BNUS ANNUAL REPORT-2022

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

Mehedi Ahmed Ansary

April 2023

CONTENTS
PART-I: SEISMIC PERFORMANCE ANALYSIS OF SPUN
PRECAST CONCRETE PILE IN RECLAIMED SOIL
3
PART-II: A NUMERICAL INVESTIGATION OF NEW AUSTRIANTUNNELING METHOD AND TUNNEL BORING METHOD FOR
TUNNEL CONSTRUCTION
81
PART-III: NUMERICAL ANALYSES OF A MAT BELOW A
NUCLEAR POWER REACTOR UNDER SEISMIC LOADING
158
PART-IV: NUMERICAL MODELING OF PILED RAFT FOUNDATIONSYSTEM SUBJECTED TO SEISMIC LOADING
226
PART-V: EVALUATION OF CONSOLIDATION CHARACTERISTICS
FROM PIEZOCONE PENETRATION TEST
346
PART-VI: MICROZONATION OF RANGPUR CITY CORPORATIONAREA BASED ON SITE AMPLIFICATION USING NONLINEARTECHNIQUE AND LIQUEFACTION
394
PART-VII: ESTIMATION OF LIQUEFACTION SUSCEPTIBILITY OF
A NEW INTERNATIONAL AIRPORT SITE IN SYLHET,BANGLADESH
444
PART-VIII: ASSESSMENT OF SOIL-BUILDING RESONANT EFFECTFOR DMDP AREA IN BANGLADESH
468
PART-IX: DEVELOPMENT OF CORRELATION EQUATIONSBETWEEN SHEAR WAVE VELOCITY AND STANDARDPENETRATION TEST VALUES FOR DIFFERENT SOIL TYPES FOR
DMDP AREA OF BANGLADESH USING MULTIVARIATEANALYSIS
497
PART-X: EFFECT OF SURCHARGE PRESSURE ON MODELGEOTEXTILE WRAPPED-FACE WALL UNDER SEISMIC
CONDITION
515
PART-XI: RECENT MAJOR FIRE/OTHER INCIDENCES INBANGLADESH
532

PART-I

SEISMIC PERFORMANCE ANALYSIS OFSPUN PRECAST CONCRETE PILE IN
RECLAIMED SOILBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By:

Kh. Afia Farzana Haque
Mehedi Ahmed Ansary

CHAPTER 1
INTRODUCTION
1.1

GeneralIncreased demand for high-rise buildings for the ever-growing urban population madeengineers build structures in poor ground condition. In this case, heavy loads coming fromstructures near the ground drive the engineers to adopt a deep foundation. Pile foundations can
be classified into two categories: displacement piles and replacement piles. The displacement
pile is installed by pushing into the ground which causes soil displacement around the pile. In
replacement piles, the soil is replaced with subsequent placement of pile material. A Prestressed
spun concrete pile is a displacement pile driven into an end bearing layer. It is newly introducedin Bangladesh for its better-quality control technique and quiet pilling operation. A precast
prestressed spun pile can provide high bearing capacity from large shaft resistance and toe
bearing.
The main reason for the pile foundation is to limit the settlement and control damage of thestructure due to the soft layer underground. If the loose sand under the structure is saturated, it
tends to behave like a liquid during earthquake shaking and tries to flow laterally. This makes
the foundation vulnerable to extensive damage as the soil losses shear strength due to porewater pressure generation. The extensive damage caused by liquefaction of both superstructureand foundation is observed during past earthquakes namely Niigata earthquake in Japan 1964,
1995 Kobe Earthquake. Bangladesh and north Indian states are seismically active regions in
the world. In the last 200 years, it has experienced numerous large magnitude of earthquakes.
Though Dhaka did not encounter large to moderate magnitude earthquakes in the past but
researchers pointed out four vulnerable points as a source of an earthquake that makes Dhaka
a risky city among 20 unsafe cities in the world. Recently a mild tremor of 3.4 magnitudes was
felt in Sylhet, Bangladesh. An earthquake of 4.5 magnitudes was felt in 2001 with a focal depthof 10 km near Dhaka. With the increased population, Dhaka city is going through rapid
urbanization. As a result, many lowland areas are now being used and filled up with loose
sandy dredged soil which is susceptible to liquefaction during seismic action.
Most piles are designed considering the axial load coming from the structure but during seismic
events, it can suffer from substantial lateral pressure and large settlement in liquefiable soil.
Previous studies showed that a pile can sustain axial load during the earthquake but it fails in

1lateral load, so it is mandatory to design a pile in the seismic region considering both axial andlateral load to overcome unwanted sudden damage of foundation and superstructure.
Numerical analysis is a reliable way to determine the seismic performance of a pile for aparticular subsoil condition. By considering both geological properties and structural loading
conditions, numerical investigation can evaluate the pile-soil response during seismic wave
propagation. Researchers use finite element modeling to determine the factors affecting pile
behavior in seismically vulnerable areas where piles can encounter possible failure due to weaksoil during the liquefaction phenomenon.
For simulating pile-soil behavior, PLAXIS 3D finite element software is used in this thesis.
Emphasis is given on soil modeling with earthquake loading and its effect on the pile. Different
constitutive models are incorporated in PLAXIS such as Mohr-Coulomb (MC) model, theelastic-plastic non-linear stress-dependent stiffness Hardening Soil (HS) model, UBC3D-PLM,
etc. In this study, the Hardening soil model is used for soil modeling for analysis of static andearthquake loading conditions. UBC3D-PLM model is used to capture the liquefaction
probability during earthquake in loose sandy soil. The pile is modeled as an embedded beam
row element. The function of embedded beam row is widely acknowledged by researchers insimulating dynamic pile response.
In this investigation, a static SPC pile load test has been conducted, and also SPT test has been
also carried out in the study site. After the field tests, a numerical model is validated with thepile load test data and pile is simulated under static loading. A detailed numerical investigation
has been conducted to observe the SPC pile response in earthquake loading in liquefiable soil
situated in Jolshiri reclaimed land.
1.2

Background of the Study

Researchers have found much evidence of pile damages during earthquakes due to inertia
forces of superstructures and piles lateral displacement. Spun Prestressed Concrete (SPC) pilehas become a convenient choice for engineers in cohesionless liquefiable soil for building
structures because of its low construction cost, high bearing capacity, and good reliability. The
pile foundation is designed to sustain vertical and lateral load but sufficient lateral resistance2

needs to be considered for resisting structural damage of piles during an earthquake. The SPC
piles are widely used abroad and many researchers have conducted experimental and numericalinvestigations to see the SPC pile capacity under axial and lateral load. The present study
intends to investigate the seismic performance of SPC pile foundation in a reclaimed area of
Dhaka susceptible to earthquake-induced liquefaction using three-dimensional numericalmodeling.
Spun Prestressed Concrete (SPC) pile is a reliable alternative to conventional driven or boredpile due to its high ultimate load capacity and skin friction (Akiyama et al., 2012). Under
dynamic loading prestressed pile showed larger peak displacement for saturated soil rather thanunsaturated soil but prestressed pile can resist the damage well (Huang et al., 2017; Huang andYu, 2017). A pile can be yielded before the complete liquefaction took place in the reclaimed
layer (Uzuoka et al., 2007). The static load test can accurately measure the ultimate bearing
capacity of prestressed high strength concrete pile compared to SPT blow count, CPT method(Wei et al., 2020). Numerical investigations are also done by researchers to observe pileperformance in different soil characteristics (Kyi and Yangon; Lozovyi and Zahoruiko, 2014;
Mohey Mohamed et al., 2020; Shafiqu and Sa'ur, 2017). Belinchón et al. (2016) have carriedout a numerical investigation to model the negative skin friction of hollow prestressed piledriven into soft soil. The increased reinforcement ratio, pile depth, and prestressing level canmove the plastic hinge location of the pile at a deeper depth and improve soil-pile interaction(Huang et al., 2020). Yang et al. (2018) have observed that the increase in reinforcement ratio
of prestressed tendons and concrete infilling can improve ductility and bearing capacity of thepiles.
Though SPC is widely used worldwide for its high strength capacity but in the context of
Bangladesh SPC pile is newly introduced for reclaimed areas. Again, there is gap in literature
to study SPC pile in loose soil susceptible to liquefaction during seismic excitation. Very few
researchers addressed the problem of pile behavior in weak liquefiable soil. So, it is imperative
to understand the pile behavior both in terms of vertical loading and lateral loading conditionin subsoil conditions like reclaimed areas where the soil is highly susceptible to liquefaction
phenomenon. The accurate way to measure the bearing capacity of pile foundation is to conduct
in situ static pile load test. In the study area, this test is conducted to know the ultimate pile
vertical load-bearing capacity. Pile foundation analysis is a three-dimensional problem. This
study uses 3D finite element software to validate the vertical bearing capacity with field load
test data and simulate the seismic behavior of the SPC pile under earthquake loading.
3

1.3

Objectives of the Study

The following are the main objectives of the research:(i) To investigate the soil characteristics of the study site by conducting field and laboratory
tests.
(ii) To develop a 3D finite element numerical model of SPC pile of at the site soil conditionand compare it with the static pile load test data.
(iii) To observe SPC pile performance numerically under seismic excitation and conduct theparametric study.
1.4

Scope of the StudyFirstly, to know the soil characteristics of the soil Standard Penetration Test (SPT) has been
done and soil samples has been collected to the laboratory for determining soil index and shear
strength properties. A static pile load has also been performed to estimate pile capacity in
Jolshiri Abashon area.
Secondly, a numerical finite element modeling has been done in PLAXIS 3D using Hardening
soil model and embedded beam row to simulate static pile load test behavior. The developedmodel has been validated with the results of the static pile load test. A parametric study has
also been done to observe the influence of mesh size, pile length and diameter on pile response.
Thirdly, the numerical model has been subjected to earthquake ground motion to observe thepile dynamic response using proper boundary condition. Liquefaction behavior of pile and soil
has been simulated using UBC3D-PLM model during earthquake excitation.
Figure 1.1 shows the flowchart of the work procedure used to conduct the study.

4

Field data collection and laboratory test

Conduct static pile load test

Determine bearing capacity of SPC pile and liquefaction susceptibility of soil
from SPT N value

Develop FEM model in PLAXIS 3D and validate the model with pile load test
data

Conduct parametric study numerically considering mesh size, pile length anddiameter variation

Conduct dynamic analysis numerically using different earthquake data to
determine pile and soil response

Conduct liquefaction analysis to determine liquefaction susceptibility of soil andit’s response on pile in study site using UBC3D-PLM model in PLAXIS 3D

Comparing the earthquake effect on liquefiable and improved soil
Figure 1.1: Flowchart of the study5CHAPTER 3
FIELD DATA COLLECTION AND BEARING CAPACITY ANALYSIS

3.1

Introduction

In this present study, the Jolshiri Abashon project area has been selected which is a reclaimed
land located at the center of the eastern side of the DMDP area, Dhaka, Bangladesh. Jolshiri
Abashon is 1.3 km from the south side of Purbachal's new town and it is surrounded by theBalu River on the west and the Shitalakkhya River on the east. Figure 3.1 shows the site
location.

Figure 3.1: Jolshiri Abashon area
Primarily, at this site the subsoil investigation has been carried out and required soil propertiesare determined in the laboratory. A pile load test has also been conducted on a SPC pile in
Jolshiri area for determining in-situ vertical bearing capacity. The results are verified withdifferent existing empirical methods to estimate the bearing capacity.

43

3.2

Geometry of SPC Pile

Hollow prestressed precast reinforced concrete piles are termed as spun prestressed concrete(SPC) pile. SPC pile’s geometry is commonly used in electric poles and they can be fabricatedat the same factory. The concept of using spun pile as the foundation of soft soil particularly inthe coastal zone has gained popularity for the last two decades mainly due to its easierinstallation, low cost, higher bearing capacity and easier insurance of material quality before
pile casting. The hollow circular geometry of the SPC pile used in this study is shown in Figure
3.2 (a), the fabricated SPC pile and the long section of the pile with reinforcement are shownin Figure 3.2 (b), and Figure 3.2 (c), respectively. The SPC piles are fabricated through a special
arrangement of caging, prestressing followed by the procedure of concrete pouring, rotating,steam curing etc. The aggregate size is usually 12mm and downgrade and ordinary portland
cements (OPC) are used in the construction of SPC piles. PCC cements are also used in someconstruction. Relatively, high strength concrete (a concrete strength 50 MPa and above) andhigh strength strands (a nominal strength of 1860 MPa) are used for SPC pile casting. A
prestress of 50 MPa is used in these piles to enhance the bending capacity that can ensure thepiles to sustain lifting and handling stress. The basic features of the used SPC piles in this study
are presented in Table 3.1.
Generally, the bearing capacity of the SPC pile is governed by the structural capacity of thepile. The length of the pile is designed based on the ability to penetrate through the soil.
Subsequently, the lateral capacity of the pile is also designed as per the requirement of the site
condition. The cross-sectional area of the SPC piles are low therefore shear reinforcement plays
a key role against shear forces generated from seismic excitation. The allowable vertical
capacity of SPC piles may be given by the API guideline as shownin equation 3.1(Piling.2019).
P

A 0.33 f

0.27f

Where
Pa, the allowable service level axial load bearing capacity of SPC pile
Ag, gross cross-sectional area of pilef'c, compressive strength of concrete at 28 days
fpc = effective prestress in the pile

44

3.1

450 mmCircular

(a)

(b)

(c)
Figure 3.2: Geomtery of SPC pile: (a) Circular hollow cross section; (b) SPC pile ready fortransportation; (c) Long section of SPC piles showing the spiral reinforcement
details.

45

Table 3.1: Properties of SPC pile used in this study
SI
Description
1. Diameter

Properties (Unit)
450 mm

2. Length

12 m / 9 m / 6 m

3. Cement used

OPC/PCC

4. Concrete Mix Ratio
FM of Sand
Max Agg Size

1:1.25:2.5
2.5 FM(4-8) mm and (12 to 16)mm
110 mm
7 Nos (pre-stressed)
50 MPa1860 MPa
440 MPa
At top and bottom 1.5 m
At the middle
2500 kN

5. Wall Thickness
6. Material Spec:
Concrete Strength
Strands: 9mm dia
4mm MS wire ultimate load
7. 4mm MS wire @50mm c/c
4mm MS wire @75C/C
8. Design Compressive Load
(12m)
9.

3.3

Bending Strength

180 kN-mLaboratory Test Results

To obtain the soil stratification of the selected site, subsoil investigation has been carried out.
Three boreholes have been conducted within a residential building site. Each boring is
associated with a Standard Penetration Test (SPT) and collection of disturbed and undisturbed
samples from different depths of the boreholes. Figure 3.3 (a, b) shows the schematic diagramof borehole location for Standard Penetration Test (SPT). Figure 3.4 also shows the different
soil stratum which are obtained from the subsoil investigation. In Figure 3.5, three boreholes
are presented with respect to SPT blow count at different depths. As can be seen from the
Figure, the top layer of the soil (up to 4.5 m depth) is consisting of very loose sand with an SPT
value below 11. All three boreholes confirmed that there is a 33 m thick soft clayey sandy silt.

46

(a)

(b)

Figure 3.3: a) Standard Penetration Test (SPT) b) Borehole Location

47

Figure 3.4: Borehole cross-sections

48

49

Depth (m)

0
1.5
3
4.5
6
7.5
9
10.5
12
13.5
15
16.5
18
19.5
21
22.5
24
25.5
27
28.5
30
31.5
33
34.5
36
37.5
39
40.5
42
43.5
45
46.5
48
49.5

0

10

30

SM (Dense Silty Sand)

ML (Soft Clayey Silt)

SP (Loose Fine Sand)

20

SPT N value
40

50

Depth (m)030

ML (Soft Clayey Silt)

SP (Loose Fine Sand)

20

SM (Dense Silty Sand)

10

40

50

Figure 3.5: SPT N values for three boreholes

0
1.5
3
4.5
6
7.5
9
10.5
12
13.5
15
16.5
18
19.5
21
22.5
24
25.5
27
28.5
30
31.5
33
34.5
36
37.5
39
40.5
42
43.5
45
46.5
48
49.5

SPT N value

Depth (m)

0
1.5
3
4.5
6
7.5
9
10.5
12
13.5
15
16.5
18
19.5
21
22.5
24
25.5
27
28.5
30
31.5
33
34.5
36
37.5
39
40.5
42
43.5
45
46.5
48
49.5

0

30

ML (Soft Clayey Silt)

SP (Loose Fine Sand)

20

SM (Dense Silty Sand)

10

SPT N value
40

50

The first layer shows loose sandy soil, the second layer is soft clayey silt, third layer is dense
silty sand layer. A hard stratum is found once the depth of penetration exceeds 37.5 m. The
soil classifications are done with the data found from laboratory test results such as grain size
analysis, CD triaxial test, Atterberg limit, moisture content, direct shear test, organic content
test, unit weight, consolidation test, unconfined compressive strength test etc. Disturbed andundisturbed test samples have been collected from the study site at different depths. The
laboratory tests are performed to identify the soil index and strength properties. The Laboratory
tests are conducted by following the provisions of the standard code of practices such as BNBC,AASHTO and ASTM as shown in Figure 3.6. The soil layers are classified on the basis oflaboratory test results according to the Unified Soil Classification System (USCS) for threeboreholes. In absence of test results for any depth of a borehole, standard correlation with SPTN values is followed based on soil characterization presented in this study.
3.3.1

Grain Size Analysis

Sieve Grain Size Analysis is done to determine the particles’ size ranging from 0.075 mm to
100 mm. Particles smaller than 0.075 mm is distributed using the Hydrometer Method. The
particle-size distribution curve is used to calculate the coefficient of uniformity and thecoefficient of curvature. Based on the lab test results, grain size distribution curve is presented
on Figure 3.7. The D50 mean for loose and medium sand are 0.1850 mm and 0.3038 mm, while
the fine fraction < 0.075 mm are 11% and 9%, respectively. For clayey silt the D50 mean is0.0125 mm and fine contents is 95%. In dense sand, D50 mean is 0.255 mm and fine contents
are between 44% and 25%. The SPT, soil classification, basic strength and index properties arepresented in Table-3.2. The tables show that the soil strata containing ML is highly plastic witha LL of 32-38% and PI of 6-12%. Nearly 90-95% of the particle is passing #200. When thedepth exceeds 37.5 m, dense silty sand is found with a SPT value of 50 and above. From 7.5 m
to 37.5 m a layer of dark gray soft clayey silt layer exists which is not suitable for supporting
end bearing resistance of pile foundation. Beyond 37.5 m brown dense silty sand continues
which is capable of withstanding deep foundation’s end bearing. Based on the geotechnicalparameters, it is decided that the toe of the SPC piles will rest at this layer.

50

Figure 3.6: Laboratory test (a) Disturbed soil sample (b) Undisturbed soil sample (c) Specificgravity test (d) Direct shear test (e) Atterberg limit test (f) Triaxial test.

51

100
90

Percent Finer

80
70
60
50
40

Clayey Silt'

Dense Silty Sand
Loose Fine Sand

30
20
10
0
0.0001

0.001

0.01

0.1

1

10

Diameter, mm

Figure 3.7: Particle size distribution curve

3.3.2

Atterberg Limit Test

Atterberg limit tests has been conducted with the soil samples collected from different depts toestimate the liquid limit, plastic limit and plasticity index of soil. Thus the soil is classified at
depth 16 m using Casagrande Plasticity Chart as shown in Figure 3.8. At depth 21 m, 16 m and30 m the Atterberg limit test has been done and it is found that the LL is between 36-37%, PI
ranges from 6-9 %. The soil at this layer is classified as Clayey silt soil.

52

Figure 3.8: Casagrande Plasticity Chart
3.3.3

Unconfined Compression Test

The unconfined compression test is also called unconfined compressive strength test. It is done
under uniaxial compression condition to determine undrained shear strength of saturated soil
Cu. In this study unconfined compression test has been done at a depth of 8.7 m. The Cu value
ranges from 20-35 kPa for different borelogs, see Figure 3.9 (a). The shear failure of soil
samples are shown in Figure 3.9 (b).
(a)
Corrected Deviator Stress in kPa

80
70
60
50
40
30
20

BH-1
BH-2
BH-3

10
0
0

2

4

6

8

10

Axial Strain in %

53

12

14

(b)

Figure 3.9: (a) Relationship between axial strain and stress and (b) brittle failure mode
3.3.4

Consolidated Drained Direct Shear Test

To determine the shear strength of soil materials, direct shear test has been done at different
depth 37 m, 39 m and 40 m. It is conducted for cohensionless soil to determine internal angleof friction. The internal angle of friction value varies between 25- 32o for different depth. In
Figure 3.10 the stages of direct shear test has been shown and at depth 40 m the phi value isfound to be 32o.
(a)
600

Shear Stress in kPa

500
400
300
200

200 kPa
400 kPa100

800 kPa

0
0

2

4
6
Shear Displacement in mm

54

8

10

12

(b)
0

2

Shear Displacement in mm
4
6

8

10

12

Normal Displacement in mm

0.0
1.0
2.0
3.0
4.0
5.0

200 kPa

6.0

400 kPa
800 kPa

7.0(c)

Figure 3.10: Direct shear test, relationship between (a) maximum shear stress and normal
stress (b) deformation and root time (c) shear stress and horizontal displacement(d) vertical and horizontal displacement55

3.3.5

Consolidated Drained Triaxial CompressionTest

To determine the soil shear strength parameter in drained condition Consolidated Drained (CD)triaxial compression test is an effective way. The CD test has been done at a depth of 11.7 m.
The mohr circles obtained from the test is shown in Figure 3.11 (a). From the stress and strain
relationship in Figure 3.11 (b) is used to determine stiffness parameters of soil. Figure 3.11 (c)Explains the change of volumetric strain with axial strain. Figure 3.11 (d) shows the shear
failure modes of soil samples.
(a)

400 kPa

200 kPa
100 kPa

Corrected Deviator Stress in kPa

(b)
500
450
400
350
300
250
200
150
100 kPa
200 kPa
400 kPa

100
50
0
0

2

4

6

8

Axial Strain in %

56

10

12

14

(c)
0

Volumetric Strain %

0

2

4

6

8

10

12

14

-0.5
-1
-1.5
100 kPa-2

200 kPa
400 kPa-2.5

Axial Strain in %(d)Figure 3.11: Relationship between (a) Shear stress and principal stress (b) Deviator stress andaxial strain (c) Volumetric strain and axial strain and (d) shear failure modes of soil
samples
3.3.6

One-Dimensional Compression Test

One dimensional consolidation test has been done at a depth of 10 m with undisturbed soil
sample to determine the initial void ratio, compression index. From void ratio to appliedpressure graph as shown in Figure 3.12, the void ration is 0.87 and compression index is 0.261
and swelling index is 0.058 with a preconsolidation pressure of 100 kPa.

57

0.75

Void Ratio,e

0.7

0.65

0.6

0.55

0.5
10

100

1000

Pressure, P in kPa

Figure 3.12: Relationship between void ratio and applied pressure

Table 3.2: SPT and Subsoil Classification
Result SummaryDepth

SPT range

USCS

Basic soil properties

0 to 4.5

0 to 11SP

γ =14 kN/m3, γsat =15 kN/m3,Gs=2.61,wn=41.7% ,Fines (#200 passing) = 11.0% , ϕ= 26.0o

4.5 to 37.5

1 to 4ML

γ =16 kN/m3, γsat =17.5 kN/m3, LL = 32-38%,
PI = 6 -12%, Fines (#200 passing) = 90-95%,
wn = 35 %, Cu = 20-24 kPa.

>37.5

30 to 50SM

γ =18 kN/m3, γsat =20 kN/m3 , Gs=2.67, wn=1315%, Fines (#200 passing) = 25-44%, φ = 33.0o

58

(b)

(a)

Shear Modulus. Gmax (MPa)Shear Velocity. Vs (m/s)
100

200

300

0

400

0

5

5

10

10

15

15

Depth, (m)Depth, (m)

0
0

20

25

BH-01

100

200

300

20

25

BH-01
BH-02

BH - 0230

30

BH - 03

BH - 03
35

35

40

40

45

45

50

50

Figure 3.13: a) Depth vs Shear wave Velocity b) Depth vs Shear Modulus, Gmax
The dynamic soil properties like Shear-Wave Velocity (Vs) and Small Strain Shear Modulus(Gmax) are correlated from field SPT N values as described in chapter two. In this study,
equation suggested by JRA (1980) has been used for calculating of shear wave velocity andshear modulus from SPT N values and presented in Figure 3.13 (a) and (b) respectively. The
Figure shows that both the shear wave velocity and shear modulus of the soil increase as thedepth of penetration increases though there are some fluctuations.

59

The minimum shear wave velocity is observed in a layer of 12-37.5 m deep which is 100-130m/s. The maximum wave velocity is observed to be 300 m/s at a depth 40 m and above. As canbe seen from Figure 3.13 (b) that the minimum shear modulus is 18 MPa at a depth of 12 to37.5 m and the maximum value of the G is 200 MPa which is observed at depth 40 m andabove.
3.4

Field Test

The SPC pile is installed in the site by push piling method. Then a static pile load test has been
conducted on the installed SPC pile to determine the in-situ pile bearing capacity.
3.4.1

Pile Load Test

A single circular hollow SPC pile of 450 mm diameter and 110 mm wall thickness is driven
through the soil stratum where it has been rested on a dense sand layer at an embedment depthof 42.5 m. To obtain a stable foundation, the pile is penetrated through the soft layers to dense
sand layer. The pile is inserted by push piling method with maximum load of 4067 kN. Lateron the static pile load test on spun pile is performed according to ASTM D-1143 (ASTM.1994).
The incremental compressive load is applied as 10% of design load until 250 ton design load
is reached. The pile is loaded till failure by applying 428 ton load. The applied load ismaintained in each case for 1 hr and the load is removed in decrements equal to the loading
increments, a 20 min in between gap is provided for decrements. After removing eachmaximum applied load, reapply the load to each preceding load level in increments equal to 50% of the design load, allowing 20 min between increments. Applied the additional loads after
the design load is reached and maintained till failure occurs. After the maximum required test
load has been applied, hold and removed the test load when the pile is failed under maximum
load. Site photographs showing push-in test is presented in Figure 3.14 and in Figure 3.15 thepile load setup is shown.

60

Figure 3.14: Push-in test in study area

61

(b)

(a)

Concrete Block

Hydraulic Jack
Dial gauge

Reference Beam

(d)

(c)

Figure 3.15: a) Performing static load test b) Schematic diagram of static load test c) spun pilefor driving in soil d) Hydraulic jack and dial gauge setup during the test

62

3.5

Liquefaction Analysis in Jolshiri Site

After determining different soil parameters from field and laboratory test of disturbed andundisturbed samples, the liquefaction analysis has been done after (Seed et al.,1983). The soil
parameters like SPT N values, fine contents, unit weight, groundwater table, D50 results havebeen obtained and used for the liquefaction analysis.
The reclaimed areas are expanding at a faster rate due to industrialization and facilitate theinhabitants. To provide a safe structure, a geotechnical engineer needs to do the liquefaction
analysis. In Jolshiri site, the liquefaction analysis is done for identical boreholes from SPT N
values and data acquired from soil investigation reports. The cyclic stress ratio is determinedusing borehole information, total and effective overburden pressure. The SPT test is done ateach 1.5 m interval and ended up to 45 metres.
The SPT N values are used to estimate the cyclic resistance ratio. According to Bangladesh
National Building Code (BNBC) 2020 the maximum considered earthquake (MCE) for
Bangladesh corresponds to 2% probability of exceedance for 50 years of return period. Recent
researches and historical data shows that Bangladesh is prone to experience a magnitude of 7.0
or greater earthquake near future. There are four zone coefficient in BNBC-2020 and Dhaka
lies in zone-II. So for Dhaka city maximum peak ground acceleration (PGA) at the groundsurface and magnitude of earthquake is considered to be 0.20 g and 7.5.
At different depths, the factor of safety against liquefaction is calculated. Figure 3.16 shows
the liquefaction assessment curve for three boreholes analysed by the mentioned method above.
The curve is shown for different magnitude of earthquake 7.5, 6.5, 6, 5.5 and 5. The threeborehole are identical and first layer is loose sandy type of soil. Up-to depth 4.5 metre the factorof safety values lies less than one which indicates strong liquefaction probability at upper layer.
The result has also showed compatibility with existing literature for loose sandy or silty soil
layers liquefaction analysis.

63Factor of Safety (FSL)
0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

0
5
10

Depth(m)152025

Mw=7.5
Mw=6.5
Mw=6.0Mw=5.5Mw=5.0

30
35
40
45
50

Figure 3.16: Comparison of liquefaction assessment
3.6

Bearing Capacity Analysis of SPC pile

After collecting the SPT values and data from laboratory test results, the bearing capacity forthe test site is evaluated by analytical procedure as described in chapter two. In Figure 3.17 (a)and (b) the bearing capacity with and without considering liquefaction is shown with respect
to borehole depth. From Figure 3.18 (a), it is observed that in liquefiable soil the skin frictionof pile is reduced considerably for borehole one, two and three around 9.41 %, 8.71 % and10.15 % respectively. The ultimate bearing capacity is also affected by liquefiable soil
characteristics as shown in Figure 3.18 (b). The ultimate pile capacity decreases 3.97% for
borehole one and 3.80 %, 4.50% for borehole two and three respectively. So the liquefaction
potentiality of any vulnerable site should be taken into consideration to evaluate the actual
bearing capacity for designing a safe foundation system.

64

65

45

45
(a)

40

40

30

25

20

15

10

5

0

35

capacity 2842 kN

capacity 2807 kN

capacity 2770 kN

BH:03

BH:02

BH:01

500 1000 1500 2000 2500 3000 3500

35

30

25

20

15

10

5

0

0

0

(b)

capacity 2714 kN

capacity 2702 kN

capacity 2660 kN(b) Bearing capacity considering liquefaction by analytical method

BH:03

BH:02

BH:01

500 1000 1500 2000 2500 3000 3500

Pile Load Capacity (kN)

Figure 3.17: (a) Bearing capacity without considering liquefaction by analytical method.

Depth from EGL (m)Pile Load Capacity (kN)

Depth from EGL (m)(a)Comparison of skin friction (with and without liquefaction)
Not considering liquefaction
1400
1200

1180

1217
1069

Considering liquefaction
1251
1111

1124

1000
800
600
400
200
0
BOREHOLE-1

BOREHOLE-2

BOREHOLE-3

Figure 3.18: (a) Comparison of skin friction considering with and without liquefaction(b)Comparison of ultimate bearing capacity (with and withoutliquefaction)
Not considering liquefaction

3000

2770

2660

2808

Considering liquefaction
2702

2842

2714

2500
2000
1500
1000
500
0
BOREHOLE-1

BOREHOLE-2

BOREHOLE-3

Figure 3.18: (b) comparison of bearing capacity considering with and without liquefaction.

66

After completion of pile load test, the result has been prepared from the field data. Loadsettlement curve of tested SPC pile (450mm dia) is shown in Figure 3.20 . Final result of staticload test is presented by following Bangladesh National Building Code (BNBC).
However, for simplicity and as widely adopted practice in Bangladesh, load correponding to asettlement of 12 mm is considered as design criteria in this study as shown in Figure 3.19. The
allowable load from the load-settlement curve is 150 ton corresponding to 12 mm settlementfor 450 mm diameter pile with a design load of 250 ton and maximum applied failure load
427.88 ton. Davission offset method is another widely accepted method for load capacity
interpretation from pile load test. In this method the ultimate capacity is estimated to be 3790
kN concerning 43.13 mm settlement as shown in Figure 3.20. The shape of curvature method
is widely used practice to determine the ultimate bearing capacity from field test data. The
tangent from the initial part of the loading curve and the ending part of loading part intersect ata point and that point is considered as the ultimate loading capacity of the pile. Figure 3.21
shows the bearing capacity 3463 kN and settlement is 24.60 mm in shape of curvature method.

D = 450 mm; L = 42.5 m; Design Load = 250 ton
Load (ton)
0

50

100

150

200

250

300

350

400

0

Settlement (mm)

15

30

45

60

75

Figure 3.19: Load vs Settlement plot of conducted load tests

67

450

Load (kN)
0

1,000

2,000

3,000

4,000

5,000

0

Settlement(mm)

10
20
30
40
50

Qult=3790 kN

60
70
80

Figure 3.20: Load-Settlement curve derived from pile load test by Davisson offset method

Load (kN)
0

1,000

2,000

3,000

4,000

5,000

0

Settlement (mm)

10
20
30
40

Qult = 3463 kN

50
60
70
80

Figure 3.21: Load-Settlement curve derived from pile load test by Shape of curvature method

68Pile Capacity (ton), Qult
0

100

200

300

400

500

0
SP
15
30
45

Pile-2 (450mm)
Analytical Capacity-450mm

Depth(ft)

60
75

ML

90
105
120
135

SM

150

Figure 3.22: Comparison of pile bearing capacity determined from Push-in test andanalytical method
Analytical bearing capacities of SPC piles are verified through field push-in test at selected siteof Jolshiri Abason. Push-in test has been conducted for 450 mm diameter SPC piles with aprogressive load at the rate of 1.52 m (5 ft) length. Figure 3.15 shows comparison between
analytical capacities and push-in values. Site photographs showing push-in test is presented in
Figure 3.14. From Figure 3.22, it is observed that beyond 37.5 m ultimate capacities of 450mm
diameter piles yield greater than 100 ton. However, in practice after 37.5 m further driving into the layer of hard soil (SPT>50) will depend on pile’s structural capacity and requirementson pile tip stability.

69

3.7

SummaryThis chapter deals with the field test data acuired in invetigation site. The bearing capacity
determined from both analystical and in-situ pile load test is obtained in this part. From theanalysis it can be summarized that:
1. For determining different soil strength parameters, conducting field and laboratory testis the only viable way. With this aim at the very outset, sub soil investigation is
performed in the study area and soil samples both disturbed and undisturbed arecollected for laboratory tests.
2. The soil boring data obtained from the site is important to classify the soil. From soil
investigation it is found that the top 4.5 m is filled with loose sand with a shear wave
velocity less than 180 m/s and SPT value less than 15. This layer is susceptable toliquefaction in saturated condition under seismic event.
3. The liquefaction analysis is done to observe the liquefaction susceptibility of the top
layer of soil using Seed and Idrris method. It is obtained that the CRR/CSR ratio is lessthan 1. So in this type of soil SPC pile is installed to increase the bearing capacity andreduce probable pile failure during earthquake.
4. The pile is installed by Push-in method in the site with an ulmimate load capacity of
414 ton for 450 mm diameter SPC pile. After that, in situ static pile load test is
performed in the site. The design load for the pile is 250 ton and the pile is tested to
failure with 427.88 ton load. The ultimate pile bearing capacity is also determined inthis chapter by analytical method with and without considering liquefaction
phenomenon.
5. The allowable bearing capacity of pile is determined from load-settlement curve
obtained from field load test data according to BNBC 2020. This curve is used further
to validate the FEM model for numerical investigation. Finally the Push-in test method
result is compared with the analytical at the pile tip.

70

CHAPTER 4
NUMERICAL MODELING
4.1

Introduction

To evaluate the bearing capacity of pile under static loading condition, the in situ pile load testis the most reliable and accurate method. In this investigation, the study area is filled with loose
silty sand type soil which is susceptable to liquefaction if earthquake occurs, so the chance of
pile failure during earthquake event is more likely to happen. Though the pile can sustain axial
load under design condition but the possibilities of failure under seismic excitation inliquefiable soil should be taken into consideration. The performance of SPC pile is evaluatednumerically considering both axial and earthquake loading condition.
In this segment, the results of numerical investigation is presented for SPC pile installed into
the study location. The FEM model is calibrated with the field pile load test data. The result ofembedded pile deformation is shown using HS soil model. The model parameters are
determined from field test results. Also the different stress distribution in soil during earthquake
and liquefaction are discussed here. At the end, a comparison is made between axially loaded
pile with the earthquake loading.
4.2

FEM Model in PLAXIS 3D

In this section, modeling assumptions for numerical analysis is described. Soil is modeled by
10 noded element. Drained analysis has been adopted for Hardening Soil (HS) model.
Groundwater table is taken at the GL. The soil parameters are determined from SPT N value
correlations and laboratory test results. A 42.5 m SPC pile is modeled using embedded beam
element with a outer diameter of 450 mm and wall thickness of 110 mm. Each soil layer
thickness is taken from the borelog profile collected from the study site and presented in chapter
three.
4.3

Derivation of Soil Stiffness Parameters

In Jolshiri study area, both field and laboratory tests are performed to determine different soil
index and strength properties which can act as input parameters for soil modeling in plaxis.

714.3.1

Field and Laboratory Tests Performed for Determination of Soil Parameters

Standard penetration test has been conducted in Jolshiri site up-to 45 m depth. SPT N values
are recorded at every 1.5 m depth. Both disturbed and undistrubed samples are collected fortesting in laboratory. The test procedure is done according to ASTM D 1586. To determine soil
index and shear strength properties and to know the actual soil condition in site, performing
laboratory test is a must. In this investigation different laboratory tests such as specific gravity
test, grain size analysis, Atterberg limit test, CD triaxial test, consolidation test, direct shear
test, unconfined compression test etc are carried out.
4.4

Modeling Parameters

In this section the input parameters in PLAXIS 3D for both soil and structural element arepresented.
4.4.1

Soil Modeling Parameters

Hardening Soil (HS) model is advanced model in predicting and simulating behavior of soft
soil as well as stiff soil. In hardening soil model yield surface is not fixed in principle stressspace but as a result of plastic straining yield surface can develop. This will change the soil
stiffness after loading and unloading. After applying primary deviatoric loading, soil shows
decreasing stiffness and irreversible plastic strain develops. For HS model the basic idea is todevelop hyperbolic relationship between vertical strain and deviatoric stress. It also controls
stress dependency level. The parameters requires for HS model are shown in Figure 4.1. HS
model uses the theory of plasticity than elasticity theory. In this model the input parametersare; m the stress dependent stiffness according to power law, plastic straining due to primarydeviatoric loading E50ref , plastic straining due to primary compression Eoedref , elastic unloading
Eurref and c, φ, ψ are the failure according to the Mohr-Coulomb failure criterion parameters.
The stiffness parameters are determined from triaxial test and consolidation test. In PLAXIS
K0nc is automatically recommended based on Jacky’s formula. νur and Rint are also
recommended values from PLAXIS. The required estimated parameters for HS model ispresented in Table 4.1.

72

Figure 4.1: Parameters for HS model73

Table 4.1: Material properties for the soil layers

4.4.2

Parameters

Unit

Loose sand

Clayey silt

Silty sandUnsturated unit weight(γunsat)

kN/m3

16

16

18

Sturated unit weight (γsat)

kN/m3

17

17.5

20

Secant stiffness modulus(E50ref)

kN/m2

10000

15000

38000

Oedometer modulus(Eoedref)

kN/m2

10000

15000

38000

Unloading/reloading
stiffness (Eurref)

kN/m2

30000

45000

114000Poisson’s ratio, ν

0.3

0.3

0.3

Cohesion, c

0

15

0

Angle of friction, φ

23

25

36

Dilation Angle, Ψ

0

0

0

Unloading/reloading
poisson’s ratio, νur

0.2

0.3

0.25

Power for stress-level
dependency of stiffness, m

0.5

0.5

0.5

K0 value for normallyconsolidated factor, K0 nc

0.531

0.577

0.412

Interface factor, Rint

0.7

0.9

0.9

Embedded Pile Modeling Parameters

The finite element modeling is done in PLAXIS 3D and validiated with the static pile load test
conducted on site. The soil is modeled using HS model parameters and SPC pile is modeled asembedded beam element in PLAXIS. The SPC pile is loaded under different axial load duringpile load test and reached to the ultimate load capacity. In PLAXIS the bearing capacity of pileis the input parameter for embedded pile rather than the result of finite element calculation.
The embedded pile input parameters are determined from pile load test. As embedded pile is74considered as beam element so the parameters are presented in terms of Young modulus E andthe unit weight γ of pile material. For modeling different geometric properties of pile,predefined shapes (masive circular pile, circular tube, square pile) with pile diameter and wall
thickess are provided. The properties of pile soil interaction is defined by skin resistance andbase resistance. In Table-4.2 the required properties of embedded pile are given.
Table 4.2: Required parameters of the embedded pile
Parameters

Name

Value

Unit

Predefined beam typeCircular tube--

Diameter

Diameter

0.450mWall thickness

Thickness

0.110

m

Young’s modulusE

32.88*106

kN/m2

Unit weight

γ

24

kN/m3

Skin resistanceType

Linear-Skin resistance at the beginning of
the embedded beam

Ttop,start,max

20

kN/m

Skin resistance at the end of theembedded beamTbot,end,,max

100

kN/m

Base resistance

Fmax

1600

kN

4.5

Numerical Modeling

The FEM model is developed for both axial and earthquake loading condition using same
parameters stated in Table 4.1 and 4.2. The soil profiles are modeled by consulting the borelog
collected from site to the depth of borelog up-to 45 m. Each layer has different characteristics
according to several tests performed. At first a borehole is located at (0,0,0) point. For model
perimeter 20 m in x direction and 20 meter in y direction are taken as model width. The model
depth is taken as 45 m in z direction as shown Figure 4.2. The water table is assumed at theexisting ground level. The pile is located at the middle of the soil perimeter as shown in Figure
4.3 (a). In this stage axial load is provided as a ponit load at the top of the pile. After completing75

the soil and structural modeling, the finite elemnt meshing is done. Figure 4.3 (b) shows theconnectivity plot of the model after meshing stage. The stage construction phases of PLAXIS
for axially loaded pile are given below in Table 4.3. In Table 4.4 the break down of loading
and unloading stages are given.

Figure 4.2: FEM model developed in PLAXIS 3D76

Table 4.3: Stage construction phases for compressive loading
Phase

Analysis type

InitialK0

Pile construction

Loading stage

Unloading stage

Plastic

Elements

Activated

Soil volume√

Embedded pile elementx

Point loadx

Soil volume√

Embedded pile element√

Point loadx

Soil volume√

Embedded pile element√

Point load√

Deformation in z
direction√

Soil volume√

Embedded pile element√

Plastic

Plastic

Point load (design load inreverse order)
Deformation in z
direction√√

Table 4.4: Stage construction phases for increamental loading and unloading stages
Phase

Analysis type

Loading stage

Plastic

Unloading stage

Plastic

77

Increamental loading
and unloading stages
L=0
L = 590 kN
L = 1202 kN
L = 1815 kN
L = 2490 kN
UL = 1815 kN
UL = 1202 kN
UL = 590 kN
UL = 0Figure 4.3: (a) Axially loaded embedded pile and (b) connectivity plot78

4.5.1

Validation with Field Pile Load Test Data

The pile load test is simulated in PLAXIS 3D and the maximum settlement from the analysis
is 18.47 mm which is very close to the maximum settlement of field test 17.60 mm as shownin Figure 4.4. The simulated result shows good agreement with the field pile load test results
under static loading condition. Therefore, this calibrated model can be used for further analysis.

Load (kN)
0

500

1000

1500

2000

2500

3000

0
2

Settlement (mm)46Pile Load Test

8

PLAXIS 3D

10
12
14
16
18
20

Figure 4.4: Comparison of PLAXIS 3D obtained results with field measured result

4.5.2

Pile Deflection under Axial Loading

After completing the numerical model, the pile is analysed under different incremental loading
condition similar to the field condition as shown in Table 4.4. At different loading stages pile
exhibits displacement in both lateral and vertical direction. In PLAXIS displacement are shownin three direction i.e. Ux, Uy, Uz as well as total displacement is also depicted in form of graphor contour plot. Ux, Uy displays displacement in lateral direction and Uz in vertical direction.

79

Figure 4.5 shows the axial load distribution along the pile length. The vertical load is appliedat pile head at different stages and the result shows that with increasing depth the axial loaddecreases. Figure 4.6 shows the three dimentional view of displacement contour of pile in z
direction around the pile from the modeling results from compression loading. The
displacement field is concentrated around the pile with a pile head displacement of 18.47 mm.
Figure 4.7 shows the top view of pile displacement. The pile shows tolerable displacement
under design load 2500 kN.

Axial Load (kN)
-2500.00 -2000.00 -1500.00 -1000.00
0.00-500.00

0.00

5.00

10.00

Length (m)

15.00

20.00

25.00

30.00

590 kN
1202 kN

35.00

1815 kN
2490 kN

40.00

45.00

Figure 4.5: Relationship between pile depth and axial load

80

(a)

(b)

Figure 4.6: a) Displacement field around pile b) Top view of displacement contour

81

4.5.3Stress Distribution

The Principle total stress in soil skeleton is shown in Figure 4.7 at 42.5 m depth. The maximum
stress generated due to axial loading is 647 kN/m2. The stress field is concentrated around thepile and it is represented as red color. The yellow field shows stress distribution in soil particles.
The total strain contour at the top of the pile in z direction is presented in Figure 4.8 and the
maximum strain is 0.016. The stress strain relationship of a particular point at bottom end isdisplayed in Figure 4.9. It seems that mostly the strain develops in soil element as the result ofplastic strain.

Figure 4.7: Total principle stress at surrounding soil at pile bottom

82

Figure 4.8: Total strain in z direction
195.00
194.00q (kN/m2)

193.00
192.00191.00190.00189.00-0.00058-0.00056-0.00054-0.00052-0.00050-0.00048

ε1

Figure 4.9: Stress-strain relationship83-0.00046-0.00044

4.6

Parametric Study

The numerical model can be influenced by pile diameter, length and mesh size that can affectthe pile response in soil body. The parameters can make differences in terms of accuracy andefficienecy of the computation. Influence of different pile diameter, length and mesh sizes isalso investigated through parametic analysis.
4.6.1

Influence of Mesh Size

For performing finite element calculation, a fully defined geometry is divided into finite
elements. This combinations of finite element is called mesh. Mesh coarseness is considered
to have significant effect on calculated results. Fine meshing is important to get accurate resultin any analysis but it takes longer time for calculation. The mesh generation process includes
soil stratigraphy, structure, loads and boundary. The element distribution depending on relative
element size factor (re), there are five global levels in PLAXIS as as shown in Table 4.5.
Table 4.5: Element size factor with element distribution
Element Distribution

reVery Coarse

2

Coarse1.5

Medium

1.0

Fine

0.7

Very Fine

0.5

In this study, three mesh sizes have been used to see the sensitivity of mesh sizes on results
obtained in the analysis. Figure 4.10 (a), (b) and (c) shows the fine, medium and coarse meshconnectivity plot respectively. For the current study fine mesh element has been used for bothvertical and earthquake loading conditions. Figure 4.11 shows that the full loading stage iscompleted and Mstage value reaches to 1 which means all the out-of-balance forces are omitted
during each stage calculation process. In the end, ultimate displacement is found to be very
close for fine and medium mesh sizes on the top of the pile, 18.47 mm and 18.35 mm
respectively at ultimate load. For coarse mesh the axial displacement is 17.54 mm as shown in
Figure 4.12. Figure 4.13 diplays the moment generated under different meshing condition. It isevident from these above plotted graph that effect of meshing variation on the ouput results is84

significant in case of moment generation. The deviation among the result are very close to each(a) Fine
85

Figure 4.10: mesh element connectivity plot(b) Medium(c) Coarse

other in terms of displacement.

Figure 4.11: Total displacement of pile with respect to full loading stage for different meshcondition
Displacement (m)0.00000.00

0.00500.01000.01500.0200

5.00

10.00

Length (m)

15.00

20.00

25.00

30.00
Fine Mesh

35.00

Medium Mesh
Coarse Mesh

40.00

45.00

Figure 4.12: Distribution of displacement with pile depth for different mesh condition
86Moment (kN-m)-4.0000-3.0000-2.0000-1.0000

0.00000.00

10.00

1.00002.00003.00004.0000Fine mesh

Depth (m)Medium mesh
Coarse mesh
20.00

30.00

40.00

Figure 4.13: Comparison of moment for different mesh size
4.6.2

Effect of Pile Length

To achieve adequate bearing capacity, a pile tip needs to be placed in dense stratum of soil. In
this study the different soil layers from borelog shows that up-to 37.5 m depth soil is clayeysilt. After that the dense sand layer is found with SPT value 50. The required pile depth is 42.5
m for this area. To observe the effect of pile length on displacement, three pile depths 35 m,
42.5 m and 50 m are selected. By using pile length 35 m, pile shows higher displacement about
24.20 mm. But when pile lengths are 42.5 and 50 m, the pile shows almost similar displacement
18.47 mm and 18.56 mm respectively which are lower than the displacement related to 35 m
pile length as shown in Figure 4.14. It can be seen that increase in pile length can reduce pile
displacement significantly.

87Displacement (m)0.00000.00

0.01000.02000.0300

10.00

Length (m)

20.00

30.00

35 m

40.00

42.5 m
50 m

50.00

60.00

Figure 4.14: Distribution of displacement with pile depth for different pile length
4.6.3

Effect of Pile Diameter

Effect of pile diameter on axially loaded pile is investigated by considering three different pile
diameters and same wall thickness in this analysis, i.e 400, 450 and 500 mm. Wall thickness ofthe hollow pile is assumed to be 110 mm in all cases. This variation shows that pile with larger
diameter results in lower displacement of pile at the top whereas small diameter pile causes
larger displacement, see Figure 4.15. The maximum displacement of pile occurs at the top inloose sandy soil. For D 400 and 450 mm the displacements are 24.02 and 18.47 mm. For D =500 mm the displacement is 16.50 mm. That portrays that piles with larger diameters offers
more resistance to the soil movements, resulting in a higher load carrying capacity of pile.

88Displacemnt (m)0.00000.00

0.00500.01000.01500.02000.0250

5.00

10.00

Length (m)

15.00

20.00

25.00

30.00
400 mm

35.00

450 mm
500 mm

40.00

45.00

Figure 4.15: Distribution of displacement with pile depth for different pile diameter
4.7

Earthquake Analysis

For earthquake analysis, the free field site response has been carried out along a 1D linear
elastic frequency domain. In this study, PLAXIS 3D finite element software is used to conduct
this analysis. For the current study HS model is used for modeling soil element according tosoil investigation done in the study site previously. The earthquake load is applied at the bottomof the FEM model as prescribed displacement. In dynamic loading condition, using HS model
generates plastic strain with increased preconsolidation stress in soil. Under this condition
damping is defined by Rayleigh damping. The stage construction phases in PLAXIS 3D forearthquake loading condition are given below in Table 4.6.

89

Table 4.6: Stage construction phases for earthquake analyis
Phase

Analysis type

InitialPile construction

Loading stage

Earthquake loading
stage

4.7.1

K0

Plastic

Plastic

Dynamic

Elements

Activated

Soil volume√

Embedded pile elementx

Point loadx

Soil volume√

Embedded pile element√

Point load
Soil volumex√

Embedded pile element√

Point load (design load)
Deformation in z
direction
Soil volume√√

Embedded pile element√

Prescribed surface
displacement (input
earthquake loading)√Deformation in x
direction√

Boundary condition for
dynamic√√

Dynamic Soil Behavior

Constitutive model presents in PLAXIS needs to be validiated for seismic analysis before
implementation. Every constitutive model can be used for modeling material behavior. But
due to some limitations each model cannot simulate seismic behavior. During an earthquake,soil is subjected to cyclic shear loading showing a nonlinear disipative behavior. The total
amount of damping is introduced through frequency dependent Rayleigh formula. Which isconsidered in HS model as previously discussed. Generally HS and hardening soil with small
strain (HSSM) models are recognized for using in earthquake analysis. Here in this study,
Hardening Soil model with the same soil properties have been used for seismic analysis asshown in Table-4.1 with assigning 5% Rayleigh damping as shown in Figure 4.16.

90Figure 4.16: Assigned Rayleigh damping for soil
4.7.2 Boundary Condition
A proper boundary condition is important for analyzing pile accurately. The overall dimensionof the model is same as the axially loaded pile model. Earthquake load is applied in the model
as uniform prescribed displacement in x direction as shown in Figure 4.17. The deformation isfree in Xmin and Xmax direction. In Ymin,max and Zmin,max direction the deformation is kept fixed.
To introduce the soil strength reduction due to soil movement, an interface surface withstrength reduction at the bottom surface is added. For input seismic motion the boundaries in x91

direction are kept free. The free field boundary condition for lateral deformation keeps theboundary free for motion to move at the sides and also absorbs the reflected secondary waves.
In Y direction it is none as no absorbant boundary condition is applied. In Zmin compliant baseis assigned and Zmax is none for unabsorbing bedrock. A Compliant base boundary for bottom
boundary ensures the reflection of waves from above layers are absorbed and thus direct
earthquake accelerogram can be applied directly.

Figure 4.17: 3-D view of boundary condition924.7.3

Earthquake Input Signal

In this analysis 1995 Kobe and 1989 Loma Prieta earthquake motions are used. These two
motions have different charateristics. Kobe earthquake is a severe one with a magnitude Mw=
7.2 and PGA = 0.75 g. Loma Prieta has a magnitude Mw= 6.8 and PGA = 0.36 g. The
acceleration time histories of 40 s duration are presented in Figure 4.18 a and b. These records
are applied in the horizontal direction at all bottom node of the model. They are scaled intosame acceleration 0.15 g for Dhaka zone. In order to reduce the calculation time only 5 s of
Kobe earthquake and 5 s of Loma prieta earthquake are applied. Figure 4.19 shows the Kobe
earthquake acceleration data input in PLAXIS 3D for earthquake analysis.

8

Acceleration (m/s2)

6
4
2
0
-2

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

3

3.5

4

4.5

5

-4
-6
-8

Time (s)-10

Acceleration (m/s2)

4
3
2
1
0
-1

0

0.5

1

1.5

2

2.5

-2
-3
-4

Time (s)Figure 4.18: Original earthquake frequency (a) 1995 Kobe (b) 1989 Loma Prieta.

93

Figure 4.19: Kobe earthquake input signal
4.8

Pile Deformation under Earthquake Loading

The deformed shape of soil body after a seismic activity can be observed in Figure 4.20. It isseen that the top soil layer is displaced in x direction relating more than the other soil layers as
the top layer is loose sandy soil. The vertical and lateral deformation of soil are illustrated in
Figure 4.21 and 4.22. It is found that majority of the vertical deformation are concentrated at
the boundaries but in case of lateral deformation, it is spread all over the soil body, see Figure
4.22 and 4.23.

94

Figure 4.20: Soil deformation due to earthquake loading (Kobe)

Figure 4.21: Vertical diplacement of soil under earthquake loading95

Figure 4.22: Lateral diplacement of soil under earthquake loading

Figure 4.23:Top view of lateral diplacement of soil under earthquake loading96

The displacement in pile occurred due to earthquake loading is compared with the displacement
occurred only under axial loading over the length of pile. The displacement at the top of thepile is significantly increased for earthquake loading condition than the axial load. In case ofLoma Prieta earthquake, the pile top displacement is increased by 8.5 times than axial load andfor Kobe earthquake loading it is reported to be increased by 40 times as shown in Figure 4.24.
This phenomenon explains that during seismic action a pile can experience excessive lateral
deformation and tends to fail. But during axial loading condition the pile can sustain the loadwith a minimum settlement. So seismic assessement should be taken into account even the pilecan sustain the compressive load.
Displacement (m)
0.000
0.00

-0.200-0.400-0.600-0.800-1.0005.00

Depth (m)

10.00

15.00

20.00

25.00

30.00

35.00

Loma Prieta
Kobe

40.00

Axial load

45.00

Figure 4.24: Displacement comparison of pile under both axial and earthquake loading

97

Earthquake load produces interal forces in the structure which causes stresses in foundation
system and propagates to the soil. These spectrums describe the maximum response offoundation system for a specified earthquake ground motion and 5% of damping. The PSA
value with respect to the natural period of vibration of structure allows to calculate themaximum shear stress at the base of the structure. In Figure 4.25 spectral acceleration for Kobe
earthquake is compared at three different depth of soil body for damping ratio ξ = 5%. At top
layer of soil there is loose sand which is susceptable to liquefaction during earthquake. Thisliquefiable layer magnifies the response spectra as shown in Figure 4.25 with blue color. The
red and cyan color spectral acceleration represents the mid and bottom layer respectively. The
PSA for these two layers are relatively lower than the top layer as these layers have stiffer soil
properties. The predominant period can be determined from PSA graph, which is 0.25 s. Figure
4.26 shows the magnitude of acceleration in x direction of Kobe earthquake at three different
soil depth. It is evident that at the top layer the acceleration is amplified.

Figure 4.25: Acceleration response spectrum of analysed model for Kobe earthquake at
different depth

98

99

Figure 4.26: Earthquake acceleration at different depth of soil

The ratio of acceleration response at the top to the response at the bottom is reported in Figure
4.27. It shows that the top point is amplified to 131 ratio with respect to bottom point under

Amplification

given earthquake loading.

Frequency (Hz)Figure 4.27: Amplification spectrum
The maximum strain develops at top and bottom stress point in soil element are shown in Figure
4.28 and 4.29 for Kobe and Loma Prieta earthquake. It is seen that at top the strain value ofKobe earthquake is 7.6 times greater than Loma Prieta whereas at bottom point it is 1.6 times
higher with respect to Loma Prieta earthquake. It is clear that the seismic excitation causes
large deformation at top level by magnifying the response spectrum. Large magnitude
earthquake can develop higher strain in soil body.

100Strain (ε xx)

Dynamic time (s)Strain (ε xx)

Figure 4.28: Maximum strain at top of soil profile for earthquake loading

Dynamic time (s)Figure 4.29: Maximum strain at bottom of soil profile for earthquake loading101Maximum shear stress τmax in the soil at the bottom of the pile is shown in Figure 4.30. At
maximum shear stress the Mohr’s circle is expanded to touch coulomb failure envelop. The
max value of shear stress is 146 kN/m2. It is 7.2 % higher than the shear stress under axial
loading, see Figure 4.31. Total stress increases about 8.5 % for seismic activity than only axial
loading condition at the bottom of pile as shown in Figure 4.32.

