performed for soil profile-01 with
mat on pile foundation considering design based earthquake (DBE) for three different events
Nonlinear Mohr-Coulomb model has been adopted in this study to simulate the nonlinear soil
behavior and possible shear failure in the soil elements during the excitation. Moreover,hysteretic damping of the soil is implemented to represent the variation of the shear modulus
reduction factor and the damping ratio of the soil with the cyclic shear strain.
Solid nonlinear elements were adopted to simulate soil elements, while linear solid elements
were used for wall elements. Columns and pile were modelled as beam elements. Slabs andRaft were simulated as shell elements.
Adjusting the boundary conditions for the static analysis, in which the system is under thegravity loads only, the bottom face of the model is fixed in all directions, while the sideboundaries are fixed in the horizontal direction. During the dynamic time-history analysis, inorder to avoid reflection of outward propagating waves back into the model, quiet boundaries
consisting of independent dash-pots in the normal and shear directions are placed at the lateralboundaries of the soil medium
Sliding can occur at the raft-soil interface. A gap or separation can form at the pile-soil
interface. Due to the different characteristics of the soil and the superstructure/piles, two setsof interface elements are modelled in this study. For the raft foundation case, the interface
elements are placed between the foundation and the soil surface. However, for the pilefoundation case, the interface elements were attached to the outer perimeter of the piles. The
adopted interfaces were modelled as spring–slider systems, while the shear strength of theinterfaces was defined by Mohr–Coulomb failure criterion.

185

PART-VIII

RECENT MAJOR FIRE OCCURRENCES INBANGLADESHBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Sayma Ahmed
Mehedi Ahmed Ansary186

UKHIYA ROHINGYA CAMP: MASSIVE FIRE RAZES HOMES
Eleven Rohingyas, including two children and a woman, were reportedly killed and around five
hundreds of others were injured in deadly fires that burned several thousand shanties at Balukhali
refugee camp in Ukhiya, Cox's Bazar on 22nd March 2021. The fire started around 4:00pm andfirefighters almost doused it an hour later. But another wave of fire broke out shortly after 11:00pm
and was burning down shanties at the densely populated camp as of 12:30am, locals said. Refugees
gather at the Balukhai Rohingya camp in Cox’s Bazar’s Ukhiya to see for themselves the damage
caused by a fire on 22nd March. Around 10,000 shanties were gutted and about 45,000 refugees
became homeless.

187

188

NARAYANGANJ FOOD FACTORY FIRE
The massive fire in a food processing factory in Narayanganj has left at least 52 people killed withdozens of workers still missing on July 08, 2021. Firefighters recovered 49 charred bodies from theburning factory building of Hashem Food Ltd, a concern of Sajeeb Group, taking the death toll to 52.
Three deaths were reported in the immediate aftermath of the fire at the six-storey factory building at
the Kornogop area of Bhulta in the district’s Rupganj upazila. Over 50 other workers were also
injured after jumping off the building immediately after the fire broke out.

189

MOGBAZAR GAS EXPLOSION IN DHAKA
The Moghbazar explosion took place on 27 June 2021 at the wireless gate of Moghbazar in Dhaka,
the capital of Bangladesh. At least 7 people were killed and more than 100 injured, out of which 66
were admitted to various hospitals. Police suspect the incident was caused by frozen gas. The forceof the explosion caused significant damage to at least seven nearby buildings, as well as three buses
and other cars. Many of the injured came from the passenger buses and other cars which were stuckin traffic in front of the building when the explosion took place.

190

PART-IX

RECENT EARTHQUAKES AROUNDBANGLADESHBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By:
Mehedi Ahmed Ansary

191

APRIL 28, 2021: TEZPUR, ASSAM, INDIA

Assam earthquake: The primary earthquake had its epicentre at latitude 26.690 N and longitude
92.360 E, about 80 km northeast of Guwahati, and a focal depth of 17 km. Several houses andbuildings were damaged after an earthquake of magnitude 6.4 on the Richter scale hit Assam around
8 am on Wednesday. Six aftershocks of magnitude ranging from 3.2 to 4.7, occurred in the two-anda-half hours following the main tremor.
HFT, also known as the Main Frontal Thrust (MFT), is a geological fault along the boundary of the
Indian and Eurasian tectonic plates. The Kopili Fault is a 300-km northwest-southeast trending fault
from the Bhutan Himalaya to the Burmese arc. People look on at debris after a portion of few shops
were damaged due to earthquake at Bhetapara in Guwahati, Wednesday, April 28, 2021. (PTI Photo)
The United States Geological Survey (USGS), a scientific agency of the US federal government,
defines a fault as “a fracture along which the blocks of crust on either side have moved relative to
one another parallel to the fracture”.
Prof Chandan Mahanta of the Department of Civil Engineering at the Indian Institute of Technology,
Guwahati, said: “The Northeast is located in the highest seismological zone, so we must haveconstant earthquake preparedness at all levels. Continuous tectonic stress keeps building up
particularly along the faultlines. Today’s earthquake was an instance of accumulated stress release —probably, stress was constrained for a fairly long time at this epicentre, and hence the release was ofrelatively higher intensity.”
Prof Mahanta said the timing of the earthquake and its duration ensured the damage was restricted.
“The earthquake occurred early in the day when people were mostly home. Had it happened during
working hours, say when there were workers at under-construction high-rise buildings, theearthquake might have taken lives,” he said.

192

“The duration is also important,” Prof Mahanta said. “Had the main tremor continued for more than
30 seconds with the same intensity, the resultant acceleration and resonance could have cause greater
damage to structures.”1.
1/9
People watch an earthquake-damaged building at Bhetapara in Guwahati. (PTI Photo)

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1.
2/9
A man searches for his belongings amidst the debris after a boundary wall of his housecollapsed following an earthquake in Nagaon district in Assam. (Reuters photo)1.
3/9
A woman points towards the crack in a building caused due to an earthquake, in Guwahati.
(PTI Photo)

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1.
4/9
Impact of earthquake caused damage to houses and building. Also, the CM Sarbananda
Sonowal tweeted, “PM Shri Narendra Modiji has taken stock of the damage due to theearthquake over the phone with me and has assured all support to Assam.” (Express Photo)1.
5/9
Epicenter of earthquake was near Dhekiajuli town, north of Guwahati, Assam. (Express
Photo)

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1.
6/9
Many buildings in Tezpur, the district headquarters of Sonitpur, Guwahati and other places
developed cracks. (Express Photo)

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1.
7/9
Most parts of the region felt the impact of the massive earthquake as people ran out of theirhomes and other places in panic.

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1.
8/9
Union Home Minister Amit Shah on Wednesday spoke to Assam Chief Minister Sarbananda
Sonowal after the state was hit by an earthquake. (Express Photo)

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1.
9/9
According to the Seismology department, the tremors were felt for at least 30 seconds.

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MAY 29, 2021: SYLHET, BANGLADESH

Tilted School

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RAJA Mansion and Modhubon Market

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