Figure 4.30: Maximum shear stress under earthquake loading

102

Figure 4.31: Maximum shear stress under maximum axial loading

Figure 4.32: Principle total stress under earthquake loading

103

4.9

Liquefaction Analysis

During earthquake seismic wave propagation, it not only causes damage to structure but also
initiate other phenomenon like landslides and soil liquefaction. So liquefaction should also be
considered while performing site response analysis in loose cohesionless soil. To evaluate theliquefaction potentiality, the triggering factor for liquefaction is to be identified. The triggeringfactors depend on the earthquake magnitude, duration and peak ground acceleration. To
understand the possibility of liquefaction in a specific site nonlinear dynamic analysis can be
done. In PLAXIS 3D hardening soil model is not able to capture the liquefaction phenomenon.
The UBC3D-PLM is a nonlinear elastic-plastic model that is capable of capturing seismicliquefaction behavior of sands and silty sands. The model can accumulate strain and porepressure of sandy soil that can capture the onset of liquefaction. the Initialy UBC3DPLM
implementation in PLAXIS was developed by Tsegaye (2010).

4.9.1

Liquefiable Sand Layer Parameters

The parameters for UBC3D-PLM can be determined from laboratory tests under cyclic loading
but if it is not possible then data can be extracted from in-situ tests like SPT N value and CPT.
There are some corelation proposed by Beaty and Byrne (1998) which can be used to determine
required parameters from corrected SPT N value. The correlations are presented below:
KeG= 21.7 x 20 x ((N1)60)0.333(4.1)

Here KeG is the elastic shear modulus
KeB= KeGx 0.7(4.2)

KpG= KeGx ((N1)60)2 x 0.003 + 100.0(4.3)

Here KeB is the elastic bulk modulus

Where KpG is the plastic shear modulus

φpi = φcv +φp= φpi + max( 0.0,

(4.4)

)

Where φpi and φcv are peak friction angle and constant volume friction angle

104

(4.5)

Rf = 1.1 x ((N1)60)-0.15(4.6)

Rf is the failure ratio
In this study, during earthquake analysis the liquefaction phenomenon is not considered andonly HS model is used for soil modeling. In this segment earthquake analysis is done
considering liquefaction phenomenon with undrained behavior in loose sandy type soil using
UBC3D-PLM model. The liquefiable sand layers parameters are shown in Table 4.7
Table 4.7: Input parameters of liquefied sand layer of UBC3D-PLM modelParameters

SymbolUnit

Value applied inmodel

Unit weightγunsatkN/m3

16

Saturated unit weight

γsat

kN/m3

17

Poisson’s ratio

ν

-

0.3

Constant volume friction angle

φcv

(o)

22

Peak friction angle

φp

(o)

23

Cohesion

c

kPa

0

Elastic shear modulus

e

KG

-

1019.0

Elastic bulk modulus

KeB

-

713.0

Plastic shear modulus

KpG

-

617.0

Elastic shear modulus index

ne

-

0.5

Elastic bulk modulus
Index

me

-

0.5

Plastic shear modulus index

np

-

0.5

Failure ratio

Rf

-

0.74

Atmospheric pressure

PA

-

100

Tension cut-off

σt

kPa

0.00

Densification factor

fdens

-

0.45

Corrected SPT value(N1)60-

13.0

Post liquefaction
FactorfEpost

-

0.20

105

Figure 4.33 shows the deformation in soil element at top layer due to liquefation. It is notedthat UBC3D-PLM model can describe the liquefaction phenomenon in loose sandy soil whichtends to liquefy at the moment of earthquake loading. There are some other state parametersthat can confirm the liquefaction event using UBC3D-PLM model. In PLAXIS liquefaction
can be explained by excess pore water pressure ratio ru. It is the ratio between excess porepressure and initial effective vertical stress at the depth.

ru = 1 Hereis the vertical stress at the end of dynamic calculation and(4.7)
is the initial verticaleffective stress earlier seismic activity. If ru is equal to 1 then the layer is in complete liquefiedstate. If a layer has ru value equal or greater than 0.7 then the layer will be defined as liquefied.
In the analysis the maximum excess pore pressure ratio ru is about 0.99 ~ 1 as shown in Figure4.34 and 4.35 for both Kobe and Loma Prieta eartquake is equal to 1.
It is obtained that if a soil layer is loose sandy soil or silty soil it can liquefy during seismic
event due to generation of excessive pore pressure. The maximum pore pressure generated
during earthquake in the liquefied layer is 1178 kN/m2 and 1048 kN/m2 for Kobe and Loma
Prieta earthquake as shown in Figure 4.36. It shows that larger the peak acceleration the larger
the pore pressure generates. During liquefaction, the relative diplacement at pile head increases
about 30 to 60 % for both Kobe and Loma Prieta earthquakes as shown in Figure 4.37. It isobserved from the deformed shape of pile that the displacement profile puts the pile in bending.
It can also be seen that the nonliquefiable layers of the soil begin to displace laterally withrespect to the liquefiable layer.

106

Figure 4.33: Deformation at the top soil layer due to liquefaction

Figure 4.34: Maximum pore pressure ratio at top soil layer for Kobe earthquake

107

Figure 4.35: Maximum pore pressure ratio at top soil layer for Loma Prieta earthquake

Figure 4.36: Maximum excess pore water pressure generated during Kobe and Loma Prieta
earthquake

108

Displacement (m)0.04000.00-0.4600-0.9600

5.00
10.00

Depth (m)

15.00
20.00
25.00
30.00
35.00

Kobe
earthquake

40.00

Loma Prieta
earthquake

45.00

Figure 4.37: Displacement comparison of pile under earthquake loading
4.10

Soil Improvement Impact on Liquefiable Soil

The presence of liquefiable soil layer in any site can immensely influence the pile responseboth in deflection and bending moment especially when subjected to increased magnitude.
During seismic action there is possibilties to develop large amount of moment that cannot be
resisted by pile. If only earthquake is considered then the observed maximum moment is 42
kN-m and 10 kN-m for Kobe and Loma Prieta earthquake respectively, see Figure 4.38. Fromthe sectional analysis it is found that the maximum moment carrying capacity of 450 mm dia
SPC pile is 180 kN-m, see Table 3.1. In this study area as there is fill soil upto 5 m so whileliquefaction event is taken into account, the maximum bending moment is found to be 478 kNm for Kobe earthquake and 242 kN-m for Loma Prieta earthquake. It is 11 times and 26 times
higher than the moment found without considering liquefaction, see Figure 4.39. The maximum

109

bending moment is found at the interface of liquefiable and non-liquefiable soil layers which
agrees with the existing literatures. However, location of maximum bending moment also
depends on pile head condition. The bending moment demand for fixed head pile is greaterthan free headed pile.

Moment (kN-m)-60.000.00-40.00-20.00

0.00

20.00

40.00

5.00

10.00

Depth (m)

15.00

20.00

25.00
Kobe
earthquake
30.00
Loma Prieta
earthquake
35.00

40.00

45.00

Figure 4.38: Comparison of moment developed under earthquake loading condition

110Moment (kN-m)-600.00
0.00-400.00-200.00

0.00

200.005.00
10.00

Depth (m)

15.00
20.00
25.00
Maximum axial load

30.00
35.00

Kobe considering
Liquefaction
Loma Prieta consideringliquefaction

40.00
45.00

Figure 4.39: Comparison of moment developed both considering and without consideringliquefaction
With generation of large force due to the lateral movement of the liquefiable and nonliquefiable layer has the potential to induce large bending moments in the piles leading to
failure. Lateral load can cause pile failure due to change in flexural stiffness and capacity. So
up-to a certain depth the soil needs to be improved so that the generated moment can be
reduced. Soil in liquefied site showed larger stiffness degradation and piles showed larger
bending moment than piles in non-liquefied site. In this study two cases are considered for soil
improvement. Up-to depth 5 m and 15 m the soil is improved to see the moment capacity of
pile. The soil improvement is simulated by increasing soil strength parameters used in UBC3DPLM model and HS model. For soil improvement only up-to 5 m, the first loose sand layer isimproved and analyzed using UBC3D-PLM model considering drained behavior. In case of 15
m soil improvement strength parameters of soil layer up-to 15 m is increased and analyzed with111

UBC3D-PLM and HS model to observe the improved soil behavior. The improved soil
parameters for first 5 m soil improvement is presented in Table 4.8. Keeping the first layer as
the same properties given in Table 4.8, material properties of remaining 10 m soil is improved
as shown in Table 4.9.
Table 4.8: Material properties for soil improvement up-to 5 m
Parameters

SymbolUnit

Value applied inmodel

Unit weightγunsatkN/m3

17

Saturated unit weight

γsat

kN/m3

18

Poisson’s ratio

ν

-

0.3

Constant volume friction angle

φcv

(o)

30

Peak friction angle

φp

(o)

33

Cohesion

c

kPa

0

Elastic shear modulus

KeG-

1316.0

Elastic bulk modulus

KeB

-

921.0

Plastic shear modulus

Kp G

-

3195.0

Elastic shear modulus index
Elastic bulk modulus
Index

ne

-

0.5

me

-

0.5

Plastic shear modulus index

np

-

0.5

Failure ratio

Rf

-

0.9

Atmospheric pressure

PA

-

100

Tension cut-off

σt

kPa

0.00

Densification factor

fdens

-

1.0

Corrected SPT value(N1)60-28.0

Post liquefaction
FactorfEpost

-

1.0

112

Table 4.9: Material properties for soil improvement up-to 15 m
Parameters

Unit

Clayey silt
(10 m)

Unsturated unit weight (γunsat)

kN/m3

17

Sturated unit weight (γsat)

kN/m3

18.5

Secant stiffness modulus(E50ref)

kN/m2

20000

Oedometer modulus(Eoedref)

kN/m2

20000

Unloading/reloading stiffness (Eurref)

kN/m2

60000

Poisson’s ratio, ν

0.3

Cohesion, c25

Angle of friction, φ28

Dilation Angle, Ψ0Unloading/reloading poisson’s ratio, νur

0.3Power for stress-level dependency ofstiffness, m

0.5

K0value for normally consolidated factor,
K0 nc

0.577

Interface factor, Rint

0.9

Figure 4.40 and 4.41 shows that if the soil layer is improved only up to 5 m then moment inpile is reduced to a certain limit 45 kN-m and 6 kN-m for Kobe and Loma Prieta earthquake
respectively which is within the pile moment capacity but if up to 15 m soil can be improved
then it comes to 20 kN-m and 3 kN-m. It is significantly smaller under earthquake loading.

113

Moment (kN-m)-100.000
0.00-50.000

0.000

50.000100.000

5.00

10.00

Depth (m)15.00
Improved soil
upto 5 m

20.00

Improved soil
upto 15 m

25.00

30.00

35.00

40.00

45.00

Figure 4.40: Comparison of moment reduction after soil improvement for Kobe earthquake

114

Moment (kN-m)-100.00-50.00

0.00
0.00

50.00

100.00

5.00

10.00

Depth (m)

15.00

20.00

Improved soil
upto 5 m
Improved soil
upto 15 m

25.00

30.00

35.00

40.00

45.00

Figure 4.41: Comparison of moment reduction after soil improvement for Loma Prieta earthquake
In Figure 4.42, a comparison is made among moment generated during earthquake without
considering liquefaction, considering liquefaction phenomenon and soil improvement. Due tosoil improvement the moment in pile decreases to 96% and 100% at the interface of filled soil
and clayey silt soil for Kobe and Loma Prieta earthquake respectively than the unimproved
soil. Again, it can be observed that soil improvement up-to 15 m depth can reduce moment
considerably than improved soil up-to 5 m depth. However,it can be concluded that soil

improvement technique can enhance the pile flexural capacity under earthquake loading.
Mostly spun pile damages occurs due to flexural failure. So soil improvement technique canminimize the chance of pile collapse and probability of liquefaction as well.

115

79

40.00
45.00

45.00

40.00

Soil improvement
up-to 15 m

Consideringliquefaction

Soil improvement
up-to 15 m

35.00

30.00
35.00

Kobe earthquake

25.00

Consideringliquefaction-100.000

Soil improvement
up-to 5 m

-200.000

30.00

20.00

15.00

10.00

5.00

-300.000
0.00

Soil improvement
up-to 5 m

200.00Loma Prieta
earthquake

0.00

25.00

20.00

15.00

10.00

5.00

-600.00 -400.00 -200.00
0.00

Moment (kN-m)
0.000

100.000

Figure 4.42: Comparison of moment considering liquefaction, withoutout liquefaction and soil improvementfor (a) Kobe (b) Loma Prieta earthquake

Depth (m)Moment (kN-m)

Depth (m)4.11

SummaryThis chapter explains the finite element modeling analysis of SPC pile under both axial andearthquake loading condition. The analysis can be summarized as follows:
1. For practical application and model validation a realistic soil constitutive soil modelneeds to be chosen which can simulate the nonlinear and stress dependent
characteristics of soil. For FEM model HS model is chosen for simulate soil behavior.
For structural component like pile embedded beam element is chosen. The input
parameters are determined from laboratory test results and empirical correlations. The
static pile load test result is validated with the FEM model using the soil and structuralmodeling parameters in PLAXIS 3D for Jolshiri site.
2. The parametric study is conducted to observe the influencing effect of pile diameter,
length and mesh size of model on the simulated results under static loading condition.
3. The pile response under earthquake loading is simulated. The stage construction steps
are presented for the analysis in PLAXIS 3D. Two seismic signal, Kobe and Loma
Prieta are used as input earthquake loading to observe pile displacement, stress andstrain distribution in soil body.
4. Liquefaction phenomenon has been simulated using UBC3D-PLM model in PLAXIS
3D during earthquake event. The top layer is susceptible to liquefaction effect due toexcess pore water pressure generation. The maximum pore pressure ratio and pile
displacement are determined for Kobe and Loma Prieta during liquefaction.
5. The large moment generation during liquefaction can lead the pile to collapse due to
flexural failure. Liquefaction can trigger the pile to produce larger moment than the
moment generated during seismic event without liquefaction occurrence. Soil
improvement effect on the liquefiable layer is observed at the end of this chapter toreduce large moment generation and pile failure.

80

PART-II

A NUMERICAL INVESTIGATION OF NEW
AUSTRIAN TUNNELING METHOD AND
TUNNEL BORING METHOD FOR
TUNNEL CONSTRUCTIONBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Johana Sharmin
Mehedi Ahmed AnsaryChapter 1
INTRODUCTION
GeneralTunnels can be defined as an important section of subterranean structures and undergroundpassages constructed to mitigate the traffic hassle by ensuring the direct transportation ofpassengers or goods between two certain points through certain obstacles. Tunnels are analyzed
according to their shapes, prevailing ground conditions, construction techniques, groundresponse, changes in pore pressure, plasticity, lining deformations, effects of existing
structures, etc. Numerical procedures, such as finite element technique, can simulate
construction sequence, model realistic soil behavior, handle complex ground and hydraulicconditions, deal with ground treatment, account for adjacent services and structures, deal withmultiple tunnels, simulate intermediate and long-term conditions, etc. and produce realistic
results.
When underground space or a large span tunnel is excavated, there is an inevitable chance ofdisturbing the in-situ stress field causing ground movements leading to surface settlement andpotential damage to adjacent structures. Selection of an appropriate excavation method(depends on tunnel depth, tunnel shape, tunnel length, tunnel diameter, conditions of groundwater present, use of tunnel, supporting logistics, and appropriate management of risks) forlarge span urban tunnel projects in soft ground is a key factor for successful completion of the
project.
NATM (New Austrian Tunneling Method) is based on the concept that the ground around thetunnel acts as a load as well as a load-bearing element and the tunnel can stabilize itself byusing the surrounding rock mass geological stress. It was developed soon after World War II
and since then consistent improvements have been made by Mueller, Rabcewiz, Brunner andPacher. It is now established as a well-recognized flexible technique due to its success indiverse conditions ranging from hard rock to soft rock, soft stable ground to weak, friable andunstable ground. Depending on the project conditions (e.g., shallow soft ground tunnel, deeprock tunnel) and the result of the geotechnical parameters, the requirements of the specificsupport are determined. The excavation cross section is divided into crown, bench and invert(for soft ground, invert arch is generally required to ensure stability) depending on
environmental factors, surface settlements, ground conditions and logistical requirements and81the tunnel is typically advanced by drill and blast following the sequential excavation method.
The performance of this method is not found satisfactory in weak formations and shallow
tunnels in the urban areas because (1) deformation to some extent is the requirement of thesystem to relieve or minimize he amount of stress, (2) the ratios of the horizontal to the verticalstress is not the requirement to keep the tunnel face stable, (3) vibration may cause damage tothe existing buildings, and (4) need of installation of structural support around the tunnel
excavation to re-establish the equilibrium.
TBM (Tunnel Boring Machine) is used for the excavation of tunnels with a cross section of
circular or rectangular shape through the different types of rock and soil strata. Diameters of
the excavated tunnel can be varied from 1m to almost 16m. TBMs have limitations ofpredetermined tunnel diameter and shape along the length of TBM drive. During the excavation
process of tunnel, TBMs limit the surrounding ground disturbance and produce a smooth wallof tunnel. EPB (Earth Pressure Balance) tunneling machine is used to provide the support tothe tunnel face by the excavated soil itself during the excavation process. EPB consists ofseveral devices like cutting wheel for excavating soil, screw conveyor for removing soil fromworking compartment, pressure cells for monitoring the pressure in the working chamber,
excavation chamber closed from tunnel face by pressure bulkhead, mixing vane for assisting
to remould the soil. EPB machine is mostly used in the variable and poor ground conditions
with low cohesion ground, high permeable ground, high water pressure ground, and clay withgravel, boulder and sand interfaces.
The construction of a tunnel usually leads to surface disturbance, particularly settlement (notimportant in greenfield sites). The available analytical and empirical solutions are not sufficient
to include complex ground conditions and hence a comprehensive analytical solution couple
with numerical modelling is necessary to model the effect of surface settlement due to soft
ground tunneling. This research discusses different approaches in predicting the settlement andcomparison with numerical analysis is also done to validate the solutions.
The objective of the MRT Line – 1 project is to mitigate the traffic congestion, improve
environmental pollution, and contribute to economic and social development in Dhaka city by
constructing mass rapid system. MRT Line 1 consists of two lines: one route connects
Kamlapur in central Dhaka with the Dhaka International Airport (hereafter the Airport Line),
and the other route branches off from the Airport line at Notun bazar station to the Purbachal
area (hereafter the Purbachal Line) where large scale urban development is currently under82

way. The airport line will run entirely through an underground tunnel (14.765km) and the
Purbachal line will become an elevated structure to its destination at depot in Rupganj(15.426km). This research presents a framework for selecting the appropriate tunneling method(NATM and TBM) with respect to induced ground surface settlements considering proposed
underground tunnel alignment of MRT Line 1 based on PLAXIS 3D numerical analysis.
For simulating tunnel construction methods interaction with soil, PLAXIS 3D finite element
software is used in this thesis. Different consecutive models are incorporated in PLAXIS suchas simple linear elastic-perfect plastic Mohr-Coulomb (MC) model, the elastic-plastic nonlinear stress-dependent stiffness Hardening Soil (HS) model, and isotropic work-hardening
plasticity cap Modified Cam-Clay (MCC) model. The real behavior of the excavation process,3D arching of soil, distribution of settlement, etc. can be precisely simulated in this software.
In addition to evaluating the effects of the consecutive model on the soil behavior, empiricalmethods are used and all results are compared with each other eventually.

Background of the Study
The Strategic transport Plan (STP) (20-year long plan) has been addressed by Bangladesh
Government with JICA (Japan International Corporation Agency) to fix the road congestion
caused by crippled transportation system coupled with sluggish traffic conditions. Since 2009
till date, a plan for Mass rapid Transit (MRT) was conceptualized forming the implementing
agency DMTCL (Dhaka Mass Transit Company Ltd.). According to the plan, there will be six
MRT lines comprising of 61.172km long underground and 68.729km long elevated network
system featured with 105 stations across Dhaka city to ease the traffic situation. MRT Line-1
is comprised of 31.241km long and is divided into two sections: Airport Route (19.872km long,
total 14 stations) and Purbachal Route (11.369km, total 7 stations). In this thesis, underground
portion is focused, where the route alignment is: Airport – Airport Terminal 3 – Khilkhet –Nadda – Natunbazar – North Badda – Badda – Hatirjheel East – Rampura – Malibagh –Rajarbagh – Kamlapur. (NKDOS Consortium Proposal, 2019)
1.2.1 General Topography and Geology of the Study Area: Dhaka is situated between
latitudes 23⁰42’N and 23⁰54’N and longitudes 90⁰20’E and 90⁰28’E. The city is bounded by
the Buriganga River to the south, Turag to the west, Balu to the east, and Tongi Khal to thenorth. The Dhaka city area does not show any surface folding, however a large number of faults
and lineaments have N-S, E-W, NE-SW, NW-SE trends recognized from air photointerpretation and the nature of the stream courses. Dhaka city and its surroundings are shown3

to be situated in the seismic zone 2 (medium risk zone). The studied area falls into Madhupur
Tripura Tract physiographic division of Bengal basin. The soil carried out up to maximum tothe Holocene and Pleistocene age sediments in geological time scale in this area. The study
area is mostly consisted of clayey soil than the sandy soils. The upper soil layer comprises ofgrayish to brownish stiff to medium stiff clayey soil and brownish medium dense soil of Basabo
Silty Clay formation and hard clayey soil or brownish very dense sand below this, can be offrom Madhupur Clay and Sand formation. (ProSoil Survey, 2019)
1.2.2 Parameters Affecting Settlements in Tunnel: To have knowledge about the effects ofthe parameters of influence zone of ground settlement, it may be helpful to carry out themeasurement and give a better solution in the form of numerical modeling. Ground surface
settlement behind a reinforced wall takes place due to the unbalanced pressures resulting
removal of soil mass inside tunnel excavation. Based upon several case history reviews, thefactors that effecting the settlement in tunneling can be grouped into three major categories,
such as, geometric parameters (tunnel diameter, tunnel depth, depth of tunnel axis from groundlevel, the distance from tunnel face excavation and face stability of shield-driven tunnels),geological conditions (geology at tunnel invert and crown, groundwater level, etc.), and shield
operation parameters (penetration rate, face pressure, pitching angle, percent of tail void
grouting and amount of excavated material per ring). In this thesis, we emphasized the effectsof tunnel geometry parameters (tunnel depth, tunnel diameter, influence zone) to thesettlements. (Loganathan and Poulos, 1998)
1.2.3 Importance of The Research: In comparison, NATM and TBM are essentiallyequivalent from the viewpoint of construction operation. The final choice is determined by the
local geological conditions for the project and the length of the tunnel. Though International
Consultants team has already proposed the Shield tunnel by TBM-EPB as the tunnel
construction method for Line 1 project, I want to shed light on some factors of NATM in urban
areas. Also, I want to compare the displacement effects between both techniques and from thisperception I want to establish the fact if NATM is also viable like TBM for our Dhaka city ornot.
1.2.4 Reliability of FEM as Method for Numerical Analysis: In a real tunnel, the different
facets are clearly coupled and the problem is complex, involving pore pressure changes,
plasticity, lining deformations and existing structures. Numerical procedures, such as the finite4

element technique, lend themselves to the analysis of such complex problems (Potts, 2001).
The finite element method can:i.

Simulate construction sequence.

ii.

Deal with complex ground conditions.

iii.

Model realistic soil behavior.

iv.

Handle complex hydraulic conditions.

v.

Deal with ground treatment (e.g., compensation grouting).

vi.

Account for adjacent services and structures.

vii.

Simulate intermediate and long-term conditions.

viii.

Deal with multiple tunnels.

1.2.5 Choosing 3D Numerical Analysis over 2D Analysis: The complex interrelation between
the interconnected elements makes for a highly complex mathematical problem. The analysis
is performed by solving the equation matrix that models, the mesh made up of the limited
number of elements. That is, a system of equations is set up which relates unknown quantities
to known quantities via a global stiffness matrix. For instance, the relationship of nodal forces
to displacements is analyzed this way throughout the finite element mesh. Highly complex
underground conditions and tunnel characteristics can be analyzed in 3D. The capability of the
3D analysis includes the simulation of complex constitutive laws, non-homogeneities, and theimpact of advance and time dependent characteristics of the construction methods. As tunnel
excavation is clearly a three-dimensional problem, considering the third dimension should
intuitively lead to more accurate predictions (Tatiya, 2005).

Objectives of the Study
The main goals of the research:i.

To conduct numerical analysis of proposed tunnel in NATM method to obtain groundmovement and deformation.

ii.

To conduct numerical analysis of proposed tunnel in TBM method to obtain groundmovement and deformation.

5

iii.

Comparison between two methods based on the results (comparative parameter:
displacements for three types of models) of numerical analysis and establish a portfolio
for the suitable method.

Methodology and Flow Chart of the Study
The field data collection are prior arrangements for determining site conditions (ground waterlevel, soil type, visual soil parameters, etc.) mobilizing the soil samples to laboratory for further
testing. Through conducting laboratory tests according to the codes, soil properties(geotechnical) can be determined which can be used as parameters for FEM analysis. FEM
analysis needs to follow some definite steps to acquire approximately accurate results which
are described later in this section. Literatures of previous researchers are needed to be verified
and numerical analysis with PLAXIS 3D have been used for the establishment of the papers.
Also, PLAXIS 3D is used to develop models varying different types and different parameters
for the NATM and TBM methods. The methodology of the study can be described in the Figure
1.1:
Field data Collection: The investigation consisted of soil boring and sampling for observationfrom secondary sources.
Determination of Geotechnical Parameters: Laboratory tests were conducted on the soil
samples to classify soil and to detemine mechanical properties. These data are collected fromsecondary data source.
Development of FEM Model using Plaxis 3D: For accurate modeling of tunnel, constitutive
soil model, tunnel lining, shield element, support face pressure should be considered. Simplified
cylindrical geometry is considered and lining is modeled by elastic constitutive model.
Validation of Model with Empirical Formula: For validation of TBM methods, two literatures
have been verified and comparison of numerical analysis with empirical formula provided bydifferent researchers have been emphasized.
Conduct Numerical Analysis by Varying Geometry Parameters: Numerical analysis wasdone for three different models: MC, MCC and HS as well as varying depths of 30m,32m and
35m and diameters of 5m, 6m and 7m for TBM. For NATM, three different models wereprepared for 35m depth and 7m diameter.
Conclusions and Recommendations: Perspectives of NATM and TBM for Metro Rail Line-1
has been focused and by comparing two methods numerically and empirically, a conclusive
remarks about functionality of both tunnels in Dhaka city is made.
Figure 1.1: Overall Methodology Flow Chart of the Research
6Development of FEM model analysis consists of following steps:
Step 1: Define the Objectives for Model Analysis: If the objective is to decide which is
proposed to explain the behavior of a system, then a crude model may be constructed, provided
that it allows the mechanisms to occur. Complicating features should be omitted if they arelikely to have little influence on the response of the model.
Step 2: Create a Conceptual Picture of the Physical System: It is important to have a conceptual
picture of the problem to provide an initial estimate of the expected behavior under the imposed
conditions. The considerations which will dictate the gross characteristics of the numericalmodel are: anticipation of stability or instability of the system, linear or non-linear response,large or small expected movements, effect of well-defined discontinuities, influence ofgroundwater interaction, geometric symmetry of the structure, etc.
Step 3: Construct and Run Simple Idealized Models: When idealizing a physical system fornumerical analysis, it is more effective to construct and run simple test models first before
creating the detailed model. The results from the simple models help to guide the plan for datacollection by identifying which parameters have the most influence on the analysis.
Step 4: Assemble Problem-Specified Data: The types of data required for analysis of a model
include: details of the geometry, locations of geologic structure, material behavior, initialconditions, and external loadings. Since typically, there are large uncertainties associated withspecific conditions, a reasonable range of parameters must be selected for this investigation.
Step 5: Prepare a Series of Detailed Model Runs: The numerical analysis involves a series ofcomputer simulations that include the different mechanisms under investigation. It can bedifficult to obtain information to arrive at a useful conclusion if model run times are excessive.
The state of the models is saved at several intermediate stages so that the entire run does nothave to be repeated for each parameter variation.
Step 6: Perform the Model Calculations: At any time during a sequence of runs, it is possible
to interrupt or pause the calculation, view the results, and then continue the model.
Step 7: Present Results for Interpretation: The final stage of problem solving is the presentationof the results for a clear interpretation of the analysis.

7Chapter 3
MODEL VALIDATION
Introduction
This chapter emphasizes on the validation of two metro rail lines of Iran and Delhi with
PLAXIS 3D. For Mashhad Metro Line 2, each section of the ground was modeled by two
constitutive models, namely MCC and Mohr-Coulomb (MC). Numerical modeling was
originally performed by FLAC3D software. Afterwards, the results of two types of numericalanalyses and empirical data were compared with each other. Based on the transverse andlongitudinal sections settlement, the MCC model showed high capabilities of predicting thesurface settlement in comparison to the MC model. And also, the deviated values are less forboth of the models for O’Reily & New relationships. Originally, a 2D numerical model has
been developed using finite element software OptumG2 to replicate the Delhi Metro Phase 3
tunnel project. An elastoplastic model of the tunnel at a standard depth of 18 m has been
analyzed. After comparing results of two types of numerical analyses and empirical data ofPeck & Schmidt formula, the vertical surface settlement shows relatively closer values for both
PLAXIS 3D and OptumG2.

General Information about Line 2 Metro of Mashhad
Mashhad Metro Line 2 is the second metro line that is being developed to facilitate passengers’
transport in Mashhad, Iran. This metro line is situated beneath the street level in a tunnel
running in a Northeast-Southwest direction, as seen in Figure 3.1. In total, this line includes 12
stations. Furthermore, Metro Line 2 is connected to Mashhad Metro Lines 1 and 3 as well as
the national railway line in Iran. The total length of Line 2 is about 14.3 km. A part of thetunnel running from Station A2 through L2 and going further to the TBM exit shaft is going to
be constructed with mechanized tunneling methods, such as the Tunnel Boring Machine or
TBM. The TBM excavates the ground in front of the cutter head while pushing itself forward.
The tunnel is built up inside the TBM from concrete segments. Figure 3.2 shows the section ofground stratifications and tunnel’s location along with water level position.

57

Figure 3.1: Plan of Line 2 Metro of Mashhad (Eslami et al., 2020)

Figure 3.2: Section of ground line 2 Metro of Mashhad (Eslami et al., 2020)58

3.2.1 Soil Condition
The detailed geotechnical investigations were performed by the excavation of 61 boreholes (atotal length of 2,487.7 m) and 16 test pits (a total length of 296.95 m). These investigations
mainly included some field tests and surveys, laboratory tests, and desk studies. The field tests
included a plate loading test (PLT), in-situ shear test, pressure meter test, standard penetration
test (SPT), Lufran permeability test, and in-situ density test. The laboratory tests comprised the
direct shear test, triaxial test, particle size analysis, Atterberg limits test, consolidation,
permeability, and the Los Angeles Abrasion test. The desk studies included the collection of
the existing data such as previous reports, in-situ test results, and data processing and analyzing.
The geological section of the project is illustrated in Figure 3.3. The soil sample for testing is
considered from DH-09 Borehole.
The characteristics of Mashad's soil are illustrated in Table 3.1.
i.

Medium clay-silt (CL-ML l): The uppermost layer is the soft clay soil by low
plasticity and low moisture percentage. The average thickness is about 10 m inmost areas.

ii.

Medium clay-silt (CL-ML ll): The low layer is the soft clay soil by highplasticity and high moisture percentage. This layer can be found at depths of
10-35 m.

Cohesion

Friction Angle

Undrained(kN/m3)

(%)

kPa

deg

kPa

deg

I (A)

CL-ML I

0 ~ 10

17.00

17.00

10

25

10

25

I (B)

CL-ML II 10 ~ 35

17.50

18.00

30

23

12

20

Angle

Moisture Content

Undrained Friction

Dry Density(m)Cohesion

Depth

Notation

Layer No.

Table 3.1: Characteristics Profile of Mashhad’s Soil

59

Figure 3.3: Geological Section of Mashhad Metro Line 2 (12+500km) (Eslami et al.,2020)
The calculation of the MCC parameter was performed based on the elasticity rule:𝐸

𝐺 = 2(1+𝜗)

(3.1)

𝐸

𝐾 = 3(1−2𝜗)(3.2)

𝜅 = 𝐶𝑠 . 𝑙𝑛 10(3.3)

𝜆 = 𝐶𝑐 . 𝑙𝑛 10(3.4)

𝜗0 = 1 + 𝜗(3.5)

Table 3.2: Soil characteristics and the respective parameters for MCC Model
Parameter

Description

Values for Soil Layer
I (A)II (A)E (MPa)Young Modulus

100

120

G (MPa)Shear Modulus

40

48

ρ (kN/m3)

Density

19.85

20.65

M

Frictional Constant

0.983

0.898

Κ

Slope of Swelling 0.0345

0.044

line
υ

Poisson ratio

0.27

0.27

60

3.2.2 Numerical Modeling
For accurate modeling of a tunnel in soft ground by FEM methods, some of key parametersthat affect the surface settlement such as constitutive soil model, tunnel lining, over excavation,and shield element should be considered. In this study, the result of field tests, in situ
measurements, and laboratory data is utilized to describe two different constitutive models.
Since there is a complicated correlation between the target parameter (surface settlement) andother factors, the input parameters of constitutive models should be considered accurately.
To obtain a rational result, all main elements of mechanized excavation should be modeled
such as: TBM's shield, concrete tunnel lining, support face pressure, tail void grouting, andover excavation. Therefore, FLAC3D (Version 3.0) code, a commercial software package
based on the generalized finite difference method, was used to develop the numericalsimulation. The standard dimensions followed for the numerical modeling is displayed in
Figure 3.4 in FLAC3D.

Figure 3.4: Dimension of the 3D Simulation in FLAC3D (Eslami et al., 2020)
For validation purpose, PLAXIS 3D software is used to compare the result with the literature’s
numerical and empirical results. The shield of TBM was modeled using a plate element and asimplified cylindrical geometry is considered. The segmental lining and shield elements aremodeled by the elastic constitutive model. The effect of virtual boundary on the results were
neglected because the model has a longitudinal dimension (y direction) of 6.5D, an extension
under the tunnel axis (z direction) of 3D, and a transverse extension of 4D, where D is thetunnel diameter. As the underground water table in this project is lower than the project line,
all analyses have been performed in drain condition. The tunnel length of 15m (1/1000th of61

actual length), radius of 4.55m and depth of 14m have been considered for simplified
modelling.
The order of excavation integrated into the models is as follows:
Step 1: Excavation of tunnel (about 1.5m)
Step 2: Application of face pressure by the TBM on the new excavation face of the tunnel
Step 3: Excavation of the tunnel by driving the EPB machine
Step 4: Generation of both the gap filling and segment elements performed after excavation of
the tunnel
Step 5: Removing the previous face pressure on the tunnel face.
Step 6: Repeating the steps 1 to 5 until the TBM reaches its destination
3.2.3 Distribution of Surface Settlements in Transverse Section
The semi-empirical relation of Peck was obtained in following equations, showing the shapeof transverse settlement:
2

2

𝑦
𝑦
𝑉𝐿
(− )
(− )
𝑆 = 𝑆𝑚𝑎𝑥 𝑒 2𝑖2 = 𝑖√2𝜋
𝑒 2𝑖2

(3.6)

2

𝑦
+∞
(− )
𝑉𝑆 = ∫−∞ 𝑆𝑚𝑎𝑥 𝑒 2𝑖2 = √2𝜋𝑖𝑆𝑚𝑎𝑥

𝑉

𝑉𝐿 = 𝑉𝑆 ∗ 100
0

(3.7)
(3.8)

Here,
S = vertical surface settlement at y location (m)y = distance of the considered point from the tunnel axis (m)Vs = volume of settlement per meter of tunnel advancement (m3/m)
i = trough width parameter (i = kZ0, where k is a dimensional constant depending on soil type
and Z0 is the depth of the tunnel axis below surface
VL = volume of settlement per unit length expressed as a percentage of the total excavatedvolume of the tunnel
V0 = volume required to construct the tunnel
62In Figure 3.5, three-dimensional view of a tunnel is shown where the tunneling direction isconsidered along X-axis and settlement trough is considered to be deformed along verticallydownward Z-axis. The distance between ground surface and center of the tunnel is considered
Z0. The inflection point where the sagging stops and hogging starts is considered the horizontal
distance, i, from center point (maximum settlement), which is clearly shown in the A-A crosssectional view.
O’Reily & New showed that point of inflection (trough width parameter) i had a linear relation
with depth of tunnel and they suggested equations:𝑖 = 0.43𝑍0 + 1.1 (For cohesive soil)(3.9)

𝑖 = 0.28𝑍0 − 0.1 (For granular soil)(3.10)A summary of all relations suggested by different researchers is presented in Table 3.3. The
behavior of the surface settlement in transverse section follows the Gaussian distribution andbased on this assumption, a Gaussian curve is fitted to the data monitoring outputs. As a result,the Gaussian distribution is analyzed for obtaining trough width parameter, i, which is about
7.41m and this value is very close to the O’Reily & New relation whose deviated value wasabout 3.91% (less deviation of all). In our numerical analyses, the deviated value for thisrelationship is also less than others. The deviated percentages are approximately 1.66% and4.81% for MC and MCC models consecutively. The transverse profile of the surface settlement
was compared with the numerical results obtained from the MCC model and the MC model. It
can be clearly seen that results of the MCC model have the best fit to the data points. According
to the literature, the MC model substantially differs from data monitoring outputs, thus theelasto-plastic model (e.g., the MCC model) is considered to be suitable for this type of soils.
In the literature, comparing the maximum settlements of numerical analyses and Peck formula,about 9.6% and 41% deviations were found for MC and MCC models respectively. In ourcomparative analyses of Plaxis, the values are 11.11% and 44.4% for MC and MCC models
respectively.

63

Figure 3.5: Distribution of Surface Settlement Trough (a) Three-dimensional view (b)Cross Sectional view (Transverse Section) (Lu et al., 2019)64

Figure 3.6: Relevant parameters for relations (Eslami et al., 2020)
Table 3.3: Empirical Relations based on different researchers
Researchers
Peck, 1969
Clough & Schmidt, 1981

Empirical Relations𝑖
𝑍0= ( )𝑛 (𝑛 = 0.8 − 1)
𝑅
2𝑅
𝑖
𝑍0
= ( )𝑛 (𝑛 = 0.8)
𝑅
2𝑅

Atkinson & Potts, 1977

𝑖 = 0.25 (1.5𝑍0 + 0.5𝑅)

O’Reily & New, 1982

𝑖 = 0.43𝑍0 + 1.1

Mair & Taylor, 1999

𝑖 = (0.4 − 0.5)𝑍0 + 1.1

Attewell & Farmer, 1974

𝑖
𝑍0
=( )
𝑅
2𝑅

To predict the surface settlement, the MCC model is proposed in soft clay with a low overconsolidation ratio or normal consolidation similar to the soil in this site. In other words, where
the shear modulus is independent of the shear strain, the surface settlement has a wide andshallow profile. Since the over consolidation clay exhibits non-linear stress strain behavior at
the small strain prior to crossing the plastic yielding, it is very important to consider the
behavior of these kinds of soils under small strain condition. Nevertheless, the shear modulus
in the MC model is constant and the shear strain doesn’t change with shear stress; this isprobably the main reason for the difference between the results. Based on the results of Bolton
for the prediction of surface settlement, strain non-linearity within the elastic domain must be
implemented. The MCC model has a relatively precise prediction of the surface displacement
in clay, either by normal consolidation or low OCR value.
65

In Table 3.4, the results are shown after calculating the distance of inflexion point from center
based on different researchers’ empirical formulas for both MC and MCC models of TBM
method. And after analyzing, the deviated percentage from PLAXIS and literature is marked
in O’Reily & New relationship as it shows the lowest deviated percentages (%) among all.
Also, the maximum transverse settlement and settlement at inflection point do not vary a lot
from literature’s perspective. Therefore, for measuring the distance, i, O’Reily & New formulacan be reliable to use which is validated in this chapter.
From the comparative analysis of Mashhad Metro Line 2, it can be seen that O’ Reily & New
empirical relation shows closest values (3.91%, 1.66% and 4.81% deviation with FLAC 3D,
MC model in PLAXIS 3D and MCC model in PLAXIS 3D respectively).
Table 3.4: Calculation of inflexion point distance from center based on different researchersfor MC and MCC Models (TBM method) and Comparison with Numerical Analysis (forDeviated Value

Value from Literature

Deviated Value

%

m

%

14

4.55

6.42

7.24

3.31

7.41

5.53

14

4.55

6.42

7.24

11.32

7.41

14

4.55

5.82

7.24

19.64

14

4.55

7.12

7.24

1.66

inflexion

Value from PLAXIS
m

mm

mm

mm

0.17

-8.0

-7.0

-5.0

-4.0

13.33

0.17

-8.0

-7.0

-5.0

-4.0

7.41

21.47

0.17

-8.0

-7.0

-5.0

-4.0

7.41

3.91

0.17

-8.0

-7.0

-5.0

-4.0

Settlement(Literature)atmm

Difference in inflexion point

Settlement at inflexion (Plaxis)

Distance to Point of Inflexion, im

Max Settlement from literature

Tunnel Radiusm

Max Settlement from PLAXIS

Tunnel depth

Researchersm

Schmidt& Potts& New

AtkinsonO’ ReilyMC

Clough &PeckModel Type

literature and PLAXIS both)66

Tunnel Radius

Distance to Point of Inflexion, iValue from PLAXIS

Deviated Value

Value from Literature

Deviated Value

Difference in inflexion point

Max Settlement from PLAXISMax Settlement from literature

Settlement at inflexion (Plaxis)

inflexion

Tunnel depth

5.60

7.24

3.31

7.41

5.53

0.17

-8.0

-7.0

-5.0

-4.0

14

4.55

7.00

7.24

3.31

7.41

5.53

0.17

-8.0

-7.0

-5.0

-4.0

14

4.55

6.42

7.48

6.42

7.41

5.53

0.17

-5.0

-4.0

-4.0

-3.0

14

4.55

6.42

7.48

14.14

7.41

13.33

0.17

-5.0

-4.0

-4.0

-3.0

14

4.55

5.82

7.48

22.21

7.41

21.47

0.17

-5.0

-4.0

-4.0

-3.0

14

4.55

7.12

7.48

4.81

7.41

3.91

0.17

-5.0

-4.0

-4.0

-3.0

14

4.55

5.60

7.48

25.13

7.41

5.53

0.17

-5.0

-4.0

-4.0

-3.0

14

4.55

7.00

7.48

6.42

7.41

5.53

0.17

-5.0

-4.0

-4.0

-3.0

(Literature)

Settlement

TaylorFarmerSchmidt& Potts& New
TaylorFarmerAttewell &

Mair

&

O’ Reily

MCC

AtkinsonClough &Peck

Attewell &atResearchers
&

4.55

Mair

Model Type14

In Figure 3.7, the transverse settlement profile from PLAXIS, FLAC3D and Peck’s empiricalformula is plotted in graphical form, where it can be seen that every curve follows the Gaussian
distribution curve. Curves for MC (PLAXIS and FLAC3D both) tends to show similar pattern67

as the Peck’s curve and settlement values are larger in MC than MCC models. The center of
the tunnel is depicted as 0 in X-axis of the graph. Different findings of distance of inflection
point from center from PLAXIS values and empirical relations established by various
researchers is shown in Figure 3.8, where it can be indicated that the O’Reily & New formula
gives comparatively closer value of numerical findings among all. The distribution of total
displacement in PLAXIS 3D for MC and MCC model are represented in Figure 3.9 and Figure
3.10 respectively.
Settlement at Transverse Section
0.0
0

2

4

6

8

10

12

14

16

-1.0

-2.0

Settlement (mm)

-3.0

-4.0

-5.0

-6.0

-7.0

-8.0

-9.0

-10.0

Distance from center (m)MC_PLAXIS

MCC_PLAXISPeck

MC_FLAC3D

MCC_FLAC3D

Figure 3.7: Comparison of Settlement at Transverse Section between PLAXIS 3D,
FLAC 3D and Peck’s Formula

68

Distance of Point of Inflexion from Center
Monitored Value from Literature

MCC_PLAXIS 3D

MC_PLAXIS 3D

Attewell & Farmer

Mair & Taylor

O'Reily & New

Atkinson & Potts

Clough & Schmidt

Peck
7.41
7.48
7.24
7.00
5.60
7.12
5.82
6.42
6.42

Figure 3.8: Comparison between Different Findings of Distance of Point of Inflexion
from Center69

MC Model

Figure 3.9: Representation of Distribution of Total Displacement of Mashhad Metroin PLAXIS 3D (MC Model)

MCC Model

Figure 3.10: Representation of Distribution of Total Displacement of Mashhad Metroin PLAXIS 3D (MCC Model)

70

3.3

General Information about Delhi Metro Phase 3, India

In Delhi Metro Phase-3, a record of 30 TBMs was used to bore about 80km of undergroundtunnels in total (combining the length of both way tunnels). The total length of the underground
corridor in this phase is about 54km. The new tunnels passed below existing operational
elevated viaducts, an operational tunnel of DMRC, the rocky Aravalli ranges, heritage
monuments, and densely populated areas. The tunnel passed underneath the old dilapidated
buildings, which were undergoing reconstruction or repairs. The Figure 3.11 represents the
proposed plan of Delhi Metro Phase 3.

Figure 3.11: Proposed Plan of Delhi Metro Phase 3 Line (Dotted Lines are
Underground portions) (Naqvi et al., 2021)
3.1.1 Soil Condition and Parameters
The soil used in this analysis was Delhi silty sand. The properties of soil and concrete tunnel
lining are given in Table 3.5 and Table 3.6.

71

Field data shows that the cohesionless of soil of Delhi has horizontal stratification with thevariation in Young’s modulus at various depths. To replicate the field condition, the Young’s
modulus of soil is linearly varied from top to bottom, with 7.5 MPa at top and 50 MPa at thebottom. In Figure 3.12, the variation in Young’s modulus with depth is shown for clear view.
The location of tunnel and tunnel specification is defined in Figure 3.13.
Table 3.5: Soil and Concrete Lining Properties found from Soil Test Data
Delhi Silty Sand
Bulk Density

kN/m3

18

Saturated Density

kN/m3

20

Poisson’s Ratio

0.25

Friction Angle

35

Dilatation Angle

5
Concrete Lining

DensitykN/m3

25

Young’s Modulus

kPa

3.16 X 107

Poisson’s Ratio

0.15

Sectional Area

cm2/m

2500

Plastic Section Modulus

cm3/m

15625

Moment of Inertia

cm4/m

130208.33

Yield Strength

MPa

30

Weightkg/m/m625

Table 3.6: Young’s Modulus of Delhi Silty Sand at Various depths
Depth (m)Young’s Modulus (kPa)

0 ~ 107500

10 ~ 2015000

20 ~ 3530000

35 ~ 5040000

50 ~ 60

50000

72

Figure 3.12: Representation of Young’s Modulus of Delhi Silty Sand at Various
depths (Naqvi et al., 2021)

Figure 3.13: Schematic Representation of Model Parameters (Naqvi et al., 2021)

73

3.1.2 Numerical Modelling
2D plain strain model has been a model using commercially available finite element software
Optum G2. The elastoplastic model of soil was modelled using the Mohr-Coulomb criterion.
The dimensions of the soil model are considered as 50 m width and 54 m height. The range of
depth of tunnel found in the Delhi Metro Phase 3 project is 12–30 m. Depth 18m was chosen
for simplification of modeling. The excavated diameter of the tunnel is kept 6.35 m. In order
to avoid the boundary effect in numerical analysis, the outer boundary was placed at a distanceof 3 diameters away from the center of the tunnel. The thickness of the concrete lining used forthe modelling was kept 25 cm. Tunnel length of 54m (1/1000th of actual length) and radius of
3.175m have been considered.
3.1.3 Stages of Analysis
The analysis was performed in below mentioned stages to simulate the real field conditions asfollows:
Stage 1: A Greenfield condition having soil modelled similarly to field conditions. The analysis
performed in this stage, known as initial stress analysis.
Stage 2: A second stage where the tunnel is excavated. The tunnel perimeter is here fully
supported.
Stage 3: The lining was inserted in the third stage, and all supports around the tunnel perimeter
were removed and were replaced by a plate to model the lining. The elastoplastic analysis wasthen carried out.
For the validation of the present numerical analysis, the surface settlement has been calculated
through established empirical formulas and compared with the numerical results of OptumG2
in literature and of PLAXIS 3D in this research. A closed-form solution had been proposed by
Peck and Schmidt (1969) to calculate the surface settlement in soil due to an undergroundopening.
𝑆𝑣 =𝑉𝑠√2𝜋𝐾𝑍0𝑒−𝑦2
2𝐾2 𝑍0 2(3.11)

Where Vs is the volume of the settlement trough per meter of tunnel advance (m3/m), defined
as a percentage volume loss of the unit volume V of the tunnel, and was taken as 0.35% for
low plastic silty soil, K is trough width parameter and was taken as 0.5 for ML soil, y is thelateral distance from the tunnel centerline (m), and Z0 is the depth of the neutral axis from the74

surface. Vertical settlement profile of ground from the center of model (point above crown) to
the lateral boundary was plotted using the above two formula and numerical results obtained
from Optum G2 and PLAXIS 3D. The variation or deviation percentage between numericalanalysis and peck formula was considered approximately 13% in literature whereas in our
computation after numerical analysis, the deviations are approximately 15%. This comparisonof settlement values of Peck’s empirical formula, OptumG2 and PLAXIS 3D numericalanalyses for MC model type are shown in Table 3.7 and Figure 3.14. In Figure 3.15, Figure
3.16, and Figure 3.17, the meshing condition in Optum G2, the meshing condition in PLAXIS
3D and distribution of vertical surface settlement in PLAXIS 3D are shown.
It can be seen from the validation result of PLAXIS 3D, Optum G2 and Peck formula, thedifference percentage between Optum G2 and Peck’s formula is 12.69% whereas the difference
percentage between PLAXIS 3D and Peck’s formula is 14.93% and the difference percentage
between PLAXIS 3D and Optum G2 is 4.81%.
Table 3.7: Calculation of Vertical Surface Settlement based on Peck & Schmidt Formula and

12.69

14.93

4.81

Optum

Difference

31.20

PLAXIS

29.70

Difference

34.10

G2

3.175

Difference

18

PLAXIS)(%)

Settlement(%)

Vertical(%)

Optum G2)

(mm)

Settlement(mm)

Vertical(mm)

Peck formula)

(m)

75

G2

PLAXIS and Optum

betweenEmpirical FormulaandbetweenEmpirical Formulaandbetween(from

Surface(from

Surface

(from

(m)

Settlement

Vertical

SurfaceRadius, R

MC

Tunnel Depth, Z0

Model Type

Comparison with Numerical Analysis Data

VERTICAL SURFACESETTLEMENT AT TRANSVERSESECTION
-27.0
-28.0

Settlement (mm)

-29.0
-30.0

-31.0
-32.0
-33.0
-34.0
-35.0

MC_PLAXIS
Peck & Schmidt
MC_Optum G2

0
-31.2
-34.1
-29.7

Figure 3.14: Comparison of Vertical Surface Settlement between PLAXIS 3D, Optum
G2 and Peck & Schmidt Formula

Figure 3.15: Meshing Condition in Optum G2

76

Figure 3.16: Meshing Condition in PLAXIS 3D

Figure 3.17: Distribution of Vertical Surface Settlement in PLAXIS 3D

77

3.4
i.

Summary
The detailed geotechnical investigation report of Mashhad Metro Line 2 has been
implied in PLAXIS 3D to validate the researcher’s result with the numerical result. The
researchers used FLAC 3D for numerical analysis and compared the result with
empirical relations.

ii.

From the empirical relations suggested by the researchers, it can be seen that O’Reily
and New relations show better error value than others. Also, in our numerical analyses
with PLAXIS 3D, the error values for this relationship are 1.66% and 4.81% for MC
and MCC models respectively which are comparatively less than other relationships.

iii.

Comparing the FLAC 3D result and Peck formula for maximum settlement, 9.6% and
41% error were found for MC and MCC models respectively, whereas comparing
PLAXIS 3D and Peck formula for maximum settlement, 11.11% and 44.4% were foundfor MC and MCC models respectively which is approximately close to the literature.

iv.

From the comparative analysis of Mashhad Metro Line 2, it can be seen that O’ Reily& New empirical relation shows closest values (3.91%, 1.66% and 4.81% deviation
with FLAC 3D, MC model in PLAXIS 3D and MCC model in PLAXIS 3D
respectively).

v.

The detailed geotechnical investigation report of Delhi Metro Phase 3 has been impliedin PLAXIS 3D to validate the researcher’s result with the numerical result. The
researchers used Optum G2 for numerical analysis and compared the result with
empirical relations.

vi.

The variation percentage between numerical analysis of Optum G2 and Peck’s formula
was approximately 13% whereas in PLAXIS 3D and Peck’s formula wasapproximately 15% which is approximately close.

vii.

It can be seen from the validation result of PLAXIS 3D, Optum G2 and Peck formula,
the difference percentage between Optum G2 and Peck’s formula is 12.69% whereas
the difference percentage between PLAXIS 3D and Peck’s formula is 14.93% and thedifference percentage between PLAXIS 3D and Optum G2 is 4.81%.

78

Chapter 4
NUMERICAL MODELING AND ANALYSIS
Introduction
In this chapter, the outline of proposed MRT line 1 project, the detailed route of undergroundpart, and geology and soil condition of the selected study area are described with appropriate
maps. The field study investigation including physical and laboratory tests of soil samples aredone in accordance with the ASTM standards which are also discussed and a longitudinal soil
profile for the study area is created with the help of the field study data. The different test
results of the field study investigation are mentioned in this chapter and in Appendix which arecollected from secondary sources. FEM analysis (numerical modelling) is done by PLAXIS
3D for both NATM and TBM methods for different types of models (MC, MCC and HS) aredescribed in details in this chapter.

Context of Underground Part of Dhaka Mass Rapid Transit Line 1
The length of the MRT line 1 will be 28.2 km with 19 stations and one depot in Purbachal area.
As per the plan, the MRT line 1 consists of two lines, one being the route that connects
Kamalapur with the Hazrat Shahajalal International Airport (hereafter the “Airport Line”). Theline will be runs through underground tunnel, starts at the Kamlapur station of Bangladesh
National Rail (BR), travels westward under the Outer Circular Road, northward under the
Rampura DIT Road and Pragati Sharani Road, crosses the Kuril flyover, and proceeds under
the New Airport Road to its destination at Dhaka International Airport. Out of total 28.2 km,
the airport line will be 14.8 km underground line comprising total 12 underground stations.
Construction of the underground running section shall be done by Tunnel Boring Machine(TBM) and stations will be constructed either by Cut and Cover method. The outer diameterof the tunnel is 7m and standard length of station is 250m. The metro tunnels will range from
20m to 50m below the ground in different locations with average depth of 35 meter (NKDOS
Consortium Proposal, 2019). The Figure 4.1 represents the alignment map of MRT Line 1
where green line, red line, green labels and red labels are represented as underground section,
elevated section, underground stations, and elevated stations respectively. The Table 4.1
specifies the underground stations’ names, station types and tier type or connectivity locations
with other stations.

79

Table 4.1: List of Underground Stations in MRT Line 1
SL.

Underground Stations

Station TypeSpecial Consideration

1

KamlapurStandard

2

Rajarbagh

Narrow/DeepTwo-tier Station

3

Malibagh

Narrow/DeepTwo-tier Station

4

RampuraStandard

5

Hatirjheel East

Standard

6

Badda

Standard

7

North Badda

Standard

8

Natun Bazar

Wide Station

No.

Connectivity with Line 5 South Station

Connectivity with Line 5 North Station and proper
protection for existing DWASA pipe line

9

Nadda

Double/DeepTwo-tier Station

10

Khilkhet

Standard

11

Airport Terminal - 3

Standard

Connectivity with New Airport Terminal 3

12

AirportStandard

Connectivity with BR Station and Extension Line 1

Figure 4.1: Map showing the MRT Line 1 Alignment with Stations Location (NKDOS
Consortium Proposal, 2019)80

3.3.1

Geology and Soils

Dhaka lies in the extreme south of the Madhupur Tract, which is situated in the central-easternpart of Bangladesh. The planning area is covered mainly by the Pleistocene Madhupur Clay, ayellowish brown to the highly oxidized reddish brown silty clay; and by Holocene sediments
to the south, west and east made up of alluvial silt and clay and marshy clay and peat. The
moisture content and liquid limit results obtained for the Madhupur clay show that it isnormally consolidated to slightly over-consolidated, perhaps due to groundwater pumping. The
clay has intermediate to high plasticity, and is overlain by the Dupi Tila formation of medium
to coarse sand. The incised channels and depressions within the city are floored by recent
alluvial flood plain deposits. The project location in geology of Bangladesh map is shown in
the Figure 4.2.

Figure 4.2: MRT Line 1 Location in Geology of Bangladesh Map (NKDOS
Consortium Proposal, 2019)
According to the soil maps of Bangladesh (Figure 4.3), the project site falls under the shallow
red-brown terrace soil and deep red-brown terrace soil. The shallow red-brown soils are81

imperfectly to moderately well drained. The topsoil of deep red-brown terrace soils usually is
8-10 cm thick and has a brown to yellow brown color, loam to clay loam texture and rusty
stains along root channels. The subsoil usually is 60-120 cm thick.

Figure 4.3: MRT Line 1 Location of Soils of Bangladesh Map (NKDOS Consortium
Proposal, 2019)
Dhaka city falls in seismic zone II of the seismic zoning map of Bangladesh which means thecity is at moderate risk (basic seismic coefficient is 0.5 g). Neotectonic movement in andaround the city has been reported widely. The Madhupur Tract as a whole is a structural highin which the Dhaka-Tongi block is the most uplifted part. The boundaries of the tract to thewest, south and east are characterized by step faulting. The high land area which varies up to
100ft shows low relief. The high lands are composed of Pleistocene Madhupur Clay and Sand
formation where the low lands are recent floodplain deposits. The studied area is mostly
consisted of clayey soil than the sandy soils. There are some sandy soils interbedded between
these clay layers. The upper part comprises grayish to brownish stiff to medium stiff clayeysoil and brownish medium dense soil of Basabo silty clay formation and lower brownish very
dense sand and hard clayey soil below it can be of from Madhupur clay and sand formation.
The degree of concentration and thickness of clayey soil is also influenced by the neo-tectonics
of this region, which causes undulation of ground surface. The surface elevation of the area
Dhaka are ranges between 1 and 14m and most of the built-up areas located at the elevations82

of 6-8m (Follow Figure 4.4). The drainage system will be hampered due to construction
activities like as infilling, construction of the depot, construction yards and haul routes. A major
impact during construction stage is due to suspended solids entrained in runoff that can bringsoil surfaces and clog drainage system. Underground tunnel construction may impact on
ground water quality and depth of the underground water level. Potential impacts on
groundwater are insignificant. In Dhaka City, Ground Water extraction started from a depth of
100m and in some extreme condition the well goes up to 300 meters to reach the main aquifer.

Figure 4.4: Elevation Map of the Project Area (NKDOS Consortium Proposal, 2019)
3.3.2

Field Investigation of the Study Area

The objectives of the geotechnical survey are to obtain physical and mechanical properties ofsoil and soil design parameters through field and laboratory tests. In field, in-situ tests, such as
standard penetration tests and pressure meter tests were conducted and index and mechanicalproperties tests such as compression, consolidation tests etc. were conducted in the laboratory.
The investigation program was consisted of soil boring and sampling at desired intervals for
subsequent observation and laboratory testing (ProSoil Geotechnical Survey, 2019). The soil

83

report and physical and mechanical properties of soil are collected from secondary data
sources.
The selected borehole’s location (BH-24) is marked in the route map in Figure 4.5 and Table
4.2. The portion of longitudinal soil profile (geotechnical) of the Airport route and soil
stratification of BH-24 is presented in Figure 4.6. The physical description of soil strata withSPT values and depth range are mentioned in Table 4.3.

Figure 4.5: Location of Selected Borehole (BH-24) for Investigation (NKDOS
Consortium Proposal, 2019)
Table 4.2: Identification of Borehole 24
Borehole No.

24

Location

Under Kuril Flyover (In front of Walton
Showroom)

Coordinates

23.82075N, 90.42077E

RL+8.313m84

Figure 4.6: Subsoil Stratification of BH-24
85

Table 4.3: Description of Soil Layers from SPT Test Result (BH-24)
Soil
Soil
SL.
Consistency
Layer
Description
No.
and Relative
Notation
Density
1

SF

Made
Ground2

AC3

Lean Clay

Medium Stiff

3

AC4

Fat Clay

Stiff

4

AC4

Lean Clay

Stiff

5

AS3

Sandy Silt

Medium Dense

6

AS3

Silt

7

AC5

Lean Clay

8

AS3

Silt

9

AS3

Sandy Silt

Very Stiff

Medium Dense

Soil Color
Gray, Gray to
Reddish Gray,
Reddish Gray
Gray, Reddish Gray,
Gray to Yellowish
Gray, Brown
Brown, Gray, Gray to
Yellowish Gray,
Grayish Brown toGray, Gray to Brown,
Grayish Brown
Brown, Gray, Gray to
Yellowish Gray,
Grayish Brown toGray, Gray to Brown,
Grayish Brown
Gray, Yellowish
Gray, Yellowish Grayto Brown, Brown
Gray, Yellowish
Gray, Yellowish Grayto Brown, Brown
Yellowish Gray,
Yellowish Gray to
Reddish Brown,
Brown to Gray, Gray,
Gray to Reddish
Gray, Reddish
Brown, Brown, Dark
Gray, Reddish Gray,
Gray to Yellowish
Gray, Red, Grayish
Brown, Black, Grayto Brown, Brown to
Brownish Gray,
Brownish Gray to
Brown
Gray, Yellowish
Gray, Yellowish Grayto Brown, Brown
Gray, Yellowish
Gray, Yellowish Grayto Brown, Brown

Depth
SPT
Range
Range
(m)
0–
4.5

10-15

4.5 –
5.0

7

5.06.012

6.07.5

15

7.5 –
9.0

11

9.012.0

16

12.0 –
13.5

19 –
21

13.5 –
16.5

21-29

16.5 –
18

31

86

Soil
Soil
SL.
Consistency
Layer
Description
No.
and Relative
Notation
Density

Soil Color

Depth
SPT
Range
Range
(m)

Gray, Yellowish
Gray, Brown, Gray to
Brown, Brown to
Grayish Brown,
18 –10 AS4
Silty Sand
Dense
Yellowish Gray to
37
21
Brown, Gray,
Reddish Gray,
Brownish Gray to
Gray
Gray, Yellowish
Gray, Brown, Gray to
Brown, Brown to
Grayish Brown,
21 –
42 –
11 AS4
Sandy Silt
Dense
Yellowish Gray to
22.5
45
Brown, Gray,
Reddish Gray,
Brownish Gray to
Gray
Gray, Brown, Gray to
Brown, Yellowish
Brown, Yellowish
Gray, Reddish Gray,
22.5 – 38 –12 AS5
Silty Sand
Very Dense
Brown to Grayish
41
50
Brown, Red, Grayish
Brown to Brown,
Brownish Gray to
GrayUnconfined compression test results, UU triaxial test results for determining undrained shear
strength, secant modulus, angle of friction, and cohesion are included in this chapter andsummary test result sheet collected from secondary source is mentioned in Appendix A. As thesoil was found unsaturated, the angle of friction was found deviated from zero.

87

Figure 4.7: Unconfined Compression Test Result (Depth 5.0-6.0m) – Soil Type: Fat
Clay

88

Figure 4.8: UU Triaxial Test Result (Depth 5.0-6.0m)

89Numerical ModelingTo evaluate the settlement or displacement of tunnel under static condition, the numericalmodelling in PLAXIS 3D can simulate the significant results which is difficult to conduct inlaboratory or field or empirical conditions. In this investigation, the study area is filled withclayey type soil and sandy silt type soil in between. Therefore, there is a minimal chance of
having liquefaction effect in seismic condition in this area. The FEM model is calibrated withthe field and laboratory tests data. The result of TBM and NATM tunnels are shown using MC,
MCC and HS soil models. The effect of varying tunnel depths and diameters is shown for TBM
methods. At the end a comparison is made between NATM and TBM method in respect tosettlement for three different models. Assumptions used in the estimations are as follows:i.

Cross-section of the tunnel is almost circular.

ii.

Undulation in existing ground level is ignored.

iii.

Tunnel is considered to move along a straight line.

iv.

Tunnel is deep enough (35m from EGL) for avoiding the effect of adjacent structuresand foundations.

v.

Tunnel passes through clayey soil formation.

vi.

Tunneling method is both NATM and TBM.

vii.

Estimations are valid for completed primary support

viii.

Long term consolidation settlement is ignored.

ix.

Static and Dynamic loading effects are ignored.

3D model is chosen because for 2D FE models, it is not so easy to estimate pre-relaxation
factors (sometimes called stress reduction factors), which is fraction of load effecting ontunnels, and purely based on practical experience. With the 3D model, estimation of prerelaxation factor is no longer required when excavation stages can be modelled not only incross-section but also in the longitudinal section, e.g., excavation of the bench and invert canbe modelled in the actual distance behind the excavation of the top heading.
Limitations:i.

Existing ground surface abruption and ground water level effect (flow water condition)
is not considered.
90

ii.

Due to considering one borehole data, the soil properties and division of layers are kept
equal all along the assumed length.

iii.

Diameter (7m) is considered according to the feasibility report of MRT line 1 Project.
Though for TBM analysis, variations in diameter (up to 5m) have been considered.

FEM Model in PLAXIS 3D (TBM Method)
The lining of a shield tunnel is often constructed using prefabricated concrete ring segments,
which are bolted together within the TBM to form the tunnel lining. During the erection of thetunnel lining the TBM remains stationary. Once a tunnel lining ring has been fully erected,
excavation is resumed, until enough soil has been excavated to erect the next lining ring. As aresult, the construction process can be divided into construction stages with a length of a tunnel
ring, often about 1.5m long. In each of these stages, the same steps are repeated over and overagain. In order to model this, a geometry consisting of slices each 1.5m long was used. The
calculation consists of a number of plastic phases, each of which models the same parts of the
excavation process; the support pressure at the tunnel face needed to prevent active failure at
the face, the excavation of soil and pore water within the TBM, the installation of the tunnel
lining and the grouting of the gap between the soil and the newly installed lining. This tunnel
advancement process is illustrated in Figure 4.9. In each phase the input for the calculation
phase is identical, except for its location, which will be shifted by 1.5m each phase.

Figure 4.9: Schematic illustration of tunneling simulation process (Bentley, 2018)91

3.5.1

Geometry

In the model, only one symmetric half is included. The model is 25m wide, it extends 60m in
the y-direction and it is 41m deep. These dimensions are sufficient to allow for any possible
collapse mechanism to develop and to avoid any influence from the model boundaries. The
subsoil consists of 11 layers. The soil layers with depth and soil conditions with parameters for
all models are given below. The tunnel excavation is carried out by a tunnel boring machine(TBM) which is 10m long and 7m diameter with 0.25m concrete lining. The TBM wasconsidered to be advanced 25m into soil. Subsequent phases will model an advancement by
1.5m each. The locations of tunnels considered in simulation are 30m, 32m, and 35m depth
from ground surface (Figure 4.10).

Made Ground
Lean Clay, AC3
Lean Clay, AC4
Sandy Silt, AS3
Silt, AS3
Lean Clay, AC5
Sandy Silt, AS3
Silty Sand, AS4
Sandy Silt, AS4
Considered Locations of tunnels
for 3D Analysis (At 30m, 32m
and 35m depth)

Silty Sand, AS5

Figure 4.10: Locations of TBM machines in Soil (NKDOS Consortium Proposal,
2019)
92

3.5.2

Definition of Structural Elements

A soil structure interaction has to be added on the outside of the tunnel due to the slight cone
shape of the TBM. Typically, the cross-sectional area at the tail of the TBM is about 0.5%
smaller than the front of the TBM. The reduction of the diameter is realized over the first 7.5m
length of the diameter while the last 1.5m to the tail has the constant diameter. So, in modeling,
uniform and incremental contraction has been considered according to the advancement of the
TBM. The surface load representing the grout pressure is constant during the building process.
In the specifications of the tunnel boring process, it is given that the grout pressure should be 100kN/m2 at the top of the tunnel and should increase with -20kN/m2/length. The tunnel facepressure is a bentonite pressure (Bentonite slurry) or an earth pressure (Earth Pressure balance)that increases linearly with depth.
For the initial position of the TBM and the successive four positions when simulating theadvancement of the TBM, a tunnel face pressure was defined. In order to simplify the definitionof the phases in Staged construction mode, the sequencing of the tunnel was defined. The soil
in front of the TBM will be excavated, a support pressure will be applied to the tunnel face, theTBM shield will be activated, and the conicity of the shield will be modelled, at the back of the
TBM the pressure due to the backfill grouting will be modelled as well as the forces of thehydraulic jacks driving the TBM exert on the already installed lining, and a new lining ring
will be installed. In the mesh mode, medium mesh was used to generate. Since water levels
will remain constant the flow conditions mode was skipped. The excavation of the soil and theconstruction of the tunnel lining was modelled in the staged construction mode. The first phasediffers from the following phases, as in this phase the tunnel is activated for the first time. In
the Table 4.4, parameters are defined for HS, MC and MCC model types for TBM construction
method. The soil parameters depicted are:i.

Dry and Wet Density, Initial Void Ratio, Cohesion (cref), Internal Friction (φ)

ii.

Secant Modulus at 50% strength (E50ref), Modulus for Oedometer conditions (Eoedref),Unload-Reload Modulus (Eurref)iii.

Cam Clay isotropic compression index (λ), Cam Clay isotropic swelling index (κ),
Tangent of the critical state line (M)iv.

Young’s Modulus (E’), Poisson’s Ratio (ʋ)

93FEM Model in PLAXIS 3D (NATM Method)
NATM is characterized by the fact that a tunnel is excavated in different parts (crown, bench,and invert), where subsequent parts are executed at a certain distance (lag) behind the previous
part. After each excavation part the tunnel contour is secured by means of a temporary liningof sprayed concrete. A final lining can be installed later if the long-term soil conditions requiresuch. As per the real tunnel excavation, in the modelling excavation of three parts were
included. The model is basic and medium in order to restrict the computation time and memory
consumption.

Figure 4.11: Basic NATM method assuming for Numerical Modelling (Sinha, 1989)
4.5.1

Geometry

The top of the tunnel is 35m below the ground surface considered. The full tunnel has the heightof 7m and a width of 10m. The crown was excavated in a section of 1.0m length. After the
excavation the surrounding soil was secured with sprayed concrete. The excavation of thebench is always some meters behind the heading. A length of 9m behind the bench excavation
was included in the model to create the starting situation. The invert is much further behind
and it is of almost 5m behind the benching. For reasons of symmetry, only half of the geometry
is modelled, whereas symmetry conditions were adopted at the center plane. The model isextended 25m sideways (in y direction) from the center plane, 60m in x direction and -40m inz direction.

944.5.2 Definition of Structural Elements
The mesh is generated automatically (usually medium) and some refinements was applied by
PLAXIS in order to get smaller mesh sizes in the tunnel vicinity where the stresses anddeformations are concentrated. The mesh for the 3D model consists of the default 10-node
tetrahedron elements. For plates used to simulate tunnel linings, 6-node plate elements areapplied which are compatible with the 6-node face of a soil element. Moreover 12-nodeinterface elements are used to simulate soil-structure interaction behavior. In the staged
construction, the advancement of top heading, bench and invert excavations are assumed to
2m. Although this value is a little bit higher than the common practice, shorter advancements,
i.e., shorter slice lengths, result in excessive run times and memory consumption. The tunnel
length is taken as 19m which is suitable for displaying deformations and stresses due to surface
excavation and construction along the tunnel of actual length of MRT Line-1.
The excavation process was divided in two different stages for each advance: the first stage
simulates the excavation and the second stage the application of the concrete lining. It was
assumed that the soil and initial ground support deforms to equilibrium after each 1 m advance
before the primary sprayed lining is applied, furthermore no time effects were taken into
account for the PLAXIS plastic calculations. The hosting media is assumed to be consisting of
11 layers of soil. It is assumed that no water table is encountered in the problem domain. All
the analyses are performed by considering the drained condition. The tunnel is modelled withthree different types of models (MC, MCC and HS), where modulus of elasticity (initial,
unloading/reloading, oedometer, etc.) are chosen satisfactorily and according to the soil test
results. The elasticity modulus of the soil is stress dependent and the loading history has a great
influence on the soil non-linear behavior. Interfaces were applied only to the negative side of
the tunnel lining, meaning only in the contact places with the soil mass, and not on the insideof the tunnel, where the soil volume is excavated. The shotcrete is modeled as a linear elastic
material. The main parameter for the linear elastic materials in PLAXIS 3D tunnel is theYoung’s modulus. The modulus for shotcrete has been evaluated by using the empiricalformula suggested by American Concrete Institute which relates the Young’s modulus with thecompression strength of the concrete:
𝐸 = 4900𝜎 0.5(4.1)

Where σ is the 28-day compression strength of the concrete.

95

The final lining of the tunnels is actually not the main load carrying components in short term.
They are designed for the long term since the shotcrete is degraded in time and it loses its load
carrying capacity. The final lining is assumed to be reinforced concrete. After the K0
procedure, which is the initial phase, the phases of excavation and primary lining installation
are modelled in a sequence as it would happen in site. The main idea behind the staged
excavation modelling is to simulate the real construction procedure and thus take the archingeffect and the effects of the sequential construction to the 3D model into account. After eachof the excavation phase, a so-called nil step is used to regenerate equilibrium for the next
calculation which reduces the instability of the model. Plastic calculations are executed in orderto calculate the unfactored deformations and pressures to allow a fair comparison. The analyses
have been made for excavation depth 35m and diameter 7m.

Figure 4.12: Phases of construction used for PLAXIS 3D modelling (Sinha, 1989)
The soil layers for different depths are specified along with soil condition parameters in Table
4.4. In the Table, parameters are defined for HS, MC and MCC model types for NATM and
TBM construction method. The soil parameters depicted are: Dry and Wet Density, Initial Void
Ratio, Cohesion (cref), Internal Friction (φ), Secant Modulus at 50% strength (E50ref), Modulus
for Oedometer conditions (Eoedref), Unload-Reload Modulus (Eurref), Cam Clay isotropic
compression index (λ), Cam Clay isotropic swelling index (κ), Tangent of the critical state line(M), Young’s Modulus (E’), Poisson’s Ratio (ʋ).
In Table 4.5, the stage construction phases followed for numerical modelling in NATM and
TBM construction methods are emphasized. And in Figure 4.13 and Figure 4.14, thedeformation patterns in PLAXIS 3D for NATM method and TBM method (depth 35m anddiameter 7m) for HS, MC and MCC models are depicted. The depth variation and diametervariation has been considered also in calculation which is not shown in this report.

96

Table 4.4: Soil Layers with Depth Range and Soil Condition Parameters using in NATM and TBM Methods
General Information
SL.
No.

Depth
Description Range

HS ModelDry

Wet

InitialDensityDensityVoid(m)(kN/m3)(kN/m3)

Ratio

cref

MCC Model

φE50ref

Eoedref

Eurref(deg)(kN/m2)(kN/m2)(kN/m2)

MC Model

λ

κ

M

E’

ʋ

1

Lean Clay

4.5 – 5.0

17.50

21.04

0.60

48

10

282.4*103

272.2*103

1.05*106

0.40

0.10

0.90

282.4*103

0.20

2

Fat Clay

5.0-6.0

17.10

20.72

0.57

48

20

282.4*103

222*103

1.01*106

0.78

0.17

0.80

282.4*103

0.20

3Lean Clay

6.0-7.5

17.50

21.04

0.60

48

10

282.4*103

272.2*103

1.05*106

0.41

0.10

0.90

282.4*103

0.20

4Sandy Silt

7.5 – 9.0

18.70

21.71

0.44

30

25

282.4*103

228.7*103

1.05*106282.4*103

0.20

3

6

3

0.20

282.4*103

0.20

5

Silt

6

Lean Clay

7

Silt

8

Sandy Silt

9

Silty Sand

10

Sandy Silt

11

Silty Sand
Concrete

9.0-12.0
12.0 –
13.5
13.5 –
16.5
16.5 –
18
18 – 2121 –
22.5
22.5 –
41

18.67

21.76

0.45

30

27

282.4*10

17.50

21.04

0.60

48

10

18.67

21.76

0.45

30

18.70

21.71

0.44

17.85

20.22

18.70

17.85
24

3

223*101.05*10282.4*103

272.2*103

1.05*10627

282.4*103

223*103

1.05*106282.4*103

0.20

30

25

282.4*103

225.7*103

1.05*106282.4*103

0.20

0.32

30

30

282.4*103

224.7*103

1.05*106282.4*103

0.20

21.71

0.44

30

25

282.4*103

225.7*103

1.05*106282.4*103

0.20

20.22

0.32

30

30

282.4*103

224.7*103

1.059*106

282.4*1030.20

28.0*106

0.20

0.50

31.11*106

282.4*10
0.41

0.10

0.90

97

Table 4.5: Stage Construction Phases for both NATM and TBM
MethodPhase

Calculation

Action Taken

Type

NATM

InitialK0 procedure

Phase 1

Plastic

Crown excavation, bench excavation, invert excavation, Lining installed in the excavated portions

Phase 2

Plastic

Crown excavation

Phase 3

Plastic

Crown excavation

Phase 4

Plastic

Bench excavation, lining installed in previous crown excavation

Phase 5

Plastic

Bench excavation, lining installed in previous bench excavation

Phase 6

Plastic

Invert excavation, lining installed in previous bench excavation

Phase 7

Plastic

Crown excavation, lining installed in previous invert excavation

Phase 8

Plastic

Crown excavation, lining installed in previous crown excavation

Phase 9

Plastic

Bench excavation, lining installed in previous crown excavation

Phase 10

Plastic

Bench excavation, lining installed in previous bench excavation

Phase 11

Plastic

Invert excavation, lining installed in previous bench excavation

Phase 12

Plastic

Invert excavation, lining installed in invert excavation

InitialK0 procedure

Phase 1

Plastic

Excavation for TBM launching

Phase 2

Plastic

Concrete Lining installation for the excavated portion, excavation stepping ahead, activation of negativeinterface, contract pressure, surface load

TBM
Phase 3

Plastic

Excavation stepping ahead and concrete lining installation for previous excavation, activation of negativeinterface, contract pressure, surface load

Phase 4

Plastic

Excavation stopped and concrete lining installation for previous excavation, activation of negative interface,contract pressure, surface load98

Figure 4.13: NATM Method (MC, MCC, HS model): Depth 35m and Diameter 7m99

Figure 4.14: TBM Method (MC, MCC, HS model): Depth 35m and Diameter 7m

100

Effect of Meshing in Maximum Settlements for NATM and TBM Methods
FEA is the process of dividing geometry into smaller pieces (elements), applying loads andboundary conditions to those elements, and then solving the matrix equations assembled fromthe mesh. Theoretically, the more elements used in the model, the closer the results get to theactual behavior (as modeled), but it may take more computational time. It is found in Yaning
Li and Tomasz Wierzbicki’s research that the stress and strain fields have high gradients in thelocalization zone and the continuing application of the classical stress-strain relation in thelocalization zone is the cause for mesh size effects in Finite Element simulations. The smaller
elements in a finer mesh can more accurately capture stress gradients across the element.
When the geometry model is fully defined the geometry has to be divided into the finite
elements to perform finite element calculations. Very fine meshes should be avoided since thiswill lead to excessive calculation times. The basic soil elements of the 3D finite element mesh
are the 10-node tetrahedral elements. The mesh generator in PLAXIS 3D requires a global
meshing parameter that represents the target element size, le, which is based on the relevant
element size factor (re). The values of this parameter for the element distributions predefinedin the program are: very coarse = 2.0, coarse = 1.5, medium = 1.0, fine = 0.7, and very fine =0.5. The exact number of elements depend on the shape of the geometry and optional local
reinforcement settings. By default, the element distribution is set to Medium (1.0) but for thisresearch, this value has been changed to coarse (1.5) and fine (0.7) also for comparing theanalysis results for tunnel depth = 35.0m and diameter =7.0m for both NATM and TBM
models.
From Figure 4.15 to Figure 4.20, different pattern of meshes (coarse, medium and fine) andeffects in deformation for HS models of NATM and TBM construction methods are shown.
Also, different patterns of meshes have been considered for MC and MCC models like this.
And the element number, node number, and maximum settlement values for different meshpatterns are shown in Table 4.6 and Figure 4.21 with proper description.

101

Figure 4.15: NATM method (HSModel): coarse mesh

Figure 4.16: NATM method (HSModel): medium mesh

Figure 4.17: NATM method (HSModel): fine mesh

102

Figure 4.18: TBM method (HSModel): coarse mesh

Figure 4.19: TBM method (HSModel): medium mesh

Figure 4.20: TBM method (HSModel): fine mesh103

Table 4.6: Comparison of Settlement Values for Different Types of Mesh Sizes in
NATM and TBM Methods
Method
Type

Model
Name
HS

NATM

MCC

MC

HS

TBM

MCC

MC

MeshingType

Element
No

CoarseMediumFine
CoarseMediumFine
CoarseMediumFine
CoarseMediumFine
CoarseMediumFine
CoarseMedium
Fine

16987
19246
60145
16987
19246
60145
16987
19246
60145
32439
34047
72882
32439
34047
72882
32439
34047
72882

Maximum
Settlement
(mm)
24881
-23.7228495-20.9887801-19.2224881-26.5228495-22.5187801-20.7524881-27.5628495-26.4287801-23.4251593-19.5354177-18.54110410-18.4651593-17.9854177-17.47110410-16.6651593-19.0154177-18.11110410-18.03
Node
No

Maximum Settlement (mm)
NATM

Fine
-18.03Fine-16.66

MediumMedium
-17.47-18.11

Coarse-17.98

CoarseFine-18.46-19.01

Medium-18.54MC

CoarseMCC-19.53Medium
-26.42HS

Fine

Coarse-27.56MC

Fine

MediumCoarseMCC

Fine

MediumCoarse

HS

TBM

0
-5
-10

-23.42-20.75-22.51-26.52-30-20.98-25-23.72-20-19.22-15

Figure 4.21: Effect on Maximum Settlement due to Refinements of Meshing forDifferent Models
104

It can be said from the above results that for the finer meshes, the settlement values are lower
than the coarse and medium ones. It can be shown that the variation is more fluctuated for
NATM models than TBM ones. For NATM models, the variation from medium mesh to coarse
or fine mesh is about 10% whereas for TBM models, the variation value is almost 4% only. As
the variation is considerable, medium mesh can be considered for models to save the runningtime.

Validation with Empirical Formulas for Inflexion Points and Maximum
Settlement
Peck (1969) showed that a Gaussian distribution curve provided a reasonable fit to tunnel
induced surface settlements. The value of inflexion point, i, is generally expressed as:𝑖 = 𝑘𝑍0(4.2)

Where Z0 is the tunnel axis depth and K is a dimensionless empirical constant referred to as
the trough width parameter. Values of K for Gaussian curves fitted to surface settlement data
have been found to be close to 0.5 for tunnels in undrained clay, and typically range between
0.25 and 0.45 for tunnels in sands and gravels. Mair (1993) showed that subsurface settlement
troughs in undrained clays can also be fitted well with a Gaussian curve, and that the value ofi decreases approximately linearly with depth at a slope of -0.325.

Figure 4.22: Greenfield Settlement Trough (Peck, 1969)
105

The tunnel excavation methods simulated in PLAXIS 3D and the settlement values from theanalyses are validated with empirical formulas explained in different researches. Theseempirical formulas are applicable for TBM methods only. In numerical analyses, depth
variations (30m, 32m and 35m) and diameter variations (5.0m, 6.0m, 7.0m) have been
considered for TBM method to validate the analysis.
The empirical formula considered for validation are:
SL. No.

Researchers

Empirical Relations𝑖
𝑍0= ( )𝑛 (𝑛 = 0.8 − 1)
𝑅
2𝑅
𝑖
𝑍0
= ( )𝑛 (𝑛 = 0.8)
𝑅
2𝑅

1Peck, 1969

2

Clough & Schmidt, 1981

3

Atkinson & Potts, 1977

𝑖 = 0.25 (1.5𝑍0 + 0.5𝑅)

4

O’Reily & New, 1982

𝑖 = 0.43𝑍0 + 1.1

5Mair & Taylor, 1999

𝑖 = (0.4 − 0.5)𝑍0 + 1.1

Following the empirical formulas, distance of inflexion point from center for different models
at different diameters and depths are calculated and compared with PLAXIS value in Table
4.7. Also, maximum settlement values and settlement values at inflexion point are determinedfrom PLAXIS models. From Figure 4.23 and Figure 4.25, comparison of distance of point of
inflexions from centers calculated from different empirical formulas for different depths anddiameters are emphasized in three graphs for MC, MCC, and HS models respectively.
Transverse settlement trough pattern for the half tunnel segment for three types of models withvariation of depths and radiuses are shown in Figure 4.26 and Figure 4.27 respectively. The
pattern is then compared with the empirical standard Gaussian curve to validate the shape ofthe curve. Effect on maximum settlement at varying depths and radius are emphasized clearlyin Figure 4.28 and Figure 4.29 respectively. Also, effect on distance of inflexion point from
center at varying depths and radius are shown effectively by graphical representation in Figure
4.30 and Figure 4.31 respectively.
According to the empirical formula of different researchers, O’Reily & New relationship has
the best behavior of surface settlement in transverse section which follows the Gaussian
distribution. Based on this assumption, Gaussian curve is fitted to the data monitoring outputs.
106

As a result, the average deviated values between the numerical result for obtaining trough widthparameter, i, and the empirical result of O’Reily & New are obtained as 5.38%, 3.84% and6.39% for MC, MCC and HS models respectively. These deviations are very less than otherempirical relations described in researches. This difference is due to the fact that otherresearchers used the probability function in the estimation of inflexion point location which
may not necessarily fit with the present results.
The transverse profile of the surface settlement of numerical results obtained from the MC,
MCC and HS models are compared with the empirical relationship’s graphs. It can be clearlyseen that results of the MCC model have the best fit to the data points. The MCC model isconsidered to be suitable for this type of clay-based soils. To predict the surface settlement, the
MCC model is proposed in soft clay with a low over consolidation ratio or normal consolidation
similar to the soil in this site. In other words, where the shear modulus is independent of theshear strain, the surface settlement has a wide and shallow profile. Since the over consolidation
clay exhibits non-linear stress strain behavior at the small strain prior to crossing the plastic
yielding, it is very important to consider the behavior of these kinds of soils under small strain
condition. Nevertheless, the shear modulus in the MC model is constant and the shear strain
doesn’t change with shear stress; this is probably the main reason for the difference between
the results. The semi empirical method does not yield a precise prediction of ground settlement
and this approach must be used only to give a general overview to designers. The
implementation of MCC model is suggested in clayey soils as it has a relatively precise
prediction of the surface displacement in clayey soil (normally consolidated or low OCR
value). At depth, or as volume loss is increased, the fit of the Gaussian curve becomes lessgood.
Tunnel diameter has significant effect on the magnitude of the ground settlement, as a smaller
tunnel tends to cause lesser ground settlements than larger tunnel. Distance of inflexion pointfrom center tends to be smaller for increasing tunnel diameter. The stress redistribution fromoverburden soil must be the reason for the possibility of influencing zone below the tunnel
especially of smaller diameter. This effect reduces when the tunnel diameter increases. The
self-weight of the tunnel and grains redistribution may increase the settlement in loose sandbelow the bottom of the tunnel when the tunnel diameter increases.
And for larger depth, maximum settlement decreases than smaller depth as well as distance of
inflexion point from center decreases for increasing tunnel diameter. This variation in107settlement due to the depth variation is because in elastic homogeneous medium, the upward
movement of the soil is due to relief effect of the excavated soil above the tunnel but thismovement decreases as depth increases. As the soil is remote from concentration of loading,the settlement value is larger in lesser depth and smaller in greater depth.
It can be concluded after analyzing the results that the total settlement decreases with anincrease in depth of the tunnel (almost 11% decrement for every 5m increment of depth) andincreases with an increase in diameter (almost 20% increment for every 1m increment of
diameter). Increasing the TBM depth results to increase around 4% in distance of inflexion
point from center whereas increasing in radius results to decrease around 5% in inflexion point
distance from center of the tunnel.
Table 4.7: Calculation of distance of Inflexion Point from center and Settlement
values (maximum and at inflexion point) for different models, diameters and depths
Empirical
FormulaResearchers

Depth
, Z0
(m)

Radiu
Distance ofDistance ofMaximum
Deviateds, RInflexion
Inflexion Point
Settlement
value (%)(m)
Point (m)from PLAXIS (m)(mm)
Depth considered as 30.0m, Radius considered as 3.50m

Settlement at
Inflexion Point(mm)

Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

30

3.50

8.73

16.57

70.44

-20.85

-6.00

30

3.50

8.73

16.57

39.81

-20.85

-6.00

30

3.50

11.69

16.57

19.40

-20.85

-6.00

30

3.50

14.00

16.57

3.45

-20.85

-6.00

30

3.50

12.00

16.57

17.24

-20.85-6.00

MC ModelDepth considered as 32.0m, Radius considered as 3.50m
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

32

3.50

9.19

15.85

71.16

-19.53

-6.00

32

3.50

9.19

15.85

42.02

-19.53

-6.00

32

3.50

12.44

15.85

21.53

-19.53

-6.00

32

3.50

14.86

15.85

6.25

-19.53

-6.00

32

3.50

12.80

15.85

19.24

-19.53-6.00

Depth considered as 35.0m, Radius considered as 3.50m
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

35

3.50

9.87

14.50

69.82

-18.11

-6.00

35

3.50

9.87

14.50

40.42

-18.11

-6.00

35

3.50

13.56

14.50

18.15

-18.11

-6.00

35

3.50

16.15

14.50

2.53

-18.11

-6.00

35

3.50

14.00

14.50

15.51

-18.11-6.00

Depth considered as 35.0m, Radius considered as 3.00m

108Empirical
FormulaResearchers
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

Depth
, Z0
(m)
35

Radiu
s, R
(m)
3.00

Distance ofInflexion
Point (m)9.87

Distance ofInflexion Point
from PLAXIS (m)
16.99

65.67

Maximum
Settlement
(mm)
-16.7

Settlement at
Inflexion Point
(mm)
-5.00

35

3.00

9.87

16.99

41.89

-16.7

-5.00

35

3.00

13.50

16.99

20.54

-16.7

-5.00

35

3.00

16.15

16.99

4.94

-16.7

-5.00

35

3.00

14.00

16.99

17.60

-16.7

-5.00

Deviatedvalue (%)

Depth considered as 35.0m, Radius considered as 2.50m
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

35

2.50

9.87

17.89

60.87

-14.27

-4.00

35

2.50

9.87

17.89

44.82

-14.27

-4.00

35

2.50

13.44

17.89

24.89

-14.27

-4.00

35

2.50

16.15

17.89

9.73

-14.27

-4.00

35

2.50

14.00

17.89

21.74

-14.27-4.00

Depth considered as 30.0m, Radius considered as 3.50m
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

30

3.50

8.73

16.27

70.00

-19.66

-9.00

30

3.50

8.73

16.27

38.90

-19.66

-9.00

30

3.50

11.69

16.27

18.18

-19.66

-9.00

30

3.50

14.00

16.27

1.99

-19.66

-9.00

30

3.50

12.00

16.27

15.99

-19.66-9.00

MCC Model

Depth considered as 32.0m, Radius considered as 3.50m
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

32

3.50

9.19

15.19

69.91

-18.93

-8.00

32

3.50

9.19

15.19

39.51

-18.93

-8.00

32

3.50

12.44

15.19

18.13

-18.93

-8.00

32

3.50

14.86

15.19

2.18

-18.93

-8.00

32

3.50

12.80

15.19

15.74

-18.93-8.00

Depth considered as 35.0m, Radius considered as 3.50m
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

35

3.50

9.87

14.28

69.27

-17.47

-8.00

35

3.50

9.87

14.28

39.32

-17.47

-8.00

35

3.50

13.56

14.28

16.64

-17.47

-8.00

35

3.50

16.15

14.28

0.74

-17.47

-8.00

35

3.50

14.00

14.28

13.95

-17.47-8.00-16.25-7.00

Depth considered as 35.0m, Radius considered as 3.00m
Peck, 1969

35

3.00

9.87

17.01

65.71

109

Empirical
FormulaResearchers
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

Depth
, Z0
(m)

Radiu
s, R
(m)

Distance ofInflexion
Point (m)Distance ofInflexion Point
from PLAXIS (m)Deviatedvalue (%)

Maximum
Settlement(mm)

Settlement at
Inflexion Point
(mm)

35

3.00

9.87

17.01

41.96

-16.25

-7.00

35

3.00

13.50

17.01

20.63

-16.25

-7.00

35

3.00

16.15

17.01

5.06

-16.25

-7.00

35

3.00

14.00

17.01

17.70

-16.25-7.00

Depth considered as 35.0m, Radius considered as 2.50m
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

35

2.50

9.87

17.79

60.65

-13.95

-6.00

35

2.50

9.87

17.79

44.50

-13.95

-6.00

35

2.50

13.44

17.79

24.47

-13.95

-6.00

35

2.50

16.15

17.79

9.22

-13.95

-6.00

35

2.50

14.00

17.79

21.30

-13.95-6.00

Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

30

3.50

8.73

16.92

70.67

-19.57

-9.00

30

3.50

8.73

16.92

40.27

-19.57

-9.00

30

3.50

11.69

16.92

20.00

-19.57

-9.00

30

3.50

14.00

16.92

4.18

-19.57

-9.00

30

3.50

12.00

16.92

17.86

-19.57-9.00

Depth considered as 30.0m, Radius considered as 3.50m

HS ModelDepth considered as 32.0m, Radius considered as 3.50m
Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

32

3.50

9.19

15.61

70.72

-18.77

-9.00

32

3.50

9.19

15.61

41.14

-18.77

-9.00

32

3.50

12.44

15.61

20.34

-18.77

-9.00

32

3.50

14.86

15.61

4.82

-18.77

-9.00

32

3.50

12.80

15.61

18.02

-18.77-9.00

Peck, 1969
Clough &Schmidt,
1981
Atkinson &Potts, 1977
O'Reilly &New, 1982
Mair &
Taylor, 1999

35

3.50

9.87

14.61

70.45

-18.54

-9.00

35

3.50

9.87

14.61

41.65

-18.54

-9.00

35

3.50

13.56

14.61

19.84

-18.54

-9.00

35

3.50

16.15

14.61

4.55

-18.54

-9.00

35

3.50

14.00

14.61

17.25

-18.54-9.00

Depth considered as 35.0m, Radius considered as 3.50m

Depth considered as 35.0m, Radius considered as 3.00m
Peck, 1969
Clough &Schmidt,
1981

35

3.00

9.87

17.44

66.55

-17.04-10.00

35

3.00

9.87

17.44

43.39

-17.04-10.00110

Distance ofInflexion Point from Center (m)
8

6

4

2

10

12

PLAXIS 3D_35m depth_3.50m radius, 14.50

PLAXIS 3D_35m depth_3.00m radius, 16.99

PLAXIS 3D_35m depth_2.50m radius, 17.89

PLAXIS 3D_32m depth_3.50m radius, 15.85

PLAXIS 3D_30m depth_3.50m radius, 16.57

Mair & Taylor_35m depth_3.50m radius, 14.00

Mair & Taylor_35m depth_3.00m radius, 14.00

Mair & Taylor_35m depth_2.50m radius, 14.00

Mair & Taylor_32m depth_3.50m radius, 12.80

Mair & Taylor_30m depth_3.50m radius, 12.00

O'Reily & New_35m depth_3.50m radius, 16.15

O'Reily & New_35m depth_3.00m radius, 16.15

O'Reily & New_35m depth_2.50m radius, 16.15

O'Reily & New_32m depth_3.50m radius, 14.86

O'Reily & New_30m depth_3.50m radius, 14.00

Atkinson & Potts_35m depth_3.50m radius, 14.50

Atkinson & Potts_35m depth_3.00m radius, 13.50

Atkinson & Potts_35m depth_2.50m radius, 13.44

Atkinson & Potts_32m depth_3.50m radius, 12.44

Atkinson & Potts_30m depth_3.50m radius, 11.69

Clough & Schmidt_35m depth_3.50m radius, 9.87

Clough & Schmidt_35m depth_3.00m radius, 9.87

Clough & Schmidt_35m depth_2.50m radius, 9.87

Clough & Schmidt_32m depth_3.50m radius, 9.19

Clough & Schmidt_30m depth_3.50m radius, 8.73

Peck_35m depth_3.50m radius, 9.87

Peck_35m depth_3.00m radius, 9.87

Peck_35m depth_2.50m radius, 9.87

Peck_32m depth_3.50m radius, 9.19

Peck_30m depth_3.50m radius, 8.73

20Comparison of Point of Inflexions for MC Models for Different Depths and Radiuses

18

16

14

0

Figure 4.23: Comparison of Distance of Inflexion Points for MC Models for Different Depths (30m, 32m, 35m) and Different Radiuses(2.5m, 3m, 3.5m)
112Distance of Inflexion Point from Center (m)
8

6

4

2

10

12

PLAXIS 3D_35m depth_3.50m radius, 14.28

PLAXIS 3D_35m depth_3.00m radius, 17.01

PLAXIS 3D_35m depth_2.50m radius, 17.79

PLAXIS 3D_32m depth_3.50m radius, 15.19

PLAXIS 3D_30m depth_3.50m radius, 16.27

Mair & Taylor_35m depth_3.50m radius, 14.00

Mair & Taylor_35m depth_3.00m radius, 14.00

Mair & Taylor_35m depth_2.50m radius, 14.00

Mair & Taylor_32m depth_3.50m radius, 12.80

Mair & Taylor_30m depth_3.50m radius, 12.00

O'Reily & New_35m depth_3.50m radius, 16.15

O'Reily & New_35m depth_3.00m radius, 16.15

O'Reily & New_35m depth_2.50m radius, 16.15

O'Reily & New_32m depth_3.50m radius, 14.86

O'Reily & New_30m depth_3.50m radius, 14.00

Atkinson & Potts_35m depth_3.50m radius, 13.56

Atkinson & Potts_35m depth_3.00m radius, 13.50

Atkinson & Potts_35m depth_2.50m radius, 13.44

Atkinson & Potts_32m depth_3.50m radius, 12.44

Atkinson & Potts_30m depth_3.50m radius, 11.69

Clough & Schmidt_35m depth_3.50m radius, 9.87

Clough & Schmidt_35m depth_3.00m radius, 9.87

Clough & Schmidt_35m depth_2.50m radius, 9.87

Clough & Schmidt_32m depth_3.50m radius, 9.19

Clough & Schmidt_30m depth_3.50m radius, 8.73

Peck_35m depth_3.50m radius, 9.87

Peck_35m depth_3.00m radius, 9.87

Peck_35m depth_2.50m radius, 9.87

Peck_32m depth_3.50m radius, 9.19

Peck_30m depth_3.50m radius, 8.73

Comparison of Point of Inflexions for MCC Models for Different Depths and Radiuses

20

18

16

14

0

Figure 4.24: Comparison of Distance of Inflexion Points for MCC Models for Different Depths (30m, 32m, 35m) and Different Radiuses(2.5m, 3m, 3.5m)
113

Distance of Inflexion Point from Center (m)
8

6

4

2

10

12

PLAXIS 3D_35m depth_3.50m radius, 14.61

PLAXIS 3D_35m depth_3.00m radius, 17.44

PLAXIS 3D_35m depth_2.50m radius, 18.15

PLAXIS 3D_32m depth_3.50m radius, 15.61

PLAXIS 3D_30m depth_3.50m radius, 16.92

Mair & Taylor_35m depth_3.50m radius, 14.00

Mair & Taylor_35m depth_3.00m radius, 14.00

Mair & Taylor_35m depth_2.50m radius, 14.00

Mair & Taylor_32m depth_3.50m radius, 12.80

Mair & Taylor_30m depth_3.50m radius, 12.00

O'Reily & New_35m depth_3.50m radius, 16.15

O'Reily & New_35m depth_3.00m radius, 16.15

O'Reily & New_35m depth_2.50m radius, 16.15

O'Reily & New_32m depth_3.50m radius, 14.86

O'Reily & New_30m depth_3.50m radius, 14.00

Atkinson & Potts_35m depth_3.50m radius, 13.56

Atkinson & Potts_35m depth_3.00m radius, 13.50

Atkinson & Potts_35m depth_2.50m radius, 13.44

Atkinson & Potts_32m depth_3.50m radius, 12.44

Atkinson & Potts_30m depth_3.50m radius, 11.69

Clough & Schmidt_35m depth_3.50m radius, 9.87

Clough & Schmidt_35m depth_3.00m radius, 9.87

Clough & Schmidt_35m depth_2.50m radius, 9.87

Clough & Schmidt_32m depth_3.50m radius, 9.19

Clough & Schmidt_30m depth_3.50m radius, 8.73

Peck_35m depth_3.50m radius, 9.87

Peck_35m depth_3.00m radius, 9.87

Peck_35m depth_2.50m radius, 9.87

Peck_32m depth_3.50m radius, 9.19

Peck_30m depth_3.50m radius, 8.73

20Comparison of Point of Inflexions for HS Models for Different Depths and Radiuses

18

16

14

0

Figure 4.25: Comparison of Distance of Inflexion Points for HS Models for Different Depths (30m, 32m, 35m) and Different Radiuses(2.5m, 3m, 3.5m)
114

CL
0

Settlement Curve at Transverse Section with variation of depth (m)
2

4

6

8

10

12

14

16

18

20

22

24

0
-2
-4
-6

Settlement (m)

-8
-10
-12
-14
-16
-18
-20

-22

Distance from center (m)MC_30mMC_32mMC_35m

MCC_30m

MCC_35m

HS_30mHS_32mHS_35m

MCC_32m

Figure 4.26: Transverse Settlement Trough Pattern with variation of depth (30m, 32m, 35m) for MC, MCC and HS Models
115

CL
0

Settlement at Transverse Section with variation of radius (m)
2

4

6

8

10

12

14

16

18

20

22

24

26

28

0.00
-2.00
-4.00

Settlement (m)

-6.00
-8.00
-10.00-12.00-14.00-16.00-18.00-20.00Distance from center (m)MC_2.50m

MC_3.00m

MC_3.50m

MCC_2.50m

MCC_3.50m

HS_2.50m

HS_3.00m

HS_3.50m

MCC_3.00m

Figure 4.27: Transverse Settlement Trough Pattern with variation of radius (2.50m, 3.0m, 3.50m) for MC, MCC and HS Models
116Effect on Maximum Settlement for varying depth-15

Settlement (mm)

-16
-17
-18
-19
-20
-21
-22
MC
MCC
HS

30
-20.85-19.66-19.5732-19.53-18.93-18.7735-18.11-17.47-18.54

Depth (m)Figure 4.28: Effect on Maximum Settlement for increasing of depth (30m, 32m and35m)

Effect on Maximum Settlement for varying radius-12

Settlement (mm)

-13
-14
-15
-16
-17
-18

-19
MC
MCC
HS

2.50
-14.27-13.95-14.483.00-16.70-16.25-17.043.50-18.11-17.47-18.54

Depth (m)Figure 4.29: Effect on Maximum Settlement for increasing of radius (2.50m, 3.00m
and 3.50m)
117Inflexion Point Distance from Center (m)Effect on Inflexion Point for varying depth

12
13
14
15
16

17
18
MC
MCC
HS

30
16.57
16.27
16.92

32
15.85
15.19
15.61

35
14.50
14.28
14.61

Depth (m)Inflexion Point Distance from Center (m)Figure 4.30: Effect on Inflexion Point for increasing of depth (30m, 32m and 35m)

Effect on Inflexion Point for varying radius
20

18

16

14

12
MC
MCC
HS

2.50
17.89
17.79
18.15

3.00
16.99
16.15
17.44

3.50
14.50
14.28
14.61

Radius (m)Figure 4.31: Effect on Inflexion Point for increasing of radius (2.50m, 3.00m and3.50m)
118

Validation with Empirical Formulas for Vertical Settlement
For drained soils, such as sands and gravels, the volume of the soil is not constrained, andshearing causes contraction and dilation to occur. This causes the volume of the settlement
trough, Vs, to vary with depth (Vs,s ≠ Vs,z), and means that an assessment of volume loss
based on surface measurements will not provide an entirely accurate measurement ofsubsurface volume loss. In order to analyze trends in settlement trough shape, a curve must be
fitted to settlement data. The use of a curve that gives a good fit to settlement data is importantin order to perform an effective analysis of trough shape, and when evaluating the effect oftunnelling on nearby infrastructure or buildings. It has been reported that the Gaussian curve
does not always provide a good fit to settlement trough data. Jacobsz (2004) used a slightly
different version of the Gaussian curve that, like the Gaussian curve, has two degrees of
freedom, represented by Smax and i. Celestino and Vorster used curves with one additional
degree of freedom compared with the Gaussian curve, thus giving more flexibility to the shapeof the curve.
Vertical settlement values derived from PLAXIS 3D and different empirical formula and also
the deviation percentages for both NATM and TBM methods are shown in Table 4.8. In Figure
4.32, these values are depicted in graphical representation. Maximum settlements for NATM
and TBM methods from PLAXIS 3D for different types of models are compared in Figure
4.33. Transverse settlement trough curves for both methods considering 35m depth and 7m
diameter derived from PLAXIS 3D are shown in Figure 4.34. Longitudinal settlements andlateral settlements for both methods from PLAXIS 3D are emphasized in Figure 4.35 andFigure 4.36.
It can be evaluated from the result that the deviation percentages of vertical settlement fromPLAXIS with Peck, Peck & Schmidt and Jacobsz formula are almost 10% and 34% for TBM
and NATM respectively. Chow’s formula shows much less values than other empiricalformulas (Peck, Peck & Schmidt, and Jacobsz), which can indicate that this formula is not
appropriate for clayey soil. Also, the Jacobsz formula (2004) shows a good agreement andapproximately close value compared to the settlement values obtained from PLAXIS 3D (for
NATM, the variation is about 2 ~ 16% and for TBM 3 ~ 10%.
From comparison of longitudinal and lateral settlement, it can be shown that NATM method
shows more settlement (10 to 30% more) than TBM method as it includes blast techniquewhich induce more ground surface variation than TBM machine advancement, especially in
119soft soil. In settlement at transverse sections for both NATM and TBM, MCC model shows thebest fit curve in Gaussian distribution.

TBM

Deviation of Uz value from

U at Inflexion Point (mm)formula (mm)Uz according to Jacobsz

Schmidt formula (mm)Uz according to Peck

PLAXIS (m)Uz according to Peck &Vertical Settlement, Uz

Longitudinal Settlement,

Lateral Settlement, Ux

HS-20.98 -2.754-11.24-15.12 16.58 -12.50 -12.71 -14.83

-1.71

-9.00

17.343

PLAXIS (%)

Empirical formula to24.069formula (mm)-8.00

Uz according to Chow

-1.94

9.85

formula (mm)-9.35 -16.01 -18.68

Inflexion Point from

-12.31(mm)-13.11Ux (mm)-26.42 -5.818(mm)

Maximum Settlement,

MC

Smax (mm)Model Type

NATM

Method Type

Table 4.8: Comparison of Settlements of PLAXIS with Empirical Formulas (for Depth
35m and Diameter 7m)

MCC -22.51-7.36-10.34-16.61 13.16 -10.58 -13.64 -15.91-1.83 -11.00

36.280MC-18.11

-0.35

-8.67

-14.07 15.19 -12.49 -10.97 -12.80

-2.09

-6.00

11.218HS-18.54

-0.85

-9.53

-13.53 16.92 -12.73 -11.24 -13.11

-2.09

-9.00

5.896

MCC -17.47

-0.62

-7.98

-13.99 18.15 -12.29 -10.59 -12.35

-2.09

-8.00

12.135120

Settlement (mm)
-2.00

-4.00

-6.00

-10.00

NATM_MC_Peck, -16.01

NATM_MC_Peck & Schmidt, -9.35

NATM_MC_Chow, -1.94

NATM_MCC, -16.61

NATM_MCC_Jacobsz, -15.91

NATM_MCC_Peck, -13.64

NATM_MCC_Peck & Schmidt, -10.58

NATM_MCC_Chow, -1.83

NATM_HS, -15.12

NATM_HS_Jacobsz, -14.83

NATM_HS_Peck, -12.71

TBM_MCC, -13.99

TBM_MCC_Peck & Schmidt, -12.29

TBM_MCC_Jacobsz, -12.35

TBM_MCC_Peck, -10.59

TBM_MCC_Chow, -2.09

TBM_MC, -14.07

TBM_MC_Jacobsz, -12.80

TBM_MC_Peck, -10.97

TBM_MC_Peck and Schmidt, -12.49

TBM_MC_Chow, -2.09

TBM_HS, -13.53

TBM_HS_Jacobsz, -13.11

TBM_HS_Peck & Schmidt , -12.73

TBM_HS_Peck, -11.24

TBM_HS_Chow, -2.09

NATM_MC, -12.31

NATM_MC_Jacbosz, -18.68-12.00

NATM_HS_Peck & Schmidt, -12.50-8.00

NATM_HS_Chow, -1.71

Comparison of Vertical Settlements from PLAXIS and Empirical Formulas

0.00-14.00-16.00-18.00-20.00Figure 4.32: Comparison of Vertical Settlements of Different Empirical Formulas for both NATM and TBM methods (for different
models)121Comparison of Maximum Settlements for NATM and TBM from PLAXIS
0

-5

-10

-15

-20

-25

-30
NATM_HS
NATM_MCC
NATM_MCTBM_HS
TBM_MCC
TBM_MC1-20.98-22.51-26.42-18.54-17.47-18.11Figure 4.33: Comparison of Maximum Settlement for NATM and TBM Methods from PLAXIS (for different types of models)122

Settlement at Transverse Section for NATM and TBM
0.00
-2.00
-4.00
-6.00
-8.00

Settlement (m)-10.00-12.00-14.00-16.00-18.00-20.00-22.00-24.00-26.00-28.00Distance from center (m)NATM_MCTBM_MC

NATM_MCCTBM_MCC

NATM_HSTBM_HS

Figure 4.34: Settlement at Transverse Section for both NATM and TBM methods considering 35m depth and 3.50m radius (from
PLAXIS)
123

Comparison of Longitudinal Settlements from PLAXIS
0
-1
-2

-6
-7

-13.11

-7.98

-9.53

-10.34

Settlement (mm)-5-11.24

-4

-8.67

-3

NATM_MCNATM_HS
NATM_MCC
TBM_HS-8

TBM_MC-9

TBM_MCC

-10
-11
-12
-13
-14

Figure 4.35: Longitudinal Settlements for both NATM and TBM methods considering 35m depth and 3.50m radius (from PLAXIS)

124

Comparison of Lateral Settlements from PLAXIS

-0.85

-0.35

-1

-0.62

0

-3

-2.754

Settlement (mm)-2
NATM_MCC
NATM_MCNATM_HS-4

TBM_HS
TBM_MCC-5

TBM_MC-5.818

-6

-8

-7.36

-7

Figure 4.36: Lateral Settlements for both NATM and TBM methods considering 35m depth and 3.50m radius (from PLAXIS)

125

Summaryi.

The mass rapid transit Line -1 is going to be established in underground and elevatedportions. In this report, only underground section is focused whose length isapproximately 14.8 km. The site area is basically from Pleistocene Madhupur clay and
Holocene sediments with intermediate to high plastic clay and overlain by medium tocoarse sand. The study area is in seismic zone II and it is mostly consisted of clayeysoil than sandy soils. The borehole location is under Kuril flyover and all of the field
investigation and laboratory tests collected from secondary sources. From the test
results, subsoil stratifications are prepared.

ii.

Numerical models are prepared in PLAXIS 3D for NATM and TBM methods for threedifferent types of models (MC, MCC, and HS), where NATM models are done fordepth 35m and 7m diameter, but TBM models are done for depth 30m, 32m, and 35m
and for diameter of 5m, 6m, and 7m. Construction sequences for both methods areincluded in modelling.

iii.

For practical application and model validation, realistic soil constitutive models need
to be chosen which can simulate the nonlinear and stress dependent characteristics ofsoil. For FEM model, MC, MCC and HS model are chosen for simulating soil behavior
with real time field and laboratory test data. The input parameters are determined fromlaboratory test results and empirical correlations. The empirical and analytical results
are validated with the FEM model using the soil and structural parameters in PLAXIS
3D for MRT Line-1 tunnel alignment. Specific borehole data (BH-24, under the Kuril
flyover) is chosen to simulate the soil structure interaction.

iv.

The effect in maximum total displacements is computed for different types of mesh fordifferent conditions of both NATM and TBM methods and for different models before
starting the comparative analysis. For NATM models, the variation from medium meshto coarse or fine mesh is about 10% whereas for TBM models, the variation value isalmost 4% only. As the variation is considerable, medium mesh can be considered formodels to save the running time.

v.

From the comparison between the results of PLAXIS 3D and empirical formulas
derived from different researchers for MRT Line 1, it can be said that the average
deviated values between the numerical result for obtaining trough width parameter, i,and the empirical result of O’Reily & New are obtained as 5.38%, 3.84% and 6.39%
156

for MC, MCC and HS models respectively. These deviations are very less than otherempirical relations described in researches.
vi.

The transverse profile of the surface settlement of numerical results obtained from theMC, MCC and HS models are compared with the empirical relationship’s graphs. It
can be clearly seen that results of the MCC model have the best fit to the data points.

vii.

After analyzing the relationship between settlement and depth or radius and also,
between the location of inflexion point and depth or radius, it can be concluded to statethat the total settlement decreases with an increase in depth of the tunnel (almost 11%
decrement for every 5m increment of depth) and increases with an increase in diameter(almost 20% increment for every 1m increment of diameter). Increasing the TBM depth
results to increase around 4% in distance of inflexion point from center whereas
increasing in radius results to decrease around 5% in inflexion point distance from
center of the tunnel.

viii.

Comparing the vertical settlement found from PLAXIS 3D and various empiricalformula given by different researchers, it can be said that the deviation percentages ofvertical settlement from PLAXIS with Peck, Peck & Schmidt and Jacobsz formula arealmost 10% and 34% for TBM and NATM respectively.

ix.

The Jacobsz formula (2004) shows a good agreement and approximately close value
compared to the settlement values obtained from PLAXIS 3D (for NATM, the variation
is about 2 ~ 16% and for TBM 3 ~ 10%).

x.

From comparison of longitudinal and lateral settlement found from PLAXIS 3D, it canbe shown that NATM method shows more settlement (10 to 30% more) than TBM
method. As the NATM method includes blast technique, it may induce more vibrating
effect than TBM method which indicates this variation in settlement calculation.

xi.

For Dhaka city, NKDOS consortium proposed TBM-EPB machine for MRT Line 1
tunnel construction. It can be said from this study that, for our city TBM should performbetter than NATM method considering the settlement parameter and average soil
condition.

157

PART-III

NUMERICAL ANALYSES OF A MAT BELOW A
NUCLEAR POWER REACTOR UNDERSEISMIC LOADINGBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Md. Shariful Islam
Mehedi Ahmed AnsaryChapter One
INTRODUCTION
1.1 General
Bangladesh is the largest delta island in the world, is formed predominantly by alluvial
sediments. Development of heavy foundation like nuclear power reactor in this soils arechallenging for the strain-sensitiveness and high seasonal ground water movement.
There are various suitable modern technologies of soil improvement; such as pilefoundation, the technology of jet grouting, the technology of deep vibration
replacement and the technology of deep soil mix for the purposes of improving
deformation properties of soils for heavy earth foundation. In case of pile foundation
shaking-induced liquefaction and associated lateral spreading has caused extensive
damage due to lack of efficient prediction for estimating seismic response of piles andsoils in liquefied and laterally spreading ground.
Currently, Bangladesh Government is implementing country’s first Nuclear Power
Plant project in the history of Bangladesh, which is located in Rooppur, Pabna. Rooppur
is located beside the Padma river. Nuclear Power Reactor is heat source of Nuclear
Power Plant (NPP) in which the control of nuclear fission reaction has taken place andtransformed enormous heat as thermal power from nuclear fuel. As of 2018, 451
nuclear power reactors are in operation and 55 reactors under construction in 33
countries as per International Atomic Energy Agency (IAEA). Among the 33 countries,
Bangladesh is an embarked country in construction of Nuclear Power Reactors of
VVER technology. Bangladesh has started the nuclear construction for two-reactor
power unit 2x1200 MWe in Rooppur, Ishwardi, Pabna. Site location of Rooppur
Nuclear Power Plant is shown in Figure-1.1.
Bangladesh is surrounded by regions of high seismicity like the Himalayan Arc and theShillong plateau in the north, the Burmese Arc-Arakan Yonia anticlinoriurrt in the eastand the complex Naga-Disang-Haflong thrust zones in the northeast. It is also the site of
the major Dauki fault system along with numerous subsurface active faults and aflexure zone to be called as Hinge zone. These weak zones are believed to provide with
the necessary planes for movements within the basin area. Bangladesh experienced
158

several historical great earthquakes during last century and has been affected by small
earthquakes occasionally. The epicenters of large earthquakes lying beyond the bonierof Bangladesh equally effect the country for its morphotectonic continuity. The
movement in the Dauki fault system influences the present configuration of the Surmabasin and plays a vital role in the seismicity of the northern region of Bangladesh. The
seismicity of Bangladesh is deeply related with tectonic behavior in and around
Bangladesh which is caused by the subduction of the Indian plate below the Tibet
subplate in the north.

Figure 1.1: Site Location of Rooppur Nuclear Power Plant (Google Earth location map)
Heavy, durable and stable foundation is one of the key concerns in nuclear construction
as it is directly related to plant safety. In connection of stable foundation subsurface
investigation at a nuclear power plant site is important at stages of the site evaluation
process. The purpose of this investigation is to provide information or basic data for
decisions on the nature and suitability of the subsurface materials for constructing plantfoundation. Bangladesh have already been faced four major earthquakes between 7-8.5
Mw. So, there is a threat for nuclear power plant in Bangladesh. The subsoil
investigations, geotechnical, site specific seismic hazard assessment are the specificareas for major consideration for the selection of the site.

159

According to the seismic zoning map Bangladesh is divided in to zone-1, zone-2 andzone-3. Rooppur site is in zone-3 which is seismically quiet. No indication of surface
faulting around RNPP has been realized. The peak ground acceleration (PGA) isestimated 0.18g for the return period of 2475 years which is much smaller than thedesigned basis PGA values of nuclear reactors. From the seismic hazard analysis andsub-soil investigation, any heavy structure like RNPP with the design basis PGA values
above 0.2g-0.25g could withstand a 7.5-9.5 Mw earthquake and can damage the RNPP
in future.
Nuclear power plant structures are designed to withstand the ground motion caused bymost severe earthquake that is like to be experienced. From historical records of seismic
event in the plant vicinity, the earthquake that would be expected to produce the largest
ground motion at the Power Reactor site is predicted, which is called safe shutdown
earthquake. In this earthquake power reactor can be tripped but the engineered safety
features must be function properly to make plant safe. Furthermore, the plant must be
capable of remaining in full operating condition should a specified “operating basis
earthquake” be experienced. In developing the design necessary to meet theserequirements, dynamic analysis based on expected ground acceleration spectra isapplied to those components and structures (called class I). The proposed lay-out for
construction of Rooppur Nuclear Power Plant has been shown in Figure-1.2.
Numerical analysis is a proven technique for visualization the geotechnical problems
and the settlement of building or structures. Numerical analysis can deal both thegeotechnical and structural aspect such as soil properties, structures and construction
sequences of mat foundation placed on improved or unimproved soil. In this research, amat foundation model of a nuclear reactor building is used for evaluating the status of
unimproved and improved soil under static and dynamic (seismic) loading using Plaxis
3D software.

3

Figure 1.2: Lay-out of Rooppur Nuclear Power Plant (Rooppur NPP FCD Publication,
2017)
1.2 Objectives and possible outcomes
The objectives and possible outcomes of this research are mentioned below:
1. To conduct numerical analysis of a mat foundation on unimproved/natural soilof a nuclear power reactor under static and dynamic loads for getting thedeformation results
2. To conduct numerical analysis of a mat foundation on improved soil of a
nuclear power reactor under static and dynamic loads for getting thedeformation results.
3. To compare results between unimproved and improvement soil.

4

produce relatively uniform block of modified soil, the establishment of secant soilcement piles is implied. This method provides the reliable possibility of uniform block
creation, significant soil deformation properties improvement and prevention of soilliquefaction over the depth of the improved soil interval.
Furthermore, the WSM technology implies the usage of drilling rods with the length up
to 20 m. After reaching this length the additional operation is required – up building ofdrilling rods length with connection of them that can significantly affect the
productivity. At the further design stages the technology is chosen for the maximal
productivity, i.e. the making of the auxiliary construction pits if necessary. Between thebuildings the movement joints are implied in order to prevent uncontrolled cracks
formation due to various stress-strain states of improved soil blocks under different
structures during construction and in the final state.

Chapter Three
DATA COLLECTION BEFORE AND AFTER GROUNDIMPROVMENT
3.1 Introduction
In this chapter, the properties of the soil parameters of existing natural soil from field
and laboratory tests are discussed. The first nuclear power plant (NPP) of Bangladesh is
the Rooppur NPP which is under construction. For this research works all data werecollected from Rooppur NPP site. The Data consists of angle of internal friction (φ),
cohesion (c’), Young’s Modulus (E), Density (γ), unit weight and Poisson’s ratio ν,
permeability coefficient (k), Secant Modulus of Elasticity, E
Elasticity, E, Oedometer Modulus of, Unloading/Reloading Modulus of Elasticity, Eur are collected andderived from empirical formulas.

3.2 Engineering-Geological Conditions of the Rooppur NPP Site
3.2.1 Geomorphological Characteristics
Geomorphology of the territory of Bangladesh is presented mainly with alluvial plains.
Three main geomorphological types of relief are distinguished:73

- Hills that occupy 12.5% of the territory of the country generally located in eastern andnorth-eastern parts of Bangladesh. Hills are composed of Neogene-Paleogene
sandstones and mudstones;- Uplands or so-called terraces comprising 8 % of the territory. These are Madhupur,
Barind and Lalmay Highs composed of reddish and dark-brown clayey deposits of the
Pleistocene age;
- Plains occupying 80 % of the territory: piedmont plains, alluvial plains and deltaic
dales. Deposits are presented by disperse sandy and clayey soils.
The geomorphological scheme of Bangladesh is shown in Figure 3.1. The site is locatedon the east bank of the Ganges River (which is known as the Padma River in
Bangladesh). The survey site is a plain locality, the ground absolute elevation varies
from 13.96 m to 15.29 m from the sea level. The landscape is presented by chains ofsmall hills, low lands and channels. The relief is locally irregular alongside the present
and former river courses, comprising a rapidly alternating series of linear low ridges
and depressions (Oxbow lake). Clayey soils prevail in depressions, loamy soils (in someplaces sandy) are present at ridge back.

74

Figure 3.1: Geomorphological map of Bangladesh

3.2.2 Drilling and Digging Works
Drilling were be taken up to exactly define geological cross-section parameters. Field
study of soil properties has been carried out to determine hydrogeological parameters of75

aquifiers and aeration zone, to perform geophysical survey, to take soil and water
samples, to determine groundwater depth and to level. Drilling was carried out using
cable-tool drilling method by GY-50, TBM-88 and DANDO BEOTEC 2 drilling tools.
Soils samples were fully collected in course of drilling for laboratory tests, andhydrological observations were performed.
Soil samples were collected from every lithological difference at 2 m interval. On
completion of drilling works boreholes were abandoned via backfilling and marks(benchmarks) with borehole No. indicated were installed on borehole drilling spot. In
total 32 boreholes were drilled using cable-tool method (1152.5 running m). Location of
boreholes is shown at the Map shown in Figure 3.2. Test excavations had dimensions of2 x 2 m with depth of about 3.0 m, test pits were up to 0.6 m deep. In total 12 test
excavations and 10 test pits were done at the NPP site.
3.2.3 Borehole Logs and Properties of SoilAmong boreholes, borehole no. 1, 5 and 26 are described in Figure- 3.3 to 3.5, which
describe the soil profiles of total depth 30 m, 50 m and 106.5 m respectively. Other 5soil profiles of Borehole Logs are shown in Appendix A.
Soil composition and conditions, strength and deformation properties were studied
during field works (drilling, cone penetration tests, standard penetration tests, pressure
meter (radioactive logging) and laboratory methods. Results of laboratory tests havebeen analyzed, soils were united into engineering geological layers with account ofstratigraphy, genesis and textural and structural features.
Modern Man-made Soils (tQIV) are presented by fine loose in wash sands. As forgrainsize distribution prevailing is fraction with diameter of particles of 0.25 to 0.1 mm(62.7 %). 15 soil samples were studied in the laboratory.

76

Figure 3.3: Borehole No. 1 (Absolute elevation of wellhead 12.6 and total depth 30 m)

78

Figure 3.4: Borehole No. 5 (Absolute elevation of wellhead 15 and total depth 50 m)

79

Figure 3.5: Borehole No. 26 (Absolute elevation of wellhead 14.4 and total depth 106.5m)80Natural moisture content of soils is 0.054 to 0.93 u.f. (average value is W= 0.069 u.f.),density in-situ 1.4 to 1.7 g/cm3 (average value is 1.59 g/cm3), density of soil particles is
2.66 t/m3, porosity ratio is equal to е = 0.823 u.f., moisture content Sr =0.22. Density ofsoil in ultimate-loose and ultimate-compacted structure is in average 1.25 and 1.48
g/cm3. Soil natural friction angle in air-dry state is 39o, under water 31o.
Facies of Flood Plain Eluviated Soils (a(e)QIV) comprises the upper part of the section
down to depth of 0.2 to 2.0 m and is presented by light macropore loams and sandy
loams, solid and semi-solid. 17 soil monoliths were studied in the laboratory. Natural
moisture content of loams is 0.135 to 0.253 (average value is W= 0.209 u.f.), soil
density ρн = 1.61 g/cm3, density of dry soil is ρd = 1.33 g/cm3. Average value ofporosity ratio is above 1 and is equal to е = 1.022 u.f., liquidity index IL= minus 0.30.
As for grain-size distribution in loams prevailing is fraction with diameter of particles
of 0.05 to 0.01 mm. The content of such particles is average to 49, 4%. Content ofclayey particles (less than 0.005 mm) is 11.7 %. According to grain-size distribution
and plasticity index loam is light silty. Moreover, according to grain-size distribution
and plasticity index unundoable loam is heavy silty. Physical properties of sandy loam
were studied for 8 samples. As per results of performed tests natural moisture content offlood-plain sandy loams is W= 0.179 u.f., density in-situ 1.74 g/cm3, density of dry soil
is ρd = 1.48 g/cm3, porosity ratio is equal to е = 0.823 u.f., density of soil particles –2.68 to 2.69 g/cm3 (average value is 2.68 g/cm3). Plasticity index varies from 0.031 to
0.067 u.f., moisture content at the limit of liquidity is WL = 0.273 u.f., moisture content
at the limit of plasticity WP = 0.224 u.f., liquidity index is less than zero.
As for grain-size distribution in sandy loams content of clayey particles (less than 0.005mm) is in average 8.8 %, content of sandy particles is 45.9%, silty particles – 45.3%.
Organic matter percentage in loams and sandy loams is 3.3 to 7.5 % respectively.
Modern Quaternary Alluvial Deposits of the Flood Plain Facies (aprQIV) are presented
by sandy soils and cohesive soils.
Loams are prevailing in cohesive soils of flood-plain alluvium, clays and sandy loams
are much rarer. Loams are of semi-solid and low-plastic consistency. 28 soil monoliths
were studied in the laboratory. Natural moisture content of semi-solid loams is 0.156 to
0.287 (average value is W= 0.247 u.f.), average soil density in-situ ρн = 1.74 g/cm3,
density of dry soil is ρd = 1.40 g/cm3. Average value of porosity ratio is equal to е =81

0.935 u.f., plasticity index IP= 0.093. Natural moisture content of low-plastic loams isin average Wн= 0.297 u.f., average soil density in-situ ρн = 1.88 g/cm3, density of dry
soil is ρd = 1.45 g/cm3. Average value of porosity ratio is equal to е = 0.863 u.f.,plasticity index IP= 0.092.
As for grain-size distribution in semi-solid and low-plastic loams content of clayey
particles (less than 0.005 mm) is 16.4 to 15.7%, content of sandy particles is 29.5…31.7%, silty particles 54.1 to 52.6%. According to grain-size distribution and plasticity
index loam is light silty. Organic matter percentage by two determinations is 5.5 to
6.4% respectively. Sandy loams of flood-plain alluvium are solid (sometimes plastic).
Physical properties of sandy loam were studied for 14 samples. As per results ofperformed tests natural moisture content of sandy loams is W= 0.262 u.f., density insitu 1.77 g/cm3, density of dry soil is ρd = 1.40 g/cm3, density of soil particles 2.68
g/cm3. Moisture content at the limit of liquidity is WL = 0.340 u.f., moisture content at
the limit of plasticity WP = 0.285 u.f. Index of liquidity is IL = 0.42.
As for grain-size distribution in sandy loams content of clayey particles (less than 0.005mm) is in average 8.9 %, content of sandy particles is 42.3%, silty particles 48.8%.
Organic matter percentage by single determination is 6.1%. Clays of flood plain
alluvium are of limited distribution and thickness. Physical properties of clays werestudied for 3 samples. As per results of performed tests natural moisture content ofclays is W = 0.317 to 0.341 u.f. Moisture content at the limit of liquidity is, W L = 0.43
to 0.452 u.f., moisture content at the limit of plasticity, W P = 0.260 to 0.281 u.f., densityof soils in-situ 1.87 to 1.95 g/cm3. Average value of density is ρ = 1.91 t/m3, porosity
ratio is equal to е = 0.901 g/cm3. Average value of soil liquidity index corresponds to
low-plastic consistency, IL= 0.34.
As for grain-size distribution in clays prevailing are silty fractions (55.6%). Weightcontent of clayey particles is 6.5 to 9.0 %. According to grain-size distribution andplasticity index clay is light silty. Sandy layer of modern alluvial deposits of the flood
plain facies is presented by silty and fine loose sands (mostly silty sands).
As for grain-size distribution in fine sands prevailing is fraction of 0.25 to 0.1 mm
diameter of grains (59 % in average). Organic matter percentage is 2.0 to 2.3%.
Medium sands were studied in 120 samples. Natural moisture content is 0.223 u.f.,density of soil particles is 2.65 t/m3. Soil natural friction angle in air-dry state is 36o,82

under water 32o. Density of sands in ultimate-loose and ultimate compacted conditions
is in average 1.35 and 1.62 t/m3. According to results of gamma-gamma density logging
density of medium sands in situ is ρ = 1.96 g/cm3. As for grain-size distribution in
medium sands prevailing is fraction of 0.5 to 0.25 mm diameter (58.8 % in average).
Organic matter content is 1.1 %.
Coarse sands have limited distribution in form of layers and lenses. Density of sands inultimate-loose and ultimate compacted conditions is 1.44 and 1.69 g/cm3. As per data ofgeophysical survey density of coarse sands in-situ is ρ = 2.05 t/m3. Soil natural friction
angle in air-dry state is 37o, under water 33o. As for grain-size distribution in coarse
sands prevailing is fraction of 0.25 to 0.1 mm diameter (52.6% in average). Content ofparticles with diameter of 2 to 1 mm varies from 0.0 to 25.1 % (average value is 0.9%).
Content of fractions with diameter less than 0.1 mm is 4.9 %. Gravel soils contain
44.8% of pebble, 21.3% of gravel and almost no clayey material (less than 3 %).
3.3 Field Geotechnical Soil Survey
3.3.1 Pressuremeter Tests and Analysis of Results
Pressuremeter tests were done at the Rooppur NPP site within the area of the main
structures. In total 43 tests in two 50-m deep boreholes (No 24a and 28a). 21 tests weredone in borehole No 24a. 22 tests were done in borehole No 28a. Tests were be
performed in every lithological difference uncovered starting from depth of 4.0 m to50.0 m. Interval between tests was ~2.0 m.
Tests were conducted by stages (0.25 to 0.05 MPa) with a final load exceeding the totalsoil gravity load at the testing depth. It was required to keep ground pressure in theboreholes during test performance using dense clay drilling mud. All works were donein accordance with GOST 20276-99 named “Soils. Methods for Field Determination ofStrength and Strain Characteristics”. Test results of first two pressuremeter tests ofBorehole No. 28a have been shown in Figure 3.6 and 3.7. Other test results ofpressuremeter tests are given in Appendix B. Results of pressuremeter tests aredescribed in Table 3.1.

83

Figure 3.6: Pressuremeter Test No. 1 and Borehole No. 28a.

Figure 3.7: Pressuremeter Test No. 2 and Borehole No. 28a.

84

Table 3.1: Pressuremeter test Results
Borehole
No.

Depth oftesting

24a
28a
28a

4.0
4.3
6.6

24a
24a
24a
24a
24a
24a
24a
28a
28a
28a
28a
28a
28a
28a
24a
24a
24a
24a
24a
28a
28a
28a
28a
28a
28a
24a
24a
24a
24a
24a
24a
24a
24a
24a
24a
24a
24a
24a
24a
24a

6.5
8.5
10.5
15.0
18.0
20.0
22.0
8.6
10.6
12.6
14.6
16.6
18.6
20.6
13.0
25.0
27.5
30.0
32.0
22.6
25.5
27.6
30.0
32.0
34.0
34.0
36.0
39.0
40.8
42.8
44.8
46.8
49.5
36.0
38.0
40.0
42.8
45.5
47.0
49.5

Name of Soil

Deformation
Normative value ofmodulus E, MPa deformation modulus E, MPa
Deposits of flood plain facies (aprQIV)
Loam
10
7
7
Loam
5
Silty sand77pt
Deposits of channel facies (a QIV)
Silty sand
4
17
23
Silty sand
11
Silty sand
13
Silty sand18
Silty sand
13
Silty sand17
Silty sand20
Silty sand
15
Silty sand18
Silty sand21
Silty sand18
Silty sand
22
Silty sand19
Silty sand21
Fine Sand
16
21
Fine Sand
16
Fine Sand
24
Fine Sand
26
Fine Sand
28
Fine Sand
20
Fine Sand
26
Fine Sand
17
Fine Sand
20
Fine Sand
23
Fine Sand
21
Medium Sand
29
32
Medium Sand
26
Medium Sand
28
Medium Sand
34
Medium Sand
33
Medium Sand
34
Medium Sand
39
Medium Sand
35
Medium Sand
26
Medium Sand
30
Medium Sand
27
Medium Sand
32
Medium Sand
33
Medium Sand
35
Medium Sand3685

3.2 Standard Penetration Tests and Analysis of Results
Standard penetration tests at the Rooppur NPP site were done by following GOST
19912-2001 which refers to “Soils. Field Testing Methods for Cone and Standard
Penetration Tests”. SPT method was applied to modern eluviated soils (a(e)QIV),
modern alluvial deposits of flood plain facies (аprQIV), modern alluvial deposits ofchannel facies (aptQIV). SPT tests were executed at the studied site at 5 points. Depth oftest penetration varies from 12.2 to 17.0 m. Total scope of SPT tests was 70.0 r.m.
Recordings for every point were processed interval-wise (for every lithologicaldifference).

Figure 3.8: Changes of n (blows) and Pd (MPa) by immersion depth of probe H (m)(Results of soil test by dynamic sensing in point no. 2).
Recordings for every point were processed interval-wise (for every lithologicaldifference). Boundaries of lithological differences were taken as per borehole data
drilled in the close vicinity of the SPT point. Value of apparent dynamic resistance pd
was calculated for each stratigraphic lithological layer using formula86

𝑃 = 𝐴 . 𝐾 . 𝐾 . 𝑛 ⁄ℎWhere, A – specific energy of test, for used equipment is equal to 1120 N/cm;
К1 – coefficient considering energy loss during hammer blows and elastic strainof rods (shall be determined using Table 4 from GOST 19912-2012“Soils. Field
test methods by static and dynamic sounding”)
К2 – coefficient considering energy loss due to friction of rods against soil
(should be determined using GOST 19912-2012 “Soils. Field test methods bystatic and dynamic sounding”)
n – number of hummer blows per run;h – probe penetration depth per one run, cm
As per results of SPT tests for eluviated soils and alluvial sands (below 1.0 m depth)
using tables of SP 11-105-97 “Engineering and geological surveys for construction”,
the following was calculated: density, normative values of angle of internal friction (φ)
and deformation modulus (E) (specific cohesion is taken close to zero) and alsoliquefaction potential under dynamic loads. Location of SPT test is shown at the map ofFigure-3.2. Soil resistance depth curves are given in Figure-3.8 for point no. 2. For
other points of SPT test, graphs are presented in Appendix C.
Eluviated soils studied via SPT at the Rooppur NPP site are presented mainly by solidand semi-solid loams and solid sandy loams. Alluvial sandy deposits are presented bysilty and fine sands (rarely medium sands) with various water saturation degree. Resultsof determination of relative dynamic resistance of sandy soils against probe penetration
pd, normative values of deformation modulus and angle of internal friction are given in
Table 3.2. As per results of standard penetration tests sandy soils have the following
density:- Silty sands (aprQIV) slightly wet and wet – medium density;- Silty sands (aprQIV) water-saturated – medium density;- Fine sands (aprQIV) slightly wet and wet – medium density;- Fine sands (aprQIV) water-saturated – medium density;- Silty sands (aptQIV) slightly wet and wet – medium density;- Silty sands (aptQIV) water-saturated – medium density;- Medium sands (aptQIV) water-saturated – medium density;87

Table 3.2: Relative dynamic resistance for sandy soils against probe penetration pd,
deformation modulus and angle of internal friction.
Name of the soil

Length of studiedinterval, m(No. ofmeasurements)
12.8 (128)

Relative
Deformation
Angle ofdynamic soil
modulus E,internal
resistance pd,
MPafriction φ,MPadegreeSilty sand (aprQIV),
1.0…7.6
17.0
27.5
slightly wet and wet
2.7
Silty sand (aprQIV),
3.2 (32)
6.8…9.6
water-saturated
3.7
Fine sand (aprQIV),
3.5 (35)
1.6…6.2
18.2
30.0
slightly wet and wet
2.8
Fine sand (aprQIV),
1.2 (12)
4.0…5.2
15.0
29.0
water-saturated
1.8
Silty sand (aptQIV),
0.7 (7)
6.4…7.1
15.0
27.0
wet
1.9
Silty sand (aptQIV),
19.0 (190)
5.2…15.6
water-saturated
4.8
Fine sand (aptQIV),
7.5 (75)
7.1…17.0
26.3
32.5
water-saturated
5.0
Medium sand (aptQIV)
1.6 (16)
8.9…10.5
33.5
35.0
5.0
Note: value of relative dynamic resistance of soil (Pd) is given in decimal: in numerator –measurement interval, in denominator – average value.

Assessment of sand liquefaction potential was done using average values of relative
dynamic resistance pd (Table 8 of SP 11-105-97). In the layer of Modern Quaternary
alluvial deposits of the flood plain facies predominant are wet and water-saturated silty
and fine sands. Liquefaction potential of Modern Quaternary alluvial deposits of theflood plain facies for slightly-wet, wet and water-saturated silty sands and slightly wet
and wet fine sands is low, but for fine water-saturated sands liquefaction potential israther high. In the layer of Modern Quaternary alluvial deposits of the channel facies(аptQIV) predominant are wet and water-saturated silty sands, water-saturated fine sands
and medium sands. Liquefaction potential of Modern Quaternary alluvial deposits ofthe channel facies for slightly-wet and wet silty sands – is rather expectative, and forwater-saturated silty, fine and medium sands – is almost equal to zero. Results ofdetermination of liquefaction potential for sands under dynamic loads are given in
Table 3.3.

88

Table 3.3: Liquefaction potential for sands under dynamic loads.
Stratigraphic
index

Name of soils

Average valueof pd, MPa

aprQIV

Silty sand,slightly wet andwet
Silty sand,water-saturated
Fine sand, wetFine sand,water-saturated
Silty sand,slightly wet andwet
Silty sand,water-saturated
Fine sand,water-saturated
Medium sand

2.7

Liquefaction
potential for sands
under dynamic
loads
Low

3.7

Low

2.8
1.8

Low
Possible

1.9

Possible

4.8

Almost Possible

5.0

Almost Possible

5.0

Almost Possible

aptQIVAt the Rooppur NPP site, clay soils are observed sandy loams and loams of various
consistency. For clayey soils average values of relative dynamic soil resistance were
determined as per SPT data. Results of standard penetration tests for clayey soils of the
Rooppur NPP site are given in Table 3.4.
Table 3.4: Relative dynamic resistance for clayey soils against probe penetration pd anddeformation modulus
Stratigraphic
index

Name of soils

Length of studiedinterval, m(No ofmeasurements)

а(е)QIV

Solid and semisolid loam
Solid sandy loam

1.3 (13)

Solid and semisolid loam
Low-plastic andhigh plastic loam
Plastic sandyloam

1.3 (13)

aprQIV

0.6 (6)5.1 (51)
1.4 (14)89

Relativedynamic
soil resistancepd,
MPa
1.0…1.7
2.8
1.0…1.6
1.5
2.6…4.2
2.4
1.5…4.2
1.0
3.6…5.0
2.1

Deformation
modulus E,
MPa-арtQIV

High-plastic
4.5 (45)
6.2…11.7
loam
2.1
3.4 Geo-Physical Survey (Cross-Section of Soil Profile along Reactor Building)
Large-scale comprehensive engineering-geological and engineering-geotechnicalsurvey was carried out for assessment and characterization of engineering-geologicaland engineering-geotechnical of the Rooppur NPP Site. The cross-sections of soil
profile are presented through Figure 3.8 and 3.9 of reactor areas and characterizationof engineering-geological and engineering-geotechnical comprising of the following
laboratory works:
The selection of soil samples from the boreholes was performed every 1.0 - 2.0 m on
average.
For sandy and coarse disturbed soils, the following properties were defined:1.

the natural moisture content by drying to constant weight;2.

the density of sand in loose and dense state;

3.

density of soil particles with picnometric method;

4.

angle of friction in air-dry condition and under water;

5.

determination of granulometric composition by sieving;

6.

determination of relative organic compound with the method of ignition loss;

7.

strength properties using direct shear test for given values of density andmoisture content;

8.

deformation properties using triaxial compression test and uniaxial test for given
density and moisture content.

The following properties were defined for the undisturbed sandy soil:
1.

the natural moisture content by drying to constant weight;

2.

density determination with cutting ring;3.

the density of sand in loose and dense state;

4.

density of soil particles with picnometric method;90

Figure 3.10: Section of engineering-geological borehole of Reactor Units
3.5 Physical-Mechanical Properties of Soils
Foundation soils of the RNPP site down to the studied depth of 120 m are combinedin 12 engineering-geological elements (EGE) with consideration of genesis,
lithological composition and physical-mechanical properties obtained during field andlab studies. EGE present main soil units for engineering-geological schematization of
the soil mass.

91The following EGE are differentiated in the foundation soil:
EGE-1 – clays with liquidity index < 0.75 u.f. Soils of element are locally distributedin form of lenses and interlayers.
EGE-2 – is presented by loams and sandy loams with liquidity index <0.75 u.f. Soils
are locally distributed and occur mainly in upper part of the section in form of lenses
and interlayers.
EGE-3 – is presented by loams and sandy loams with liquidity index ≥ 0.75 u.f. In
some cases clays are observed in this EGE. Soils of the EGE are locally distributed inform of lenses and interlayers;
EGE-4 – is presented by silty and fine sands of the zone of GWL seasonal
fluctuation. Soils of this EGE are distributed throughout;
EGE-5 – is presented by silty sands of water-saturation zone. Soils of this EGE are
distributed throughout.
EGE-6 – is presented by fine sands of water-saturation zone. Soils of this EGE are
distributed throughout;
EGE-7 – is presented by medium sands of water-saturation zone. Soils of this EGE
are dis- tributed throughout.
EGE-8 – is presented by coarse sands of water-saturation zone. Soils are locally
distributed in form of lenses and interlayers. Sandy soils that occur in water-saturation
zone at depths below 27.5-45 m
EGE-9 – is presented by medium sands with lenses of coarse and gravel sands ofwater- saturation zone. Soils of this EGE are distributed throughout;
EGE-10 – is presented by fine sands with single interlayers of silty sands ofwater- saturation zone. Soils are locally distributed in form of lenses and interlayers.
EGE-11 – is presented by gravel soils of water-saturation zone. Soils of this EGE are
dis- tributed throughout in the lower parts of geological section
EGE-12 – is presented by gravel sands with lenses and interlayers of coarse andmedium sands of water-saturation zone. Soils of this EGE are distributed throughout
in the lower parts of geological section.
3.6 Engineering and Geotechnical test Results. Summary Table of PhysicalMechanical Soil Properties
The collected samples from different engineering geological layers were subjective tolaboratory studies and geophysical tests like pressuremeter and cone penetration wereconducted to get deformation modulus, cohesion and angle of internal friction ofrespective soil layers. The outcomes of engineering and geotechnical test results are
mentioned in Table 3.5.
92

3

4

5
6
7
8

9

10

1.5 0.098 0.13

8

11

11

20

20

1.5 0.056 -0.64

7

8

15

21

24

7

11

12

20

21.5

1.81 1.5

Deformation modulus
based on triaxial tests
4

Liquidity index I L. u.f.
.

1.90 1.4 0.194 0.24

Plasticity index Ip. u.f.

φ. °Dry soil density ρd.
g/cm3

Modulus ofdeformation

2

Clays with JL≤ 0.75
0.316
Clay loams with
0.263
JL<0.75
Sandy loams with JL<
0.210
0.75
Clay loams and sandy
loams with JL< 0.75
0.243
(joint processing)
Clay loams with JL≥
0.352
0.75
Sandy loams with JL≥
0.316
0.75
Clay loams and sandy
0.343
loams with JL≥ 0.75
Dusty sand of aeration
0.101
zone
Fine sand of aeration
0.071
zone
Dusty and fine sands
0.097(joint processing)
Dusty sand of water
0.244
saturation zone
Fine sand of water
0.234
saturation zone
Mean coarseness sandof water saturation
0.202
zone
Coarse sand of water
0.216
saturation zone
Average coarse sand of
0.191
water saturation zone
Coarse sand of water
0.178
saturation zone
Medium and coarse
sand of water
saturation zone
Fine sand of water
0.220
saturation zone

Modulus of deformationpressuremeter tests results

1

Lithology

Soil density ρd. g/cm3

EGE

Natural moisture content
W. u.f.

Physical-mechanical soil properties
regarding to laboratory studies

Cone penetration
tests

С.
kPa

1.4 0.106 0.91

8

1.4 0.058 1.00

14

6

18

16

1.88 1.4

9

6

18

16

1.4

5

9

22.7

31

1.4

5

10

24.2

32

1.56 1.4

5

9

22.9

32

1.85 1.5

16

15

24

31

1.90 1.5

24

25

24

31

28

33

28

33

37
1.6

40

Soil density regarding togeophysical survey data

Table 3.5: Engineering and Geotechnical Survey Results

1.45-1.86
1.73

1.86-1.93
1.92

1.51-1.87
1.71
1.80-1.94
1.92
1.70-1.97
1.92
1.86-1.95
1.92
1.93

35

41
1.6

40

35

46

30

11

Gravel soil

142

12

Gravel sand withinterlayersof medium and coarse
sand

137

93

1.92-1.97
1.94
1.92-1.95
1.94
1.92-1.96
1.94
1.94

3.7 Improvement of Soil under Reactor Building
The ground improvement work was conducted by deep soil mixing technology underpower reactor building and its surrounding facilities to enhanced soil deformation
properties of the site soil. The ground improvement depth was 20 meters of having two
meters diameter pile which overlapped each other’s and formed a solid rock strata inthat area. The average use of cement for improved soil was 278 kg/m3

1.

(b)

(c)
Figure 3.11: (a) works performed (b) piles top (c) digging pile for physical checking
94

Figure 3.12: Plan view of cement grout piles

During performing soil stabilization works wet samples are collected and for hardening
process water curing method is applied.

Figure 3.13: In situ wet grab samples collection during soil stabilization work95

Figure 3.14: Wet grab samples are submerged in water for curing.
Coring is performed after 28 days of piles execution. The core samples are important to
get actual information and engineering properties of soils as it collected from working
platform.

Figure 3.15: Core samples are collected and transported to site laboratory.

96

3.8 Results of Stabilized Soil
Engineering properties of stabilized soil are found through following tests
3.8.1 Drilling Works
When recovering the core (49 boreholes), RQD index was determined, the averagevalue of which for all the boreholes was 92%. Based on the RQD index obtained acc. tomethodology of GOST 25100-2011, the quality of the rock soil is characterized as very
good (> 90%).
3.8.2 Pressuremeter tests
Pressuremeter tests were performed in five piles (No 13, No 392, No 580, No 1760, No2120) through the whole pile depth with interval of 3 m, achieving the maximal depth
19 m. Results of pressuremeter tests of stabilized soils are given in Table 3.6.
Table 3.6: Result of pressuremeter tests

97

Table 3.7: Result of pressuremeter tests (continued..)983.8.3 Plate-Bearing Tests
Six plate bearing tests were performed on heads of the piles No 413, No 524, No 896,
No 1672, No 1744 and No 2354 after the cleaning of the site not earlier than 29 days
after making of piles. Results of plate-beating tests are given in Table 3.7.
Table 3.8: Results of plate-beating tests

3.8.4. Tri-axial Tests
Lab tests were performed on wet grab samples collected during stabilization works andcore samples from piles of the age of 28-39 days. Results of lab tests for determinationof values of physical-mechanical properties of stabilized soils and their statisticalanalysis in accordance with GOST 20522-2012. The results of tri-axial tests are in
Appendix D.
3.8.5 Permeability test
Permeability test is also performed on samples taken from the depth from 7.3 to 17.9 m.
The values of permeability were in the range from 5.58 х 10-6 to 2.93 х 10-5 m/s,
average value 1.58 х 10-5 (or 1.36 m/day).

99

Table 3.9: Presents normative and design values of physical-mechanical properties ofstabilized soils based on results of lab tests.

3.8.6 Geophysical Survey
Engineering-geophysical studies as a part of engineering geological survey for quality
control of the stabilized foundation soils of the Rooppur NPP buildings and structures
solved the following tasks:
Determination of the propagation velocities of compressional (Vp) and shear (Vs)seismic waves and the study of their distribution in plan view and in depth of thestabilized foundation soil;
1.

Assessment of homogeneity of the foundation according to seismic properties.

2.

The set of geophysical studies included down hole and surface seismic methods:

3.

Seismic logging;

4.

Crosshole seismic survey on longitudinal P-waves;

5.

Seismic profiling on compressional (P) and shear (S) waves.

Seismic logging (SL) in boreholes was performed to obtain data on the P- and S-wave
velocities along borehole and to calculate dynamic moduli, Poisson ratio.
100

3.8.7 Seismic Properties of Stabilized Soil according to Seismic Logging Data
According to the data of seismic logging processing, all boreholes show an increase in
the P- and S-wave velocities with depth. In the upper part of stabilized soil mass Pwave velocities are from 1920 to 2300 m/s, S-waves from 1020 to 1145 m/s. In thelower part P-wave velocities are from 2500 up to 2730 m/s, S-wave from 1320 to 1460
m/s.

101

Figure 3.16: Charts of P- and S-wave interval velocities for borehole 987102Figure 3.17: Charts of P- and S-wave interval velocities for borehole 989

103Figure 3.18: Charts of P- and S-wave interval velocities for borehole 995

3.9 Results Summery of Soil Samples
Based on the test results of soil samples of Rooppur NPP Site, the required engineeringparameters are taken for developing Plaxis 3D software model of natural/unimproved
and improved soil.
3.9.1 Input parameters of the Mohr Coulomb model and Hardening Soil model ofunimproved soil.
Table 3.10: Parameters of Mohr-coulomb model of unimproved/natural soil
SL

Properties

Unit

Loam/
Layer
thickness
1.8 m(-1.8 m)Finesand/layer
thickess
13 m(-14.8 m)

1

Unsaturated
Unit
Weight,γunsatSaturated Unit
Weight, γsat
Modulusof
Elasticity, E
Poisson’s ratio,νCohesion, c’
AngleofFriction, Interface factor,
Rint
Dilation Angle,
Ψ

kN/m3

14.5

15.0

Mediumcoarse
sand/
layer
thick
10 m
(-24.8)
15.3

kN/m3

18.2

18.5

kN/m2

9000

2
3
4
5
6
7
8

CoarseGravel/
sand/
layer
layer
thicknessthickness 35.0 m
59.3 m(-119.1)(-84.1)
16.3

16.3

18.9

19.4

19.4

15000

25000

37000

137000

0.35

0.35

0.35

0.35

0.35

kN/m2
Degree

21.5
19

0
29

0
29

0
36

0
39

Degree

0

0

0

0

0

104

Table 3.11: Parameters of HS Model of unimproved soil
SL

Properties

Loam/
Layer
thickness 1.8
m
(-1.8
m)
14.5

Fine
sand/layerthickness
13 m(-14.8m)
15.0

Mediumcoarsesand/ layer
thick
10 m
(-24.8)

Coarsesand/
layer
thickness
59.3 m(-84.1)

Gravel/layer
thickness
35.0 m(-119.1)

1

Unsaturated Unit kN/m 3
Weight, γunsat
Saturated
Unit kN/m 3
Weight, γsat
Secant Modulus kN/m2

15.3

16.3

16.3

18.2

18.5

18.9

19.4

19.4

18000

30000

50000

74000

274000

4

of Elasticity, 𝐸
Oedometer
kN/m2
Modulus
of

14400

24000

40000

59200

2192005

Elasticity, 𝐸
Unloading/Reload kN/m2
ing Modulus of

54000

90000

150000222000822000

0.35

0.35

0.35

0.35

0.35

21.5
19

0
29

0
29

0
36

0
39

0
0.2

0
0.2

0
0.2

0
0.2

0
0.2

0.7

0.7

0.7

0.7

0.7

0.674

0.515

0.412

0.412

0.37

2
3

Unit

Elasticity, 𝐸
6
7
8
9
10

11
12

Poisson’s ratio, ν
Cohesion, c′
kN/m2
Angle of Friction, DegreeDilation Angle, Ψ Degree
Unloading
Reloading
Poisson’s Ratio,νurInterface factor,
Rint
K0 value fornormalconsolidation(default
𝐾 = 1 - sin φ)
𝐾

105

SL

Properties

Unit

13

Power for stresslevel dependencyof stiffness, m

Loam/
Layer
thickness 1.8
m
(-1.8
m)
0.5

Fine
sand/layerthickness
13 m(-14.8m)
0.5

Mediumcoarsesand/ layer
thick
10 m
(-24.8)

Coarsesand/
layer
thickness
59.3 m(-84.1)

Gravel/layer
thickness
35.0 m(-119.1)

0.5

0.5

0.5

3.9.2 Input parameters of the Mohr Coulomb model and Hardening Soil model of
improved soil.
Summary of input parameters of Mohr Coulomb model and Hardening soil model of
improved soil is given in Table 3.11 and Table 3.12.
Table 3.12: Parameters of Mohr-coulomb model of improved soil
SL

Properties

Unit

1

Unsaturated
Unit
Weight,γunsatSaturated
Unit
Weight, γsat
Modulus of
Elasticity, E
Poisson’s
ratio, ν
Cohesion, c’
AngleofFriction, Interfacefactor, Rint
DilationAngle, ΨkN/m3

Soil-cement
stabilized
soils
20m
(-20m)
21.0

kN/m3

22.0

18.9

19.4

19.4

kN/m2

200000

25000

37000

137000

0.35

0.35

0.35

0.35

kN/m2
Degree

0
38.0

0
29.0

0
36.0

0
39.0

Degree

0

0

0

0

2

3
4
5
6
7
8

MediumCoarse sand/coarse sand/ layer thickness
layer thick
59.3 m4.8 m(-84.1)(-24.8)
15.3
16.3

106

Gravel/layer
thickness
35.0 m(-119.1)
16.3

Table 3.13: Parameters of HS Model of improved soil
SL

Properties

1

3

Unsaturated
Unit kN/m 3
Weight, γ unsat
Saturated
Unit kN/m 3
Weight, γsat
Secant Modulus of kN/m2

4

Elasticity, 𝐸
Oedometer Modulus kN/m2

2

5

Unit

of Elasticity, 𝐸
Unloading/Reloading kN/m2
Modulus of Elasticity,

Improved
soil
Layer
thickness 20
m(-20 m)14.71

Mediumcoarsesand/layer thick
4.8 m(-24.8)15.3

Coarsesand/ layer
thickness
59.3 m(-84.1)

Gravel/layer
thickness
35.0 m(-119.1)

16.3

16.3

18.63

18.9

19.4

19.4

83800

50000

74000

274000

66000

40000

59200

219200251400150000222000822000𝐸
6Poisson’s ratio, ν

0.35

0.35

0.35

0.35

7
8
9
10

Cohesion, c′
kN/m2
DegreeAngle of Friction, 
Dilation Angle, Ψ
DegreeUnloading Reloading
Poisson’s Ratio, νurInterface factor, Rint
K0 value for normal
consolidation (default
𝐾 = 1 - sin φ) 𝐾

176
49
0
0.2

0
36
0
0.2

0
36
0
0.2

0
39
0
0.2

0.7
0.245

0.7
0.412

0.7
0.412

0.7
0.37

11
12

107

SL

Properties

13

Power for stress-level
dependency
ofstiffness, m

Unit

Improved
soil
Layer
thickness 20
m(-20 m)0.5

Mediumcoarsesand/layer thick
4.8 m(-24.8)0.5

Coarsesand/ layer
thickness
59.3 m(-84.1)

Gravel/layer
thickness
35.0 m(-119.1)

0.5

0.5

Chapter FourNUMERICAL MODELLING AND ANALYSIS
4.1 Introduction
The chapter is intended to present the numerical modeling and derivation of
geotechnical parameters for numerical analysis using the finite element method
PLAXIS 3D. Software PLAXIS is a package of calculation software using the Finite
Element method, designed specifically for the analysis of deformations and the stabilityof geotechnical structures. The software allows to simulate incrementally the processesof construction and the excavation of soil, the application loads and calculate theconsolidation, etc. This method gives a realistic assessment of the stresses and strains.
The PLAXIS 3D has been chosen for the research study because it is mainly developed
for foundation design and analysis and has popularity amongst practicing engineers,and over the years a wealth of knowledge and experience available for reference has
been accumulated.

108

In the following sections, the original base design using the Harding Soil (HS) model
together with the design assumptions and modeling approach using idealization ofvarious structural components of the mat foundation is reported.
4.2 FEM Model in PLAXIS 3D Software
The software package PLAXIS 3D is designed for the performance of Finite Element
stress-strain analysis considering the interaction of the foundation with the subsoil in
3D boundary conditions. The following steps are implemented utilizing the software:compilation of 3D design model of the foundation and subsoil below the building andstructures, soil improvement by changing the physical and mechanical properties ofsoils under the buildings and structures, applying the loads from foundation to thesubsoil, calculation of settlements of the foundations on the improved soil, calculationof deformations and stresses in the soil massive, calculation of tilting. Soils weremodeled by 10-noded elements. The Drained Method was adopted for HS model.
Groundwater is 6.5 meters below the existing ground surface at Rooppur site. The soil
profile is modeled up to 119.1 m with varying layers.

4.2.1 Reactor Building geometry

The reactor building is the heart of a nuclear power plant, which produced
enormous heat energy from a nuclear chain reaction. The building has two
containments (inner and outer) to maintain radiological integrity and resist
external thrust. The approx. size of the foundation is 73 m X 79 m. The thicknessof mat foundation is 3.0 meters. The total height of the building from thefoundation mat to above is about 72.0 meters. A nuclear reactor is a complex
structure having different dimensional vibratory dynamic loads.
Following external loads are considered in Figure 4.1 including dead, live, andvibratory which come to the foundation mat as uniformly distributed load 491 kN/m 2.
The mat’s center of gravity and total building center of gravity is same.

109

Figure 4.1: Cross-section of reactor building with all external loads

4.2.2 Soil Stratigraphya) Natural or Unimproved Soil
Considering the uniformity of soil properties in unimproved soil beneath reactor up to
120m the subsoil consists of five layers. The upper loam layer lies between the groundlevel (z=0) and z= -1.8 m. The under-laying 2nd layer is up to fine sandy layer lies to 14.8 m. The 3rd layer medium coarse sand up to -24.8, 4th layer coarse sand up to -84.1
m and 5th layer consists of gravels start from -84.1 to -119.1m. All other properties ofsoil geological layers are collected and recorded bellow in Table 4.1:
Table 4.1: Parameters of HS Model of unimproved soil
SL

Properties

Unit

1

Unsaturated Unit
Weight, γ unsat

kN/m 3Loam/
Layer
thickness 1.8
m
(-1.8
m)
14.5

110

Fine
sand/layerthickness
13 m(-14.8 m)
15.0

Mediumcoarse
sand/
layer
thick
10 m
(-24.8)15.3

Coarsesand/
layer
thickness
59.3 m(-84.1)

Gravel/layer
thickness
35.0 m(-119.1)

16.3

16.3

2
3
4

5

6
7
8
9
10

11
12

13

Saturated Unit
Weight, γsat
Secant Modulus of
Elasticity, 𝐸
Oedometer
Modulus of
Elasticity, 𝐸
Unloading/Reloadi
ng Modulus of
Elasticity, 𝐸
Poisson’s ratio, ν

kN/m 3

18.2

18.5

18.9

19.4

19.4

kN/m2

18000

30000

50000

74000

274000

kN/m2

14400

24000

40000

59200

219200

kN/m2

54000

90000

150000222000822000

0.35

0.35

0.35

0.35

0.35

Cohesion, c′Angle of Friction,
Dilation Angle, ΨUnloading
Reloading
Poisson’s Ratio,νurInterface factor,
Rint
K0 value fornormalconsolidation(default
𝐾 = 1 - sin φ)𝐾Power for stresslevel dependencyof stiffness, m

kN/m2
Degree

21.5
19

0
29

0
29

0
36

0
39

Degree

0
0.2

0
0.2

0
0.2

0
0.2

0
0.2

0.7

0.7

0.7

0.7

0.7

0.674

0.515

0.412

0.412

0.37

0.5

0.5

0.5

0.5

0.5

b) Improved Soil
The top layer of 20 m thickness is improved with cement slurry using DSM technology.
The improved subsoil consists of four layers. The upper layer is improved and lies
between the ground level (z=0) and z= -20.0 m. The under-laying 2nd layer is up to finesandy layer lies to -24.8 m. The 3rd layer medium-coarse sand up to -84.1 and 4th layer
consists of gravels starting from -84.1 to -119.1m. All properties of soil geologicallayers are recorded is below Table 4.2:
Table 4.2: Parameters of HS Model of improved soil
SL

Properties

Unit

Improved soilLayer
111

Mediumcoarsesand/

Coarsesand/
layer

Gravel/layer
thicknethickness 20 m(-20 m)kN/m 3

14.71

2

Unsaturated Unit Weight,
γ unsatSaturated Unit Weight, γsat

layer
thick
4.8 m
(-24.8)15.3

kN/m 3

18.63

18.9

19.4

19.4

3

Secant

of

kN/m2

83800

50000

74000

274000

4

Elasticity, 𝐸
Oedometer Modulus of

kN/m2

66000

40000

59200

219200kN/m2251400150000222000822000

0.35

0.35

0.35

0.35

176
49
0
0.2

0
36
0
0.2

0
36
0
0.2

0
39
0
0.2

0.7
0.245

0.7
0.412

0.7
0.412

0.7
0.37

0.5

0.5

0.5

0.5

1

5

Modulus

Elasticity, 𝐸
Unloading/Reloading
Modulus of Elasticity,

thickness
59.3 m(-84.1)16.3

ss
35.0 m(119.1)
16.3

𝐸
6
7
8
9
10
11
12

13

Poisson’s ratio, ν
Cohesion, c′Angle of Friction, 
Dilation Angle, ΨUnloading
Reloading
Poisson’s Ratio, νurInterface factor, Rint
K0 value for normal
consolidation(default
𝐾 = 1 - sin φ) 𝐾

kN/m
Deg
Deg

2

Power for stress-level
dependency of stiffness, mc) Structural properties of reactor foundation mat
The mat is reinforced cement concrete. The grade of concrete is B30W6, B30 is thecompressive strength 30 MPa and W6 is water permeability category. Table 4.3 shows
the other parameters required for analysis.
Table 4.3: Properties of foundation mat concrete
Parameter name

Symbols

Unit

Thickness/depthdM

Values3.0
3DensitykN/mYoung’s Modulus

E1

kN/m2

Poisson’s ratio

12

25.0
2.57 x107
0.2

112

4.2.3 Development of Plaxis 3D Model using unimproved and improved soil profile
under Power Reactor.
The following four models are developed as per soil profiles and foundation mat
mentioned in Table 4.1, 4.2 and Table 4.3 for numerical analysis using Plaxis 3D.
Table 4.4: Soil Models in improved and unimproved soil using Plaxis 3D
Designation

Model

Type of soil
condition

Static loads
On matkN/m2

Appliedearthquake

Earthquake
load
PGA

HS-

Hardening

Unimproved

491

Kobe

0.33 g

US_Koba

Soil model

HS-

Hardening

Unimproved

491

Loma

0.33 g

US_Loma

Soil model

HS-IS_Koba

Hardening

Improved

491

Kobe

0.33 g

Improved

491

Loma

0.33 gSoil model
HS-IS_Loma

Hardening
Soil model

The soil model size in the plan views 300 meters x 300 meters and the size of mat
foundation is 73 meters x79 meters. The elevation of the surface is considered at 13.4meter from the mean sea level. The excavation depth is -1.0 meter. Earth’s gravity is
9.8 m/s2 and water is 10 kN/m3. The calculations are not taken into account the mutual
influence of other surrounding buildings and structures.
Appropriate material properties and their parameters are assigned to the mat structuresduring modeling. For soil profile modeling, in situ soil properties are applied.
Hardening Soil models (HS) are developed in Plaxis 3D for taking into account thedifference in hardness elements during initial loading of soil and it’s unloading withsubsequent loading. Here, four models are developed. One, the mat is placed in natural(unimproved) soil and in another the mat is placed in improved soil.
The models are loaded with the same static and two different earthquake Kobe (1995)
and Loma Prieta (1989) loads have been applied alternatively. These two motions havedifferent characteristics. Kobe earthquake is a severe one with a magnitude Mw= 7.2
and PGA = 0.75 g. Loma Prieta has a magnitude Mw= 6.8 and PGA = 0.36 g. These
records are applied in the horizontal direction at all bottom node of the model. They are113

scaled into same acceleration 0.33 g (Safe Shutdown Earthquake) for Rooppur NPP
case. In order to reduce the calculation time only 5 s of Kobe earthquake and 5 s ofLoma prieta earthquake are applied.

Figure 4.2: Original earthquake frequency (a) 1995 Kobe (b) 1989 Loma Prieta.

The design earthquake of Rooppur NPP is collected from Rooppur Project. The projectis designed based on safety criteria of international regulations and safety guide of
IAEA, the NPP structures and systems are required to be designed as follows:i)

Seismic Level, SL1- is called operating basis earthquake (OBE)/Design
Earthquake. The OBE is reasonably expected to be experienced at the site
during operating life of NPP. For Rooppur NPP, PGA 0.172g which isconsidered during analysis.

ii)

Seismic Level, SL2- is called Safe Shutdown Earthquake (SSE). The SSE
has a very low probability of being exceeded and a return period of the orderof 10,000 years which is considered during analysis, for this PGA of 0.33 g.

114

4.3 Mesh Generation
Mesh generation is the practice of generating a mesh that approximates a geometricdomain. Meshing is a collective term to denote the pre-processing phase of the Finite
Element Analysis (FEA). For performing finite element calculation, a fully definedgeometry is divided into finite elements. It is a tool that engineers use to complete theiranalysis of a particular design. The model is calculated using four types of meshingnamely very course meshing, course meshing, medium meshing, and fine meshing. It isnoticeable that the finer the meshing system, the more time has been required for thecomputation. The mesh generation process includes soil stratigraphy, structure, loads
and boundary, the number of nodes generated for each type of meshing is shown in
Table 4.5.
Table 4.5: Generated nodes for different type of meshingType of meshing

Soil elements

Number of nodes

Very course meshing

2343

4468

Course meshing

5814

9484

Medium meshing

12519

20491

Fine meshing

27366

40936

Very fine

64663

98127

For the current study medium mesh element has been used for both vertical andearthquake loading conditions. Following figures 4.3 to 4.7 shows the different meshingmodel.

115

Figure 4.3: The model is meshed with Very Coarse meshing

Figure 4.4: The model is meshed with Coarse meshing116

Figure 4.5: The model is meshed with medium meshing

Figure 4.6: The model is meshed with fine meshing117

Figure 4.7: The model is meshed with Very fine meshing

4.4 Development of model and analysis
For the current study, HS model is used for modeling soil element according to soil
investigation data available from Rooppur NPP which are listed in the above tables.
The earthquake load is applied at the bottom of the FEM model as prescribed
displacement in x-direction. In dynamic loading condition, using HS model generates
plastic strain with increased preconsolidation stress in soil. Under this condition
damping is defined by Rayleigh damping. The stage construction phases in PLAXIS 3D
for earthquake loading condition are given below in Table 4.6.
The total amount of damping is introduced through frequency dependent Rayleighformula. Here, Hardening Soil model with the same soil properties have been used forseismic analysis with assigning 5% Rayleigh damping. All the models medium meshing
are used for getting results uniformity. The deviations of results between medium andfine meshes are less than 10%.

118

Table 4.6: Stage construction phases for calculation
Phase

InitialExcavation

Foundation Mat stage

Loading on Mat

Earthquake loading stage

Analysis
type
K0

Plastic

Plastic

Plastic

Dynamic

Prime Elements

Activated

Soil volume√

Foundation mat

x

loads

x

Soil volume
Foundation mat
loads
Soil volume

√
x
x
√

Foundation mat

√

loads

x

Soil volume
Foundation mat
Distributed load
Dynamic loads
Soil volume

√
√
√
x
√

Foundation mat√

Distributed loadx

Dynamic loads√

4.4.1 Model of Unimproved Soil with Kobe earthquake HS_US_Kobe
This Hardening Soil model is developed using natural/unimproved soil of Rooppur NPP
site in accordance with Table 4.1 and 4.3. All static loads are applied on mat as
distributed and Kobe earthquake load is applied considering design basis earthquake
PGA (Peak Ground Acceleration) 0.172 g and SSE (safe shutdown earthquake) 0.33g.
Since the maximum acceleration of Kobe was 0.75g, the scale is selected as(0.33g/0.75g) 0.44.

119Figure 4.8: Applied earthquake Kobe using scaling factor for Rooppur NPP

Figure 4.9: Model of Unimproved Soil with Kobe earthquake
The model is run for analyzing soil with the specified loads and earthquake and find
impact on mat due to static and dynamic load. Following figures are shown the analysis
results of displacements in different directions of mat is observed due to earthquake.
120

Figure 4.10: The total displacement due to Static load

Figure 4.11: The total displacement due to earthquake

121

Figure 4.12: Tilting; Maximum and minimum displacements due to dynamic loading

Figure 4.13: Cross-section of displacement due to static loading

122

The results of model analysis of settlement, tilting, forces and moments are tabulated inTable 4.7 and 4.8 respectively.
Table 4.7: Results of the deformation analysis of Reactor building on model
HS_US_Kobe at operational stage

Model nameMax settlement
due to Static load,cm

Max UzMim UzM Calculated
relateddifference ofsettlement∆ s/L

42.28

79.64

-4.57

0.0036

HS_U_Kobe

Displacement due toearthquake, cm

According to Russian code PiNAE-5.10-87 “Rules and Regulation in Nuclear Energy”
regarding foundation for reactor compartment of NPP, the maximum allowablesettlement of structural foundation of reactor building is S u  30 cm; and tilting isallowable  0.001. Considering seismic settlements, the tilting is iu<0.003.
Table 4. 8: Forces on Reactor foundation mat of model HS_US_Kobe
Force/moment

Maximum

minimum

1

Axial force, N

72.18 x 104 kN-36.56 x 106 kN

2

Shear force, Q13

46.98 x 104 kN

5332 kN

3

Shear force, Q23

13.58 x 104 kN-13.80 x 104 kN

4

Bending moment, M2

68.19 x 107 kN-m

-57.19 x 106 kN-m

5

Bending moment, M3-26.08 x 107 kN-m

-54.52 x 107 kN-m

Figure 4.14: Dynamic time Vs Acceleration in unimproved soil of HS model

123

4.4.2 Model of improved Soil with Kobe earthquake HS_IS_Kobe
The model is developed considering improved soil of Rooppur NPP site and Kobe
earthquake load. All static loads are applied on mat as distributed and Kobe earthquake
load is applied considering design basis earthquake PGA (Peak Ground Acceleration)
0.172 g and SSE (safe shutdown earthquake) 0.33g.
Since the maximum acceleration of Kobe was 0.75g, the scale is selected as 0.33g/0.75g = 0.44

Figure 4.15: Prepared model using improved soil conditions

The model is run with the specified loads and earthquake and find impact on mat due tostatic and dynamic load. Following figures are shown the analysis results ofdisplacements in different directions of mat is observed due to earthquake.

124

Figure 4.16: Maximum settlement due to static loading

Figure

4.17:

Cross-section

of

mat

125

foundation

under

staticloadingFigure 4.18: Maximum displacement in X-direction due to earthquake loading

Figure 4.19: Maximum and minimum displacements due to dynamic loading

126

The results of model analysis of settlement, tilting, forces and moments are tabulated inTable 4.9 and 4.10 respectively.
Table 4.9: Results of the analysis of Reactor building on HS_IS_Kobe model

Model name

HS_IS_Kobe

Max settlement
due to Staticload, cm

Displacement due toearthquake, cm
Max UzMim Uz

9.4

-5.45

23.68

Calculated
relateddifference ofsettlement∆s/L
0.00018

According to Russian code PiNAE-5.10-87 “Rules and Regulation in Nuclear Energy”
regarding foundation for reactor compartment of NPP, the maximum allowablesettlement of structural foundation of reactor building is Su  30 cm; where max  10
cm during operation life and tilting is allowable  0.001. Considering specificconditions and seismic settlements, the tilting is iu<0.003.
Table 4.10: Forces/moments in foundation mat of HS_IS_Kobe
Force/moment

Maximum

minimum

1

Axial force, N-6.455 x 106 kN-30.42 x 106 kN

2

Shear force, Q13

62.78 x 103 kN

8300 kN

3

Shear force, Q23

6.344 x 105 kN-5.406 x 105 kN

4

Bending moment, M2

36.76 x 107 kN-m

-14.33 x 108 kN-m

5

Bending moment, M3-12.63 x 107 kN-m

-57.73 x 107 kN-m

Being analyzed of two above models, the acceleration due to earthquake on improved
soil is steady and less compare to unimproved soil which is reflected in graph Figure
4.20

127

Figure 4.20: Acceleration Vs Dynamic time in improved and unimproved soil using
Kobe earthquake

4.4.3 Model of Unimproved Soil with Kobe earthquake, HS_US_Loma
The model is developed using unimproved soil of Rooppur NPP site and Loma Prieta
earthquake load. All static loads are applied on mat foundation as uniformly distributedand Loma earthquake load is applied considering design basis earthquake PGA (PeakGround Acceleration) 0.172 g and SSE (safe shutdown earthquake) 0.33g. Since themaximum acceleration of Loma was 0.20 g, the scale is selected as (0.33g/0.20g) 1.65.

128

Figure 4.21: Loma earthquake loads is applied on HS_US_Loma model
The model is run with the specified loads and earthquake to find impact on mat due tostatic and dynamic load. Following figures are shown the analysis results ofdisplacements in different directions of mat is observed due to static load andearthquake.

Figure 4.22: Max displacement in Z-direction due to static loads
129

Figure 4.23: Cross-section of max displacement place due to static loads

Figure 4.24: Max. displacements due to dynamic loading is revealed at X-direction

130Figure 4.25: Displacements difference at Z-direction due to dynamic loading
The model analysis results of settlement, tilting, forces and moments are tabulated inTable 4.11 and 4.12 respectively.
Table 4.11: Results of the deformation analysis of Reactor building on model
HS_US_Loma

Model nameMax settlement
due to Static load,cm

Max UzMim UzCalculated
relateddifference ofsettlement ∆s/L

42.34

11.97

-18.840.002

HS_US_Loma

Displacement due toearthquake, cm

According to Russian code PiNAE-5.10-87 “Rules and Regulation in Nuclear Energy”
regarding foundation for reactor compartment of NPP, the maximum allowablesettlement of structural foundation of reactor building is Su  30 cm and tilting isallowable  0.001.
Table 4.12: Forces/moments in foundation mat in model HS_US-Loma
Force/moment

Maximum

minimum

1

Axial force, N-2.501 x 106 kN-37.12 x 106 kN

2

Shear force, Q13

4.32 x 105 kN-7.01 x 105 kN

3

Shear force, Q23

20.30 x 103 kN-11.71 x 103 kN

4

Bending moment, M2-51.19 x 106 kN-m

-77.73 x 107 kN-m

5

Bending moment, M3-33.58 x 106 kN-m

-15.04 x 108 kN-m

131

Figure 4.26: Acceleration Vs Dynamic time in unimproved soil in HS_US-Loma model
4.4.4 Model of Improved Soil with Kobe earthquake, HS_IS_Loma
The model is developed using improved soil of Rooppur NPP site and Loma Prieta
earthquake load. All static loads are applied on mat foundation as distributed and Lomaearthquake load is applied considering design basis earthquake PGA (Peak GroundAcceleration) 0.172 g and SSE (safe shutdown earthquake) 0.33g. Since the maximum
acceleration of Loma was 0.20 g, the scale is selected as (0.33g/0.20g) 1.65. Following
results are observed after analysis:
The model is run with the specified loads and earthquake to find impact on mat due tostatic and dynamic load. Following figures are shown the analysis results ofdisplacements in different directions of mat is observed132

Figure 4.27: Maximum settlement in Z-direction due to static loading

Figure 4.28: Cross-section of Maximum settlement in Z-direction due to static loading133

Figure 4.29: Maximum settlement due to earthquake loading

Figure 4.30: Displacements in X-direction due to seismic loading

The results of model analysis of settlement, tilting, forces and moments are tabulated inTable 4.13 and 4.14 respectively.

134

Table 4.13: Results of the deformation analysis of Reactor building on model
HS_IS_Loma

Model nameMax
settlement
due to Staticload, cm

HS_IS_Loma

23.60

Calculated
Relativedifference ofsettlements,

Displacement due to earthquake
Max UzMim Uz

cm

cm

29.53

-2.19

∆ s/L (Tilting)0.0014

According to Russian code PiNAE-5.10-87 “Rules and Regulation in Nuclear Energy”
regarding foundation for reactor compartment of NPP, the maximum allowablesettlement of structural foundation of reactor building is S u  30 cm;
Table 4.14: Forces/moments in foundation mat in model HS_US-Loma
Force/moment

Maximum

minimum
6

1

Axial force, N-4.585 x 10 kN-34.68 x 106 kN

2

Shear force, Q133970 kN-2.712 x 105 kN

3

Shear force, Q23

20.29 x 104 kN-1.573 x 106 kN

4

Bending moment, M2-91.45 x 106 kN-m

-19.17 x 108 kN-m

5

Bending moment, M3-14.19 x 107 kN-m

-84.35 x 107 kN-m

Figure 4.31: Acceleration Vs Dynamic time in improved and unimproved soil in Lomaearthquake.

224

4.5 Result Summary
Upon application of Kobe and Loma earthquake loading on improved and unimproved
soil conditions, four models have following summarized result on the Table 4.15:
Table 4.15: Displacement results summery of models in X and Z-direction of mat
SL

1
2
3
4

Model

HS-USKobe
HS-USLoma
HS-ISKobe
HS-ISLomadisplacement due to Static, cm
X-direction
Max.
Mim.
10.82 -10.13

Z-direction
Max. Mim.
0.025 -42.36

displacement due to earthquake,cm
X-direction
Z-direction
Max. Mim.
Max. Mim.
6.53-60.43 79.64 -4.57

10.06-10.190.021-42.34

6.57-99.25

79.18

-4.39

3.31

-3.31

0.014

-23.682.38-61.68

9.4

-5.45

3.16

-3.20

0.015

-23.606.33-61.65

29.53

-2.19

The results show that the maximum settlement is 42.36 cm at Z-direction for static
loadings and maximum displacement is found 145.80 cm at X-direction. Both values
are found on unimproved soil model.
After improvement of soil using deep soil mixing technology same static andearthquake loadings are applied. The maximum settlement due to static loading is
reduced to 23.68 cm at Z-direction and the maximum displacement is found 61.68 cm
at X-direction.
Table 4.16: Tilting results of respective models
SL

Model

Settlement due to earthquake, cm
X-direction
Z-direction
Max.
Mim.
Max.
Mim.

1
2

HS-US-Kobe
HS-US-Loma

6.53
23.51

-60.43-145.8

79.64
11.97

-4.57
-18.84

Calculated
Relativedifference ofsettlements,∆ s/L (Tilting)
0.00360.00253
4HS-IS-Kobe
HS-IS-Loma

2.38
6.33

-61.68
61.65

9.4
29.53

-5.45
-2.19

0.00180.0014After application of Kobe earthquake on unimproved soil, tiling is observed 0.0036
which is reduced to 0.0018 on improved soil. On the other hand, tilting is observed due

225

PART-IV

NUMERICAL MODELING OF PILED RAFT
FOUNDATION SYSTEM SUBJECTED TO
SEISMIC LOADINGSBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Naim Parves
Mehedi Ahmed AnsaryChapter 1
INTRODUCTION
1.1 General
Design of a safe and economical foundation system is an important task in tall building
design. Deep foundations such as piled foundations are generally adopted to transfer
heavy loads from superstructure to the bearing stratum. Providing adequate
geotechnical capacity and limiting the deferential settlement are two important design
considerations in the design of piled foundations. The foundation design becomes
economical when both the criteria of bearing capacity and settlement are satisfied in
an optimum way. A piled raft foundation is an advanced concept in which the total load
coming from the superstructure is partly shared by the raft through bearing from soil
and the remaining load is shared by piles through skin friction and end bearing.
Consequently, piled raft system is generally adopted when pile foundations for tallbuildings become uneconomical or unsatisfactory.
For situations in which a raft foundation is found to have an adequate factor of safety
against failure but which is likely to settle excessively, a method is developed for
determining the number of piles which need to be added to the raft to reduce thesettlement to a tolerable amount. It is found from recent studies that the addition ofrelatively few long piles may be effective in reducing settlement even though the piles
themselves may have reached their ultimate load. The design of the required numberof piles on a settlement basis rather than on the more usual ultimate bearing capacity
basis leads to a system which, although it contains considerably fewer piles, settles only
slightly more and is quite adequate for bearing capacity purposes.
Firstly, the piles are constructed and then the raft is placed combining all the piles.
Interaction of the pile, soil, and raft is the key factor considered in designing the piled
raft foundation. The efficient use of the interaction leads to end up with the economical
design. Due to the three-dimensional nature of the load transfer, piled raft foundations
are regarded as very complex systems involving many interaction factors such as pile
to-raft, raft-to-soil, and pile-to-soil. This study intended to present a detailed discussion
226

on the analysis of piled raft system addressing the effect of different parameters for
piled raft foundation system. PLAXIS-3D software has been used to generate
Earthquake load and to analyze the results for different parametric study.
1.2 Background of The Study
Recently with the increasing in economic development, rapid industrialization anddecreasing availability of land for construction in thickly populated cities like Dhaka,scope for extending construction in horizontal direction is becoming increasingly lesser
resulting in construction of high-rise building with increasing number of floors. In thedesign of foundations for large buildings on deep deposit of soft or loose soils it isgenerally seen that raft foundation be chosen the foundation will have sufficient factorof safety against shear failure but corresponding settlement will be very high to permit.
In such cases pile foundation are generally selected causing very large cost for suchfoundations. The settlements are successfully controlled in such foundations, howeverin the late, it has been recognized if few numbers of piles are installed at suitablelocations below the raft foundation for such structures, the resultant settlement undersuch structure will be much smaller and will be within permissible limits compared tothat below the raft without provision of piles. Use of raft in conjunction with some piles
will be costlier than in case where only raft is used if possible but much less than thecase when only piles are used.
As a result, in the past decades there has been increasing recognition to use some piles
with raft to reduce the total and differential settlement of raft leading to considerable
economy without compromising the safety and performance of the foundation
structure system. Such a foundation system is called piled-raft. One of the mostimportant buildings constructed with such system is for the foundation system of theworld’s tallest building the Burj Dubai. The adoption of piled-raft foundation for highrise buildings is also very common in European cities. Thus, it seems on the othercountries, piled-raft foundation will be increasingly adopted as a most economic safe
foundation system. A piled raft foundation has some advantages over the pile group interms of the design and from a serviceability and economic point of view. They include
the following: (i) a piled raft foundation will require fewer piles in comparison to a pile227

group to satisfy the same design requirements; this will lead to a more economical
design; (ii) for a piled raft, the piles will provide sufficient stiffness to control thesettlement and differential settlement at serviceability load; and the raft will provide
additional capacity at ultimate load; (iii) in case any piles in the piled raft become
defective, the raft allows re-distribution of the load from the damaged piles to the otherpiles (Poulos et al. 2011); (iv) a raft in the piled raft foundation can carry a higher
percentage of the applied load and transmit to the soil (Clancy and Randolph, 1993);
and (v) the pressure applied from the raft to the subsoil may increase the lateral stressbetween underlying piles and the soil, which can increase the pile bearing capacity
accordingly compared to the piles in a pile group (Katzenbach et al. 1998).
In recent years, large number of mega projects were constructed using the piled raftfoundation system concept in Dhaka city. Hence a noticeable attention has been drawn
toward better understanding of the performance of piled raft foundation systems
subjected to Seismic loading. An innovative application of the piled raft is its special
adjustment to cases of foundations with large load eccentricities or very different
loaded parts of buildings to avoid the need of complex settlement joints especiallybelow ground water table. This research work has been studied on a piled raft
supported structure in Dhaka city with various loaded portions. Due to application ofearthquake load, eccentric load also acting on this selected structure. The study
concentrates on the effect of engineering factors related to pile in raft foundation suchas raft thickness, number of piles, pile layout and pile diameter on the behavior of the
piled raft foundation; analysis is carried out by 3D finite element method via PLAXIS-3D
Foundation software. Both the immediate and Consolidation settlement due to thevariation of different parameters has been observed in this study.
1.3 Objective of The Study
The study will throw light on the effects of considering seismic effect on Piled-raftfoundation system on the design parameters of a tall building for Dhaka soil conditions.
The results are expected to give some guidelines for designing tall buildings/skyscrapers
on piled raft foundations in Dhaka city. The main objectives of this research work arelisted below.

31. Analyzing a selected structure in Dhaka using numerical model
2. Simulation of Earthquake load using PLAXIS-3D software
3. Parametric study of the developed piled-raft foundation system
4. Study the lateral deformation of pile under seismic loading
1.4 Organization of The Thesis
There are total six chapters which are chronologically developed on the basis of theresearch work towards its main objective. Brief descriptions of the five chapters are
given below:
Chapter One deals with few general issues, background of the research, necessity of
piled raft of foundation system in Dhaka city, research scheme and objective of theresearch. It also gives a brief overview of the other chapters.
Chapter Two is devoted to review past researches related to the theme of this thesis.
Various analytical theories of pile raft foundations are discussed in this chapter.
Overview of PLAXIS-3D software and a brief description of Hardening soil modeling inthis software is also discussed in this chapter.
In Chapter Three, overall input parameters for the study like Site location, Subsoil
parameters and Description selected structure of the thesis have been discussed.
Chapter Four represents the Numerical model development procedures. Soil andmaterial model, embedded beam, details of different parametric study models andgeneration of earthquake effect in PLAXIS-3D have been discussed in this chapter.
Results obtained through the analysis and calculations are presented in Chapter Fivewith specific findings. Effects of different parametric study for both un-piled raft andpiled raft have been discussed in this chapter. At the end of this chapter summary on
findings are highlighted in the form of discussion.
Conclusive remarks on the parametric study of piled raft foundation system for Dhaka
city are presented in Chapter six. This chapter also includes the scopes for future
researches with specific recommendations.

4Chapter 3
STUDY OF SUBSOIL INVESTIGATION DATA AND
SELECTION OF SUITABLE STRUCTURE

3.1 Site Description
The selected site for this study is located in the center of Dhaka city. It is bounded by
Kafrul, cantonment and Tejgaon industrial area thanas on the north, Kalabagan and
Ramna thanas on the south, Tejgaon Industrial Area thana on the east, Sher-e-Bangla
Nagar and Kafrul thanas on the west. The site is fairly level and elevations and theexisting ground level vary from quarter to one and half-a meter above from existing site
adjacent road level.

Figure 3.1: The selected site location (marked in red circle) for this study

55

3.2 Geological Condition of The Selected Site
At the beginning, field investigation and Standard penetration test is carried out tomeasure the SPT values up to 70.5m depth. Both disturbed and undisturbed samples
are collected for further tests in laboratory. Based on the field investigation, visualclassification of soil and Laboratory tests on the collected samples, it is found that thesubsoil of the selected site represents the typical Dhaka soil. A summary of the subsoil
strata description is as follows:
Table 3.1: General description of soil profile of the selected site

SL.

Depth

No.

(m)

1
2
3
4
5
6

0-2
2-6
6-15
15-27
27-30
30-70.5

Layer
thickness
(m)
2
4
9
12
3
40

SPT
value
8-12
14-25
30-37
10-13
50+

Average
SPT

Soil description

value
9
18
33
11
50+

Fill
High Plastic Medium stiff to Stiff Clay
Medium dense Silty Sand
Medium dense to Dense Silty Sand
High Plastic Stiff Clay
Very dense poorly graded Sand with Silt

Details geotechnical description of the soil is described in later part of this chapter.
3.3 Ground water level of The Selected Site
With reference to the measured groundwater table during Soil investigation (SI) works,
the groundwater table for the site was found to be varying between two stages of SI
work due to the wash boring technique, therefore it was not possible to estimate theexact levels. Subsequently, a water standpipe had been installed at site and Table 3.2
below shows the ground waters tables reading between February 2019 and April 2019.
Based on the information, the ground water table at this region are believed to be at asignificant depth below EGL. However, the adopted ground water table respective tothe onerous water table level could be adopted at 14m below ground level for the upliftdesign check and below the soffit of the slab for the pile raft design check. Again, thewater level may rise above during rainy season. So, in this study we have assumed theground water level at 14m below existing ground level.

56

Table 3.2: Ground water level measurement using standpipe method
SL.
No.
1
2
3
4
5
6
7
8

Date ofobservation
February 25,
2019
February 26,
2019
February 27,
2019
February 28,
2019March 01,2019
March 02,2019
March 20,
2019
April 15,2019Time ofobservation

Depth of water level below EGL

12:30 PM

Water was observed at a depth of 16.7 m

10:00 AM

Water was observed at a depth of 16.03 m

10:00 AM
10:00 AM
10:00 AM
10:00 AM
1:30 PM
10:00 AMNo water was observed up to a depth of 18.3 m;
mud was encountered at this levelNo water was observed up to a depth of 18.3 m;
mud was encountered at this levelNo water was observed up to a depth of 18.3 m;
mud was encountered at this levelNo water was observed up to a depth of 18.3 m;
mud was encountered at this levelNo water was observed up to a depth of 18.3 m;
mud was encountered at this levelNo water was observed up to a depth of 18.3 m;
mud was encountered at this level

3.4 Subsoil Investigation Data
All the Subsoil investigation data used in this study was collected from reliable sources.
Standard penetration test was done up to 70.5m depth to count the SPT values at 1.5m
following ASTM D-1587 standard. The drilling work was done by rotary method. Later,
the collected disturbed and undisturbed samples were transported to the laboratory
with proper caution. Based on the Particle size distribution (as per ASTM D-6913 &ASTM D-7923) and Atterberg limit test (as per ASTM D-4318) results, the soil samples
were classified by Unified Soil Classification System (USCS) as per ASTM D-2487.
Unconfined Compression strength test was done on cohesive soil layers as per ASTM D2166. One dimensional Consolidation test was also performed on cohesive soil layer as
per ASTM D-2435. Details of field investigation and laboratory tests are mentioned inAppendix-1. Based on in situ and laboratory tests, the soil properties have been usedwhile developing the numerical models in PLAXIS-3D for this study.

57

3.5 Seismic Information of The Site
The selected site is situated in the district of Dhaka, which falls into the seismic intensity
zone with Z = 0.15 (Zone 2) and has a maximum PGA value of 0.15g. This zoning map isbased on peak ground accelerations estimated by Hattori (1979) for a return period of
200 years. The study was initiated considering the PGA values as per BNBC 2006.
However, while this study was in progress, the new Code BNBC-2020 get published. The
intent of the seismic zoning map according to BNBC-2020 is to give an indication of theMaximum Considered Earthquake (MCE) motion at different parts of the country. In
probabilistic terms, the MCE motion may be considered to correspond to having a 2%
probability of exceedance within a period of 50 years. According to BNBC-2020, Dhaka
district falls in the seismic intensity zone with Z=0.20 and a maximum PGA value of
0.20g. The design basis earthquake (DBE) ground motion is selected at a ground shaking
level that is 2/3 of the maximum considered earthquake (MCE) ground motion. So, thedesign basis earthquake for the site becomes 0.133g.
Seismic down hole test is performed to directly measure the compressional (P) andshear (S) waves velocity profile of subsoil stratum of the selected site. P-wave travel
time is calculated by the first arrival of either peak or trough in the seismogram. S wave
travel time is calculated from the first cross of generated opposite phase shear waves
in radial and transverse direction. First arrival time of P and S waves are plotted against
depth and the time-depth curves for borehole as follows:(a)58

Figure 3.2: P-wave for upper 30m depth. (a) P-wave trace, (b) Corresponding timedistance curve with layer velocity at the selected site

(a)

59

Figure 3.3: S-wave for upper 30m depth. (a) S-wave trace, (b)Corresponding timedistance curve with layer velocity at the selected site
As per BNBC-2020, Site should be classified as type SA, SB, SC, SD, SE, S1 and S2 basedon the provisions of Table 6.2.13 of BNBC-2020 and based on the soil properties ofupper 30 meters of the site profile. Site class could be determined by Shear wave
velocity or Field (uncorrected) Standard Penetration Value or Undrained shear strengthof cohesive layers.
According to BNBC-2020 Table 6.2.14, the soil that is deep deposits of dense or medium
dense sand, gravel or stiff clay with thickness from several tens to many hundreds ofmeters should be classified as “SC”. For “SC” type soil, average shear wave velocity ofupper 30m soil should be in between 180-360 m/sec and average SPT value for upper60

30m soil should be in between 15-50. In this study, it is found that the site class is “SC”
type soil by using both Shear wave velocity and SPT values.
Table 3.3: Down hole survey results showing S wave and AVs30 velocities

SL.
no.

Layer 1
S wave Thickness
(m/s)
(m)

1

179

8

Shear Wave Velocity
Layer 1
Layer 1
S wave Thickness S wave Thickness
(m/s)
(m)
(m/s)
(m)
Base not
275
12
310
seen

Total depth
investigated
(m)

AVs30

30

293

Table 3.4: Down hole survey results showing P wave and AVp30 velocities
Shear Wave Velocity
SL.
no.

1

Layer 1

Layer 1

Layer 1

S wave(m/s)

Thickness(m)

S wave(m/s)

Thickness
(m)

246

8

422

12

Total depth
S wave Thickness investigated
(m)
(m/s)
(m)
Base not
496
30
seen

Average shear wave velocity of upper 30 meters of the site profile is 293 m/s which
satisfies the requirement of Site Class SC. Again, average field (uncorrected) Standard
Penetration Value of upper 30 meters of the site profile is 15.96 which indicates the siteclass is SC.
3.6 General Description of The Selected Structure
The selected structure is an inverted L shaped 40 storied commercial building withapproximate 155m height with five basements with the total area of 2716 square meter
including the Podium area. Podium is 4 storied structure with a height of 14.55m.
Central core shaft in the middle with dimensions 37.5m×28.5m. The foundation system
is piled raft system. The reason behind selecting this structure is recently with theincreasing in economic development, rapid industrialization and decreasing availabilityof land for construction in thickly populated cities like Dhaka, scope for extending
construction in horizontal direction is becoming increasingly lesser resulting inconstruction of high-rise building with increasing number of floors. So, considering the

61

AVp30

443

current and future demand, this structure is selected. Overall summary of the structure
is given in the following Table:
Table 3.5: General description of the selected structure
SL. No.

Name of feature

Description

1

Story

40

2

Approx. Length (m)59.325

3

Approx. Width (m)

45.78

4

Area including Podium (sqm)

2716

5

Podium story

4

6

Podium height (m)

14.55

7

Core Length (m)

37.5

8

Core Width (m)

28.5

9

Core Area (sqm)1068.75

10Core height (m)

155

11

Clear floor to floor height (m)

4

12

Shape

Inverted L

13

Number of Basement

514

Basement floor to floor height (m)315

Bottom of Basement below EGL (m)

18m

16

Foundation system

Both only Raft and Piled raft
considered in this study

17

Raft thickness (m)2.5, 3, 3.5

18

Pile diameter (m)1, 1.2, 1.5

18

Pile number

58, 69, 82

62

Figure 3.4: Front elevation of the structure63Figure 3.5: Side elevation of the structure64Figure 3.6: Column, Shear wall and Retaining wall layout plan
Foundation details have been discussed in chapter-4 as we have different Pile number,Pile diameter and mat thicknesses for parametric studies.

65

Chapter 4
NUMERICAL MODELING

4.1 Introduction
Identifying the important parameters which significantly affect the performance of
piled-raft foundations can assist in optimizing the design of such foundations.
Therefore, studying the effect of different design parameters on the behavior of piledraft foundations was carried out. This study focused on the effect of some parameterson the load-settlement between the raft and piles of piled-raft foundations. The effectof the selected parameters on the load-settlement relationship will be investigated atsmall and large settlements. The tests in this study were carried out using the developed
PLAXIS-3D model.
The software program consists of three basic components, namely Input, Calculation
and Output. In the input program the boundary conditions, problem geometry withappropriate material properties are defined. In PLAXIS 3D, soil properties and material
properties of structures are stored in material data sets. There are six different types ofmaterial sets grouped as data sets for soil and interfaces, beams, embedded beams,
plates, geogrids anchors. All data sets are stored in the material database. From thedatabase, the data sets can be assigned to the soil clusters or to the corresponding
structural objects in the geometry model. The model includes an idealized soil profile,structural objects, construction stages and loading. Then the calculation phase starts
which performs plastic, dynamic and consolidation analysis of the developed numericalmodel. As soon as the calculation phase is completed, the output can be checked where
all the geotechnical and structural parameters of the numerical model can bethoroughly studied.
4.2 Development of the Numerical model in PLAXIS-3DThe finite element method based on software PLAXIS-3D is used for three-dimensionalmodelling of 40-storey building structure with five basements and having piled-raftfoundation in layered soil field. An overall assessment of the both raft only and piled

66

raft foundation system under actual loading conditions across the site was carried out
by using PLAXIS-3D, which is a three-dimensional, finite-element-based geotechnicalsoftware. The overall numerical modelling in PLAXIS-3D has five steps as shown in the
Figure 4.1. A brief discussion on each stage is given below:

Figure 4.1: Steps for numerical modelling in PLAXIS-3D
4.2.1 Soil
The subsoil was modelled using ten nodded tetrahedral elements that are available inthe standard library of PLAXIS-3D. The subsoils primarily comprised typical Dhaka soil
as discussed in Table 3.1 of chapter-3. The soil stratigraphy is defined in the soil modeusing the Borehole feature of the program. When a new project is created, the soil
contour defined in the Project properties window is displayed in the drawing area.
There is an option “create boreholes” where all the information of boreholes can beprovided. Boreholes are locations in the drawing area at which the information on theposition of soil layers and the water table is given.

Figure 4.2: Defining the soil layers as per borelog mentioned in Appendix-1

67

If multiple boreholes are defined, PLAXIS 3D will automatically interpolate between
boreholes, and derive the position of the soil layers from the borehole information.
Each defined soil layer is used throughout the whole model contour. In other words, allsoil layers appear in all boreholes. The top and the bottom boundaries of the layers mayvary through boreholes, making it possible to define non-horizontal soil layers of nonuniform thickness as well as layers that locally have a zero thickness. To simlify thenumerical model and to avoid long calculation time, only one borehole representing in
PLAXIS-3D.
Ground water level has been considered at 14m below existing ground level. In order
to avoid an undesirable boundary effect, the lateral dimensions of the soil model were
set to be five times the width of the raft. The vertical extent of the soil model was set
to be 10m below the pile tip. A mesh optimization study was carried out in order todetermine the extent of the model boundaries, which helps in reducing computational
effort. The soil model (500m long, 350m wide and 70 m deep) was created as shown in
Figure 4.2.

Figure 4.3: The volume of defined soil model in PLAXIS-3D
68

The soil was modelled using the Hardening soil constitutive model. This is an advanced
model for the simulation of soil behavior. The Hardening Soil model is an elastoplastic
type of hyperbolic model, formulated in the framework of shear hardening plasticity.
Moreover, the model involves compression hardening to simulate irreversible
compaction of soil under primary compression. This second-order model can be used
to simulate the behavior of sands and gravel as well as softer types of soil such as clays
and silts. Soil strength parameters (cohesion and angle of internal friction) and Modulus
of Elasticity, E50ref values has been calculated from soil types and well-establishedcorrelations with SPT-values. Other parameters for performing the numerical model
have been calculated the PLAXIS-3D based on the information given by the user. The
soil properties for hardening soil model used in PLAXIS-3D are given in following Tables.
Table 4.1: Soil properties used in hardening soil model

Identification

Layer
thickness (m)Soil Volume
No.

Fill

2

Clay

Sand

Sand 15m-

Clay

Sand 30m-

upto 6m

6m-15m27m

27m-30m

70m

4

9

12

3

40

Soil_5

Soil_6

Soil_3,
Soil_1

Soil_2

Soil_7,
Soil_8

Soil_4,
Soil_9ColourDrainage typeϒ(unsat)(kN/m3)ϒ(sat)(kN/m3)

DrainedUndrained(B)

DrainedDrainedUndrained(B)

Drained

14

16

17

18

16

18

16

18

19

20

18

20

69

Contd. Table 4.1
Clay

Sand

Sand

Clay

Sand

upto 6m

6m-15m

15m-27m

27m-30m

30m-70m

12000

8000

45000

85000

8000

130000Eoedref (kPa)

12000

8000

45000

85000

8000

130000Eurref (kPa)

36000

24000

13500025500024000

390000Power, m

1

1

0.5

0.5

1

0.5

cref (kPa)

1

50

1

1

70

1

Ф (deg)

30

0

32

36

0

38

Rf

0.9

0.9

0.9

0.9

0.9

0.9

Rinter

0.67

0.67

0.67

0.67

0.67

0.67

IdentificationFill

E50ref (kPa)

4.2.2 Structure
In this section, the structural component is modelled. This phase of numerical modelingconsists of the following:
1. Material properties: All the structural member’s properties are assigned in thisphase of modeling. The interaction effect of pile and soil at the pile shaft isconsidered by means of Elasto-Plastic line-to-volume and point-to-volumeinterfaces as an embedded pile model. The embedded pile model consisting of
beam elements with non-linear skin and tip interfaces. For defining the pile
bearing the capacity, the option “Layer dependent” is chosen. The piles weremodeled as “embedded elements.” In this case, the piles do not have a “real”
volume or a “real” interface. However, a virtual elastic zone is created byassigning an equivalent pile diameter within the material data set of theembedded pile. This virtual elastic zone disregards the plastic behavior of the70

soil within the zone and approaches the actual volume pile behavior. On theother hand, due to the “virtual” volume and interface, evaluation of the effectof strength reduction factor (Rinter) cannot be realized. Rinter is taken as rigid (1.0)
with the assumption that the interface does not have a reduced strength. Thereis no need for mesh refinement around piles as 3D mesh is not distorted byintroducing embedded pile model. The basement floor slab, retaining wall andraft is discretized using 6-node triangular plate elements with linear elastic
properties. Summary of the material properties is given in Table 4.2 and 4.3.
Table 4.2: Material properties of Plates(Raft, basement floor slab and retaining wall) in PLAXIS-3D
Name of Structural Member

Raft

Retaining wall

Basement slab

IdentificationMat

R.wallBasement floors

Material model

Elastic

Elastic

Elastic

Thickness (m)1, 1.5, 2.5, 3,

0.6

0.3

3.5
ϒ (kN/m3)

24

24

24

E (kPa)29730000

29730000

29730000

Table 4.3: Material properties of Embedded beam or Pile in PLAXIS-3D
Name of Structural Member

Pile

Identification

P1

Material model

Elastic

Diameter (m)1, 1.2, 1.5

ϒ (kN/m3)

24

E (kPa)24870000

Axial skin resistance

Layer dependent

Maximum base resistance (kN)

5000

71

2. Geometry: The geometry of raft, retaining wall and piles are assigned in thisphase as per structural information mentioned in chapter-3. As mentioned, theshore protection and effect of excavation is not focused in this study.
3. Loads: Service loads like dead loads and live loads of superstructure has beencreated by creating a FEM model in ETABS-2017 software. Most of previous
study and research on piled raft has been performed using uniformly distributedload over the raft. But to observe the actual and more accurate stress andsettlement behavior of raft only or piled raft foundation, point load has been
assigned in this study. The effect of eccentric load has been addressed due topoint load application. Service loads from the superstructure has been given in
Table 4.4.

Figure 4.4: Joint locations from structural FEM ETABS model
72

Table 4.4: Loads of Superstructure applied on raft in PLAXIS-3D
Joint location
1
3
5
6
7
8
9
10
11
12
13
14
17
18
19
20
21
22
23
25
26
29
31
33
35
39
41
45
54
55
56
71
72
73
81
82
83
85
86
88
89
91
94

Load combination
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live73

Loads (kN)
39860
52457
13599
15740
29209
1986
7004
6893
20363
5304
4347
9091
5408
2907
18279
3492
22389
22486
37114
404
26846
12683
10635
6428
5900
1505
7538
6468
1539
1666
44771
2416
2348
1919
1668
1859
13678
5502
3380
2352
2625
52040
931

Joint location
95
96
97
99
100
102
103
105
124
128
132
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167

Contd. Table 4.4:
Load combination
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live74

Loads (kN)
4415
17453
1098
1154
7622
6626
2371
6043
5873
3460
5954
6225
4907
3226
3683
3788
3915
3280
3033
3816
3749
2879
2657
2159
2163
2063
2880
2275
3052
2106
1107
1322
1734
2784
2180
2566
3349
3147
2527
2526
2470
1353
770
859

Joint location
168
170
171
172
173
174
175
177
179
181
182
191
192
249
250
251
252
253
254
255
256
257
258
259
260
261
262
264
265
266
267
268
269
270
271

Contd. Table 4.4:
Load combination
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live
Dead + Live

Loads (kN)
2194
5078
2416
2348
1919
3109
2840
2530
3586
2917
1859
4592
1674
49646
50804
53813
45326
49988
50567
1098
27127
1313
443
1537
1564
1693
1698
5449
966
964
7526
1088
623
768
772

4. Interfaces: Interfaces are joint elements to be added to plates or geogrids toallow for a proper modelling of soil-structure interaction. Interfaces may be used
to simulate, for example, the thin zone of intensely shearing material at thecontact between a plate and the surrounding soil. Interfaces can be created next
to plate or geogrid elements or between two soil volumes. When the geometric75

entity (surface) is already available in the model it is advised to assign aninterface to it without recreating the geometry in order to prevent the modelfrom being unnecessarily large and unwieldy. Distinction is made between apositive interface (the side of the surface at the positive local z-direction) and anegative interface (the side of the surface at the negative local z-direction). The
sign of an interface is only used to enable distinguishing interfaces at either sideof a surface, but it does not affect its behavior. In the numerical model, negativeinterface has been used for raft and positive interface has been used forretaining wall.

4.2.3 Earthquake loads
Analysis: For earthquake analysis, the free field site response has been carried out along
a 1D linear elastic frequency domain. In this study, PLAXIS-3D finite element software isused to conduct this analysis. For the current study HS model is used for modeling soil
element according to soil investigation done in the study site previously. The
earthquake load is applied at the bottom of the FEM model as prescribed displacement.
In dynamic loading condition, using HS model generates plastic strain with increased
pre-consolidation stress in soil.
Dynamic soil behavior: Constitutive model presents in PLAXIS needs to be validated forseismic analysis before implementation. Every constitutive model can be used formodeling material behavior. But due to some limitations each model cannot simulate
seismic behavior. During an earthquake, soil is subjected to cyclic shear loading showing
a nonlinear dissipative behavior. The total amount of damping is introduced throughfrequency dependent Rayleigh formula. Which is considered in HS model as previously
discussed. Generally, HS and hardening soil with small strain (HSSM) models arerecognized for using in earthquake analysis. Here in this study, Hardening Soil modelwith the same soil properties have been used for seismic analysis as shown in Table-4.1.
Boundary Condition: A proper boundary condition is important for analyzing pileaccurately. Earthquake load is applied in the model as uniform prescribed displacementin x direction as shown in Figure 4.5. The deformation is free in Xmin and Xmax76

direction. In Ymin,max and Zmin,max direction the deformation is kept fixed. To
introduce the soil strength reduction due to soil movement, an interface surface withstrength reduction at the bottom surface (70m below existing ground level; bottom of
the soil volume) is added as shown in Figure 4.6. For input seismic motion theboundaries in x direction are viscous. The viscous field boundary condition for lateral
deformation keeps the boundary capable for motion to move at the sides and also
absorbs the reflected secondary waves. In Y direction it is none as no absorbent
boundary condition is applied. In Zmin none is assigned and Zmax is also none forunabsorbing bedrock. The dynamic analysis time interval is assigned 48 sec. A properboundary for bottom boundary ensures the reflection of waves from above layers areabsorbed and thus direct earthquake accelerogram can be applied directly.

Figure 4.5: Boundary condition for earthquake load simulation

Figure 4.6: Prescribed displacement method for earthquake load simulation
77

Earthquake Input signal: In this analysis 1995 Kobe earthquake motion is used. Kobe
earthquake is a severe earthquake with a magnitude Mw= 7.2 and PGA = 0.821g. The
acceleration time histories of 48 second duration are presented in Figure 4.7. These
records are applied in the horizontal X direction at all bottom (70m below EGL) node of
the model. They are scaled to design basis earthquake value the site 0.133g for Dhaka
zone. Figure 4.8 shows the Kobe earthquake acceleration data input in PLAXIS 3D forearthquake analysis.
0.8

Accelartion (m/s2)

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

5

10

15

20

25

30

35

40

45

Time (sec)Figure 4.7: Original Kobe 1995 earthquake data

Figure 4.8: Kobe 1995 Earthquake input signal (both raw and scaled data)
78

50

4.2.4 Mesh
Generating a proper Finite Element mesh is an important intermediate step between
the definitions of the geometry and the construction stages. In order to have a smooth
and accurate calculation the finite element mesh has to fulfill several criteria. For thenumerical stability of the calculation, the mesh should have a good quality, that is tosay, the elements should be regular without being excessively long and thin. For theaccuracy of the calculation, the elements should be small enough, especially in thoseareas where significant changes in stress or strain can be expected during the analysis.
But that does not mean one should just generate an entire mesh of very small elements
as this will lead to a very large calculation time. Therefore, proper care should be taken
to find the right balance between accuracy and calculation time while supervising on
the mesh quality.

Figure 4.9: Mesh quality and quality spheres of numerical model
After assigning all the geometry parameters, meshing can be done. Mesh dimension
should be appropriately defined, to prevent boundary conditions. Very fines meshshould be avoided in order to reduce the number of elements, thus reduce the memory
consumption and calculation time. In this study, for raft only models, effect of different
mesh size has been studied by applying very coarse, coarse and medium mesh.
However, for piled raft models, only very course mesh was used to avoid longer
computation time.

79

The mesh generator requires a global meshing parameter le, which represents thetarget element dimension. In PLAXIS 3D this parameter is calculated from the outergeometry dimensions (xmin, xmax, ymin, ymax, zmin, zmax) and the Element
distribution selected in the Mesh options window. The target element dimension is
calculated using the equation 4.1.
le = re × 0.05 × √(xmax − xmin )2 + (ymax − ymin )2 + (zmax − zmin )2(4.1)
where the Relative element size factor (re) is derived from the Element distribution.
There are five global levels. By default, the Element distribution is set to Medium but
the user may select one of the other levels to make the mesh globally finer or coarser.
The predefined values of the parameter re (Element distribution) are:Table 4.5: Relative element size factor for different mesh size
Element distribution

reVery coarse

2

Coarse1.5

Medium

1

Fine

0.7

Very fine

0.5

4.2.5 Staged Construction:
In PLAXIS 3D, only raft or piled raft foundation is provided as a staged construction
process. In every calculation step, the material properties, geometry of the model,
loading condition and the ground water level can be redefined. During the calculations
in each construction step, a multiplier that controls the staged construction process
denoted by ΣM stage is increased from zero to ultimate value 1. After staged
construction the PLAXIS results were obtained. In this study total 4 construction stages
were created. Stage construction details as follows:80

Initial Phase: Firstly, in the initial stage, in-situ stress state or it is also called primarystress conditions is applied. In the step, only the own weight of the soil domain will be
activated.
Phase_1: This phase starts after initial stage. As shore protection or excavation effect is
not focused in this study so in this phase, retaining wall, raft, piles, interfaces all are
activated. The soil excavation up to a depth of 18m below GL also done in this stage.
This was modeled by deactivation of the soil element from ground surface up to 18m.
The analysis type is Plastic.
Phase_2: This stage starts after Phase_1. In this stage, the loads from superstructure
applied as point loads on the raft. The analysis type is Plastic in this phase.
Phase_3: This stage starts after Phase_2. This stage is devoted to application
earthquake load and dynamic analysis of the numerical model. The analysis type is
Dynamic in this phase. Total dynamic time interval is 48 seconds. Prescribed
displacement is activated in this phase along with the necessary boundary condition
modification discussed in 4.2.3.
Phase_4: This stage also starts after Phase_2. This final stage is created to calculated
the consolidation settlement effect. Calculation type Consolidation is selected with 90%
degree of consolidation in this stage of construction.

Figure 4.10: Different construction stages in PLAXIS-3D.

81

For better understanding of the stage construction, Table 4.6 can be followed.
Table 4.6: Summary of the stage construction
Phase

Analysis type

Initial phase

K0

Phase_1(Excavation up todredging level,
Raft, piles,
retaining wall
activation)

Plastic

Phase_2(Gravity Load
activation)

Phase_3(Earthquake Load
activation)

Phase_4(Consolidation
analysis)

Elements
Soil volume
Point loads
Embedded beams
PlatesInterfaces
Surface displacements
Soil excavation
Soil volume
Point loads
Embedded beams
PlatesInterfaces
Surface displacements
Soil excavation

Activated
√
x
x
x
x
x
x
√
x
√
√
√
x
√

Soil volume√

Point loads√

Embedded beams√

Plates√Interfaces√

Surface displacements

x

Soil excavation√

Soil volume√

Point loads√

Embedded beams√

Plates√Interfaces√

Surface displacements√

Soil excavation
Soil volume
Point loads
Embedded beams
PlatesInterfaces
Surface displacements
Soil excavation

√
√
√
√
√
√
√
√

Plastic

Dynamic

Consolidation82

4.2.6 Calculation
In this study following calculation types are adopted in PLAXIS-3D
Initial stress generation: The first step in a PLAXIS 3D analysis is defining a calculation
type of a phase in the Calculation type drop-down menu in the Phases window. The
options available are K0 procedure and Gravity loading for the initial phase to generate
the initial stress state of soil. Many analysis problems in geotechnical engineering
require the specification of a set of initial stresses. The initial stresses in a soil body are
influenced by the weight of the material and the history of its formation. This stressstate is usually characterized by an initial vertical effective stress (σ'v,0). The initialhorizontal effective stress σ'h,0 is related to the initial vertical effective stress by thecoefficient of lateral earth pressure K0 (σ ′ h, 0 = K0 ⋅ σ ′ v, 0).
Plastic calculation: A Plastic calculation is used to carry out an elastic-plastic
deformation analysis in which it is not necessary to take the change of pore pressure
with time into account. If the Updated mesh parameter has not been selected, thecalculation is performed according to the small deformation theory. The stiffness matrix
in a normal plastic calculation is based on the original undeformed geometry. This typeof calculation is appropriate in most practical geotechnical applications.
Although a time interval can be specified, a plastic calculation does not take time effects
into account, except when the Soft Soil Creep model is used. Considering the quick
loading of saturated clay-type soils, a Plastic calculation may be used for the limitingcase of fully undrained behavior using the Undrained (A), Undrained (B) or Undrained(C) option in the material data sets. On the other hand, performing a fully drained
analysis can assess the settlements on the long term. This will give a reasonably
accurate prediction of the final situation, although the precise loading history is notfollowed and the process of consolidation is not dealt with explicitly.
An elastic-plastic deformation analysis where undrained behavior (Undrained (A) or
Undrained (B) is temporarily ignored can be defined by checking the “Ignore undrained
behavior” (A, B) parameter. In this case the stiffness of water is not taken into account.

83

Note that “Ignore undrained behavior” does not affect materials of which the drainage
type is set to Undrained (C).
In a Plastic calculation loading can be defined in the sense of changing the load
combination, stress state, weight, strength or stiffness of elements, activated bychanging the load and geometry configuration or pore pressure distribution by meansof Staged construction. In this case, the total load level that is to be reached at the endof the calculation phase is defined by specifying a new geometry and load configuration,
and/or pore pressure distribution, in the Staged construction mode.
The options for Pore pressure calculation type for a Plastic phase are:
1. Phreatic
2. Use pressures from previous phase
3. Steady state groundwater flow
Consolidation calculation: A Consolidation calculation is usually conducted when it isnecessary to analyze the development and dissipation of excess pore pressures in asaturated clay-type soil as a function of time. PLAXIS- 3D allows for true elastic-plastic
consolidation analysis. In general, consolidation analysis without additional loading is
performed after an undrained plastic calculation. It is also possible to apply loads during
a consolidation analysis. However, take care when a failure situation is approached,since the iteration process may not converge in such a situation. A consolidation
analysis requires additional boundary conditions on excess pore pressures
In PLAXIS 3D, pore pressures are divided into steady-state pore pressures and excess
pore pressures. Steady state pore pressures are generated according to the waterconditions assigned to the soil layers for each phase, whereas excess pore pressures arecalculated as a result of undrained soil behavior (Undrained (A) or Undrained (B)) or
consolidation. A Consolidation calculation in PLAXIS 3D only affects the excess porepressures. Rather than considering the drainage type settings Undrained (A) or
Undrained (B), a Consolidation calculation considers the corresponding permeabilities
as defined in the Groundwater tab of the material data set instead.

84

A Consolidation calculation does not affect Undrained (C) materials since such materials
do not allow (excess) pore pressures to be generated.
In a Consolidation analysis, the following options are available:
1. Consolidation and simultaneous loading in the sense of changing the load
combination, stress state, weight, strength or stiffness of elements, activated bychanging the load and geometry configuration by means of Staged construction.
It is necessary to specify a value for the Time interval parameter, which has inthis case the meaning of the total consolidation period applied in the current
calculation phase. The load is linearly increased to the specified level within thetime interval. The applied first-time increment is based on the First-time step
parameter in the Numerical control parameters subtree. The Staged
construction option should also be selected if it is desired to allow for a certain
consolidation period without additional loading.

2. Consolidation without additional loading, until all excess pore pressures havedecreased below a certain minimum value, specified by the Minimum excess
pore pressures parameter. By default, the Minimum excess pore pressures is set
to 1 stress unit, but this value may be changed by the user. Please note that the
Minimum excess pore pressures parameter is an absolute value, which applies
to pressure as well as tensile stress. The input of a Time interval is not applicablein this case, since it cannot be determined beforehand how much time is needed
to fulfill the minimum excess pore pressure requirement. The applied first-timeincrement is based on the First-time step parameter in the Numerical control
parameters subtree.
3. Consolidation without additional loading, until a desired degree ofconsolidation, specified by the Degree of consolidation parameter, is reached.
By default, Degree of consolidation parameter is set to 90.0 %, but this value
may be changed by the user. The input of a Time interval is not applicable in thiscase, since it cannot be determined beforehand how much time is needed tofulfill the degree of consolidation requirement. The applied first-time increment85

is based on the First-time step parameter in the Numerical control parameters
subtree.
However, although the degree-of-consolidation is officially defined in terms of target
settlement over final settlement, in PLAXIS-3D it is defined as the target minimum
excess pore pressure over the maximum initial excess pore pressure pmax/pmax, initial.
Dynamic calculation: The Dynamic option should be selected when it is necessary toconsider stress waves and vibrations in the soil. Dynamic loads can come in various
types such as machine induced loads, impact loads, blast load, moving vehicle load or
as earthquake loads. With PLAXIS 3D it is possible to perform a dynamic analysis forthese types of loads after a series of plastic calculations. It is possible to apply dynamic
loads through displacement multipliers or load multipliers. They can be defined as
harmonic or as input table. The applied dynamic load is the product of the input valueof the defined dynamic load and the corresponding dynamic load multiplier. Besides
the activation of the dynamic load or dynamic prescribed displacement, special
absorbent boundary conditions can be defined for a Dynamic calculation. A Dynamic
time interval can be defined to specify the calculation duration and an automatic time
stepping scheme takes care of the best combination of Max steps and Number of substeps, based on the estimated time steps.
Earthquake Analysis: This section provides an overview of the Geotechnical earthquake
modelling and analysis capabilities of PLAXIS. A variety of nonlinear native and UDSM
models for earthquake analysis are offered in PLAXIS. In general, all native models
offered in PLAXIS can be used in combination with Dynamic analysis. However, the user
is expected to know the limitations of each of the models being used. Here are somemodels which are often used in combination with Seismic analysis. HS-small and its
UDSM version GHS can simulate strain dependency of stiffness and hysteretic damping.
UBC3D-PLM (native) and PM4Sand (UDSM) are liquefaction models available in PLAXIS
for which the parameters can be estimated from SPT or CPT data in the absence of lab
tests. Processing and modification of input accelerograms are a key component ofearthquake analysis. Options are available in the dynamic multiplier tab to scale thesignal to the required PGA. Furthermore, the input accelerograms can be easily

86

transformed and visualized as Fourier amplitude spectrum, Power spectrum, PSA as
well as Arias Intensity. A drift correction to correct the displacement drift due to
instrument noise or background noise can also be applied automatically during a
dynamic calculation. Special boundary conditions are required for earthquake motion
in order to minimize wave reflection at model boundaries. The compliant baseboundary condition for the bottom boundary ensures that reflected waves from layers
above are absorbed and allows direct application of an input (upward propagating)accelerogram. Free field boundary conditions for lateral boundaries impose free-fieldmotion at the sides, additionally it absorbs the reflected secondary waves. Tied degrees
of freedom connects the nodes on the same elevation at left and right boundaries,
which can be used to simulate one-dimensional wave propagation.
Energy dissipation due to vibrational or cyclic loading can be defined through Damping.
PLAXIS offers both hysteretic and viscous material damping, as well as numerical
damping. Hysteretic damping is inherent to the HS-small model, whereas, Rayleighdamping is a numerical feature to simulate viscous material damping, which can beapplied in each individual material data set. Numerical damping can be imposed bychanging the default Newmark alpha and beta parameters. Dynamic calculations canbe conducted as drained, undrained or as Dynamic with consolidation. Automatic time
stepping scheme allows for a proper selection of the time step to accurately model
wave propagation and reduce the numerical error due to integration of time history
functions. The user can also control the number of steps using the semi-automatic or
Manual option for accurate modelling.
Curves in Dynamic calculations explains output curves generation options for dynamic
analysis. It is possible to transform the generated curves from the time domain to thefrequency domain automatically using Fast Fourier Transform (FFT). From FFT, PowerSpectrum and Fourier Amplitude Spectrum (FAS) can be plotted for each acceleration
component. From output curves it is possible to produce PSA spectrum to determine
the predominant period as well as Relative displacement response spectrum,
Amplification factor that displays the magnification of the response at a point withrespect to the given excitation, and Arias intensity to determine the strength of a87

ground motion. Furthermore, plots can be generated for extreme accelerations,velocities and displacements for dynamic phases.
It should be noted that steady-state pore pressures in a Dynamic calculation are always
taken from the steady-state pore pressures generated in the parent phase. It is possible
to calculate excess pore pressures in undrained soil layers in a dynamic analysis.
However, the accuracy at which pore pressures are predicted depends on thecapabilities of the soil models being used. A standard dynamic calculation may involve
the generation of excess pore pressures, but not the dissipation of excess porepressures. If the latter is required, a Dynamic with consolidation calculation should be
performed. In a Dynamic calculation loading can be defined in the sense of applying apredefined combination of external loads as dynamic forces using dynamic multipliers
activated in the Staged construction mode. Dynamic calculations can also deal withmoving loads.
4.2.7 Output
The main output quantities of a finite element calculation are the displacements andthe stresses. In addition, when a finite element model involves structural elements, thestructural forces in these elements are calculated. An extensive range of facilities exists
within the PLAXIS-3D Output program to display the results of a finite element analysis.
The main output features of PLAXIS-3D could be classified into four categories:
1. Connectivity plot
A Connectivity plot is a plot of the mesh in which the element connections are clearlyvisualized. It is the result of the meshing process. It is available only in the
representation of spatial variation of the results. This plot is particularly of interest
when interface elements are included in the mesh. Interface elements are composed ofpairs of nodes in which the nodes in a pair have the same coordinates.
In the Connectivity plot however, the nodes in a pair are drawn with a certain distancein between so that it is made clear how nodes are connected to adjacent elements. This
option is available from the Mesh menu. In the Connectivity plot it can, for example, beseen that when an interface is present between two soil elements, that the soil

88elements do not have common nodes and that the connection is formed by theinterface. In a situation where interfaces are placed along both sides of a plate (Positive
interface and Negative interface), the plate and the adjacent soil elements do not havenodes in common. The connection between the plate and the soil is formed by theinterface. An example of Connectivity plot is given in Figure 4.11.

Figure 4.11: Typical connectivity plot in output interface (structure only view)
In the Connectivity plot it is possible to view soil clusters and structural chains that are
excluded from the strength reduction procedure in a (enhanced) safety calculation,
provided that the Hide items without strength reduction option in the View menu has
been selected. These clusters and structures are indicated by a custom color; thedefault color is grey, but this can be changed in the settings of Modifying the display
settings.
2. Deformations
The Deformations menu contains various options to visualize the displacements andstrains in the finite element model. By default, the displayed quantities are scaled
automatically by a factor (1, 2 or 5) ·10n to give a diagram that may be read
conveniently. The scale factor may be changed by clicking the Scale factor button in the89

toolbar or by selecting the Scale option from the View menu. The scale factor for strains
refers to a reference value of strain that is drawn as a certain percentage of thegeometry dimensions. To be able to compare plots of different calculation phases ordifferent projects, the scale factors in the different plots must be made equal.

Figure 4.12: Typical deformation (plan and section) view in output interface
3. Stresses
Various options are available to visualize the stress state in the finite element model.
The Stresses menu also contains options to display the results of groundwater flow andthermal flow calculations. Following parameters can be visualized in PLAXIS-3D output
interface
1. Cartesian effective stresses
2. Cartesian total stresses
3. Principal effective stresses
4. Principal total stresses
5. Initial conditions
6. Pore pressures
7. Groundwater flow
8. Plastic points, etc.

90Figure 4.13: Typical cartesian total stress view in output interface
4. Structures and interfaces
By default, the structures active in the current phase are displayed in the model.
Otherwise, these objects may be displayed in by switching the view on in the
explorer. Output for structures and interfaces can be obtained by clicking the Selectstructures button and then double-clicking the desired object in the 3D model. As aresult, a new form is opened on which the selected object appears. At the sametime the menu changes to provide the particular type of output for the selected
object.
All objects of the same type with the same local coordinate system are automaticallyselected. When multiple objects or multiple groups of objects of the same type need
to be selected, the Shift key should be used while selecting the objects. The last
object to be included in the plot should then be double clicked. When all objects ofthe same type are to be selected, select one of the objects while pressing Ctrl-A
simultaneously. If it is desired to select one or more individual elements from agroup, the Ctrl key should be used while selecting the desired element.
91Another option of selecting structural elements in the output is by clicking the Draga window to select structures button and drawing a rectangle in the model. As aresults, the structures in the rectangle will be selected. Now for understanding theaxial force, shear force and bending moment directions, the Structure axes option
from the View menu may be used to display the beam's local system of axes (1,2,3).
Figure 4.14 and 4.15 shows the local axis direction for beam or embedded beam
structures. Local axis for plates is demonstrated in Figure 4.16-4.18.

Figure 4.14: Forces in beam or embedded beam structure.
a) Local axes. b) Axial force N. c) Shear force Q12. d) Shear force Q13

Figure 4.15: Positive bending moments in beams.
a) Bending Moment M3, b) Bending Moment M2

92

Figure 4.16: Positive axial forces in plates.
a) Local plate directions, b) Axial force N1, c) Axial force N2

Figure 4.17: Positive shear forces in plates.
a) Shear force Q12, b) Shear force Q13, c) Shear force Q23

Figure 4.18: Positive bending moments in plates.
a) Torsion moment M12, b) M11, c) Bending moment M22

93

Figure 4.19: Typical bending moment M11 results view of raft in output interface

Figure 4.20: Typical axial force and bending moment diagram of embedded beamshown in PLAXIS output interface

4.3 Model Validation
Before starting the numerical modeling and parametric study of this research, the
PLAXIS-3D software which has been used was calibrated and validated by remodelingsome previous study examples. The objective of this validation is to make sure the
PLAXIS-3D software is showing perfect results.

94

Validation model-1: A reputed journal on pile raft foundation named” Numericalmodeling and parametric study of piled rafts foundations” authored by Ne’aimi andHussain which was Published online on 6 March 2021 in Arabian Journal of Geosciences(2021) 14: 447. This study presents a series of 3D nonlinear analysis of un-piled andpiled rafts by varying raft thickness and number, spacing and diameter of piles in thegroup. Using the same piled raft geometry, soil, material properties and constitutive
modeling we found the settlement below is similar to the original studies performed by
Ne’aimi and Hussain (2021). The summary of this validation modeling work is given in
Table 4.7.
Table 4.7: Validation of Numerical modeling summary
Input for Validation

#SL

Type

Raft
thick
ness
(m)

1

Piled raft
(10x10) sqm

1

Output

Piles
no.

Pile
dia
(m)

Pile topile
spacing(in termsof dia)

9

0.5

5

Pile
length(m)

18

Original study
Performed by
Ne’aimi andHussain (2021)

Performed
in this
study

173

173

Figure 4.21: Output results showing Settlement values performed during this study

95

Validation model-2: Another reputed journal on pile raft foundation named “3D
Numerical model for piled raft foundation” written by Sinha and Hanna which was
published in International Journal of Geomechanics on 2016. The research presents theeffect of pile length (5m, 10m and 15m) on granular soil for a piled raft foundation
system. Later on, in 2019, Mali and Singh modelled the same for their PLAXIS-3D
software validation. However, the same model once again modeled in this study tovalidate the PLAXIS software. Though in this study, the numerical model has beendeveloped only for one type of pile length. The comparison of three studies is listed inTable 4.8.
Table 4.8: Comparison of Three studies for Validation of Numerical modeling software

Load (kPa)

Original study performed by
Sinha and Hanna (2016)

Performed by Mali and Singh(2019)

Performed in this study

OutputPile length (m)Pile to pile spacing(in terms of diameter)

Pile dia (m)Number of Piles

Raft thickness (m)Foundation TypeSL. No.

Input for Validation

0

0

0

0

100

50

50

52

200

100

100

106

300

180

180

180

400

300

290

294

500

490

480

495

Piled
1

raft
(24x24)

2

16

1

6

5

sqm

From the results, it is observed that the settlement obtained for different loading values
found to be very close and almost similar. Figure 4.22 shows the output of numericalmodel discussed in above.
96

Figure 4.22: Output results showing Settlement values performed during this study
So, from two different model results validate the PLAXIS-3d software that has been used
for this study.
4.5

Parametric StudyIn this study, the effects of raft thickness, pile diameter, pile spacing, and number ofpiles on the displacement of footing system are investigated, and the results areaccordingly compared with the un-piled raft cases. Again, the effect of mesh size wasalso taken in account for un-piled raft. In the parametric study, the immediate,earthquake induced and consolidation settlement of raft and pile, load-sharing,developed stress, pile reaction, bending moment, lateral deflection of piles andretaining wall, and shear force behavior of the large piled-raft foundation on selectedsoil profiles were studied.
In all the parametric study, only one parameter was varied at a time and standard
values were selected for all other parameters. For both un-piled raft and piled raftfoundation system, the length of piles, the soil and material properties were kept

97

constant. A brief summary of the numerical models developed for parametric study are
given in the Table 4.8 and 4.9.
4.5.1 Numerical models for Un-piled raft foundation system
In case of un-piled raft foundation, the raft is rested 18m below existing ground level.
The length and width of the raft is mentioned in Figure 4.23. For this foundation system,
the effect of mesh size and the effect of raft thickness was studied. Total elevennumerical models are developed to analyze the effect of mesh size and raft thickness
for raft foundation. Un-piled foundation numerical models are named “UPR” in thisstudy.

Figure 4.23: Un-piled raft foundation layout plan98For all the combinations mentioned in Table 4.9, the soil profile and depth of raftfoundation (18m below EGL) was kept constant.
Table 4.9: Brief summary of un-piled raft
Name of Numerical model

Mesh size

Raft thickness (m)UPR-1

Very Coarse

2.5

UPR-2

Coarse2.5

UPR-3

Medium

2.5

UPR-4

Very Coarse

3

UPR-5

Coarse3

UPR-6

Medium3

UPR-7

Very Coarse

3.5

UPR-8

Coarse3.5

UPR-9

Medium3.5

UPR-10Medium1

UPR-11

Medium

1.5

4.5.2 Numerical models for Piled raft foundation system
For piled raft foundation system, the raft again rested 18m below existing ground level.
In this case, the effect of pile numbers, pile diameter, pile to pile distance and the raft
thickness were observed. In all combinations, the length of the piles, soil profile anddepth of raft (18m below EGL) were kept constant. In all the piled raft numerical models,
only one parameter was varied at a time and standard values were selected for all otherparameters. Piled raft foundation are mentioned as “PR” in this study. At first, the piled
raft was foundation system was evaluated using 58 nos. piles of different diameters(1m, 1.2m and 1.5m) with different raft thicknesses (2.5m, 3m and 3.5m). Then similarly
the raft was studied for 69 nos. and 82 nos. piles with different pile diameters and raft
thicknesses. In this study, total twenty numerical models are developed for theparametric study of piled raft foundation system using very coarse mesh size only. A
brief summary of all piled raft foundation numerical models is given in Table 4.18.
99

Figure 4.24: Piled raft layout plan for 58 nos. piles of 1m diameter.
Table 4.10: Brief summary of Piled-raft numerical model (for 58 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-1

58

1

2.5

PR-2

58

1

3

PR-3

58

1

3.5

100

Figure 4.25: Piled raft layout plan for 58 nos. piles of 1.2m diameter.
Table 4.11: Brief summary of Piled-raft numerical model (for 58 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-4

58

1.2

2.5

PR-5

58

1.2

3

PR-6

58

1.2

3.5

101

Figure 4.26: Piled raft layout plan for 58 nos. piles of 1.5m diameter.
Table 4.12: Brief summary of Piled-raft numerical model (for 58 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-7

58

1.5

2.5

PR-8

58

1.5

3

PR-9

58

1.5

3.5

102

Figure 4.27: Piled raft layout plan for 69 nos. piles of 1m diameter.
Table 4.13: Brief summary of Piled-raft numerical model (for 69 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-10

69

1

2.5

PR-11

69

1

3

PR-12

69

1

3.5

103

Figure 4.28: Piled raft layout plan for 69 nos. piles of 1.2m diameter.
Table 4.14: Brief summary of Piled-raft numerical model (for 69 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-13

69

1.2

2.5

PR-14

69

1.2

3

PR-15

69

1.2

3.5

104

Figure 4.29: Piled raft layout plan for 69 nos. piles of 1.5m diameter.
Table 4.15: Brief summary of Piled-raft numerical model (for 69 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-16

69

1.5

2.5

PR-17

69

1.5

3

PR-18

69

1.5

3.5

105

Figure 4.30: Piled raft layout plan for 82 nos. piles of 1m diameter.
Table 4.16: Brief summary of Piled-raft numerical model (for 82 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-19

82

1

2.5

PR-20

82

1

3

PR-21

82

1

3.5

106

Figure 4.31: Piled raft layout plan for 82 nos. piles of 1.2m diameter.
Table 4.17: Brief summary of Piled-raft numerical model (for 82 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-22

82

1.2

2.5

PR-23

82

1.2

3

PR-24

82

1.2

3.5

107

Figure 4.32: Piled raft layout plan for 82 nos. piles of 1m diameter.
Table 4.18: Brief summary of Piled-raft numerical model (for 82 nos. piles)
Name of Numericalmodel

Pile number

Pile diameter (m)Raft thickness (m)

PR-25

82

1.5

2.5

PR-26

82

1.5

3

PR-27

82

1.5

3.5

108

Table 4.19: Brief summary of all Piled-raft numerical models
Name of

Pile numbers

Pile diameter (m)Raft thickness (m)

PR-1

58

1

2.5

PR-2

58

1

3

PR-3

58

1

3.5

PR-4

58

1.2

2.5

PR-5

58

1.2

3

PR-6

58

1.2

3.5

PR-7

58

1.5

2.5

PR-8

58

1.5

3

PR-9

58

1.5

3.5

PR-10

69

1

2.5

PR-11

69

1

3

PR-12

69

1

3.5

PR-13

69

1.2

2.5

PR-14

69

1.2

3

PR-15

69

1.2

3.5

PR-16

69

1.5

2.5

PR-17

69

1.5

3

PR-18

69

1.5

3.5

PR-19

82

1

2.5

PR-20

82

1

3

PR-21

82

1

3.5

PR-22

82

1.2

2.5

PR-23

82

1.2

3

PR-24

82

1.2

3.5

PR-25

82

1.5

2.5

PR-26

82

1.5

3

PR-27

82

1.5

3.5

Numerical model109

Chapter 5
RESULTS AND DISCUSSION
5.1 Results of Un-piled Raft Foundation
In this part of the study and without considering the piles in the model, the effects ofdifferent thicknesses of rafts on its overall engineering performance are studied. Basedon the results of the developed numerical models performed in PLAXIS-3D for un-piled
raft foundation system, a detail parametric study has been executed. Effect of raft
thickness and mesh size for an un-piled raft is discussed in this section.
5.1.1 Effect of mesh size
In this study, three mesh sizes have been used to see the sensitivity of mesh sizes on
results obtained in the analysis. For the current study very coarse, coarse and medium
mesh element has been used for both vertical and earthquake loading conditions. From
the numerical analysis results of un-piled raft, it is found that the impact of the meshsizes on different geotechnical and structural parameters are very insignificant. Figure
5.1 and 5.2 shows the total settlement values at raft center and raft corner respectively
with different mesh sizes and mat thicknesses.
Very coarse mesh

Coarse meshMedium mesh

125

Total Settlement, mm

120
115
110
105
100
2

2.5

3

3.5

4

Raft thickness, mFigure 5.1: Effect of mesh size on total settlement values at raft center

110Very coarse mesh

Coarse meshMedium mesh

Total Settlement, mm

19
18
17
16
15
14
13
12
2

2.5

3

3.5

4

Raft thickness, mFigure 5.2: Effect of mesh size on total settlement values at raft center
Again, the effect of mesh size on developed stress beneath raft is also very negligible.
Very coarse mesh

Coarse meshMedium mesh

Max Developed stress, kPa

380
370
360
350
340
330
320
2

2.5

3

3.5

4

Raft thickness, mFigure 5.3: Effect of mesh size on maximum developed stress below raft
Effect of mesh size on bending moment of raft is also studied. Once again, the meshsize does not affect the bending moment value significantly.
Table 5.1 shows a brief summary of the mesh size effect on un-piled raft numericalmodels. Based on the numerical models on eleven different combinations of raft
thickness and mesh size, we can conclude that the effect of mesh size can be ignored in111the parametric study. So, from now onwards, all the un-piled raft parametric studies
are shown for only medium mesh size. However, the results and outputs of all thestudies for different mesh sizes are given Appendix-2.
Very coarse mesh

Coarse meshMedium mesh

28000

Moment, kN-m/m

26000
24000
22000
20000
18000
2

2.5

3

3.5

4

Raft thickness, mFigure 5.4: Effect of mesh size on bending moment values.
Table 5.1 Impact of different mesh size on un-piled numerical models

Mesh
size

Total
settlementat raft
center(mm)

Total
settlementat raft
corner(mm)

Maximum
developed
stressbelow raft
(kPA)

Bending
momentof raft,
M11 (kNm/m)Verycoarse118.6913.62

364.2920860

Coarse119.3113.59

366.72

20850

UPR-3

Medium118.8813.65

371.31

20840

UPR-4

Very
coarse109.1915.9345.5523970

Coarse109.2615.87

346.74

24060

UPR-6

Medium109.4615.98

348.08

24200

UPR-7

Very
coarse104.5718.17

343.1326330

Coarse

104.3

18.15

338.01

26540

Medium103.31

18.25

335.6326750

Foundation
Combination

Raft
thickness
(m)

UPR-1
UPR-2

UPR-5

UPR-8
UPR-9

2.5

3

3.5

112

5.1.2 Effect of raft thickness:
5.1.2.1 Settlement at raft center
Total settlement including immediate, consolidation and earthquake induced
settlement occurred at the raft center is presented in Figure 5.5 for different raft
thicknesses.
250

Settlement (mm)

200

150

100

50

0
0

0.5

1

1.5

2

2.5

3

3.5

4

Raft thickness (m)Immediate Settlement

Consolidation Settlement

Earthquake Induced Settlement

Total Settlement

Figure 5.5: Effect of raft thickness on settlement values at raft center
From Figure 5.5 it is found that, the raft thickness plays a significant role. With theincrease of raft thickness, all the settlement (Immediate, consolidation, earthquake
induced and total settlement) decreases. Though due to increase in raft thickness theself-weight increases but the stiffness also increases due to higher thickness. It is easier
for a rigid raft to distribute the stress throughout the raft preventing it from settling
more locally in the center. Figure 5.5 also shows that the earthquake induced
settlement is minor compared to immediate and consolidation settlement. The
immediate settlement governs here as the soil beneath is raft is granular soil. The
consolidation settlement happened here due to the soil layer of 27m to 30m.
113

5.1.2.2 Settlement at raft corner
Total settlement including immediate, consolidation and earthquake induced
settlement occurred at the raft corner is also studied and presented in Figure 5.6 fordifferent raft thicknesses.
20
18

Settlement (mm)

16
14
12
10
8
6
4
2
0
0

0.5

1

1.5

2

2.5

3

3.5

4

Raft thickness (m)Immediate Settlement
Earthquake Induced Settlement

Consolidation Settlement
Total Settlement

Figure 5.6: Effect of raft thickness on settlement values at raft corner
From Figure 5.6 it is observed that, the raft thickness has impact of settlement values
at raft corner as well. With the increase of raft thickness, all the settlement (Immediate,
consolidation, earthquake induced and total settlement) increases. The behavior isinverse for the settlement at the center of the raft. As the thickness represent therigidity of a raft so, it is easier for a rigid raft to distribute the stress throughout the raftand even in the corners which prevents it from settling more locally in the center.
Instead of settling locally, the raft tends settle uniformly. However, due to stressconcertation at the center, the corner settlements are lower than center settlement
values. Figure 5.6 also shows that the earthquake induced settlement is negligible
compared to immediate and consolidation settlement.

114

5.1.2.3 Differential settlement
The relationship between the raft thickness and differential settlement is inversely
proportional. Stiffness plays the vital roles as discussed earlier in section 5.1.2.1 and5.1.2.2.
215

Settlement (mm)

195
175
155
135
115
95
75
0

0.5

1

1.5

2

2.5

3

3.5

4

Raft thickness

Figure 5.7: Effect of raft thickness on differential settlement values
5.1.2.3 Angular distortion
Angular distortion for different raft thicknesses is shown in Figure 5.8. With the increasein raft thickness, the angular distortion decreases.

Settlement in terms of
distance (mm)0.00480.00430.00380.00330.00280.00230.0018
0

0.5

1

1.5

2

2.5

3

Raft thickness (m)Figure 5.8: Effect of raft thickness on angular distortion

115

3.5

4

5.1.2.4 Maximum developed stressDue to increase in raft thickness the self-weight increases but the stiffness also
increases due to higher thickness. For increasing the stiffness of the raft, the stress is
distributed throughout the raft preventing it from local stress concentration.
800
700

Stress, kPa

600
500
400
300
200
100
0
0

0.5

1

1.5

2

2.5

3

3.5

4

Raft thickness (m)Figure 5.9: Effect of raft thickness on angular distortion
5.1.2.5 Maximum bending moment of raft, M11
The maximum bending moment values obtained from numerical model is shown in
Figure 5.10. Figure 5.10 shows the relation between maximum bending moment, M11
and raft thickness. The bending moment, M11 increases with increase in raft thickness.
30000

Moment (kN-m/m)

25000
20000
M11 due to gravity load

15000

M11 due to Eq load
10000

M11 due to consolidation

5000
0
0

1

2

3

4

Raft thickness (m)Figure 5.10: Effect of raft thickness on maximum bending moment, M11116

5.1.2.6 Maximum bending moment of raft, M22
Figure 5.11 shows the relation between maximum bending moment, M22 and raft
thickness. The bending moment, M22 also increases with increase in raft thickness.

Moment (kN-m/m)

25000

20000

15000
M22 due to gravity load
10000

M22 due to Eq load
M22 due to consolidation

5000

0
0

1

2

3

4

Raft thickness (m)Figure 5.11: Effect of raft thickness on maximum bending moment, M22
5.1.2.7 Maximum torsional moment of raft, M12
Maximum torsional moment for different raft thicknesses is shown in Figure 5.12.
Figure 5.12 shows the relation between maximum torsional moment, M12 and raft
thickness. The torsional moment, M12 also increases with increase in raft thickness.

Moment (kN-m/m)

20000
16000
12000
M12 due to gravity load
8000

M12 due to Eq load
M12 due to consolidation

4000
0
0

1

2

3

4

Raft thickness (m)Figure 5.12: Effect of raft thickness on maximum torsional moment, M12117

5.1.2.8 Maximum shear force of raft, Q12
Maximum Shear force, Q12 developed in numerical model for different raft thicknesses
is shown in Figure 5.13. From the Figure, it is found that the shear force, Q12 increases
with increase in raft thickness.
7000

Shear Force (kN)

6000
5000
4000
Q12 due to gravity load
3000

Q12 due to Eq load

2000

Q12 due to consolidation

1000
0
0

1

2

3

4

Raft thickness (m)Figure 5.13: Effect of raft thickness on maximum shear force, Q12
5.1.2.9 Maximum shear force of raft, Q23
The maximum shear force, Q23 increases as the raft thickness increases up to 2.5m,
after that it starts to decrease. Figure 5.14 shows the relationship between raft
thickness and shear force Q23.
18000

Shear Force (kN)

16000
14000
Q23 due to gravity load

12000

Q23 due to Eq load

10000

Q23 due to consolidation

8000
6000
4000
0

1

2

3

4

Raft thickness (m)Figure 5.14: Effect of raft thickness on maximum shear force, Q23

118

5.1.2.10 Maximum shear force of raft, Q13
Relation between maximum shear force, Q13 and raft thickness is also similar as Q23.
Figure 5.15 shows the relationship between raft thickness and shear force Q13.
20000

Shear Force (kN)

18000
16000
Q13 due to gravity load

14000

Q13 due to Eq load
12000

Q13 due to consolidation

10000
8000
6000
0

1

2

3

4

Raft thickness (m)Figure 5.15: Effect of raft thickness on maximum shear force, Q13
5.1.2.11 Maximum bending moment of Retaining wall, M11
The maximum bending moment values of retaining wall for different raft thickness isshown in Figure 5.16. The retaining wall bending moment, M11 decreases with increasein raft thickness except for raft of 1.5m thickness.
3500

Moment (kN-m/m)

3000
2500
2000
M11 due to gravity load
1500

M11 due to Eq load

1000

M11 due to consolidation

500
0
0

1

2

3

4

Raft thickness (m)Figure 5.16: Effect of raft thickness on maximum bending moment, M11119

5.1.2.12 Maximum bending moment of Retaining wall, M22
The maximum bending moment values of retaining wall for different raft thickness isshown in Figure 5.17. The value of M22 shows irregular behavior for changing raft
thickness.
800

Moment (kN-m/m)

750
700
650
600
550

M22 due to gravity load

500

M22 due to Eq load

450

M22 due to consolidation

400
350
0

1

2

Raft thickness (m)34Figure 5.17: Effect of raft thickness on maximum bending moment, M22
5.1.2.13 Maximum torsional moment of Retaining wall, M12
The maximum torsional moment values of retaining wall for different raft thickness isshown in Figure 5.18. The retaining wall torsional moment, M12 decreases withincrease in raft thickness.
525

Moment (kN-m/m)

500
475
450

M12 due to gravity load
M12 due to Eq load425

M12 due to consolidation

400
375
350
0

1

2

3

4

Raft thickness (m)Figure 5.18: Effect of raft thickness on maximum torsional moment, M12120

5.1.2.14 Maximum shear force of Retaining wall, Q12
Except for raft with 1.5m thickness, the retaining wall shear force, Q12 decreases withincrease in raft thickness.
10000

Shear Force (kN)

9000
8000
7000

Q12 due to gravity load

6000

Q12 due to Eq load
Q12 due to consolidation

5000
4000
3000
0

1

2

3

4

Raft thickness (m)Figure 5.19: Effect of raft thickness on maximum shear force, Q12
5.1.2.15 Maximum shear force of Retaining wall, Q23
The maximum shear force values of retaining wall for different raft thickness is shownin Figure 5.20. The retaining wall shear force, Q23 decreases with increase in raft
thickness up to 2.5m thickness, then it starts to increase after 2.5m thickness.
5000

Shear Force (kN)

4500
4000
Q23 due to gravity load
3500

Q23 due to Eq load
Q23 due to consolidation

3000
2500
0

1

2

3

4

Raft thickness (m)Figure 5.20: Effect of raft thickness on maximum shear force, Q23
121

5.1.2.16 Maximum shear force of Retaining wall, Q13
Except for consolidation settlement, the retaining wall shear force, Q13 increases withincrease in raft thickness. The maximum shear force values of retaining wall for different
raft thickness is shown in Figure 5.21.
6000

Shear Force (kN)

5500
5000
Q13 due to gravity load

4500

Q13 due to Eq load
4000

Q13 due to consolidation

3500
3000
0

0.5

1

1.5

2

2.5

Raft thickness (m)

3

3.5

4

Figure 5.21: Effect of raft thickness on maximum shear force, Q13
5.1.2.17 Maximum normal force of Retaining wall, N1
The maximum normal force values of retaining wall for different raft thickness show
irregular behavior. The maximum normal force values, N1 of retaining wall for different
raft thickness is shown in Figure 5.22.
15500

Normal Force (kN)

13500
11500
N1 due to gravity load

9500

N1 due to Eq load
7500

N1 due to consolidation

5500
3500
0

1

2

3

4

Raft thickness (m)Figure 5.22: Effect of raft thickness on maximum normal force, N11225.1.2.18 Maximum normal force of Retaining wall, N2
The maximum normal force values of retaining wall for different raft thickness is shownin Figure 5.23. The retaining wall normal force, N2 increases with increase in raft
thickness up to 3m raft thickness but it starts to reduce after that.
12000

Normal Force (kN)

10000
8000
6000

N2 due to gravity load
N2 due to Eq load

4000

N2 due to consolidation
2000
0
0

0.5

1

1.5

2

2.5

3

3.5

4

Raft thickness (m)Figure 5.23: Effect of raft thickness on maximum normal force, N2
5.1.2.19 Horizontal deflection of Retaining wall (x-direction)
Figure 5.24 shows that the deflection (x-direction) increases with the increase in raft
thickness up to 3m, but after that it remains almost same.
60

Deflection (mm)50
40Deflection for gravity load
30

Deflectio for EQ load
Deflection for Consolidation20

Total deflection
10
0
0

1

2

3

4

Raft thickness (m)Figure 5.24: Effect of raft thickness on retaining wall horizontal deflection (x direction)1235.1.2.20 Horizontal deflection of Retaining wall (y-direction)
The maximum horizontal deflection at y direction for different raft thicknesses undergravity earthquake load has also been analyzed. The deflection after consolidation
effect has also been taken into account. Figure 5.25 shows that the total deflection,
deflection due to gravity and earthquake load increases with the increase in raft
thickness. However, the deflection due to consolidation increases with the increase inraft thickness up to 3m, after 3m thickness the deflection due to consolidation starts to
reduce. Again, the deflection on the y direction is less than the deflection of x direction
because the earthquake load has been applied on the x direction by prescribed
displacement method in PLAXIS-3D.
18
16

Deflection (mm)

14
12
10
8
6
4
2
0
0

0.5

1

1.5

2

2.5

3

3.5

4

Raft thickness (m)Deflection for gravity load

Deflectio for EQ load

Deflection for Consolidation

Total deflection

Figure 5.25: Effect of raft thickness on retaining wall horizontal deflection (y direction)
All the results and outputs of un-piled raft for different raft thickness are provided inAppendix-2.

124

5.2 Results of Piled Raft Foundation
Based on twenty-seven nos. finite element models developed in PLAXIS-3D software,
the effect of raft thickness, pile diameter and pile number has been studied. Brieffindings of the parametric studies on piled raft are mentioned in this section.
5.2.1 Effect of raft thickness:
5.2.1.1 Settlement at raft center
Total settlement including immediate, consolidation and earthquake induced
settlement occurred at the raft center is presented in Figure 5.26 for different raft
thicknesses.
50

Settlement (mm)

40

30

20

10

0
2

2.5

3

3.5

4

Raft thickness (m)Immediate Settlement

Consolidation Settlement

Earthquake Induced Settlement

Total Settlement

Figure 5.26: Effect of raft thickness on settlement values at raft centerof Piled raft with 58 nos. 1m diameter piles
From Figure 5.26 it is found that, with the increase of raft thickness, all the settlement(Immediate, consolidation, earthquake induced and total settlement) decreases. As
discussed earlier for un-piled raft foundation, it is easier for a rigid raft to distribute the125stress throughout the raft preventing it from settling more locally in the center. Figure5.26 also shows that the earthquake induced settlement and consolidation settlement
is negligible compared to immediate. The immediate settlement governs here as thesoil beneath is raft is granular soil. The consolidation settlement happened here due tothe soil layer of 27m to 30m. As some percentages of the total load is transferred at
60m below through the piles, the consolidation settlement here is less than the un-piled
rafts.
5.2.1.2 Settlement at raft corner
A thicker and stiffer raft can distribute stress at the rafter corners resulting in higher
settlement at the rafter corner than a thinner raft. Figure 5.27 shows the effect of raft
thickness on the settlement values at raft corners.
6

Settlement (mm)

5

4

3

2

1

0
2

2.5

3

3.5

4

Raft thickness (m)Immediate Settlement
Earthquake Induced Settlement

Consolidation Settlement
Total Settlement

Figure 5.27: Effect of raft thickness on settlement values at raft cornerof Piled raft with 58 nos. 1m diameter piles
From Figure 5.27, it is observed that the immediate settlement is again the governing
settlement at the raft corner.

126

5.2.1.3 Differential settlement
Figure 5.28 indicates that the differential settlement of piled raft foundation decreases
with the increase in raft thickness. As discussed, earlies in this section, increase in raft
thickness results in increase in raft stiffness and rigidity. Rigidity of the raft helps toreduce the differential settlement by distributing the stress along the raft area.

Settlement (mm)

35
34
33
32
31
30
29
2

2.5

3

3.5

4

Raft thickness (m)Figure 5.28: Effect of raft thickness on differential settlementof Piled raft with 58 nos. 1m diameter piles
5.2.1.4 Angular distortion
Angular distortion of piled raft foundation decreases with the increase in raft thickness
for the same reason that reduces the differential settlement.

Settlement in terms of
distance (mm)0.000760.000740.00072
0.00070.000680.00066
0.000640.00062
2

2.5

3

3.5

Raft thickness (m)Figure 5.29: Effect of raft thickness on angular distortionof Piled raft with 58 nos. 1m diameter piles

1274

5.2.1.5 Maximum developed stress at raft
The value of maximum stress developed at the raft decreases as the raft thickness
increases. Due to increase in raft thickness the self-weight increases but the stiffness
also increases due to higher thickness. For increasing the stiffness of the raft, the stressis distributed throughout the raft preventing it from local stress concentration.
340

Strees (kPa)

330
320
310
300
290
2

2.5

3

3.5

Raft thickness (m)4Figure 5.30: Effect of raft thickness on maximum developed stressof Piled raft with 58 nos. 1m diameter piles
5.2.1.6 Center pile reaction
The reaction of the center piles decreases with the increase in raft thickness for thesame reason that reduces the maximum developed stress at raft center.

Pile reaction, kN

11000
10000
9000
8000
7000
6000
2

2.5
Pile dia = 1m

3 (m)Raft thickness
Pile dia = 1.2m

3.5
Pile dia = 1.5m

Figure 5.31: Effect of raft thickness on the center pile reactionof Piled raft with 58 nos. piles

1284

5.2.1.7 Corner pile reaction
Figure 5.32 shows that the reaction of corner piles also decreases with the increase inraft thickness.

Pile reaction, kN

3300
3200
Pile dia = 1m

3100

Pile dia = 1.2m
3000

Pile dia = 1.5m

2900
2800
2

2.5

3

3.5

4

Raft thickness (m)Figure 5.32: Effect of raft thickness on the corner pile reactionof Piled raft with 58 nos. piles
5.2.1.8 Settlement of piles
Figure 5.33 shows that the raft thickness does not significantly affect the settlement
value of the center pile. Center piles are not likely to settle much (total settlement
ranges between 7-9mm) as pile tips are rested at 60m below existing ground level
where the soil is very dense sandy layer. However, the settlement value of the corner

Settlement, mm

piles is too little to analyze and hence it is ignored in this study.
9
8
7
6
5
4
3
2
1
0

Immediate settlement
EQ induced settlement
Total settlement

2

2.5

3

3.5

4

Raft thickness (m)Figure 5.33: Effect of raft thickness on the center pile settlementof Piled raft with 58 nos. piles

1295.2.1.9 Maximum bending moment of center piles
The maximum bending moment of center piles decreases as the raft thickness
increases. Figure 5.34 shows the effect of raft thickness on the maximum bending
moment values of center piles.
300

Moment, kN-m

250
200
Moment for Gravity load

150

Moment for EQ load

100

Moment after consolidation
50
0
2

2.5

3

3.5

4

Raft thickness (m)Figure 5.34: Effect of raft thickness on the center pile maximum bending momentof Piled raft with 58 nos. piles
5.2.1.10 Maximum bending moment of corner piles
Figure 5.35 shows the effect of raft thickness on the maximum bending moment valuesof corner piles. Maximum bending moment of corner piles increases with the increasein raft thickness.
800

Moment, kN-m

700
600
Moment for Gravity load
500

Moment for EQ load

400

Moment after consolidation

300
200
2

2.5

3

3.5

4

Raft thickness (m)Figure 5.35: Effect of raft thickness on the corner pile maximum bending momentof Piled raft with 58 nos. piles

1305.2.1.11 Maximum shear force of center piles
The maximum shear force of center piles decreases as the raft thickness increases.
Figure 5.36 shows the effect of raft thickness on the maximum shear force values ofcenter piles.
300

Shear force, kN

250
200
Shear for Gravity load

150

Shear for EQ load
100

Shear after consolidation

50
0
2

2.5

3

3.5

4

Raft thickness (m)Figure 5.36: Effect of raft thickness on the center pile maximum shear forceof Piled raft with 58 nos. piles
5.2.1.12 Maximum shear force of center piles
Figure 5.37 shows the effect of raft thickness on the maximum bending moment valuesof center piles. Maximum bending moment of corner piles increases with the increasein raft thickness.

Shear force, kN

550
500
450

Shear for Gravity load
Shear for EQ load

400

Shear after consolidation
350
300
2

2.5

3

Raft thickness (m)3.5

4Figure 5.37: Effect of raft thickness on the corner pile maximum shear forceof Piled raft with 58 nos. piles1315.2.1.13 Lateral deflection of center and corner piles (along x-direction)
Raft thickness does not affect the lateral deflection value of the piles below the rafts
along x-direction. The deflection along the x-direction of both the center and corner
piles remains in between 23.5-24mm for different raft thicknesses.
5.2.1.14 Maximum moments of raft
As moment is a function raft thickness so the maximum bending moment M11, M22
and the maximum torsional moment M12 all increase as the raft thickness increases.

Moment (kN-m/m)

20000

17500
M11 due to gravity load
15000

M11 due to Eq load
M11 due to consolidation

12500

10000
2

2.5

3

3.5

4

Raft thickness (m)(a)

Moment (kN-m/m)

14000
13000
12000
M22 due to gravity load

11000

M22 due to Eq load
M22 due to consolidation

10000
9000
8000
2

2.5

3

3.5

Raft thickness (m)
(b)

132

4

9000

Moment (kN-m/m)

8000

7000
M12 due to gravity load
M12 due to Eq load

6000

M12 due to consolidation
5000

4000
2

2.5

3

3.5

4

Raft thickness (m)(c)
Figure 5.38: Effect of raft thickness on the raft maximum moments of the piled rafts
with 58 nos. 1m diameter piles. (a) M11, (b) M22, (c)M12
5.2.1.15 Maximum shear forces of raft
The shear force Q12 of the raft increases with the increase in raft thickness. However,the shear force Q23 and Q13 decreases as the raft thickness increases. Figure 5.39
shows the relation between raft thickness and shear forces.
2000

Shear Force (kN)

1900

1800

Q12 due to gravity load

1700

Q12 due to Eq load
Q12 due to consolidation

1600

1500

1400
2

2.5

3

3.5

Raft thickness (m)
(a)

133

4

8500

Shear Force (kN)

8400
8300
8200

Q23 due to gravity load
Q23 due to Eq load

8100

Q23 due to consolidation
8000
7900
7800
2

2.5

3

3.5

4

Raft thickness (m)
(b)
8200

Shear Force (kN)8000

Q13 due to gravity load

7800

Q13 due to Eq load
Q13 due to consolidation

7600

7400
2

2.5

3

Raft thickness (m)

3.5

4

(c)
Figure 5.39: Effect of raft thickness on raft maximum shear forces of piled rafts
with 58 nos. 1m diameter piles. (a) Q12, (b) Q23, (c) Q13
5.2.1.16 Maximum moments of retaining wall
The effect of raft thickness on the retaining wall maximum moments is very minor.
Figure 5.40 shows that the maximum moments M11 and M12 of retaining wall slightly
decreases as the raft thickness increases. However, the torsional moment M12
increases to some extent with the increase in raft thickness.

134

Moment (kN-m/m)

1145

1140

M11 due to gravity load

1135

M11 due to Eq load
M11 due to consolidation
1130

1125
2

2.5

3

3.5

Raft thickness (m)4(a)

Moment (kN-m/m)

300

280
M22 due to gravity load
M22 due to Eq load260

M22 due to consolidation

240
2

2.5

3

3.5

4

Raft thickness (m)(b)

Moment (kN-m/m)

375

370
M12 due to gravity load365

M12 due to Eq load
M12 due to consolidation

360

355
2

2.5

3

3.5

Raft thickness (m)4(c)
Figure 5.40: Effect of raft thickness on retaining wall maximum moments of piled rafts
with 58 nos. 1m diameter piles. (a) M11, (b) M22, (c) M12135

5.2.1.17 Maximum shear forces of retaining wall
For piled raft foundation system, the shear force values of retaining wall increase with
the increase in raft thickness. Figure 5.41 shows the relation between raft thickness andretaining wall shear forces.
2900

Shear Force (kN)

2850
2800
Q12 due to gravity load
2750

Q12 due to Eq load
Q12 due to consolidation

2700
2650
2600
2

2.5

3

3.5

4

Raft thickness (m)
(a)
2250

2200

Shear Force (kN)

2150

2100

Q23 due to gravity load
Q23 due to Eq load

2050

Q23 due to consolidation

2000

1950
2

2.5

3

3.5

Raft thickness (m)
(b)

136

4

3875

Shear Force (kN)3850

Q13 due to gravity load

3825

Q13 due to Eq load
Q13 due to consolidation
3800

3775
2

2.5

3

3.5

4

Raft thickness (m)(c)
Figure 5.41: Effect of raft thickness on retaining wall maximum shear forces of piled
rafts with 58 nos. 1m diameter piles. (a) Q12, (b) Q23, (c) Q13
5.2.1.18 Maximum normal forces of retaining wall
The normal force values N1 and N2 of retaining wall increase with the increase in raft
thickness for piled raft foundation system. Figure 5.42 shows the relation between raft
thickness and retaining wall normal forces.
4250

Normal Force (kN)

4000

3750

3500

N1 due to gravity load
N1 due to Eq load3250

N1 due to consolidation

3000

2750
2

2.5

3

3.5

Raft thickness (m)
(a)

137

4

3800

Normal Force (kN)

3600
3400
3200

N2 due to gravity load
N2 due to Eq load

3000
2800
2600
2

2.5

3

3.5

4

Raft thickness (m)(b)
Figure 5.42: Effect of raft thickness on retaining wall maximum normal forces of piled
rafts with 58 nos. 1m diameter piles. (a) N1, (b) N2
5.2.1.19 Lateral deflection of retaining wall
The effect of raft thickness on the retaining wall lateral deflection is very negligible.
Figure 5.43 shows that the lateral defection along x-direction of retaining wall slightly
increases as the raft thickness increases. However, the lateral defection along ydirection decreases to some extent with the increase in raft thickness.
35

Deflection (mm)3025Deflection for gravity load

20

Deflectio for EQ load

15
10

Deflection for Consolidation

5

Total deflection

0
2

2.5

3

3.5

Raft thickness (m)
(a)
138

4

7

Deflection (mm)65Deflection for gravity load
4
Deflectio for EQ load
3
Deflection for Consolidation2
Total deflection

1
0
2

2.5

3

3.5

4

Raft thickness (m)(b)
Figure 5.43: Effect of raft thickness on retaining wall lateral deflections of piled rafts
with 58 nos. 1m diameter piles. (a) x-direction deflection, (b) y-direction deflection
5.2.1.20 Load distribution between raft and piles
The percent of load shared by the piles decreases with the increase in raft thickness. In
other words, the percent of load shared by the raft increases with the increase in raft
thickness. Increase in thickness increases the stiffness of the raft which allows the raft
to attract more loads. Figure 5.44 shows the comparison of the load shared by the piles
for different raft thickness.

% load taken by piles

23
22
21
20

2.5m raft

19

3m raft

18

3.5m raft

17
16

Raft thickness
Figure 5.44: Effect of raft thickness on % of load sharing of piled rafts
with 58 nos. 1m diameter piles

139

From the parametric study it is observed that, the raft alone takes more than 70% loads.
The reason behind the raft taking this higher percentage of load is, the raft is rested at
18m below existing ground level where the soil is Medium dense to Dense Silty Sand. If
the raft were rested on soft clay type soil, then the higher percentage of load would betransferred to piles.
The effects of raft thickness on different geotechnical and structural parameters havebeen discussed above for only the piled rafts of 58 piles with 1m diameter piles. Piled
rafts having different pile numbers and pile diameters, show the same impacts of raft
thickness and hence it is not mentioned here. Only exception is observed for the raft
shear force Q23 value for 69 piles, where the raft Q23 value increases as the raft
thickness increases. However, the effects of raft thickness on the other piled rafts are
mentioned in Appendix-3.
5.2.2 Effect of Pile numbers
5.2.2.1 Settlement at raft center
Total settlement including immediate, consolidation and earthquake induced
settlement occurred at the raft center is presented in figure 5.45 for different pilenumbers.

Settlement (mm)

40

30

20

10

0
50

55

60

65

70

75

80

Pile number
Immediate Settlement

Consolidation Settlement

Earthquake Induced Settlement

Total Settlement

Figure 5.45: Effect of pile numbers on settlement values at raft centerof Piled raft with 3m raft thickness and 1m diameter piles
140

85

From Figure 5.45 it is found that, with the increase of pile numbers, all the settlement(Immediate, consolidation, earthquake induced and total settlement) decreases. The
higher number of piles helps the raft to transfer some percentages of the loads to thepiles so the settlement below raft is reduced. Figure 5.45 also shows that theearthquake induced settlement and consolidation settlement is minor compared to theimmediate settlement. The immediate settlement governs here as the soil beneath israft is granular soil. The soil layer of 27m to 30m is responsible for consolidation
settlement. The consolidation settlement is very minor compared to un-piled raft as acertain percentage of load is transferred through the piles to pile toe at 60m below
existing ground level where the soil type is very dense sand.
5.2.2.2 Settlement at raft corner
A higher number of piles can reduce the settlement values at raft corner as well. Figure5.46 shows the effect of pile numbers on the settlement values at raft corners. From
Figure 5.46, it is observed that the immediate settlement is again the governing
settlement at the raft corner.

Settlement at Raft corner vs Pile number
5

Settlement (mm)

4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
50

55

60

65

70

75

80

Pile number
Immediate Settlement

Consolidation Settlement

Earthquake Induced Settlement

Total Settlement

Figure 5.46: Effect of pile numbers on settlement values at raft cornerof Piled raft with 3m raft thickness and 1m diameter piles

141

85

5.2.2.3 Differential settlement
Figure 5.47 indicates that the differential settlement of piled raft foundation decreases
with the increase in pile numbers. A certain of load is transferred to piles which helps a
piled raft foundation to reduce the differential settlement. In cases when un-piled raft
is not sufficient to limit the differential settlement, raft with some piles could be theoptimized solution instead of pile only foundation type. Figure 5.47 shows the relation
between pile numbers and differential settlement.

Settlement (mm)

34
32
30
28
26
24
50

55

60

65

70

75

80

85

Pile number
Figure 5.47: Effect of pile numbers on differential settlement valuesof Piled raft with 3m raft thickness and 1m diameter piles
5.2.2.4 Angular distortion
As Figure 5.48 shows, angular distortion of piled raft foundation decreases with theSettlement in termsof distance (mm)increase in pile numbers for the same reason that reduces the differential settlement.
0.00070.000680.00066
0.000640.000620.00060.00058
50

55

60

65

70

75

80

85

Pile number
Figure 5.48: Effect of pile numbers on angular distortion valuesof Piled raft with 3m raft thickness and 1m diameter piles
142

90

5.2.2.5 Maximum developed stress at raft
The value of maximum stress developed at the raft decreases as the pile number
increases. Due to increase in pile numbers, the percent of load shared by piles increases.
For increasing the percentages of load shared by piles, the stress below raft is reduced
to some extent preventing it from local stress concentration on the raft center.
350

Stress, kPa

300
250
200
150
100
50

55

60

65

70

75

80

85

Pile number
Figure 5.49: Effect of pile numbers on maximum developed stress valuesof Piled raft with 3m raft thickness and 1m diameter piles
5.2.2.6 Center pile reaction
The reaction of the center piles decreases with the increase in pile numbers for thesame reason that reduces the maximum developed stress at raft center.

Pile reaction, kN

8000

7500

7000

6500

6000
50

55

60

65

Pile number

70

75

80

Figure 5.50: Effect of pile numbers on center pile reaction valuesof Piled raft with 3m raft thickness and 1m diameter piles
14385

5.2.2.7 Corner pile reaction
Figure 5.51 shows that the reaction of corner piles also decreases with the increase inpile numbers.
3250

Pile reaction, kN

3000
2750
2500
2250
2000
50

55

60

65

Pile number

70

75

80

85

Figure 5.51: Effect of pile numbers on corner pile reaction valuesof Piled raft with 3m raft thickness and 1m diameter piles
5.2.2.8 Settlement of piles
Figure 5.52 shows that the pile number does not significantly affect the settlement
value of the center pile. Center piles are not likely to settle much (total settlement
ranges between 7-9mm) as pile tips are rested at 60m below existing ground level
where the soil is very dense sandy layer. However, the settlement value of the corner
piles is too little to analyze and hence it is ignored in this study.
9

Settlement, mm

8
7
6
5

Immediate settlement

4

EQ induced settlement

3

Total settlement

2
1
0
50

55

60

65

70

Pile number

75

80

85

Figure 5.52: Effect of pile numbers on center pile settlement valuesof Piled raft with 3m raft thickness and 1m diameter piles
144

5.2.2.9 Maximum bending moment of center piles
The maximum bending moment of center piles increases as the pile number increases
upto 69 piles. Beyond 69 piles, it starts to reduce. Figure 5.53 shows the effect of pilenumbers on the maximum bending moment values of center piles.

Moment, kN-m

800
600
Moment for Gravity load
400

Moment for EQ load
Moment after consolidation

200
0
50

55

60

65

70

75

80

85

Pile number
Figure 5.53: Effect of pile numbers on center pile maximum bending moment valuesof Piled raft with 3m raft thickness and 1m diameter piles
5.2.2.10 Maximum bending moment of corner piles
Figure 5.54 shows the effect of pile numbers on the maximum bending moment valuesof corner piles. Except for 69 nos. piles, maximum bending moment of corner piles
decreases with the increase in pile numbers.
650

Moment, kN-m

600
Moment for Gravity load

550

Moment for EQ load
500

Moment after consolidation

450
400
50

55

60

65

70

75

80

85

Pile number
Figure 5.54: Effect of pile numbers on corner pile bending maximum moment valuesof Piled raft with 3m raft thickness and 1m diameter piles

1455.2.2.11 Maximum shear force of center piles
The maximum shear force of center piles increases as the pile number increases upto
69 piles. Beyond 69 piles, it starts to reduce. Figure 5.55 shows the effect of pilenumbers on the maximum shear force values of center piles.
700

Shear force, kN

600
500
400

Shear for Gravity load

300

Shear for EQ load

200

Shear after consolidation

100
0
50

55

60

65

70

Pile number

75

80

85

Figure 5.55: Effect of pile numbers on center pile maximum shear force valuesof Piled raft with 3m raft thickness and 1m diameter piles
5.2.2.12 Maximum shear force of center piles
Figure 5.56 shows the effect of pile numbers on the maximum bending moment valuesof corner piles. Maximum shear force of corner piles decreases with the increase in pilenumbers.

Shear force, kN

500

450
Shear for Gravity load
400

Shear for EQ load
Shear after consolidation

350

300
50

55

60

65

70

75

80

85

Pile number
Figure 5.56: Effect of pile numbers on corner pile maximum shear force valuesof Piled raft with 3m raft thickness and 1m diameter piles
146

5.2.2.13 Lateral deflection of center and corner piles (along x-direction)
Pile number does not affect the lateral deflection value of the piles below the rafts along
x-direction. The deflection along the x-direction of both the center and corner piles
remains in between 23.2-23.7 mm for different pile numbers.
5.2.2.14 Maximum moments of raft
Maximum raft moment M11 and M12 decreases as the pile number increases. But M12
decreases upto 69 nos. piles. Beyond 69 piles, M22 value starts to increase.

Moment (kN-m/m)

16000

15000

14000

M11 due to gravity load
M11 due to Eq load

13000

M11 due to consolidation

12000

11000
50

55

60

65

70

75

80

85

Pile number
(a)
11600

Moment (kN-m/m)

11400
11200
11000
M22 due to gravity load
10800

M22 due to Eq load

10600

M22 due to consolidation

10400
10200
50

55

60

65

70

75

Pile number
(b)

147

80

85

Moment (kN-m/m)

7500

7000

6500

M12 due to gravity load
M12 due to Eq load

6000

M12 due to consolidation

5500

5000
50

55

60

65

70

75

80

85

Pile number(c)Figure 5.57: Effect of pile numbers on raft maximum moment valuesof Piled raft with 3m raft thickness and 1m diameter piles. (a) M11, (b) M22, (c) M12
5.2.2.15 Maximum shear forces of raft
The maximum shear force Q23 and Q13 of raft increases as the pile number increases
upto 69 piles. Beyond 69 piles, it starts to reduce. The shear force Q12 shows the
opposite behavior. Figure 5.58 shows the effect of pile numbers on the maximum shear
force values of center piles.
1850

Shear Force (kN)

1800

1750
Q12 due to gravity load
Q12 due to Eq load

1700

Q12 due to consolidation
1650

1600
50

55

60

65

70

75

Pile number
(a)

148

80

85

22500

Shear Force (kN)

20000
17500
15000

Q23 due to gravity load
Q23 due to Eq load

12500

Q23 due to consolidation
10000
7500
5000
50

60

70

80

90

Pile number
(b)
20000

Shear Force (kN)

18000
16000
14000

Q13 due to gravity load
Q13 due to Eq load

12000

Q13 due to consolidation
10000
8000
6000
50

60

70

80

90

Pile number(c)Figure 5.58: Effect of pile numbers on raft maximum shear force valuesof Piled raft with 3m raft thickness and 1m diameter piles. (a) Q12, (b) Q23, (c) Q123
5.2.2.16 Maximum moments of retaining wall
The effect of pile numbers on the retaining wall maximum moments is very minor.
Figure 5.59 shows that the maximum moments of retaining wall slightly decreases as
the pile number increases.

149

Moment (kN-m/m)

1140
1135
1130

M11 due to gravity load
M11 due to Eq load1125

M11 due to consolidation

1120
1115
50

60

70

80

90

Pile number(a)Moment (kN-m/m)

290
280
270

M22 due to gravity load
M22 due to Eq load260

M22 due to consolidation

250
240
50

60

70

80

90

Pile number(b)Moment (kN-m/m)

364
362
360

M12 due to gravity load
M12 due to Eq load358

M12 due to consolidation
356
354
352
50

60

70

80

90

Pile number(c)Figure 5.59: Effect of pile numbers on retaining wall maximum moment valuesof Piled raft with 3m raft thickness and 1m diameter piles. (a) M11, (b) M22, (c) M12150

5.2.2.17 Maximum shear forces of retaining wall
The maximum shear force Q12 and Q13 of raft decreases as the pile number increases
upto 69 piles. Beyond 69 piles, it starts to increase. The shear force Q23 decreases with
the increase in pile numbers. Figure 5.60 shows the effect of pile numbers on the
maximum shear force values of center piles.
2950

Shear Force (kN)

2900
2850
2800

Q12 due to gravity load
Q12 due to Eq load

2750

Q12 due to consolidation

2700
2650
2600
50

55

60

65

70

75

80

85

Pile number
(a)
2200

Shear Force (kN)

2150
2100
2050

Q23 due to gravity load
Q23 due to Eq load

2000

Q23 due to consolidation

1950
1900
1850
50

55

60

65

70

75

Pile number
(b)

151

80

85

3860

Shear Force (kN)

3855
3850
3845
Q13 due to gravity load

3840

Q13 due to Eq load
3835

Q13 due to consolidation

3830
3825
3820
50

60

70

80

90

Pile number(c)Figure 5.60: Effect of pile numbers on retaining wall maximum shear force valuesof Piled raft with 3m raft thickness and 1m diameter piles. (a) Q12, (b) Q23, (c) Q13
5.2.2.18 Maximum normal forces of retaining wall
The normal force values N1 and N2 of retaining wall decrease with the increase in pilenumbers for piled raft foundation system. Figure 5.61 shows the relation between pilenumbers and retaining wall normal forces.
3900

Normal Force (kN)

3700
3500
3300
N1 due to gravity load
N1 due to Eq load

3100

N1 due to consolidation
2900
2700
2500
50

55

60

65

70

75

Pile number
(a)

152

80

85

3600

Normal Force (kN)

3400
3200
N2 due to gravity load

3000

N2 due to Eq load
2800

N2 due to consolidation

2600
2400
50

60

70

Pile number

80

90

(b)
Figure 5.61: Effect of pile numbers on retaining wall maximum normal force valuesof Piled raft with 3m raft thickness and 1m diameter piles. (a) N1, (b) N2
5.2.2.19 Lateral deflection of retaining wall
The effect of pile numbers on the retaining wall lateral deflection is very negligible.
Figure 5.62 shows that the lateral defection along x-direction of retaining wall slightly
decreases as the pile numbers increases. However, the lateral defection along ydirection decreases to some extent with the increase in pile numbers.
35

Deflection (mm)

30
25
20
15
10
5
0
50

55

60

65

Pile number

70

75

Deflection for gravity load

Deflectio for EQ load

Deflection for Consolidation

Total deflection

(a)

153

80

85

7

Deflection (mm)

6
5
4
3
2
1
0
50

55

60

65

Deflection for gravity load

70

Pile number

Deflection for Consolidation

75

80

85

Deflectio for EQ load
Total deflection(b)
Figure 5.62: Effect of pile numbers on retaining wall lateral deflection of Piled raftwith 3m raft thickness and 1m diameter piles. (a) x-dir deflection, (b) y-dir deflection
5.2.2.20 Load distribution between raft and piles
The percent of load shared by the piles increases with the increase in pile numbers. In
other words, the percent of load shared by the raft decreases with the increase in pilenumbers. Higher number of piles can carry additional load from the superstructure.
However, from the parametric studies, it is found that increasing pile number does notmean that the reduction in settlement further increase, thus beyond some point thesettlement curve tends to behave as a straight line.

% load taken by piles

24
23
22
58 nos piles
21

69 nos piles
82 nos piles

20
19
18

Pile number

Figure 5.63: Effect of pile numbers on % of load sharing of piled rafts
with 3m raft thickness and 1m diameter piles
154

The effects of pile numbers on different geotechnical and structural parameters havebeen discussed above for only the piled rafts with 3m raft thickness and 1m diameter
piles. Piled rafts having different raft thickness and pile diameters, show the same
impacts of pile numbers and hence it is not mentioned here. Only exceptions areobserved as follows:
1. The maximum developed stress below raft for the piled raft of 69 nos. piles of
1.2m and 1.5m diameter is higher than the piled rafts of 58 nos. piles of 1.2m
and 1.5m diameter and 82 nos. piles of 1.2m and 1.5m diameter.
2. Raft bending moment M22 value for the piled rafts of 2.5m thick raft increases
with the increase in pile numbers.
However, the effects of pile numbers on the other piled raft foundations are mentioned
in Appendix-3.
5.2.3 Effect of Pile diameter
5.2.3.1 Settlement at raft center
Total settlement including immediate, consolidation and earthquake induced
settlement occurred at the raft center is presented in Figure 5.64 for different pile
diameters.
50

Settlement (mm)

40

30

20

10

0
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

Pile dia (m)Immediate Settlement
Earthquake Induced Settlement

Consolidation Settlement
Total Settlement

Figure 5.64: Effect of pile diameter on settlement values at raft centerof Piled raft with 2.5m raft thickness and 58 nos. piles
155

1.6

From Figure 5.64 it is found that, with the increase of pile diameter, all the settlement(Immediate, consolidation, earthquake induced and total settlement) decreases. The
large diameter piles help the raft to transfer some percentages of the loads to the piles
so the settlement below raft is reduced. Figure 5.64 also shows that the earthquake
induced settlement and consolidation settlement is minor compared to the immediate
settlement. The immediate settlement governs here as the soil beneath is raft isgranular soil. The soil layer of 27m to 30m is responsible for consolidation settlement.
The consolidation settlement is very minor compared to un-piled raft as a certain
percentage of load is transferred through the piles to pile toe at 60m below existing
ground level where the soil type is very dense sand.
5.2.3.2 Settlement at raft corner
Larger diameter of piles can reduce the settlement values at raft corner as well. Figure
5.65 shows the effect of pile diameter on the settlement values at raft corners. From
Figure 5.65, it is observed that the immediate settlement is again the governing
settlement at the raft corner.
4.5
4Settlement (mm)

3.5
3
2.5
2
1.5
1
0.5
0
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

Pile dia (m)Immediate Settlement
Earthquake Induced Settlement

Consolidation Settlement
Total Settlement

Figure 5.65: Effect of pile diameter on settlement values at raft cornerof Piled raft with 2.5m raft thickness and 58 nos. piles
156

1.6

5.2.3.3 Differential settlement
Figure 5.66 indicates that the differential settlement of piled raft foundation decreases
with the increase in pile diameters. A certain of load is transferred to piles which helps
a piled raft foundation to reduce the differential settlement. In cases when un-piled raftand piled raft with small diameter pile is not sufficient to limit the differential
settlement, raft with larger diameter piles could be the optimized solution instead ofpile only foundation type. Figure 5.66 shows the relation between pile diameters anddifferential settlement.

Settlement (mm)

36
34
32
30
28
26
24
22
20
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Pile dia (m)Figure 5.66: Effect of pile diameters on differential settlement valuesof Piled raft with 2.5m raft thickness and 58 nos. piles
5.2.3.4 Angular distortion
As Figure 5.67 shows, angular distortion of piled raft foundation decreases with theSettlement in terms of
distance (mm)increase in pile diameters for the same reason that reduces the differential settlement.
0.00080.000750.00070.000650.00060.00055
0.0005
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

Pile dia (m)Figure 5.67: Effect of pile diameters on angular distortion valuesof Piled raft with 2.5m raft thickness and 58 nos. piles
157

1.6

5.2.3.5 Maximum developed stress at raft
The value of maximum stress developed at the raft decreases as the pile diameterincreases. Due to increase in pile diameters, the percent of load shared by piles
increases. For increasing the percentages of load shared by piles, the stress below raft
is reduced to some extent preventing it from local stress concentration on the raft
center.
350

Stress, kPa

300

250

200

150
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Pile dia (m)Figure 5.68: Effect of pile diameters on maximum developed stress valuesof Piled raft with 2.5m raft thickness and 58 nos. piles
5.2.3.6 Center pile reaction
Figure 5.69 shows that, the reaction of the center piles increases with the increase inpile diameters.

Pile reaction, kN

11000

10000

9000

8000
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

Pile dia (m)Figure 5.69: Effect of pile diameters on center pile reaction valuesof Piled raft with 2.5m raft thickness and 58 nos. piles
158

1.6

5.2.3.7 Corner pile reaction
Figure 5.70 shows, the reaction of corner piles also increases with the increase in pile
diameters upto 1.2m diameter. Beyond 1.2m diameter, the reaction does not increase.

Pile reaction, kN

3300
3250
3200
3150
3100
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Pile dia (m)Figure 5.70: Effect of pile diameters on corner pile reaction valuesof Piled raft with 2.5m raft thickness and 58 nos. piles
5.2.3.8 Settlement of piles
Figure 5.71 shows that the pile diameter does not significantly affect the settlement
value of the center pile. Center piles are not likely to settle much (total settlement
ranges between 7-9mm) as pile tips are rested at 60m below existing ground level
where the soil is very dense sandy layer. However, the settlement value of the corner
piles is too little to analyze and hence it is ignored in this study.
9

Settlement, mm

8
7
6
5

Immediate settlement

4

EQ induced settlement

3

Total settlement

2
1
0
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Pile dia (m)Figure 5.71: Effect of pile diameters on center pile settlement valuesof Piled raft with 2.5m raft thickness and 58 nos. piles

1595.2.3.9 Maximum bending moment of center piles
The maximum bending moment of center piles increases as the pile diameter increases.
Figure 5.72 shows the effect of pile diameters on the maximum bending moment valuesof center piles.
1200

Moment, kN-m

1000
800
Moment for Gravity load

600

Moment for EQ load

400

Moment after consolidation

200
0
0.8

1

1.2

1.4

1.6

Pile dia (m)Figure 5.72: Effect of pile diameters on center pile maximum bending moment valuesof Piled raft with 2.5m raft thickness and 58 nos. piles
5.2.3.10 Maximum bending moment of corner piles
Figure 5.73 shows the effect of pile diameters on the maximum bending moment valuesof corner piles. Maximum bending moment of corner piles increases with the increasein pile diameters.
1000

Moment, kN-m

900
800
Moment for Gravity load
700
Moment for EQ load
600
Moment after consolidation
500
400
0.8

1

1.2

1.4

Pile dia (m)1.6

Figure 5.73: Effect of pile diameters on corner pile bending maximum moment valuesof Piled raft with 2.5m raft thickness and 58 nos. piles

160

5.2.3.11 Maximum shear force of center piles
The maximum shear force of center piles increases as the pile diameter. Figure 5.74
shows the effect of pile diameters on the maximum shear force values of center piles.
500

Shear force, kN

450
400
350
Shear for Gravity load

300

Shear for EQ load

250

Shear after consolidation

200
150
100
0.8

1

1.2

1.4

1.6

Pile dia (m)Figure 5.74: Effect of pile diameters on center pile maximum shear force valuesof Piled raft with 2.5m raft thickness and 58 nos. piles
5.2.3.12 Maximum shear force of center piles
Figure 5.75 shows the effect of pile diameters on the maximum bending moment valuesof corner piles. Maximum shear force of corner piles increases with the increase in pile
diameters.
600

Shear force, kN

550
500
Shear for Gravity load

450

Shear for EQ load
400

Shear after consolidation

350
300
0.8

1

1.2

1.4

1.6

Pile dia (m)Figure 5.75: Effect of pile diameters on corner pile maximum shear force valuesof Piled raft with 2.5m raft thickness and 58 nos. piles

161

5.2.3.13 Lateral deflection of center and corner piles (along x-direction)
Pile diameter does not affect the lateral deflection value of the piles below the rafts
along x-direction. The deflection along the x-direction of both the center and corner
piles remains in between 23.2-23.6 mm for different pile diameters.
5.2.3.14 Maximum moments of raft
Figure 5.76 shows that maximum raft moments M11, M22 and M12 decreases as thepile diameter increases.

Moment (kN-m/m)

13000

12500

12000
M11 due to gravity load
M11 due to Eq load

11500

M11 due to consolidation
11000

10500
0.8

1

1.2

1.4

1.6

Pile dia (m)(a)

Moment (kN-m/m)

10000

9500

M22 due to gravity load

9000

M22 due to Eq load
M22 due to consolidation
8500

8000
0.8

1

1.2

1.4

Pile dia (m)
(b)

162

1.6

6000

Moment (kN-m/m)

5500
5000
M12 due to gravity load
M12 due to Eq load

4500

M12 due to consolidation
4000
3500
3000
0.8

1

1.2

1.4

1.6

Pile dia (m)(c)
Figure 5.76: Effect of pile diameters on raft maximum moment valuesof Piled raft with 2.5m raft thickness and 58 nos. piles. (a) M11, (b) M22, (c) M12

5.2.3.15 Maximum shear forces of raft
The maximum shear force Q23 and Q13 of raft increases as the pile diameter increases.
However, the shear force Q12 shows the opposite behavior. Figure 5.77 shows theeffect of pile diameters on the maximum raft shear force values of center piles.
1700

Shear Force (kN)

1600
1500
1400

Q12 due to gravity load
Q12 due to Eq load

1300

Q12 due to consolidation

1200
1100
1000
0.8

1

1.2

1.4

Pile dia (m)
(a)

163

1.6

10500

Shear Force (kN)

10000

9500

Q23 due to gravity load
Q23 due to Eq load

9000

Q23 due to consolidation

8500

8000
0.8

1

1.2

1.4

1.6

Pile dia (m)
(b)
8800

Shear Force (kN)8600

Q13 due to gravity load

8400

Q13 due to Eq load
Q13 due to consolidation

8200

8000

7800
0.8

1

1.2

1.4

1.6

Pile dia (m)(c)
Figure 5.77: Effect of pile diameters on raft maximum shear force valuesof Piled raft with 2.5m raft thickness and 58 nos. piles. (a) Q12, (b) Q23, (c) Q13
5.2.3.16 Maximum moments of retaining wall
The effect of pile diameters on the retaining wall maximum moments is very minor.
Figure 5.78 shows that the maximum moments M22 and M12 of retaining wall slightly
decreases as the pile diameter increases. But moment M11 slightly increases with theincrease in pile diameter.

164

Moment (kN-m/m)

1155

1150

M11 due to gravity load

1145

M11 due to Eq load
M11 due to consolidation

1140

1135
0.8

1

1.2

1.4

1.6

Pile dia (m)(a)

Moment (kN-m/m)

275

250
M22 due to gravity load
M22 due to Eq load
225

M22 due to consolidation

200
0.8

1

1.2

1.4

1.6

Pile dia (m)(b)

Moment (kN-m/m)

375
370
365

M12 due to gravity load
M12 due to Eq load360

M12 due to consolidation
355
350
0.8

1

1.2

1.4

1.6

Pile dia (m)(c)
Figure 5.78: Effect of pile diameters on retaining wall maximum moment valuesof Piled raft with 2.5m raft thickness and 58 nos. piles. (a) M11, (b) M22, (c) M12165

5.2.3.17 Maximum shear forces of retaining wall
The maximum shear force Q12 and Q23 of raft decreases as the pile diameter increases.
However, the shear force Q13 increases with the increase in pile diameters. Figure 5.79
shows the effect of pile diameters on the maximum shear force values of center piles.

Shear Force (kN)

3000
2800
2600

Q12 due to gravity load
Q12 due to Eq load

2400

Q12 due to consolidation

2200
0.8

0.9

1

1.1

1.2

1.3

Pile dia (m)

1.4

1.5

1.6

(a)

Shear Force (kN)

2100
2000
Q23 due to gravity load

1900

Q23 due to Eq load
1800

Q23 due to consolidation

1700
0.8

0.9

1

1.1

1.2

1.3

Pile dia (m)

1.4

1.5

1.6

(b)

Shear Force (kN)

3840

3820

Q13 due to gravity load
Q13 due to Eq load
Q13 due to consolidation

3800

3780
0.8

1

1.2

1.4

1.6

Pile dia (m)(c)
Figure 5.79: Effect of pile diameters on retaining wall maximum shear force valuesof Piled raft with 2.5m raft thickness and 58 nos. piles. (a) Q12, (b) Q23, (c) Q13
166

5.2.3.18 Maximum normal forces of retaining wall
The normal force values N1 and N2 of retaining wall decrease with the increase in pile
diameters for piled raft foundation system. Figure 5.80 shows the relation between pile
diameters and retaining wall normal forces.
3100

Normal Force (kN)

3000
2900
2800
2700
2600
2500
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Pile dia (m)N1 due to gravity load

N1 due to Eq load

N1 due to consolidation

(a)
3200

Normal Force (kN)

3000
2800
2600
2400
2200
2000
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Pile dia (m)N2 due to gravity load

N2 due to Eq load

N2 due to consolidation(b)
Figure 5.80: Effect of pile diameters on retaining wall maximum normal force valuesof Piled raft with 2.5m raft thickness and 58 nos. piles. (a) N1, (b) N2

167

5.2.3.19 Lateral deflection of retaining wall
The effect of pile diameters on the retaining wall lateral deflection is very negligible.
Figure 5.81 shows that the lateral defection along x-direction of retaining wall slightly
decreases as the pile diameter increases. The lateral defection along y-direction also
decreases to some extent with the increase in pile diameters.
35

Deflection (mm)

30
25
20
15
10
5
0
0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.5

1.6

Pile dia (m)Deflection for gravity load

Deflectio for EQ load

Deflection for Consolidation

Total deflection(a)6Deflection (mm)

5

4

3

2

1

0
0.8

0.9

1

Deflection for gravity load

1.1

1.2

Pile dia (m)Deflection for Consolidation

1.3

1.4
Deflectio for EQ load
Total deflection(b)
Figure 5.81: Effect of pile diameters on retaining wall lateral deflection of Piled raftwith 2.5m raft thickness and 58 nos. piles. (a) x-dir deflection, (b) y-dir deflection344

5.2.3.20 Load distribution between raft and piles
The percent of load shared by the piles increases with the increase in pile diameters. In
other words, the percent of load shared by the raft decreases with the increase in pile
diameters. Larger diameter of piles can carry additional load from the superstructure.
However, from the parametric studies, it is found that increasing pile diameter does notalways reduce total and differential settlement significantly. Even, the percentage ofload shared by piles does not significantly change for increasing pile diameter for thisselected structure.
30% load taken by piles

25

20
1m dia pile
15

1.2m dia pile
1.5m dia pile

10

5

0

Pile diaFigure 5.82: Effect of pile diameters on % of load sharing of piled raftsof Piled raft with 2.5m raft thickness and 58 nos. piles
The effects of pile diameters on different geotechnical and structural parameters havebeen discussed above for only the piled rafts with 3m raft thickness and 1m diameter
piles. Piled rafts having different raft thickness and pile diameters, show the same
impacts of pile diameters and hence it is not mentioned here. Only exception is foundfor normal force of retaining wall for the piled rafts with 69 piles. The N1 value changes
with irregular with the increase in pile diameter. However, the impacts of pile diameterson the other piled raft foundations are mentioned in Appendix-3.

345

PART-V

EVALUATION OF CONSOLIDATIONCHARACTERISTICS FROM PIEZOCONEPENETRATION TESTBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Mohd Salman Mazhar
Mehedi Ahmed AnsaryChapter 1
INTRODUCTION
1.1 General
Determining the compressibility characteristics of fine-grained soils, due to structuralloadings or constructional activity, has always been an engineering discourse. It experiences large consolidation settlement over a long period of time and can be detrimental toboth life and property. Therefore, it is imperative to appraise the magnitude and time rateof consolidation settlement accurately. Strength and compressibility characteristics aremostly interpreted from in-situ tests and laboratory tests. Even though Standard Penetration Test (SPT) is a widely used in-situ test in Bangladesh; efforts to standardize the SPT
procedure has been a primary concern among engineers in the region—problems linked
to consistency, repeatability, and reliability persists Saha (2015). Moreover, undisturbed
samples required for the oedometer tests are small and are usually subjected to an unknown
degree of disturbance. Consequently, laboratory determined consolidation parameters often underestimate the actual in-situ conditions Bishop and Al-Dhahir (1969).
Robertson (1986, 2012a) highlighted various geotechnical parameters, required for foundation design and analysis, that correlate with CPTu data. In addition, in-situ tests otherthan CPTu, for evaluating: soil pore pressure; compressibility characteristics; and the time
rate of consolidation are listed according to their estimation degree by Robertson (2012a).
This list also exhibits the reliability of CPTu in determining the essential geotechnical parameters. The perceived applicability for most of these parameters range from moderate tohigh. In contrast to laboratory testing, Mitchell et al. (1978) addressed the precision, speed,and feasibility of in-situ tests in assessing geotechnical parameters. CPTu provides rigorous subsurface profile due to its near continuous and uninterrupted data—tip resistance 𝑞 𝑐 ,sleeve friction 𝑓𝑠 , and pore water pressure (𝑢 2 ) (Robertson, 2009). These measurements
are correlated with several geotechnical parameters, hence making it valuable for numerous geotechnical applications on assorted soils [example:Krage et al. (2015), Robertson(2009), Shahri and Naderi (2016), Sully et al. (1999), and Yu and Abu-Farsakh (2011)].
As a result, expensive and time-consuming laboratory tests can be replaced with in-situ
CPTu tests to characterize geotechnical parameters.
However, correlation models proposed in existing literature give equivocal results for different soil deposits, as outlined by Robertson (1986). Therefore, to attain an effective correlation, the model needs to be calibrated based on local experience. Given the inexorable
pace of CPTu research, development, and popularity; it is imperative that Bangladesh continues developing its own set of statistical correlations, and establish the consolidation346

parameters from CPTu.
1.2 Objectives
A review of the literature reveals an absence of an experimental research program thatquantifies consolidation parameters from CPTu in the context of Bangladesh. To quantify
the consolidation characteristics of soils using piezocone penetrometers (also known as
CPTu), the Committee for Advanced Studies and Research (CASR) of BUET has aided ininitiating and funding a research program to fulfill this goal. The objectives are:
1. To evaluate the reliability of existing CPTu interpretation methods to estimate consolidation parameters, required for determining the magnitude and time rate of consolidation settlement, in the context of Bangladesh soil.
2. To develop and build a local correlation between CPTu and consolidation parametersof cohesive soils, and justify the reliability and interpretation of the correlations withlaboratory determined consolidation parameters.
1.3 Thesis Organization and Background Information
The dissertation was written in a thesis format consisting of five chapters—the introduction, literature review, description of the experimental program, and finally the conclusion
section.
Following Chapter 1, Chapter 2 presents the theoretical background behind the principlesof CPTu. This chapter focuses on the contribution of several investigators in interpreting
CPTu data to correlate it with key geotechnical engineering parameters. In this study, theseparameters include the overconsolidation ratio, constrained modulus, compression index,
small-strain shear modulus, rigidity index, and coefficient of consolidation. The different
types of CPTu cones are also presented by outlining their advantages and limitations. The
last section in this chapter examines the importance of statistical analysis in geotechnicalengineering.
Chapter 3 focuses on the geotechnical investigations conducted in the Dhaka region study
area. Also, the laboratory investigation program implemented in conjunction with the
CPTu soundings to develop local correlations is detailed in this chapter.
Chapter 4 presents the analysis performed to develop local correlations for CPTu parameters with laboratory-derived constrained modulus, compression index, OCR, coefficientof consolidation, and undrained shear strength. The performance of existing correlations
is quantified and graphically presented in this chapter.
Finally, Chapter 5 summarizes the main conclusion from the experimental analysis followed by recommendations from this research and suggestions for future work.

Chapter 3
GEOTECHNICAL INVESTIGATION
3.1 Introduction
This chapter summarizes the field investigations and the laboratory tests conducted in the
Dhaka region. As seen in Figure 3.1, Rajdhani Unnayan Kartripakkha (RAJUK) supervised numerous in situ tests in Dhaka region as part of the Urban Resilience Project in2019. Around 15% of the tests were validated in BUET. The author personally conducted
the required laboratory tests for this research. Consequently, nineteen (19) points wereselected for scrutiny. Additionally, from the 19 points, 10 points underwent the piezocone
dissipation test. The location of these points is tabulated in Table 3.1.
The research objectives were met by conducting an experimental program comprising
three phases. Figure 3.2 shows the different research phases, outlining the focus required
at each phase to reach the objectives of this study. The first phase comprised collecting
in situ data employing CPTu and SPT as a part of the Urban Resiliency Project in 2019,supervised by the RAJUK part. The second phase involved conducting several geotechnical tests in the laboratory. The collection and analysis of these data synthesized a databank comprising of in situ and laboratory tests. The database was created using Microsoft
Excel software. The third phase expanded on this database by updating it with the laboratory test results. This research focused on quantifying key geotechnical parameters suchas undrained shear strength, constrained modulus, preconsolidation stress, coefficient ofconsolidation, and compression index. 19 points of in situ tests from this database were
examined to fulfill the objectives of this thesis.
3.2 Geologic Formation of the Research Site
Dhaka is the capital city of Bangladesh in South Asia. The urban area spans at 305.47𝑘𝑚 2 ,whereas the metro area spans around 2,161.17𝑘𝑚 2 . Geologically, it lies in the Bengal
Basin block, near the southern tip of the Madhupur tract. Due to its location on the lowland
plain of the Ganges Delta, the north is bounded by the Tongi Khal (Small River); theeastern portion bounded by the Balu River; the south and south east portion is bounded by
the Buriganga River; and the Turag River in the west. Regionally, Dhaka is located in thecentral part of the Bengal basin. Since the topography of Dhaka is flat and close to sea level,
it is susceptible to flooding during heavy rainfall and cyclones in the monsoon seasons. The
greater Dhaka area is bounded by the districts of Manikganj, Tangail, Narsingdi, Gazipur,
Rajbari, Munshiganj, and Narayanganj.
The subsurface geology of Dhaka city comprises of 6 to 12m thick formation of Madhupur
54

55

Figure 3.1: Study Site and locations of CPTu and SPT conducted.
Clay layer. The composition of Madhupur Clay is mainly Kaolinite (27% to 53%) and Illite(14% to 33%). Very small traces of Illite smectite (2%) is also found up to a depth of 5m.
Course grained soil deposit underlies the Madhupur Clay layer. (Zahid et al., 2004)
Kamal and Midorikawa (2004) presented a detailed GIS-based geomorphological map of
the Dhaka region by utilizing aerial photographs and the topographic map. The photos

56

Figure 3.2: Research Phases for this Study.
BH-ID
BH-05
BH-06
BH-18
BH-24
BH-27
BH-68
BH-97
BH-123
BH-146
BH-250
BH-253
BH-264
BH-274
BH-285
BH-296
BH-364
BH-365
BH-374
BH-398CPT-ID
CPT-10
CPT-16
CPT-149
CPT-56
CPT-58
CPT-2
CPT-20
CPT-30
CPT-36
CPT-84
CPT-86
CPT-93
CPT-100
CPT-107
CPT-105
CPT-132
CPT-134
CPT-140
CPT-149

Dissipation Test
Yes
Yes
Yes
Yes
No
No
No
No
Yes
Yes
No
Yes
Yes
No
No
No
No
Yes
Yes

Location
Tingao, Narayanganj
Aligonj Madrasa, Fatullah
Demra, Dhaka
Shere Bangla Nagar Agricultural University, Dhaka
Aftab Nagar, Dhaka
Anondo Bazaar, Fatullah
Anondo Bazaar, Fatullah
Modonpur, Narayanganj
Jatrabari, Dhaka
Badda Government Primary School, Savar
Kakabo Birulia, Savar
Kuliyadi Government Primary School, Narayanganj
Uttara, Dhaka
Ashulia, Dhaka
Annondo Bazaar Fatullah
Anondo Bazaar, Fatullah
Kashimpur, Gazipur
Keshorita Government Primary School, Gazipur
Bahadurpur Government Primary School, Gazipur

Table 3.1: Locations of the in situ points.
were interpreted by differentiating the ground of Dhaka region into 18 geomorphologicalunits. Rapid expansion of the city is observed since 1960, even in the low-lying geomorphic units—by fill practices. Based on the thickness of the fills, the fill-sites were classified
into four classes. This required data from the boreholes and an topographic map preparedin 1961. Figure 3.3 shows the geological map of Bangladesh. It is also seen that Alluvial
Silt; Madhupur Clay residium; and Alluvial Silt and Clay, dominates the Dhaka region.
The characteristics of these deposits are summarized:
1. Madhupur Clay Residium: The color of these deposits ranges from light yellowishgrey, orange, and light to brick red and grayish-white. Consists of micaceous silty
clay to sandy clay. Plastic in nature and abundantly mottled in the upper 8m of
the subsurface. It also contains small clusters of organic matter. Sand fraction isdominantly quartz; minor feldspar and mica; sand content increases with depth.

57

Figure 3.3: Geological Map of Bangladesh (after Persits et al., 2001)
Dominant clay minerals are kaolinite and Illite. Iron manganese oxide modules arerare.
2. Alluvial Silt: The color of these deposits ranges from light to medium grey andconsists of fine sand to clayey silt. Illite is the primary clay mineral. Generally,
it is poorly stratified. Also, the average grain size decreases away from the main
channels. These deposits are predominantly present in the flood basins and the interstream areas. Units include small back swamp deposits and varying episodic or
unusually large floods. Most of these areas have been flooded annually. Includedin this unit are thin veneers of sand spread by episodic large floods over flood plain
silts. Historic pottery, artifact, and charcoal were found in the upper 4 m.
3. Alluvial Sily and Clay: The color of these deposits ranges from medium to darkgrey and consists of Silt to Clay. The more the organic content, the darker the color

58
gets. The map unit in Figure 3.3 indicates that its unit is a combination of alluvial
and paludal deposits, flood-basin silt, black swampy silty clay, and organic Clayfound in sag ponds and large depressions. These depressions may have peat as well.
Large areas underlain by this unit are dry for only a few months in a year. The deeper
part of depressions and beels contains water throughout the year.
3.3 Field Investigations
A total of ninteen (19) pairs of CPT and SPT, performed up to a depth of at least 30m, wereselected for this study. As seen in Figure 3.1, each pair of CPT and SPT were executed
within 1m of each other.
3.3.1 Cone Penetration Test Equipment

Figure 3.4: The Gouda Geo-Equipment B.V. 350 kN CPT Penetrometer Pusher in
Narayanganj, Dhaka
As shown in Figure 3.4, the CPT equipment consisted of a cone penetrometer, pushingequipment and data acquistion systems. The CPT soundings were advanced using a Gouda
Geo-Equipment B.V piezocone penetrometer cone of 60°, having a cross-sectional areaof 15cm2 . The position of the porus filter—to measure pore pressure—is behind the cone(𝑢 2 ). This penetrometer is a subtraction-type cone penetrometer.

59
To perform the test, a hydraulic power pack—powered by an 18kW diesel engine—witha thrust capacity of 350kN pushes the cone at 2cm/s. During the advancement, it can simultaneously and continuously measure 𝑞 𝑐 , 𝑓𝑠 , 𝑢 2 at 10mm depth increments. The typical
penetration depth in this in situ program was 30m from the existing ground level.
The data acquisition system was suitable for both digital and analog piezocones. The CPTlogger was connected to a laptop computer for synchronizing CPT data with depth.

Figure 3.5: Typical CPT profile generated near BH-05 in Tingao, Narayanganj
A typical soil profile generated is shown in Figure 3.5. 𝑞 𝑐 was corrected to account forpore pressure effects as discussed in Section 2.3.4. SBT was generated using Equation 2.4.
The corresponding methodology is described in Chapter 2.4. Using the parameters shownin Figure 3.5, the normalized Robertson (2010) chart was generated for the 19 points asshown in Figure 3.6.
Referring to Figure 2.17, Figure 3.6 reveals that the soil data is concentrated in region 5,
which is the ”Sand mixtures—silty sand to sandy silt”. Regions 3 and 4 represent ”Clays—
silty clay to clay” and ”Silt mixtures—clayey silt to silty clay”. Also, as seen in the bottom
left of region 3, the Clays in this chart is mostly normally consolidated area with many data
points concentrated in the region indicating ”increasing sensitivity”. For CPT profiles andcharts synthesized for this study, the reader can refer to Appendix A.2.

60

SBTn, Robertson 2010

Normalized Cone Resistance, Qtn

103
7

8, 9

102
6
101

5

4
1

100 1
10

3

100
Normalized Friction Ration, FR, %2
101

Figure 3.6: A typical normalized SBT chart generated near BH-05 in Tingao, Narayanganj.

61
3.3.2 Standard Penetration Tests
As shown in Figure 3.7, a rotary drill rig was employed for drilling the boreholes. The
boring was advanced using the wash-boring method and a diamond cutter. A steel case isused to protect the topmost 1.0m depth of the borehole. The SPT was conducted as per
ASTM D1586-18 (Standard Test Method for Standard Penetration Test and Split-Barrel
Sampling of Soils). Field SPT N-values were recorded at 1.5m intervals using a donut
auto-tripped hammer. The refusal criterion was set to at least 30m if the N-value is 50
with 230mm or less penetration in last consecutive three layers.

Figure 3.7: SPT by rotary drill rig conducted in Uttara, Dhaka.
Disturbed and undisturbed sampling were according to ASTM D1586. The samples werecollected in a zipper plastic bag and stored in an airtight box. Shelby tube was used for
undisturbed sampling—conforming to the specifications set out in ASTM D1587/D1587M15 (Standard Practice for Thin-Walled Tube Sampling of Fine-Grained Soils for Geotechnical Purposes.)
A typical SPT profile is shown in Figure 3.8. Here, the exploration depth is up to 31.5m.
The range of SPT is seen between 4 and 88. In the case of cohesive deposits, it implies
that the consistency varied from being very soft to hard. SPT profiles used in this study
are attached in Appendix A.1.
3.4 Laboratory Test Program
Laboratory tests were conducted on undisturbed samples collected from boreholes drilledclose to the CPTu test points. Classification tests were performed to determine the soil
type, while undrained shear strengths were evaluated using direct simple shear tests. Atterberg limit tests and oedometer consolidation tests were also conducted on the cohesive

62
SPT-N
0

20

40

60

80

100

0

0

10 Gray stiﬀ Lean Clay (CL)10
5Gray medium stiﬀ SILT (ML)

8

8

4

5

4

Gray soft SILT (ML)66 Gray medium stiﬀ Lean Clay (CL)7

7Gray loose SILT with Sand (ML)Gray medium
dense Sandy Silt (ML)
18

18
10

10

21

21
Gray medium
dense Silty Sand (SM)21

21

14medium dense Silty Sand (SM)
Gray

14
15

17
Depth, m

Depth, m

15
8
11
20

8

17
8
Dark gray stiﬀ Fat Clay (CH)

11
20

8
Dark gray stiﬀ Elastic Silt (MH)

9

9

8

8 Gray stiﬀ Silty Clay (CL-ML)

Gray medium stiﬀ Lean Clay (CL)

7

7

25

25

22

25
30

Gray medium dense Silty Sand (SM)

22

25

68

68

Brown very dense Silty Sand (SM)

30

65

65

88

35

88

35

Figure 3.8: Typical SPT profile (Tingao, Narayanganj, BH-5)
deposits. The laboratory test results correspond to in situ test results of the same depth.
The laboratory tests conformed to the standards set out by the American Society for Testing & Materials (ASTM). The subsequent sections summarizes the test results along withthe corresponding ASTM code. The detailed results of the laboratory tests are enclosed inAppendix B.
3.4.1 Moisture Content
This test was conducted as per ASTM D2216-98. This test method covers the laboratory
determination of the water (moisture) content by mass of soil particles where the reduction
in mass by drying is due to water loss. The mass of soil solids is determined by drying thetest specimen at a constant temperature of 110° ± 5°C. The loss of mass due to drying is
the mass of water.
Results of the evaluation of the moisture content of the undisturbed samples and its corresponding borehole is summarized in Table 3.2. It is evident that the 𝑤% ranged from
20.1% to 44%.

63
Table 3.2: Summary of Moisture Content of different samples.
BH-ID
BH-5
BH-6
BH-18
BH-18
BH-27
BH-123
BH-123
BH-146
BH-250
BH-253
BH-264
BH-264
BH-274
BH-285
BH-296
BH-365
BH-398
BH-24
BH-274
BH-364
BH-374
BH-398Sample Depth, m
17.5
10.5
10
4
8
2.5
4
8.5
10
4
5.5
16
4
4
4
5.5
5.5
4
4
4
4
2.5

𝑤, %
29.2
25.6
44
32
37.7
29.3
27.8
23.2
30.4
23.6
30.3
30.5
24.7
24.3
21.2
20.1
26.6
26.7
26.9
26.3
24.5
22.3

3.4.2 Particle Size Distribution
Particle size distribution (PSD) of selected boreholes are presented in Table 3.3. The PSD
curves are shown in Appendix B.1. According to the USCS, particle size less than 75µm
are classified as clay and silt size fraction. Whereas, particle sizes over 75µm but less than
4.75mm are classified as sand size fraction. As seen in Table 3.3, the typical PSD for thisinvestigation’s course-grained or sand size fractions varied between 0 and 92%. Whereas,clay and silt size fraction varied between 8 to 99%. The subsequent sections describe thetest procedure to determine the clay size fraction and sand size fraction.
Sieve Analysis
Conducted as per ASTM D422-63 and ASTM D6913-04. Sieve analysis quantifies particle size distribution of a soil, within a specified size range, in a granular material—by
using sieves of different size openings. The distribution of particle sizes larger than 75µm
(retained on #200 sieve) is determined by sieving, while the distribution of particle sizes
smaller than 75µm is determined by a sedimentation process, using a hydrometer.
A typical PSD curve for particles larger than 75µm is illustrated in Figure 3.9, where 70%of the sample was determined to be of sand size fraction. For particle sizes smaller than
75µm, the sample that passes through #200 sieve is first washed and dried before conducting the hydrometer analysis. A typical curve generated from the hydrometer analysis is

64
Table 3.3: Particle Size Distribution of selected boreholes.
BH-ID
BH-6
BH-18
BH-27
BH-123
BH-146
BH-250
BH-253
BH-264
BH-274
BH-285
BH-365
BH-24

Fines Content (<0.075mm), %8 - 9929-10010-10028-100
46-99
28-99
24-97
31-99
21-99
22-92
19-99
24-92

Coarse-grained (0.075mm-4.75mm), %1 - 920 - 71
0 - 900 - 75
1 - 54
1 - 71
3 - 77
0 - 691 - 798 - 78
1 - 806 - 72

illustrated in Figure 3.10.
Sand

Fines

MediumFine

100

GravelCoarse90

Percent finer (%)

80
70
60
50
40
30
20
10
0
0.01

0.075 0.1

0.425
Particle Size (mm)

1

2

4.75

10

Figure 3.9: A typical PSD curve for BH-05, sample ID-20, sample depth 30.0m.
Wet Sieve Analaysis
Conducted as per ASTM D1140-00. It is a procedure to quantify particles finer than a
75µm (#200) sieve by washing. The soil specimen undergoes washing, by water, overa 75µm (#200) sieve. Clay and impurities—removed from the soil specimen during thetest—are dispersed by the water, including the water-soluble materials. The resulting loss
in mass is calculated as the mass percent of the original sample and is reported as thepercentage of material finer than a 75µm (#200) sieve. The resulting samples are thendescribed conforming to the USCS.
3.4.3 Atterberg Limit Test
Following the ASTM D4318 convention, according to Das and Sivakugan (2018):

65
Fines Content

SAND
MediumFine

100

GravelCoarse90
80

Percent finer (%)

70
60
50
40
30
20
10
0
0.001

0.002

0.01

0.075 0.1
Particle Size (mm)

0.425

1

2

4.75

10

Figure 3.10: A typical curve obtained using hydrometer analysis for BH-05, sample ID04, sample depth 6.0m.
A Casagrande device is employed to determine the liquid limit of soil. It is the moisture
content at which a groove closure of 12.7 mm occurs at 25 blows. Whereas, the plastic limit
is the moisture content at which the soil crumbles when rolled into a thread of 3.18 mm indiameter. Summary of the Atterberg limit tests of the 19 inorganic samples is presented
in Table 3.4. The LL ranges between 20 an 90. Whereas the PI ranges between 12 and 65.
The index properties are used to classify the inroganic samples conforming to USCS as
shown in Table 3.4 and Figure 3.11. It is evident that the characteristic LL for the majority of the samples is above 50%, and above the A-line—indicating a highly plastic clay
(CH). Five samples have the characteristic LL below 50%, thus classified as clays withlow plasticity (CL). Two of the samples are seen in Figure 3.11 to lie below the A-line,
having LL below 50%—thus classified as silts (ML). Similar Atterberg limit charts for the
19 boreholes are attached in Appendix B.2.
3.4.4 Density (Unit Weight)
This test method—conducted as per ASTM D7263—describes two ways of determining
the moist and dry densities (unit weights) of intact, disturbed, remolded, and reconstituted(compacted) soil specimens.
The values of the bulk and dry unit weight of the undisturbed samples are summarizedin Table 3.5. The quantitative range of the bulk unit weight ranges from 16.9kN/m3 to
20.9kN/m3 . Whereas, the dry unit weight ranges from 7.09kN/m3 to 11.09kN/m3 . Laboratory data and its evaluation is attached in Appendix B.3.
3.4.5 Specific Gravity
This test was conducted as per ASTM D854-02. Specific gravity of soil solids is determined by using a water pycnometer. The soil solids are first sieved through a 4.75mm

66

Table 3.4: Summary of Atterberg Limit of different samples.
BH-ID
BH-5
BH-6
BH-18
BH-123
BH-123
BH-146
BH-250
BH-253
BH-264
BH-264
BH-274
BH-285
BH-296
BH-365
BH-398
BH-24
BH-274
BH-374
BH-398Sample Depth, m
17.5
10.5
4
2.5
4
8.5
10
4
5.5
16
4
4
4
5.5
5.5
4
4
4
2.5

LL
60
66
40
40
35
53
48
90
74
46
47
59
85
75
59
76
57
80
49

PL
27
23
26
26
23
26
24
25
27
20
22
29
21
22
23
20
23
25
20

PI
33
43
14
14
12
27
24
65
47
26
25
30
64
53
36
56
34
55
29

USCS Symbol
CH
CH
ML
ML
CL
CH
CL
CH
CH
CL
CL
CH
CH
CH
CH
CH
CL
CH
CL

Table 3.5: Summary of unit weight of different samples.
BH-ID
BH-6
BH-5
BH-18
BH-18
BH-27
BH-123
BH-123
BH-253
BH-274
BH-285
BH-264
BH-264
BH-296
BH-398
BH-250
BH-365
BH-146
BH-68
BH-97

Sample Depth, m
10.5
17.5
4
10
8
2.5
4
4
7
4
5.5
16
4
5.5
10
5.5
8.5
47
37

Bulk Unit Weight, KN/m3
19.2
17.1
18.8
16.9
17.5
18.9
18.4
19.7
19.9
19.5
20.9
20.7
18.7
19.4
17.6
19.1
19.2
20.1
18.3

Dry Unit Weight, KN/m3
9.39
7.29
8.99
7.09
7.69
9.09
8.59
9.89
10.09
9.69
11.09
10.89
8.89
9.59
7.79
9.29
9.39
10.29
8.49

67

60

50

CH
U-Line40
PLASTICITY INDEX (PI)

A-Line

30

CL

20

MH,OH
10

ML
CL- ML

0
0

10

20

30

40

50
60
LIQUID LIMIT (LL), %

70

80

90

100

110

Figure 3.11: Plasticity chart developed for the investigated points developed using theCasagrande (1936) plasticity chart.
(Number-4) sieve. The ratio of the mass of a unit volume of a soil solids to the mass of thesame volume of gas-free distilled water at 20°C is the specific gravity of soil solids (𝐺 𝑠 )For this investigation, 𝐺 𝑠 is observed to vary between 2.65 to 2.80. Detailed calculations
in evaluating 𝐺 𝑠 is attached in Appendix B.4).
3.4.6 Soil Classification
This test was conducted as per ASTM D2487-06. The USCS was employed to identify thesoil. ASTM D 2487 standard covers the guidelines for USCS classification for engineering
purposes.
3.4.7 One-Dimensional Consolidation Test
This test was conducted as per ASTM D2435-11. This test method covers the determination of consolidation properties of cohesive soils. Incremental loads are maintained until
excess pore water pressures dissipate. The change in specimen height and the stress-strain

68graph are used to evaluate the time required for consolidation, coefficient of consolidation,
compression index, and constrained modulus.
Table 3.6: Summary of one-dimensional consolidation test result.
BH-ID
BH-5
BH-6
BH-18
BH-123
BH-146
BH-250
BH-253
BH-264
BH-274
BH-285
BH-24
BH-364
BH-374
BH-398Sample Depth, m
17.5
10.5
10
4
8
2.5
4
8.5
10
4
5.5
16
4
4

𝐶𝑐
0.38
0.23
0.58
0.13
0.18
0.20
0.17
0.35
0.17
0.18
0.17
0.24
0.17
0.14

Initial Void Ratio
0.79
0.60
1.15
0.65
0.67
0.82
0.71
1.62
0.81
0.59
0.69
0.89
0.63
0.66

𝑀, kPa1384.01615.0611.01028.11696.01657.4944.2
1043.01007.4
802.0
782.0
589.2
821.0
690.0

𝑡50 , min
1.3
20
0.5
1.5
4.5
0.4
0.9
14
0.6
3.3
2
0.4
1
4

𝑐 𝑣 , m2 /year
6.3
0.4
16.1
5.6
1.9
20.8
9.3
0.6
13.9
2.6
4.0
19.9
8.1
2.0

In this research, compressibility characteristics of 14 samples were evlauated from incremental loading in one-dimensional oedometer consolidation test. The results are summarized in Table 3.6. Consolidation tests were carried out on samples of 61.1mm and an
average height of 17.8mm. The incremental loads followed the sequence: 25kPa, 50kPa,
100kPa, 200kPa, 400kPa, 800kPa, and 1600kPa. Each loading step was held for at least
twenty-four hours. Drainage of water took place from both the top and bottom of the sample through the porus stones. A mechanical dial-gauge was used to record the deformationsat specified intervals of time.
12.6000.850
σ'v0=400 kPa
Cc= 0.380

0.800

10.600

0.750

0.700

cv, m2/year

Void Ratio, e0

8.600

0.650

6.600

4.600
0.600
2.600

0.550

0.600

0.500
5

50

500
Pressure, kPa

5000

1

10

100

1000

Pressure, kPa

Figure 3.12: Graphical representation of one-dimensional oedometer test result for the
sample in BH-05, depth at 17.5m. The graph of 𝑐 𝑣 is based on 𝑡50 .

69
A lined-scatter plot of void ratio versus log of effective pressure is shown in Figure 3.12
(refer Appendix B.6 for the plots generated in this investigation). The measured initial
void ratio ranges from 0.59 to 1.62. Using deformation versus square root of time charts,
𝑡50 was estimated. This parameter aided in generating the charts of 𝑐 𝑣 as shown in Figure
3.12. 𝑡50 is seen to vary between 0.4min to a maximum of 14min. Also, using 𝑡 50 , thevalues of 𝑐 𝑣 was observed to be 0.42m2 /year to 20.83m2 /year—depending on the stressload applied. Similarly, 𝐶𝑐 of the samples were evaluated from the loading slope portionof the graph. 𝐶𝑐 is observed to range from 0.13 to 0.58. Constrained modulus (𝑀) was
estimated using Equation 2.45. The values of 𝑀 are seen to vary between 589.2kPa and1615.0kPa.
3.4.8 Unconfined Compression Test
This test was conducted as per ASTM D2166-13. This test method covers the determination of the unconfined compressive strength (𝑞𝑢) of the soil specimen. It is experimentally
conducted by measuring the maximum load required per unit area to attain 15% strain, or
when the cylindrical soil specimen fails; whichever is attained first. 𝑞 𝑢 is calculated as thecompressive stress at failure. 𝑠𝑢 is half of 𝑞 𝑢 . As shown in Figure 3.13, 𝑞 𝑢 is evaluatedto be 184.2kN/m2 . Thus, 𝑠𝑢 was evaluated to be 92.1kN/m2 . The reader is referred toAppendix B.5 for the UCT plots used in this study.
Table 3.7: Summary of the UCT test results investigated in this study.
BH-ID
BH-5
BH-6
BH-18
BH-18
BH-27
BH-123
BH-123
BH-146
BH-250
BH-253
BH-264
BH-264
BH-274
BH-285
BH-296
BH-365
BH-398Sample Depth, m
17.5
10.5
10
4
8
2.5
4
8.5
10
4
5.5
16
4
4
4
5.5
5.5

3.5 Summary
The laboratory results are summarized as follows:

𝑞 𝑢 , kN/m2
223.1
190.7
112.6
131.7
70.3
150.1
104.4
184.2
42.3
376.3
278
416.6
284.1
466.4
170
290.8
465.2

70
220
200
180

Axial Stress (kN/m2)

160
140
120
100
80
60
40
20
0
0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

13.0

14.0

15.0

Axial Strain (%)

Figure 3.13: A typical UCT test result on an intact clay sample obtained from BH-146,
depth at 8.5m.
1. Moisture content (𝑤) varied between 20.1% to 44%.
2. For this investigation, sieve analysis reveals that sand size faction vary between 0
and 92%. Whereas, clay and silt size fraction is seen to range between 8 and 99%.
3. 19 inorganic samples were tested for evaluating Atterberg limit. The test unfolds
that LL varied between 20 and 90, whereas the 𝑃𝐼 is seen to vary between 12 and65.
4. Bulk unit weight of the soils in the study area varied between 16.9kN/m3 . Whereas, the dry unit weight is seen to range from 7.1kN/m3 to 11.1kN/m3 .
5. Specific gravity of the inorganic samples are observed to range in between 2.65 and
2.80.
6. Initial void ratio is observed to range in between 0.6 and 1.6. Compression index
𝐶𝑐 varied between 0.1 and 0.6. Constrained modulus (𝑀) is seen to vary between
589kPa and 1615kPa. Depending on the stress range, 𝑐 𝑣 is observed to vary between
0.4m2 /year to 20.8m2 /year.
7. Unconfined compression strength, obtained from UCT, is seen to be in the range of
70.3kN/m2 to 466.4kN/m2

Chapter 4
INTERPRETATION OF TEST RESULTS
4.1 Statistical Analysis for Constrained Modulus, M
One dimensional consolidation tests—adopting the procedures outlined in ASTM D2435—
were conducted on undisturbed samples, obtained using Shelby tube from the field. Leastsquares regression analyses were performed between the OCR and basic CPTu parameters—
𝑞 𝑡 , 𝑓𝑠 , 𝑢 2 —obtained from several points of the site. Also, basic soil parameters such the
moisture content (ASTM D2216), and Atterberg limits (ASTM D4318) were determinedfrom laboratory tests. Likewise, 𝜎𝑣0 and hydrostatic pore pressure (𝑢 0 ) parameters were
estimated from bore hole log information. 14 samples were utilized to conduct 1-D oedometer tests. The statistical measure of goodness of fit is reported in terms of the coefficient of determination 𝑅 2 and collinearity between the predictor and the independent data.
The collinearity between the predictor and the independent data were graphically assessed.
In this visual method, establishing the center of the quadrant required averaging the abscissa and the ordinate values. Thus, only correlations characterized by the highest visualcollinearity and calculated 𝑅 2 are summarized in Table 4.1. Also, the perceived applicability for determining the parameter 𝑀 from CPTu was rated as moderate by Robertson(2012a) (as shown in Figure 2.2).
Table 4.1: New proposed correlation for Constrained Modulus (𝑀).
Correlation
𝑀 = 3.61 ∗ 𝜎𝑣0 + 607.67

Independent Function Type
Field Based

n
14

R2
0.43

Graphical assessment of the collinearity between 𝑀 and 𝜎𝑣0 in Fig.4.1a demonstrates thatthe data points are mostly in the lower left and top right of the quadrant. Thus, an increasing linear trend between 𝑀 and overburden pressure can be established with less scatter(𝑅 2 =0.87). Similarly, graphical analysis between 𝑀 and moisture content (Fig.4.1b) reveals lot of scatter with no indication of a linear trend. A more scattered data was obtained
between 𝑃𝐼 with 𝑀 as shown in Fig.4.1c—thus no linear trend could be established withthis dataset.
After evaluating 1-D oedometer constrained modulus, scatter plots with various CPTu
parameters were plotted and presented in Figures 4.2 through 4.5. Scatter plot between
𝑀, 𝑞 𝑐 (as shown in Fig 4.2a) reveals no linear trend for this data set—the visual collinear
assessment demonstrates that data points (𝑛 = 14) are concentrated at the center of thequadrant. Similarly, the plot between 𝑀 and 𝑞 𝑡 as shown in Figure 4.2b demonstrates no71

72

3000.01800.0This Study (PI: 12 to 65)

1600.0Constrained Modulus M, kPa

Constrained Modulus M, kPa

2500.02000.01500.01000.0500.0

y = 3.61x + 607.67
R² = 0.43

1400.01200.01000.0
800.0
600.0
400.0
200.0

0.0

This Study (PI: 12 to 65)

0.0
0

100

200
σv0, kPa

300

400

0

10

(a)

20
MC, %

30

40

50

(b)
1800.0Constrained Modulus M, kPa

1600.01400.01200.01000.0
800.0
600.0
400.0
This Study (PI: 12 to 65)

200.0
0.0
0

20

40

60

80

PI, %

(c)

Figure 4.1: (a) Relationship between 𝑀 and 𝜎𝑣0 . (b) Relationship between 𝑀 and 𝑤%.
(c) Relationship between 𝑀 and 𝑃𝐼.
linear trend. In terms of cone penetration resistance, 𝛼𝑚 obtained in this study is 0.28. Thisis a very low value relative to the 𝛼𝑚 values seen in Table 2.3. Also, Kulhawy and Mayne(1990) observed that 𝛼𝑚 magnitude ranges from 0.4 to 8, with majority being in the range
between 1 and 3. The findings in this study are in stark contrast to the results reported in
the literature. One possible explanation is that probes of different configurations and test
methods were utilized in the reported literature. According to Kulhawy and Mayne (1990),
non-standard cones (electrical and mechanical) and test procedures were utilized by theseinvestigators. This observation also holds true for the CPTu probes used by Abu-Farsakh
et al. (2007) as well.
Scatter plot between 𝑀 and 𝑢 2 (as shown in Figure 4.3a) indicates no linear relationshipbetween the data points (𝑛 = 14). Similarly, the trend between 𝑀 and Δ𝑢 (Figure 4.3b)
exhibits a scattered data to establish any linear relationship for this data set.

73

9000.0100000.0
This Study (PI: 12 to 65)

This Study (PI: 12 to 65)
10000.0
Constrained Modulus M, kPa

7000.0)6000.0

ra

t(

19

72

5000.0ng

le4000.0Sa

Constrained Modulus M, kPa

8000.03000.02000.01000.0
Liu

100.0
a
-F
bu

a
rs

kh

00

(2

3)

01

(2

7)

A

10.0

1000.0
0.0

1.0
0

2000

4000
qc, kPa

6000

8000

1

10

(a)

100
qt, kPa

1000

10000

(b)

Figure 4.2: (a) Relationship between 𝑀 and cone penetration resistance (𝑞 𝑐 ). (b) Relationship between 𝑀 and corrected cone penetration resistance (𝑞 𝑡 ).
10000.0

1800.01000.0Constrained Modulus M, kPa

Constrained Modulus M, kPa

1600.0100.0

10.0This Study (PI: 12 to 65)

1400.01200.01000.0
800.0
600.0
400.0

This Study (PI: 12 to 65)

200.0

1.0

0.0
1

10

100
u2, kPa

(a)

1000

10000

0

200

400

600
Δu, kPa

800

1000

1200

(b)

Figure 4.3: (a) Relationship between 𝑀 and pore pressure (𝑢 2 ). (b) Relationship between
𝑀 and excess pore pressure (Δ𝑢).
As seen in the scatter plot (Figure 4.4a), a visual assessment for collinearity reveals thatthe data is scattered between 𝑀 and 𝑓𝑠 to reach any conclusion. Similarly, scatter is also
observed between 𝑀 and 𝐹𝑟 as seen in Figure 4.4b. In both the cases, most of the data
points are located in the bottom right quadrant. This observation is more pronounced√√
when the the CPTu parameters ( 𝑞 𝑡 and 𝑓𝑠 ) are taken as shown in Figure 4.5. Hence, noempirical correlation could be established with this data set (𝑛 = 14).
In terms of net cone resistance (𝑞 𝑡 −𝜎𝑣0 ), the scatter plot (as shown in Figure 4.6a) suggests
a similar result obtained using 𝑞 𝑐 , and 𝑞 𝑡 —accompanied by a lot of scatter exists for the1800.0

1800.01600.01600.01400.01400.0Constrained Modulus M, kPa

Constrained Modulus M, kPa

74

1200.01000.0
800.0
600.0
400.0
This Study (PI: 12 to 65)

200.0

50

100
fs, kPa

150

1200.01000.0
800.0
600.0
400.0
200.0

0.0
0

This Study (PI: 12 to 65)

0.0
0.00

200

2.00

4.00
Fr, %

(a)

6.00

8.00

10.00

(b)

1800.01800.01600.01600.01400.01400.0Constrained Modulus M, kPa

Constrained Modulus M, kPa

Figure 4.4: (a) Relationship between 𝑀 and sleeve friction ( 𝑓𝑠 ). (b) Relationship between
𝑀 and normalized sleeve friction (𝐹𝑟 ).

1200.01000.0
800.0
600.0
400.0
200.0

1200.01000.0
800.0
600.0
400.0
200.0

This Study (PI: 12 to 65)

This Study (PI: 12 to 65)
0.0

0.0
0

20

40
√qt, kPa

(a)

60

80

100

0

5

10

15

√fs, kPa(b)

Figure 4.5: (a) Relationship between 𝑀 and square-root of corrected cone tip resistance√√( 𝑞 𝑡 ). (b) Relationship between 𝑀 and square-root of sleeve friction ( 𝑓𝑠 ).
lower range of net cone resistance (less than 2400kPa). More data is required for the lower
values of (𝑞 𝑡 − 𝜎𝑣0 ) to establish a correlation. Likewise, scatter plot between 𝑀 and total
cone resistance (𝑞 𝑡 + 𝑓𝑠 + 𝜎𝑣0 ) also shows scatter with no linear trend (as seen in Figure4.6b). This relation is not found in existing literature, however, since a linearly increasing
trend was observed between 𝑀 and 𝜎𝑣0 (as seen in Figure 4.1a), an attempt was made to
explore its effect on 𝑞 𝑡 and 𝑓𝑠 . In this study, no relationship could be established using the
curated data set (𝑛 = 14).
Another set of relation not found in the literature are between 𝑀, 𝑄 𝑡𝑛 , and 𝐼𝑐 . As seen in75

1000000.0

2500.0This Study (PI: 12 to 65)

This Study (PI: 12 to 65)
2000.0Constrained Modulus M, kPa

Constrained Modulus M, kPa

100000.0
)

=5
09
αm
20
for
(
n
o
9
rts
98
be
t1
Ro
se
e
nn
Se
07
20
kh
a
s
ar

10000.0

1000.0

100.0
u-

Ab

F

1500.01000.0

500.0

10.0

1.0

0.0
1

10

100
qt -σv0, kPa

1000

10000

(a)

0

2000

4000
6000
qt +fs+σv0, kPa

8000

10000

(b)

Figure 4.6: (a) Relationship between 𝑀 and net cone resistance (𝑞 𝑡 −𝜎𝑣0 ). (b) Relationshipbetween 𝑀 and total cone resistance (𝑞 𝑡 + 𝑓𝑠 + 𝜎𝑣0 ).
Figure 4.7a, unlike the CPTu parameters 𝑞 𝑐 , 𝑞 𝑡 and 𝑞 𝑡 − 𝜎𝑣0 where the data points wereconcentrated in one point, a lot of scatter is observed between 𝑀 and normalized cone tip
resistance 𝑄 𝑡𝑛 . A negative trend is clearly visible. Howeever, it can be concluded that moredata points are needed to reach a definite conclusion for cone tip resistance correlations for
𝑀. In terms of the dimensionless parameter 𝐼𝑐 , the collinearity is clearly visible—the data
points are located at the lower left and the rop right quadrants. Hence, an increasing linear
trend is observed. In spite of obtaining a statistically significant correlation, Scattering isobserved at the upper range (<2.5) of 𝐼𝑐 as seen in Figure 4.7b. More data will be requiredin the upper range of 𝐼𝑐 to reach a definite conclusion.
4.2 Statistical Analysis for Compression Index, 𝐶𝑐
As seen in Figure 4.8 through 4.10, the scatter plots between compression index (𝐶𝑐 ) andcone tip resistance reveals a hyperbolic relationship. This finding is in agreement withthe findings of Sanglerat (1972) (refer to Figure 2.23). It is observed that the most of thedata points are within the upper limit defined by Sanglerat (1972). As seen in Figure 4.10,
the scatter plot between 𝑞 𝑡 and 𝑞 𝑡 /𝐶𝑐 exhibits a distinct linear trend (𝑅 2 = 0.95)—thus
confirming the hyperbolic distribution of 𝐶𝑐 with respect to 𝑞 𝑡 . Similar observation is also
evident for the scatter plot between compression ratio (𝐶 𝑅) and 𝑞 𝑡 as seen in Figure 4.9.
Figure 4.8 shows a positively linear trend between moisture content (𝑤%) plotted against
𝐶𝑐 . The statistical fit of goodness was measured in terms of coefficient of determination(𝑅 2 ) of 0.78. The data points are consistently less scattered below 25%. The findings arealso in agreement with Kulhawy and Mayne (1990) point that more consistent correlations

76

1800.01800.0This Study (PI: 12 to 65)

1600.01600.01400.01400.0Constrained Modulus M, kPa

Constrained Modulus M, kPa

This Study (PI: 12 to 65)

1200.01000.0
800.0
600.0
400.0

1200.01000.0
800.0
600.0
400.0
200.0

200.0

0.0

0.0
0

20

40
Qtn, kPa

60

80

0

100

0.5

(a)

1

1.5
Ic, kPa

2

2.5

3

(b)

Figure 4.7: (a) Relationship between 𝑀 and normalized cone resistance resistance (𝑄 𝑡𝑛 ).
(b) Relationship between 𝑀 and Soil Behavior Type Index (𝐼𝑐 ).
are obtained between 𝑤% and 𝐶𝑐 .
0.8

0.7

0.7

0.6

Compression Index Cc

Compression Index Cc

0.6
0.5
0.4
0.3
This Study (PI: 12 to 65)

0.2

Sanglerat (1972) Upper Limit

0.1

0

2000

4000
qc, kPa

6000

0.5

0.4

0.3
0.2

0.1

Sanglerat (1972) Lower Limit0.0

y = 0.02x - 0.31
R² = 0.78

This Study (PI: 12 to 65)

0.0
8000

0

(a)

10

20
MC, %

30

40

50

(b)

Figure 4.8: (a) Relationship between 𝐶𝑐 and cone resistance resistance (𝑞 𝑐 ). (b) Relationship between 𝐶𝑐 and 𝑤%.
4.3 Statistical Analysis for Overconsolidation Ratio, OCR′

For profiling OCR in this work, 𝜎𝑝 was determined using Casagrande (1936) graphical′interpretation method. Also, 𝜎𝑣0 was estimated using bore log information. Least-squares
regression analyses were performed between the OCR and basic CPTu parameters—𝑞 𝑡 , 𝑓𝑠 ,𝑢 2 . The statistical regression correlations models are divided into two independent function types—Field Based and Laboratory Based . In the field based models, measurements

77

70000

0.3

60000

0.3

50000
is
Th

This Study (PI: 12 to 65)
40000
qt/CR

CR = Cc/(1+e0)

0.2

0.2

St

y
ud

I:
(P

12

to

)
65

30000

0.1
20000
0.1

10000

y = 8.1534x + 2334
R²=0.91

0

0.0
0

2000

4000
qt, kPa

6000

0

8000

2000

(a)

4000
qt, kPa

6000

8000

(b)

0.7

40000

0.6

35000
30000

0.5

y
ud

is
Th

25000
0.4
qt/Cc

Compression Index C cFigure 4.9: (a) Relationship between 𝐶 𝑅 and corrected cone resistance resistance (𝑞 𝑡 ). (b)Relationship between 𝑞 𝑡 /𝐶 𝑅 and corrected cone resistance resistance (𝑞 𝑡 ).

I:
(P

12

to

)
65

St

20000

0.3
15000
This Study (PI: 12 to 65)

0.2

10000

Sanglerat (1972) Upper Limit

0.1

Sanglerat (1972) Lower Limit

0.0
0

2000

4000
qt, kPa6000

y = 4.9091x
R² = 0.95

5000
0
8000

0

(a)

2000

4000
qt, kPa

6000

8000

(b)

Figure 4.10: (a) Relationship between 𝐶𝑐 and corrected cone resistance resistance (𝑞 𝑡 ). (b)Relationship between 𝑞 𝑡 /𝐶𝑐 and corrected cone resistance resistance (𝑞 𝑡 ).
from the CPTu—𝑞 𝑐 , 𝑞 𝑡 , 𝑓𝑠 and 𝑢 2 —are utilized to formulate the correlations. Whereas in
the laboratory based models, laboratory data and or 𝜎𝑣0 are incorporated in addition to the
CPTu data to explore the correlations. It should be noted that only 14 out of 17 samples
were utilized to conduct 1-D oedometric tests on. This highlights the problems associatedwith recovering enough quality undisturbed samples for laboratory testing. Also, a certain′

degree of uncertainty involves in indexing 𝜎𝑝 from a recovered undisturbed sample—since
it requires judgment. However, statistical analysis reduces these uncertainties. The statistical measure of goodness of fit is reported in terms of the coefficient of determination 𝑅 2

78
and collinearity between the predictor and the independent data. The collinearity between
the predictor and the independent data were graphically assessed. In this visual method,establishing the center of the quadrant required averaging the abscissa and the ordinate
values. Thus, only correlations characterized by the highest visual collinearity and calculated 𝑅 2 are summarized in Table 4.3. It should be noted that Robertson (2012a) rated
the perceived applicability for determining OCR from CPTu as moderate (see Figure 2.2).
Also, as seen in Table 4.2, Chen and Mayne (1996) deemed 𝑅 2 less than 0.38 to be poor.
Similarly, Chen and Mayne (1996) rated correlations in the range of 0.47<𝑅 2 <0.67 to be
fair.
Table 4.2: Degree of statistical goodness as per Chen and Mayne (1996) for OCR of clay
deposits
Range of 𝑅 2
0.01<𝑅 2 <0.38
0.47<𝑅 2 <0.67
Correlation
𝑂𝐶 𝑅 = 0.0648 ∗ 𝑄 𝑡
𝑂𝐶 𝑅 = 0.1412 ∗ 𝑄 𝑡𝑛
𝑂𝐶 𝑅 = 1.1467 ∗ 𝐹𝑅′
𝑂𝐶 𝑅 = 0.0645 ∗ (𝑞 𝑡 − 𝑢 2 )/𝜎𝑣0′
𝑂𝐶 𝑅 = 0.0651 ∗ (𝑞 𝑡 − 𝜎𝑣0 − Δ𝑢)/𝜎𝑣0
𝑂𝐶 𝑅 = 0.1346 ∗ (𝑞 𝑡 + 𝑓𝑠 )/𝜎𝑣0′
𝑂𝐶 𝑅 = 1.1978 ∗ ( 𝑓𝑠 /𝜎𝑣0 ) + 2.526

Correlation Strength
Poor
Fair
Independent Function Type
Field Based
Field Based
Field Based
Field Based
Field Based
Field Based
Field Based

n
14
14
14
14
14
14
14

R2
0.69
0.85
0.73
0.67
0.66
0.74
0.60

Table 4.3: New proposed correlations for OCR.
Scatter plot of 𝑞 𝑐 , 𝑞 𝑡 against OCR are plotted in Figure 4.11. The laboratory derived 𝑂𝐶 𝑅
is observed to increase with 𝑞 𝑐 —this is in agreement with the findings of Tavenas andLeroueil (1979) for destructured clay. Also, similar trends were obtained by Mayne andHoltz (1988). However, for this data set (𝑛 = 14), a graphical assessment of collinearity
could not be established as seen in Figure 4.11a. Similarly, the collinearity between thelaboratory derived 𝑂𝐶 𝑅 and 𝑞 𝑡 could not be established as seen in Figure 4.11b. Moredata is required to establish this relationship, as an increasing linear trend was demonstrated by Mayne and Holtz (1988) for a relatively larger clay database. Statistically, notmuch difference is observed between the parameters 𝑞 𝑐 , 𝑞 𝑡 , and (𝑞 𝑡 − 𝜎𝑣0 ) for evaluating
OCR. Also, an upper and lower limit could not be established in this work using limited
data points. However, assuming that Tavenas and Leroueil (1979) line is the upper limit,
the results unfold that most of the data set points are well below it by at least a factor of
5. Heavily overconsolidated soils (OCR>5) were not omitted from these plots. In spiteof statistically significant results reported in the literature, Wroth (1984) suggested that

79

100

100

10

1
eil

OCR-measured

u
ro

s
na
ve

e
dL

an

Ta
1

5)
o6

d

as

an

Ta

1

12
I:
(P
y
St

t
sS

Th
is

i
Th

ud

P

y(
ud

(P

n
ve

2t

I: 1

l

ei

u
ro
Le

79
19

)
45

to

OCR-measured

to

(P

to

65
)

9
97

10

I: 7

7
I:

)
45

0

0
100

1000
qc, kPa

100

10000

1000
qt, kPa

(a)

10000

(b)

Figure 4.11: (a) Relationship between 𝑂𝐶 𝑅 and cone penetration resistance (𝑞 𝑐 ). (b) Relationship between 𝑂𝐶 𝑅 and corrected cone penetration resistance (𝑞 𝑡 ).
the maximum shear stress attained in undrained conditions must be related to the difference between two total (or two effective) stresses. Hence, caution should be exercised inutilizing correlations involving cone tip resistance only.
10

12This Study (PI: 12 to 65)
Chen & Mayne 1996(PI: 4 to 100)

10

Demers & Leroueil 2002(PI: 5 to 48)

OCR-measured

OCR-measured

8

1

6

4

2

0

0
0.1

1

10
100
Δu , kPa

(a)

1000

10000

0

0.2

0.4
Bq

0.6

0.8

(b)

Figure 4.12: (a) Relationship between 𝑂𝐶 𝑅 and 𝐵𝑞 . (b) Relationship between 𝑂𝐶 𝑅 andexcess pore pressure (𝑢 2 − 𝑢 0 ).
No correlation between OCR and Δ𝑢 was obtained as seen in Figure 4.12a. The data
points—11 in total—are highly scattered even after removing data points with a negativevalue. Robertson et al. (1986a) recommended using pore pressure measurements over 𝑞 𝑐
for evaluating 𝑠𝑢 (and in turn OCR). However, the results herein suggests otherwise. Demers and Leroueil (2002) also pointed out that the correlation of OCR using pore pressure

80
data usually results in more scattered results than those using cone tip resistance. This observation is in agreement with the findings of this study (as shown in Figure 4.12a). Mayne
and Holtz (1988) concluded that 𝐵𝑞 generally decreases with increasing OCR. This is evident in Figure 4.12b, where a negative trend is observed (the highest values of OCR are
characterized by the lower values of 𝐵𝑞 ). Similarly, Pant (2007) obtained linearly inverse
relationship between excess pore pressure generated and OCR for Louisianna clay soils.
Whereas Chen and Mayne (1996) observed marginal trend of OCR decreasing with increasing 𝐵𝑞 for both intact and fissured clays. Likewise, Demers and Leroueil (2002) also
obtained a linearly inverse relationship accompanied with a lot of scatter but concluded
that 𝐵𝑞 is not useful in determining OCR despite Wroth (1984) recommending on using
𝐵𝑞 to index OCR. Similar conclusion was also reached by Chen and Mayne (1996). Chen
and Mayne (1996) demonstrated that the assumption made by Wroth (1984) regarding 𝐵𝑞
being akin to Skempton’s triaxial pore pressure is misleading due to large octahedral normal stress component affecting the pore pressure readings from the piezocone, and thus
𝐵𝑞 . In this research, due to negative pore pressure readings, the number of workable observed data points were reduced to only 11 in numbers—which is very few in quantity toeven statistically reach any conclusion (see Figure 4.12). Hence, it is concluded that nocorrelation was obtained between 𝐵𝑞 and OCR.
10.0

100
88

tz
ol

e

n
ay

&

19

H

M

OCR-measured

)
100
4 to
(PI:

e1

)

1
02

s

er

0.1
1

10
u2 , kPa

(a)

100

to

48

I

(P

1000

10000

&

Le

ue

ro

This Study (PI: 12 to 65)

em

D

0
0.1

:5

0
il 2

Che
n

Thi

sS

tud

y (P

I: 1

996

2 to

65)

1.0

&M
ayn

OCR-measured

10

0.1

1

10

100

Δu/σ'v0(b)

Figure 4.13: (a) Relationship between 𝑂𝐶 𝑅 and pore pressure (𝑢 2 ). (b) Relationship be′
tween 𝑂𝐶 𝑅 and Normalized pore pressure 𝑢 2 /𝜎𝑣0 .
Similarly, no correlation between OCR and 𝑢 2 was obtained as seen in Figure 4.13a. The
observed trend is slightly better than that seen in Figure 4.12, however, the data points
remain limited and highly scattered. It can be concluded that pore pressure measurements
are more scattered than that obtained with cone tip resistance. This observation is in linewith Robertson (1990) that for interpreting OCR, pore pressure measurements are less81
reliable than cone resistance 𝑞 𝑐 . Pore pressure measurements are prone to error in themeasurement—such as poor calibration, unstaurated filters, and dilatory response in high
OCR soils (negative 𝑢 2 ) (Lunne et al., 1997). Despite 𝑢 2 and Δ𝑢 being known to predict
OCR of the soil deposit, a statistically significant relationship was not obtained in this′study. Normalizing 𝑢 2 readings with respect to 𝜎𝑣0 tend to smooth out the scatter slightly,
however, no correlation could be established as seen in Figure 4.13b. However, using
theory from CSSM and cavity expansion for driven piles in clay, Mayne and Holtz (1988)′

observed that Δ𝑢/𝜎𝑣0 increases with OCR. Similarly, Robertson (2009) also pointed out
the usefulness of normalizing to obtain better relationships.

1212
y = -0.0328x + 9.3318
R²=0.5610

10

8
OCR-measured

OCR-measured

8

6

4

2

6

4

2

0

0
0

100

200
σv0, kPa

300

400

0

10

20

40

50

60

(b)

12

12

10

10

8

8
OCR-measured

OCR-measured

(a)

30
MC, %

6

4

6

4

2

2
y = 0.03x + 0.68
R² = 0.60

0

0
0

50

100

150
su, kPa

(c)

200

250

300

0

20

40

60

80

PI, %

(d)

Figure 4.14: (a) Relationship between 𝑂𝐶 𝑅 and 𝜎𝑣0 . (b) Relationship between 𝑂𝐶 𝑅 and
𝑤%. (c) Relationship between 𝑂𝐶 𝑅 and 𝑠𝑢 . (d) Relationship between 𝑂𝐶 𝑅
and 𝑃𝐼.
Plot between OCR and in situ effective stress (Figure 4.14a) reveals a decreasing trend

82
taking place. However, the data points are scattered (𝑅 2 = 0.56). OCR is also found to be
influenced by 𝑠𝑢 as shown in Figure 4.14c. However, no relationship could be established
for plots between OCR, 𝑃𝐼, and 𝑤% for the heavily consolidated soils (OCR>5) as seen in
Figures 4.14b and 4.14d. A strong positively linear trend is observed in the plot between
OCR and 𝑠𝑢 (𝑅 2 = 0.88) for the 9 data points. Also, for low OCR values, the data points areless scattered than the data points for higher OCR. Likewise, the plot between OCR andPI, in linear scale, unfolds a positively increasing trend. However, more data is required
to establish this relationship.
100.0

100

10
to
I:
4
(P
96
19
ne
ay
M
&
n
)

Ch
e
48
to
5
I:

)

1.0

65

&L

(P

)

48

to

ue

m
De

2

ers

to

2

1

02

20

:5

10.0

This Study (PI: 12 to 65)

Th
is

De
m

er

St
u

s

dy

&

(P

Le

ro

I:
1

eil

u
ero

I
(P

1

a
&M

il 2

OCR-measured

Cht

OCR-measured

en

10

I: 4
(P

00

e
yn

6
99

0)

0)

0
o1

y = 0.0648x
R² = 0.69

0.1

0
100

1000
qt - σv0 , kPa

10000

(a)

0.1

1.0

10.0

100.0

Qt, kPa(b)

Figure 4.15: (a) Relationship between 𝑂𝐶 𝑅 and net cone resistance (𝑞 𝑡 − 𝜎𝑣0 ). (b) Relationship between 𝑂𝐶 𝑅 and Normalized cone tip resistance 𝑄 𝑡 .
As seen in Figure 4.15b, the parameter 𝑄 𝑡 demonstrates a linear trend (𝑅 2 =0.69). On theother hand, the CPTu parameter (𝑞 𝑡 −𝜎𝑣0 ) does not produce any linear relationship visually
as seen in Figure 4.15a—the data points are mostly concentrated near the center of thequadrant. Thus more data is required to confirm this relationship. However, normalizing
the term (𝑞 𝑡 − 𝜎𝑣0 )—resulting in 𝑄 𝑡 —tend to smooth the scatter slightly. This is in linewith reasoning of Wroth (1988). Several investigators also established good agreement
between OCR and 𝑄 𝑡 (e.g., Chen and Mayne, 1996; Demers and Leroueil, 2002; Pant,
2007 and others). Although 𝑄 𝑡 does not utilize pore pressure measurements to evaluate
OCR, it remains indispensable to obtain corrected cone resistance. Demers and Leroueil(2002) also recommended using 𝑄 𝑡 for profiling OCR in sensitive clays due to it being
independent of 𝑤%, PI and clay fraction.
Likewise, the term 𝑄 𝑡𝑛 , updated by Zhang et al. (2002), was used to profile OCR as seenin Figure 4.16a. The parameter 𝑄 𝑡𝑛 demonstrated a strong linear statistical trend with
𝑅 2 =0.85. Also seen in Figure 4.16b is the normalized sleeve friction 𝐹𝑟 plotted against
OCR. The data points are relatively scattered, accompanied by 𝑅 2 =0.73.

83

16
14
14
12
12
OCR-measured

OCR-measured

10
10
8
6

8
6
4

4
y = 0.1412x
R² = 0.85

2

2

0
0.1

20.1

40.1
60.1
Qtn, kPay = 1.1467x
R² = 0.73

0
0.10

80.1

2.10

4.10
FR, %

(a)

6.10

8.10

(b)

Figure 4.16: (a) Relationship between 𝑂𝐶 𝑅 and Normalized cone resistance 𝑄 𝑡𝑛 . (b) Relationship between 𝑂𝐶 𝑅 and Normalized friction ratio 𝐹𝑅 .
1000

10
0)
to

:1
2t

:4
PI

y(

I: 5

Ma

to

yn

48

e1

)

99

6(

St
ud
is

&M

(P
02
20

eil

(P

10

&

)

00

Th

il 2

en

t
I: 4

PI

100

1

rou

en

me

rs

&

Ch

8)

Le

1

96

19

to 4

m

o1

e
ayn

oue

Ler

I: 5

Ch

De

10

&
ers

(P
002

OCR-measured

OCR-measured

100

o6

5)

1000

De

This Study (PI: 12 to 65)
0

0
100

1000
qt - u2, kPa

0.1

10000

(a)

1

10

100
1000
(qt - u2)/σ'v0 , kPa

y = 0.0645x
R² = 0.67
10000

100000(b)

Figure 4.17: (a) Relationship between 𝑂𝐶 𝑅 and effective cone resistance (𝑞 𝑡 − 𝑢 2 ). (b)Relationship between 𝑂𝐶 𝑅 and Normalized effective cone resistance (𝑞 𝑡 −′𝑢 2 )/𝜎𝑣0 .
Relationship between OCR and the parameter (𝑞 𝑡 − 𝑢 2 ) could not be established as seen in
Figure 4.17a. Visual assessment reveals some scatter and thus failed to comprehensively
produce a collinearity. It can be concluded that more data is required to establish this cor′

relation. As seen in Figure 4.17b, utilizing 𝜎𝑣0 as the normalization factor tend to smoothout this relationship significantly (𝑅 2 =0.88). This improved relationship is in agreementwith the findings of other researchers [e.g., Chen and Mayne (1996) and Konrad and Law′(1987a) and others]. Thus, the parameter (𝑞 𝑡 − 𝑢 2 )/𝜎𝑣0 ) is found to be a good predictor of

100

100

10

10

65
)

49

to

to

PI
:

12

(P
I: 6

1

Th

is

Pa

nt

y = 0.0651x
R² = 0.66

St
ud

20

y(

07

1

)

OCR-measured

OCR-measured

840

y = 0.1346x
R² = 0.74

0
0.1

1

10
100
(qt - σv0-Δu )/σ'v0 , kPa

0.1

1000

(a)

1

10
(qt +fs)/σv0 , kPa

100

1000

(b)

Figure 4.18: (a) Relationship between 𝑂𝐶 𝑅 and Battaglio et al. (1986) referenced param′
eter (𝑞 𝑡 − 𝜎𝑣0 − Δ𝑢)/𝜎𝑣0 ). (b) Relationship between 𝑂𝐶 𝑅 and Normalized
Total cone resistance (𝑞 𝑡 + 𝑓𝑠 )/𝜎𝑣0 .
OCR. Also, a statistically significant correlation (𝑅 2 =0.66) was obtained using Battaglio′

et al. (1986) referenced parameter (𝑞 𝑡 − 𝜎𝑣0 − Δ𝑢)/𝜎𝑣0 (see Figure 4.18). A low scattering of data points is observed for OCR>5. Similarly, the normalized parameter 𝑞 𝑡 + 𝑓𝑠′

with respect to 𝜎𝑣0 slightly improves the relationship, and is thus strong indicator of OCR(𝑅 2 =0.89) as seen in Figure 4.18.
In terms of sleeve friction, a highly scattered relationship was obtained with the laboratory
derived OCR as shown in Figure 4.19a. Many investigators, such as Chen and Mayne(1996), DeJong et al. (2001), and Lunne et al. (1997), did not explore OCR correlations
with 𝑓𝑠 as they deemed it unreliable and recommended minimizing its use. Normalizing 𝑓𝑠′

with respect to 𝜎𝑣0 significantly improves the relationship (𝑅 2 =0.60) as shown in Figure
4.19b. Given the findings, it can be concluded that normalized sleeve friction can be agood indicator of OCR, despite what the literature suggests otherwise.
4.4 Dissipation Test Results
Method for obtaining 𝑡 50 was obtained using the method outlined by Sully et al. (1999).
Figures 4.20 through 4.24 indicates that most of the dissipation curve in this study weredialotry. Dilatory responses are associated with overconsolidated clays and silts (Burns
and Mayne, 1998; Sully et al., 1999). 𝑡50 was evaluated using square root of time plot tofind the initial 𝑢𝑖 .

85

49
)

12

00
7

(P
I

8

OCR-measured

Pa

nt
2

7

8
OCR-measured

:6

to

9
10

6

4

6
5)
o6

2t
:1
PI

5
y(
tud

4

S
his

T

3
2

2

y = 1.1978x + 2.5256
R² = 0.60

1
0

0
0

50

100
fs, kPa

150

0

200

1

2
fs/σ'v0

(a)

3

4

(b)

Figure 4.19: (a) Relationship between 𝑂𝐶 𝑅 and sleeve friction ( 𝑓𝑠 ). (b) Relationship be′
tween 𝑂𝐶 𝑅 and Normalized sleeve friction ( 𝑓𝑠 /𝜎𝑣0 ).
500

700
Test Depth =15.70m

450

Test Depth =16.54m

u2 (initial) = 430kPa -50kPa =380kPa

600

u2 (initial) = 640kPa - 154kPa = 486kPa

Porewater Pressure u2, kPa

Porewater Pressure u2, kPa

400
350
300

u50 = 50kPa +(380/2)kPa=240kPa

250
200
150

500
u50 =154kPa +(486/2)kPa=397kPa
400

300

200

u0 154kPa

100
t50 = (21)2= 441s

u0 50kPa

50

100
t50 = (44)2= 1936s

0

0
0

10

20

30

Square Root of Time, (s)

40

50

0

10

20

30

40

50

Square Root of Time, (s)Figure 4.20: Dissipation test result interpretation for BH-05 and BH-06.
4.4.1 Statistical Analysis for Coeﬀicient of Consolidation, 𝑐 𝑣
Linear regression models were utilized to formulate correlations between laboratory derived 𝑐 𝑣 and CPTu parameters (𝑞 𝑡 , 𝑄 𝑡𝑛 , (𝑞 𝑡 − 𝜎𝑣0 ), (𝑞 𝑡 − 𝑢 2 ), 𝑓𝑠 , Δ𝑢 2 , 𝑡 50 and 𝑢 50 ). Parameters 𝑡50 and 𝑢 50 were interpreted using dissipation curves shown in Figure 4.20 throughFigure 4.24. Scatter plots of laboratory derived 𝑐 𝑣 versus CPTu parameters are shown in
Figure 4.25 through Figure 4.29. Data from 10 samples could be utilized to formulate statistical correlations in terms of 𝑅 2 . The statistical measure of goodness of fit is reported
in terms of the coefficient of determination 𝑅 2 and collinearity between the predictor andthe independent data. The collinearity between the predictor and the independent data

86
350

Test Depth =14.31m

1400

Test Depth =6.99m

300

u2 (initial) = 1270kPa - 140.4kPa = 1129kPa

u2 (initial) = 310kPa - 69kPa = 214kPa

Porewater Pressure u2, kPa

Porewater Pressure u2, kPa

1200

1000

800

600

u50 =140.4kPa +(1129/2)kPa=705kPa

400

250
u50 =69kPa +(214/2)kPa=176kPa

200

150

100
u0 69kPa

20050

u0 =140.4kPa
t50

t50 = (12.1)2= 146.41s= (15.5)2= 240.25s
0

0
0

5

10

15

20

25

0

30

5

10

15

20

Square Root of Time, (s)Square Root of Time, (s)Figure 4.21: Dissipation test result interpretation for BH-18 and BH-24.
800
700

700

600

600

Porewater Pressure u2, kPa

Porewater Pressure u 2, kPa

800

Test Depth =25.22m

u2 (initial) = 746Pa

500
400
300

u50 =160kPa +(746/2)kPa=533kPa

200

u2 (initial) = 680kPa - 66kPa = 614kPa

500
400
u50 =66kPa +(614/2)kPa=373kPa

300
200

u0=160kPa

100

Test Depth =6.71m

u0 =66kPa

100

t50 = (3.9)2= 15.21s

0t50 = (16.2)2= 262.44s

0
0

5

10

15

20

0

Square Root of Time, (s)

10

20

30

40

50

Square Root of Time, (s)Figure 4.22: Dissipation test result interpretation for BH-146 and BH-250.
were graphically assessed. In this visual method, establishing the center of the quadrant
required averaging the abscissa and the ordinate values.
Scatter plot between 𝑐 𝑣 and 𝑡50 in this study (Figure 4.20) did not follow the conventional
inverse trend [e.g., Teh and Houlsby (1991)]. Also, no linear correlation exists with thecalculated dissipation data set (𝑅 2 < 0). Similarly, pore pressure corresponding to 50%
dissipation (𝑢 50 ) also reveals no correlation with 𝑐 𝑣 .
As seen in Figure 4.26, scatter plots between laboratory derived 𝑐 𝑣 and CPTu derived
pore pressure (beginning of dissipation test, 𝑢𝑖 ) and Δ𝑢 also demonstrates no correlation,accompanied by 𝑅 2 close to zero.

87

Test Depth =8.96m
1000

1200

u2 (initial) = 940Pa - 88.29kPa = 851.71kPa

u2 (initial) = 1140kPa - 85kPa = 1055kPa
Porewater Pressure u 2, kPa

Porewater Pressure u2, kPa

1200

Test Depth =8.62m

1400

1000

800
u50 =85kPa +(1129/2)kPa=612kPa

600

400

800

600
u50 = 88.29kPa +(851.71/2)kPa=514.15kPa
400

200

200

t50 = (49)2= 2401su0= 88.29kPa

t50 = 490s

u0 =85kPa

0

0
0

100

200

300

400

500

0

10

20

Time, (s)

30

40

50

Square Root of Time, (s)Figure 4.23: Dissipation test result interpretation for BH-264 and BH-274.
1000

450
Test Depth =5m

Test Depth =6.9m

900

400
u2 (initial) = 370Pa - 68kPa = 302kPa

u2 (initial) = 820Pa - 49kPa = 771kPa

350
Porewater Pressure u2, kPa

Porewater Pressure u 2, kPa

800
700

u50 = 49kPa +(771/2)kPa=435kPa

600
500
400
300

300
250
200

u50 = 68kPa +(302/2)kPa= 219Pa

150
100

200
t50 = (18.4)2= 339su0= 49kPa100

u0= 68kPa

50

0t50 = (8)2= 64s

0
0

10

20

30

40

50

0

2

Square Root of Time, (s)

4

6

8

10

12

14

Square Root of Time, (s)Figure 4.24: Dissipation test result interpretation for BH-374 and BH-398.
√
As seen in Figure 4.27, in this study, 𝑐 𝑣 is increasing linearly for an increasing 𝑞 𝑡 and 𝑓𝑠 .
However, more data is required to confirm the collinearity.
Figure 4.28 and Figure 4.29 shows that relationship remains scattered in terms of net cone
resistance, effective cone resistance, and normalized cone tip resistance. Thus, more data
points are required to reach a conclusion. Also, the laboratory derived 𝑐 𝑣 plotted against
CPTu derived 𝑐 𝑣 is very scattered. A few reasons can be attributed to such observations:
1. The dissipation tests were not conducted for at least 4 hours. Consequently, the early
fitting of the curve required a lot of judgement. Also, equilibrium pore pressure
had to be assumed based on ground water level instead of observing the dissipation
curve.

88

2.6E+01

5.0E+02

Coefficient of consolidation cv, (m 2/year)

Coefficient of consolidation cv, (m2/year)

4.5E+02
4.0E+02

2.1E+01

3.5E+02

1.6E+01

3.0E+02
2.5E+02
2.0E+02

1.1E+01

1.5E+02

6.0E+00

1.0E+02
5.0E+01
0.0E+00

1.0E+00
0.1

1

10

100

t50, min

0

200

400
t50, min

(a)

(b)

600

800

Figure 4.25: (a) Relationship between 𝑐 𝑣 and 𝑡50 . (b) Relationship between 𝑐 𝑣 and 𝑢 50 .
7.0E-02

1.4E-01

6.0E-02

Coefficient of consolidation cv, (m 2/year)

Coefficient of consolidation cv, (m 2/year)

1.6E-01

1.2E-01

5.0E-02

1.0E-01

4.0E-028.0E-02

3.0E-02

6.0E-022.0E-02

4.0E-02

1.0E-022.0E-02

0.0E+00

0.0E+00
0

500

1000

1500

ui, kPa

0

200

400

600
Δu, kPa

(a)

(b)

800

1000

1200

Figure 4.26: (a) Relationship between 𝑐 𝑣 and 𝑢𝑖 (estimated initial pore pressure in dissipation test). (b) Relationship between 𝑐 𝑣 and Δ𝑢.
2. In situ drainage condition may not match with the the two-way drainage conditionof the sample in the consolidation cell.
4.5 Statistical Analysis for Undrained Shear Strength
Linear and non-linear regression models were explored to formulate correlations between
𝑠𝑢 and basic CPTu parameters—𝑞 𝑡 , 𝑓𝑠 , 𝑢 2 —for Dhaka soil. In this work, the reference𝑠𝑢 (𝑙𝑎𝑏) is evaluated from unconfined consolidation test (UCT) by evaluating unconfinedcompressive strength. The undisturbed samples were collected from Shelby tubes in thelaboratory. Also, the statistical regression correlations models are divided into two inde-89

2.5E+01

Coefficient of consolidation cv, (m 2/year)

Coefficient of consolidation cv, (m 2/year)

2.5E+01

2.0E+01

2.0E+01

1.5E+01

1.5E+01

1.0E+01

1.0E+01

5.0E+00

5.0E+00

0.0E+00

0.0E+00
0

20

40√qt, kPa

60

80

100

1

51

(a)

101
fs kPa

151

201

(b)

√
Figure 4.27: (a) Relationship between 𝑐 𝑣 and 𝑞 𝑡 . (b) Relationship between 𝑐 𝑣 and 𝑓𝑠 .
2.5E+01

Coefficient of consolidation cv, (m2/year)

Coefficient of consolidation cv, (m 2/year)

2.5E+01

2.0E+01

2.0E+01

1.5E+01

1.5E+01

1.0E+01

1.0E+01

5.0E+00

5.0E+00

0.0E+00

0.0E+00
0

2000

4000
qt-σv0 kPa

(a)

6000

8000

1

2001

4001
qt-u2 kPa

6001

8001

(b)

Figure 4.28: (a) Relationship between 𝑐 𝑣 and net cone resistance. (b) Relationship between 𝑐 𝑣 and effective cone resistance.
pendent function types—Field Based and Laboratory Based . In the field based models,measurements from the CPTu—𝑞 𝑐 , 𝑞 𝑡 , 𝑓𝑠 and 𝑢 2 —are utilized to formulate the correlations. Whereas in the laboratory based models, laboratory data and or 𝜎𝑣0 are incorporated in addition to the CPTu data to explore the correlations. The statistical measure ofgoodness of fit is reported in terms of the coefficient of determination 𝑅 2 and collinearity
between the predictor and the independent data. The collinearity between the predictor
and the independent data were graphically assessed. In this visual method, establishing
the center of the quadrant required averaging the abscissa and the ordinate values. Thus,
only correlations characterized by the highest visual collinearity and calculated 𝑅 2 are90

2.5E+01

450.0

Coefficient of consolidation cv, (m2/year)

Coefficient of consolidation cv, (m 2/year)

500.0

2.0E+01

400.0
350.0
300.0

1.5E+01

250.0

1.0E+01

200.0
150.0
100.0

5.0E+00

50.0

0.0E+00

0.0
0

5

10
qc, kPa

15

20

25

0

(a)

20

40
Qtn kPa

60

80

100

(b)

Figure 4.29: (a) Relationship between Laboratory derived 𝑐 𝑣 versus CPTu derived 𝑐 𝑣 . (b)Relationship between 𝑐 𝑣 and 𝑄 𝑡𝑛 .
summarized in Table 4.4. It should be noted that Robertson (2012a) rated the perceived
applicability for determining 𝑠𝑢 from CPTu as high (see Figure 2.2).
Table 4.4: New proposed correlations for undrained shear strength.
Correlation𝑠𝑢 = 0.0680 ∗ 𝑞 𝑛𝑒𝑡
𝑠𝑢 = 0.0641 ∗ 𝑞 𝑡
𝑠𝑢 = 1.44 ∗ 𝑓𝑠
𝑠𝑢 = 0.0752 ∗ (𝑞 𝑡 − 𝑢 2 )𝑠𝑢 = 34.36 ∗ 𝐹𝑟
𝑠𝑢 = 0.0650 ∗ (𝑞 𝑡 + 𝑓𝑠 − 𝜎𝑣0 )𝑠𝑢 = 0.0582 ∗ (𝑞 𝑡 + 𝑓𝑠 + 𝜎𝑣0 )Independent Function Type
Field Based
Field Based
Field Based
Field Based
Field and Laboratory Based
Field and Laboratory Based
Field and Laboratory Based

n
17
17
17
17
17
17
17

R2
0.74
0.75
0.82
0.71
0.84
0.75
0.77

Based on Figure 4.30, the measured 𝑠𝑢 (𝑙𝑎𝑏) show lower scatter and better correlation
with 𝑞 𝑡 instead of (𝑞 𝑡 − 𝜎𝑣0 ), i.e., 𝑅 2 = 0.75. It is observed that the evaluated empiricalcone factor 𝑁 𝑘𝑡 for clay deposits in Dhaka ranges from 14.7 to 15.6. Also, no correlation
is observed between 𝑁 𝑘𝑡 and 𝑃𝐼 data— which agrees with the findings of La Rochelle
et al. (1988) report for CPTu tests on sensitive clay of eastern Canada. An attempt in
defining the 𝑁 𝑘𝑡 as a function of 𝑠𝑢 (Figure 4.30c) revealed a weak power relationship(𝑅 2 =0.42)—a stark contrast to the findings of Lunne et al. (1997) and others where a very
good correlation was obtained. As shown in Figure 4.30d, no relationship was obtained
between 𝑁 𝑘𝑡 and 𝑂𝐶 𝑅. Another classic relationship in the literature indicates that 𝑁 𝑘𝑡
decreases with 𝐵𝑞 (e.g, Knappett (2012), Lunne et al. (1997), and Mayne et al. (2015) andothers). In this study, no such correlation could be established between 𝑁 𝑘𝑡 and 𝐵𝑞 . The
resulting data was highly scattered to establish any trend.

91

10000

4500
ls

y = 15.59x
R² = 0.75

So
i

1000

to
:5

0.

PI

=

53
)

1

u
,s
dy

u

s

i
Th

100

St

t (

4)

4
to

12

05
*q

I: 4
) (P

I:

(P
qt
3*

0.

,
2

15

20

d(

ru
rls
Ka

1000

20
12
on

1500

14

,s

is

on
rts
be
o
R

St

=

)
65

8)

Th

=

kt

to

(2
01

2000

kt

N
9,
00

ils
so

in

N
y,
ud

r

fo

C

sa

2500

(P

R

os

y = 14.69x
R² = 0.74500H(qt-σv0), kPa

.7

14

to

ob
er
ts

I:

3000

12

NM

u =

)

65

qt, kPa

3500

fo
r

C
la
y

4000

10

0
0

100

200

10

300

100

1000

10000

Su, kPaSu, kPa

(a)

(b)

1000
25

This Study (PI: 12 to 65)
100

20

Nkt

Nkt

Karlsrud (2015) (PI: 4 to 44)

10

15
a

iagu

Paniagua (2019) (PI: 4 to 49)

Pan

10

1

o 49

t
I: 4

) (P

9
(201

)

4 to 44)015) (PI:
Karlsrud (2

5

0

0
0.1

1

10

100
Su, kPa

(c)

1000

10000

0.1

2.1

4.1

6.1

8.1

OCR

(d)

Figure 4.30: (a) Relationship between 𝑠𝑢 and net cone resistance (𝑞 𝑡 − 𝜎𝑣0 ). (b) Relationship between 𝑠𝑢 and corrected cone 𝑞 𝑡 . (c) Relationship between 𝑠𝑢 and net
cone resistance factor (𝑁 𝑘𝑡 ). (d) Relationship between 𝑁 𝑘𝑡 and 𝑂𝐶 𝑅.
Plot of effective cone resistance (𝑞 𝑡 − 𝑢 2 ) against 𝑠𝑢 (as shown in Figure 4.31a) is very
similar to the plot of 𝑞 𝑛𝑒𝑡 in Figure 4.30. There is scatter at the lower range of 𝑞 𝑡 . Thisfinding agrees with Lunne et al. (1997) observation for soft NMC (see section 2.3.1). Evaluation of the 𝑁 𝑘𝑒 —obtained from 𝑞 𝑛𝑒𝑡 data—revealed no correlation between 𝑁 𝑘𝑒 and 𝐵𝑞(𝑅 2 = 0.0163). The result did not agree with the findings of Karlsrud et al. (2005) findings.
Unlike 𝑁Δ𝑢 and 𝑁 𝑘𝑡 , 𝑁 𝑘𝑒 correlated fairly linearly 𝑃𝐼 with increasing 𝑠𝑢 and 𝑅 2 = 0.45(asshown in Figure 4.31). The plot is relatively scattered to be considered reliable. Similarly, a lot of scatter was observed between 𝑁 𝑘𝑒 and 𝑠𝑢 —a power trend with lot of scatter(𝑅 2 = 0.31). Also, no relationship could be established between 𝑁 𝑘𝑒 and OCR.
Using Δ𝑢 only to correlate with laboratory-derived undrained shear strength yields a rela-

92

80

10000

70

44
)
T

1
0.1

Nke

rP
I:
(fo

0
8.

20

98
(1

et

10

y = 13.299x
R² = 0.71

es

u
St

=1

Se

s
hi

ke

nn

,N
dy

30

2)
,N

3(
3.

to

40

=

2

65

ke

ru
d

(2
01

)

:1
PI

10

3

to

(P
I

50

)

:4

to

50

5)

100

Ka
rls

qt - u2, kPa

This Study, Nke = 6.65 (PI: 12 to 65)
Senneset (1982), Nke = 8.0 (for PI: 3 to 50)
Karlsrud (2015) (PI: 4 to 44)

60

1000

0
1

10
Su, kPa

100

0

1000

200
Su , kPa

(a)

400

600

(b)
80

100

70
60

Karlsrud (2015) (PI: 4 to 44)

10This Study (PI: 12 to 65)
Karlsrud (2015) (PI: 4 to 44)

50

Nke

Nke

Senneset (1982), Nke = 8.0 (for PI: 3 to 50)

Senneset (1982), (for PI: 3 to 50)

40
30

1

20
10
0

0
0.1

1

10
PI, %

(c)

100

0

5

10

15

OCR

(d)

Figure 4.31: (a) Relationship between 𝑠𝑢 and effective Cone Resistance (𝑞 𝑡 − 𝑢 2 ). (b)Relationship between 𝑠𝑢 and cone resistance factor. (c) Relationship between
net cone resistance factor (𝑁 𝑘𝑡 and 𝑃𝐼). (d) Relationship between 𝑁 𝑘𝑒 and𝑂𝐶 𝑅.
tively weaker correlation and scatter (as shown in Figure 4.32a). Also, attempts in defining
𝑁Δ𝑢 as a function of 𝑂𝐶 𝑅, 𝑃𝐼 and 𝑤 (individually) was difficult since the data points showhigh scatte. Similarly, the relationship between 𝑁Δ𝑢 and 𝐵𝑞 demonstrated high scatter visually for the 17 data points (4.32b). This is in sharp contrast to the findings of the available
literature [eg., Karlsrud et al. (2005), Lunne et al. (1997), Paniagua Lopez et al. (2019),
and Robertson et al. (1986a)], where low scatter and strong correlations were obtainedusing Δ𝑢 relationships. Relationship between normalized excess pore pressure (Δ𝑢/𝜎𝑣0 )and 𝑠𝑢 demonstrates a likely linear relationship which can be established with more data
points. However, the relationship observed between (Δ𝑢/𝜎𝑣0 ) and 𝑃𝐼 is highly scattered

93

5.0

10000

4.5
4.0
3.5

100

20

Ka

(
rud

rls

,
19

ua

10
Pa

1

I: 4
(P
5)
NΔu

=

to

4

PI:
r(

o4
4t

3.0

9)

o

,f

5
7.

4)

NΔU

Δu , kPa

1000

2.5
2.0
1.5

20

g
nia

1.0
0.5

1
1

10
su, kPa

100

0.0

1000

0

0.2

0.4
Bq

(a)

0.6

0.8

(b)
100

10

10

Δu/σ'v0 , kPa

Δu/σ'v0 , kPa

100

1

1

0

0

0.1

1

10
su, kPa

(c)

100

1000

0.1

1

PI, %

10

100

(d)

Figure 4.32: (a) Relationship between 𝑠𝑢 and excess pore pressure (Δ𝑢). (b) Relationshipbetween 𝐵𝑞 and cone resistance factor 𝑁Δ𝑈 . (c) Relationship between normalized excess pore pressure and 𝑃𝐼. (d) Relationship between normalized
excess pore pressure and 𝑃𝐼.
and would require more data to establish a correlation. Overall, the inconsistent results
herein is mainly due to the negative pore pressure readings. This is mainly due to the location of the pore pressure element 𝑢 2 —the readings are positive for intact clays. Whereas,for heavily overconsolidated fissured clays, the readings tend to be near zero or negative(Mayne et al. (1990)). The results herein confirms the findings of Demers and Leroueil(2002) and Mayne and Holtz (1988) and others that 𝑢 1 should be used instead of 𝑢 2 forsuperior data collection, especially for very stiff and heavily fissured clay. 𝑢 1 pore pressure
readings are always positive, as indicated by Mayne and Holtz (1988).
An attempt was undertaken to explore correlations between 𝑠𝑢 and normalized cone tip

94

1000

100

100

10

Qtn

Qt

10

1

1

0

0

0.1

1

10
Su, kPa

100

1000

0.1

1

(a)

10
Su, kPa

100

1000

(b)

Figure 4.33: (a) Relationship between 𝑠𝑢 and 𝑄 𝑡 . (b) Relationship between 𝑠𝑢 and 𝑄 𝑡𝑛 .
measurements (𝑄 𝑡 , 𝑄 𝑡𝑛 ). As seen in Figure 4.33, a good prediction is possible with moredata. For both the plots, 𝑠𝑢 data points are closely packed for higher values of laboratoryderived 𝑠𝑢 . At the time of writing this research, the author did not find any similar correlations by other investigators.

1000

81

(P

I:5

to

0

7
05

01

10
i
sa
os

n

,s
8)

=

1.

+

)

1.

I:

(2

fs
4*

(P

12

to

65

4

H

1

u

*f s

Fr, %

100

fs, kPa

10

)

53

s
y,
ud

s

i
Th

u

=

1.

1

St

y = 0.0291x
R² = 0.84

y = 0.6933x
R² = 0.82
0
0.1

1

10
Su, kPa

100

(a)

1000

This Study, su = 34.36*Fr (PI: 12 to 65)

0
0.1

1

10
Su, kPa

100

1000

(b)

Figure 4.34: (a) Relationship between 𝑠𝑢 and 𝑓𝑠 . (b) Relationship between 𝑠𝑢 and 𝐹𝑅 .
Plots of 𝑠𝑢 and sleeve friction ( 𝑓𝑠 ) and normalized fiction ratio (𝐹𝑅 ) are presented in Figure
4.34. An increasing linear trend is evident from the scatter plots. In both the plots, thescatter is reduced with increasing 𝑠𝑢 . This observation is profound in the 𝐹𝑅 plot. Also, thescatter is relatively lower for the 𝐹𝑟 plot (𝑅 2 = 0.84). These observations are in agreementwith the findings of the following:95
1. Tomlinson (1957) findings of driven piles in clay, where its side friction was expressed as a percentage of the undisturbed cohesion of the clay. Implying that thesleeve friction of the cone represents a ”percentage” (0.35 in this study) of the 𝑠𝑢 ofclay soils.
2. Lunne et al. (1997) demonstrated good correlation between 𝑓𝑠 and the remolded 𝑠𝑢
of fine-grained soils. However, a reservation was suggested in the case of very softsensitive clays, where very low remolded strength can result in very low 𝑓𝑠 values
and thereby reducing accuracy—as is observed for very low values of 𝑓𝑠 in Figure
4.34, which shows a lot of scatter at the lower range of 𝑓𝑠 .
Sleeve measurements are thought to be less reliable than the cone tip measurements [eg:Chen and Mayne (1996) and Lunne et al. (1997)]. However, in this work, the sleeve measurements have a significantly better correlation with the laboratory-derived 𝑠𝑢 —unlike
the correlations developed by the cone tip measurements and the pore pressure measurements.
Linear regression relations—for (𝑞 𝑡 + 𝑓𝑠 −𝜎𝑣0 ) and (𝑞 𝑡 + 𝑓𝑠 +𝜎𝑣0 )—unfolds good predictions
accompanied by 𝑅 2 = 0.75 and 0.77 respectively (as shown in Figures 4.35a and 4.35b).
The correlation obtained is slightly better than correlations obtained using 𝑞 𝑛𝑒𝑡 and (𝑞 𝑡 −𝑢 2 ). The data points are less scattered with increasing (𝑞 𝑡 + 𝑓𝑠 − 𝜎𝑣0 ). Its corresponding
cone factor shows fairly good agreement with 𝑠𝑢 —the trend is that of a decreasing powerfunction accompanied by 𝑅 2 =0.50. However, no correlation was obtained when plottedagainst 𝑃𝐼. Despite obtaining good correlations using 𝑞 𝑡 , 𝑓𝑠 and 𝜎𝑣0 , the resulting 𝑁 𝑘𝑡
ranges from 15.4 to 17.2—which is higher than the suggested value of 14 by Robertson(2009).

96

10000

100000

01

(2

.84

)0
σ v0
q t-

Ho = 0.0

:1

su

10
is

Th

S

,N
dy
tu

kt

=

.4
15

I
(P

2

to

)
53 f s*to:5 .390
IP) ( 46 +01000)

ain *(
7ss

100
qt + fs - σv0

8)

10000

)
53 *f sto0
:5 .39I(P 6 +065

qt + fs + σv0

1000

in

100

a
ss

Ho

s u=

18 0.8(20 -σ v0)
qt

(
7*

0.0

N
y,

10

7.2

2
I: 1

)
65
to

(P

=1
t

k

tud
sS

i

Th

1

1

y = 15.38x
R² = 0.75

y = 17.19x
R² = 0.77

0

0
0.1

1

10
su, kPa

100

1000

0.1

1

(a)

10
su, kPa

100

1000

60.1

80.1

(b)

80
y = 121.44x-0.54
R² = 0.50

35

60

30

50

25
Nkt

Nkt

70

40

20

30

15

20

10

10

5

0

0
0

100

200

300

0.1

20.1

40.1
PI, %

Su, kPa(c)(d)

Figure 4.35: (a) Relationship between 𝑠𝑢 and (𝑞 𝑡 + 𝑓𝑠 − 𝜎𝑣0 ). (b) Relationship between 𝑠𝑢
and (𝑞 𝑡 + 𝑓𝑠 + 𝜎𝑣0 ). (c) Relationship between normalized excess pore pressure
and 𝑃𝐼. (d) Relationship between normalized excess pore pressure and 𝑃𝐼.

4.6 Summary
This chapter compared the laboratory-derived geotechnical parameters with the CPTuderived geotechnical parameters. In the process, several new correlations were developed.
These correlations were then compared with the existing CPTu correlations graphically.
Constrained modulus 𝑀 observations:
1. A strong linear trend is observed between overburden pressure, moisture content,
plasticity index, and laboratory-derived constrained modulus. This is indicative thatthese parameters govern the constrained modulus.
2. 𝑓𝑠 based correlations yielded more scattered results than 𝑞 𝑐 based data. However,taking the square-root of 𝑞 𝑐 and 𝑓𝑠 also did not produce any relationship with thedata set. Hence, more data is required to reach a conclusion.
3. 𝑢 2 based data could not be used to estimate laboratory-derived constrained modulus
in this study.
4. 𝜎𝑣0 produced a positive linear correlation with 𝑀, accompanied by 𝑅 2 = 0.43.
5. Existing correlations in the literature seems to represent the upper bound of theresults presented herein.
For the compression index 𝐶𝑐 parameter, the following observations from this research
can be summarized:
1. A hyperbolic relationship is observed beteen 𝑞 𝑐 and 𝐶𝑐 , confirming the findingsof Sanglerat (1972). The hyperbolic relationship was further confirmed as seen in
Figure 4.9 and Figure 4.10.
2. The laboratory-derived 𝐶𝑐 were most in the upper-limit of the boundary proposedby Sanglerat (1972).
3. Moisture content is seen to have a strong positive linear trend with 𝐶𝑐 , accompanied
by 𝑅 2 = 0.78.
For OCR, the following observations from this research can be summarized:
1. In this study, normalized cone tip resistances provided less scatter and better correlations:(a) 𝑄 𝑡 : 𝑅 2 = 0.69(b) 𝑄 𝑡𝑛 : 𝑅 2 = 0.85′(c) Normalized effective cone resistance, (𝑞 𝑡 − 𝑢 2 )/𝜎𝑣0 : 𝑅 2 = 0.67′(d) Battaglio et al. (1986) referenced parameter, (𝑞 𝑡 − 𝜎𝑣0 − Δ𝑢)/𝜎𝑣0 : 𝑅 2 = 0.74

(e) Normalized cone resistance, (𝑞 𝑡 + 𝑓𝑠 )/𝜎𝑣0 : 𝑅 2 = 0.74
2. No relationship was found between CPTu derived pore pressure parameter and OCR.
The dissipation test results were conducted less than the required length of time. The
following can be summarized for evaluating coefficient of consolidation 𝑐 𝑣 using CPTu:
1. With limited data set (10 in numbers), a relationship based on cone-tip resistance,
𝑓𝑠 and 𝑢 2 could not be produced.
2. No correlation could be developed for CPTu derived 𝑢 50 and 𝑡50 .
3. No relation could be established for the scatter plot between laboratory-derived 𝑐 𝑣
and CPTu-derived 𝑐 𝑣 . A few reasons attributed to this observation:(a) Dissipation tests were conducted less than 4 hours.
(b) In situ drainage condition may not match with the two-way drainage conditionof the sample in an odeometer consolidation cell.
For the undrained shear strength parameter 𝑠𝑢 , the following observations from this research can be summarized:
1. In this study, the evaluated empirical cone factor 𝑁 𝑘𝑡 for clay deposits in Dhaka
ranges from 14.7 to 17.2.
2. Following the most popular approach, an attempt in defining the 𝑁 𝑘𝑡 as a functionof 𝑠𝑢 was difficult 𝑅 2 = 0.42. Similarly, no correlation could be established between
𝑁 𝑘𝑡 and 𝐵𝑞 .
3. 𝑓𝑠 based correlations (𝑅 2 = 0.82) yielded better than 𝑞 𝑡 based correlations (𝑅 2 =0.75).
4. Multiple and non-linear regression resulted in between several parameters (as shownin Table 4.4) resulted in strong correlations.
5. For over-consolidated clay deposits, 𝑢 2 readings are not reliable.

393

PART-VI

MICROZONATION OF RANGPUR CITYCORPORATION AREA BASED ON SITEAMPLIFICATION USING NONLINEARTECHNIQUE AND LIQUEFACTIONBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Nusrat Jahan
Mehedi Ahmed Ansary

1Chapter 1

INTRODUCTION
1.1

GeneralEarthquakes are among the natural hazards that are most threatening due to theirunpredictability and severity. The occurrence of earthquakes is caused by tectonic plateboundaries. Large earthquakes happen less often than major floods, but they have thepotential to damage far greater regions and have long-lasting repercussions on society, theeconomy, and politics (Akhter, 2010). Bangladesh is vulnerable to earthquakes, according
to historical seismic data for the country and surrounding areas. Bangladesh is the mosthighly populated place in the world. This means that if an earthquake happens there, it willaffect too many persons per unit area than in other places where earthquakes occur often.
Furthermore, due to the relatively low number of catastrophic quakes that have happened
over the course of the past century, the majority of the people as well as those responsible
for formulating policy do not consider seismic threats as being of significant concern.
Recent seismic activity in Bangladesh reveals that the country is subject to a significant
seismic threat. According to (Bilham et al., 2001), there is a significant disparity between
the amount of energy that has accumulated in this area and the frequency with which
earthquakes have occurred in the past, which suggests that the Territory is at an increased
risk of experiencing a devastating earthquake in the near future.
The high pace of modernization, uncontrolled expansion, bad land utilization management,
bad design tradition, insufficient framework and service supply, and ecological devastation
have all contributed to an increase in the likelihood of earthquake disasters in cities during
the past few decades (Erdik, 2006). Rapid urbanization and construction in hazardous areas
increase the dangers already present in major cities. It is obvious from the histories of pastearthquakes in various nations that they can’t be stopped from happening; nevertheless,appropriate risk minimization and management methods can lower the danger of thisterrible event and the repercussions of its occurrence.
The assessment of ground response being one of the most significant challenges
in earthquake engineering as well as a common challenge that engineers face. Predicting
ground surface motions helps in developing design response spectra, determining
earthquake-generated forces which can create instability of ground and earth retaining394

constructions, and assessing dynamic stress and strain helps in analysing seismic hazards.
All of these are possible with the help of ground response analyses. Modelling the rupture
framework at the earthquake's epicentre, simulating the travel of stress waves across theearth towards the top of strata underneath the specific site, and then figuring out how thesoil above the bedrock affects ground surface motion: these are the components of acomprehensive ground response analysis. This strategy is not so feasible for typicalengineering fields since the process of the fault rupture is convoluted, and the pattern of
the transmission of energy between the origin and the location is so unclear. After then, thechallenge of ground response analysis consists in figuring out how the soil deposit reacts
to the movement of the bedrock directly beneath it. It has been known for a considerable
amount of time that the local soil conditions can have a significant impact on the severityof earthquake damage. Ground response analysis has been done in many different ways
over the years. Most of the time, the methods are categorized by the number of dimensionsof the problems they can solve. However, many of the two-dimensional and threedimensional methods are simple extensions of the respective one-dimensional methods.
A microzonation assessment of a city is an important stage in the process of reducing acity's exposure to the dangers posed by earthquakes and preparing for future seismic
disasters. Seismic microzonation can be taken into account when thinking about themagnitude of earthquakes, the likelihood of liquefaction, and the potential for landslides.
In all three scenarios, seismic microzonation relies heavily on geotechnical siteclassification and evaluation of site response at the time of earthquakes. When an
earthquake impacts a human community, the local site circumstances and the effects of thelocal site are the most significant aspects to consider. Therefore, it is essential to evaluate
the localized dynamic characteristics of soils and infrastructures before the occurrence ofseismic occurrences.
Seismic hazard lets us describe the possible effects of earthquakes that should take into
account while building new constructions or improving old ones. At a micro-scale, thisassessment needs to look at the effects that seismological tremors could have on thestability of the soils, such as liquefaction and site amplification. It also needs to take into
account the existence of active seismic faults near the locations, if their characteristics
suggest that they could cause seismic deformations at the ground, and it needs to definereference seismic movements for each location, considering the different soil conditions.
395

The research that was done on several powerful earthquakes all over the world showed thatthe soil conditions, that include the unconsolidated sediments and geological characteristicsof the rocks, the tectonic fabric, and the geomorphological features, have a significant
impact on the amount of damage that is caused to structures when a powerful earthquake
occurs.
The liquefaction problem has become significant when it began to disrupt both social andhuman activities by interfering with the operation of facilities. Additionally, the problem
became significant following fast urbanization since it led to the expansion of cities into
reclaimed land. In numerous ways, liquefaction impacts structures, bridges, subsurface
pipes, and critical infrastructure. During previous earthquakes, such as the ones that
occurred in 1964 in Niigata (Japan) and 1964 in Alaska (USA), 1971 in San Fernando,
1989 in Loma Prieta, 1995 in Kobe (Japan), and 2004 in Chuetsu (Japan), ground failurescaused by liquefaction were a key contributor to the devastation that was caused. The
majority of Bangladesh, including the city of Rangpur, is an alluvial plain that is composedof fine to medium sand and has a low percentage of fine deposits. Most locations in
Bangladesh have ground water table that is shallow. In the event of a strong earthquake,the deposits can become liquid.
In this investigation, one dimensional (1-D) site response analysis has been carried out in
Rangpur City Corporation Area. 16 borehole data up to a depth of 50 meters has beencollected and used to assess site amplification, and 24 borehole data has been collected toassess (8 borehole data has been obtained from the test that was conducted previously by
BUET) liquefaction potential in the area for microzonation purposes. For the purpose ofgenerating the surface Peak Ground Acceleration (PGA) and Response Spectrum,
Equivalent Linear (EL) and Nonlinear (NL) approaches have been used. To assess theliquefaction potential surface PGA values obtained from the NL method have been usedalong with different methods.
1.2

The Study Area

Rangpur is one of those places that has expanded in recent years despite the uncertain
earthquake and liquefaction risk factors. Rangpur City Corporation is situated in the
Rangpur Sadar Upazila of the Rangpur District and Rangpur district is located in3

Bangladesh's north-western region. It is surrounded by Nilphamari and Lalmonirhat
districts on the north, Gaibandha district on the south, Kurigram district on the east andDinajpur district on the west shown in Figure 1.1 (Rangpur District - Banglapedia). The
area of Rangpur is 2370.45 square km. It ranges in latitude from 25°43' to 25°48' and inlongitude from 89°12' to 89°19'. The Teesta River is the largest river in the Rangpur
district's north-eastern region. Rangpur has a tropical humid and dry climate. Monsoon
months are characterized by the highest precipitation levels. The yearly precipitation in theregion is approximately 1,448 millimetres (Qumruzzaman et al., 2008).
According to BNBC (2020), Rangpur City is located in the northwestern region of
Bangladesh. On the seismic zonation map of Bangladesh, the area that includes Rangpur
Town and its surrounds may be found in Zone III, which has a fundamental seismic
coefficient (z) of 0.28 g. It has a severe seismic intensity. The design basis earthquake(DBE) ground motion is chosen at a level of ground shaking equal to 2/3 (two-thirds) of
the maximum considered earthquake (MCE) ground motion (BNBC-2020). The designbasis earthquake for this study is determined to be 0.19 g, and it is obtained by multiplying
the maximum earthquake considered (0.28 g) by 2/3. The majority of Bangladesh,
including the city of Rangpur, is an alluvial plain that is composed of fine to medium coarse
sand and has a low percentage of fine deposits. Most locations in Bangladesh have ashallow groundwater table. In the event of a strong earthquake, the deposits can becomeliquid.
1.3

Objectives of the Study

The following are the main objectives of the research:(1) To investigate the soil characteristics of the study site by conducting field andlaboratory tests.
(2) To study site amplification for the study area.
(3) To develop site response spectra for some selected sites.
(4) To assess liquefaction for the study area.

4

Figure 1.1: Rangpur District (after Banglapedia)

1.4

Organization of the Thesis

In order to accomplish the objectives that have been outlined, the thesis is separated into
multiple chapters. The chapters are organized in the following manner:
In the first chapter, an overview of the background of the research, a statement of the
problems, the aims, and outline of this research are given.
5

The findings of the prior study are presented in chapter two, which covers a wide range ofthemes including site response of soil, microzonation, site amplification and liquefaction,
etc.
The third chapter describes the field SPT and laboratory tests undertaken to determine thesubsoil condition of the Rangpur City Corporation area. Additionally, an overview of the
DEEPSOIL software and the methodology as a whole is presented and addressed in thischapter.
Chapter four describes the analysis procedure of the DEEPSOIL software for arepresentative borehole. The location and SPT results of one borehole are presented toinvestigate the soil characteristics of the study location. A typical analysis is presented forone sample borehole using the DEEPSOIL software. Comparison graphs, target response
spectra, a proposed design spectral acceleration curve, liquefaction susceptibility
estimation, and a liquefaction hazard map are also presented in this chapter.
The results and discussion of the research program are presented in Chapter five. In
addition to that, recommendations for the scope of future research are included in thischapter.

6

3

Chapter 3

DATA COLLECTION AND METHODOLOGY
3.1

Introduction

Data for a typical geotechnical investigation might originate from a wide number ofsources, including field investigations, site inspections, model studies, and so on. The
major goal of this study is to create a map of Rangpur City Corporation’s sub-soil features(i.e., site amplification and site response spectra) and liquefaction potential. For collecting
geotechnical data, both field and lab investigations were carried out. For the field
investigation, boreholes were drilled, samples were collected and a Standard Penetration
Test (SPT) was carried out. Some of the tests that were done in the lab were the specificgravity test, the grain size analysis test (using standard sieve), and the grain size analysis
test using a hydrometer. This chapter provides a condensed summary of both the field andlaboratory investigations that were carried out as part of the current research.
3.2

Geotechnical Data

An in-depth field survey of the Rangpur City Corporation jurisdiction was conducted. The
locations to be tested using a standard penetration test are the focus of this investigation.
Data that was necessary, such as reports on the subsurface and information on geology,
geography, and other such topics, was gathered from a variety of relevant sources. In thisparticular research, a total of 16 (sixteen) subsoil investigations were carried out, and 8(eight) additional subsurface reports were obtained from the test that was conductedpreviously by the Bangladesh University of Engineering and Technology (BUET).
3.3

Standard Penetration Test (SPT)The Standard Penetration Test, often known as the SPT, is the most common type ofsubsurface investigation assessment used for foundation design not just in Bangladesh but
all over the world. But SPT N-values can be misleading about the risk of liquefaction if thetests aren't done carefully due to their intrinsic variability, unpredictability and reactivity
to the test procedure. For the purpose of investigating the site amplification and soilliquefaction potential characteristics of the Rangpur City Corporation region, the data froma total of 16 borehole standard penetration tests were utilized. The boreholes reached adepth of up to fifty meters (50 m) in certain places. The boreholes were dug in a vertical40

orientation utilizing the wash boring method and apparatus that was able to force tube
samplers through the ground using hydraulic pressure. In each boring, a SPT was
performed at intervals of nominally 1.5 meters, and the N values that is, the number ofblows counted for each standard penetration, were recorded. Tests have been performed inaccordance with ASTM D1586 to determine liquefaction potential using SPT data. Thishas been done in order to minimize or at the very least reduce some of the major sourcesof error. Even though granular soils are ideal for the Standard Penetration Test, it has beensuccessfully applied to cohesive soils as well. The primary goals of the field investigations
include boring and tracking of soil strata, sampling, implementation of Standard
Penetration Test and recording the depth of ground water table.
The SPT value is affected by a wide variety of parameters, all of which are taken into
consideration by ASTM. The length of the drill stem and its cross-section, the blow rate,
the type of anvil, the method of operation, the type of hammer, the alignment of thehammer, the use of borehole fluid, and other factors are examples of some of these
considerations.
3.4

Laboratory tests

During the SPT, both disturbed and undisturbed samples were collected for analysis. The
collected samples were evaluated at the geotechnical laboratory of Bangladesh Universityof Engineering and Technology (BUET). The conducted experiments are listed in Table
3.1. These tests were carried out in accordance with the methodology outlined in thestandard established by the American Society for Testing Material (ASTM). The specificgravity and grain size analysis test are examples of those that were carried out in thelaboratory. The ASTM standards provide information regarding the specifications of thetesting techniques.
Table 3.1: List of conducted tests

Name of the test

Standard Reference

Specific gravity test

ASTM D854-00

Grain size analysis (sieve analysis)

ASTM D422-63
41

3.5

Location of the Borehole

Within the Rangpur City Corporation, a total of sixteen boreholes were drilled. Saha (2005)
provided the source for the collection of the data from eight boreholes, each of which werecarried out by BUET in different part of Rangpur City. Borehole coordinates and locations
can be found in Table 3.2. Figure 3.1 is a map of the Rangpur city corporation that showswhere the locations of the boreholes are.

Figure 3.1: Borehole location in Rangpur City Corporation

42

Table 3.2: Location of the boreholes
Location

Ward

Borehole

N (Latitude)

E (Longitude)

RP-1

Ward 16BH1

25°46.855΄89°13.121΄

RP-2

Ward 16BH2

25°46.800΄89°13.140΄

RP-3

Ward 16BH3

25°45.900΄

89°13.800΄

RP-4

Ward 17BH1

25°45.479΄89°13.155΄

RP-5

Ward 18BH1

25°45.120΄

89°14.100΄

RP-6

Ward 18BH2

25°44.640΄

89°14.040΄

RP-7

Ward 19BH1

25°46.500΄

89°14.400΄

RP-8

Ward 19BH2

25°45.420΄

89°14.700΄

RP-9Ward 20BH1

25°44.921΄89°15.066΄

RP-10

Ward 22BH1

25°43.913΄89°14.342΄

RP-11

Ward 24BH1

25°44.620΄89°15.802΄

RP-12

Ward 27BH1

25°43.585΄89°15.344΄

RP-13

Ward 29BH1

25°43.185΄

89°17.169΄

RP-14

Ward 29BH2

25°43.870΄89°18.361΄

RP-15

Ward 29BH3

25°44.592΄89°18.543΄

RP-16

Ward 30BH1

25°44.549΄89°16.771΄

BT-13

Ward 17BH1

25°44.922΄89°12.300΄

BT-4

Ward 23BH1

25°45.390΄

89°15.492΄

BT-2

Ward 21BH1

25°44.100΄89°15.192΄

BT-17

Ward 25BH1

25°45.180΄

89°16.218΄

BT-18

Ward 26BH1

25°44.052΄89°15.714΄

BT-1

Ward 28BH1

25°43.632΄89°16.692΄

BT-7

Ward 28BH1

25°43.026΄89°15.762΄

BT-8

Ward 30BH1

25°44.058΄89°17.334΄

CodeSourceThis Study

Study
conducted
by BUET(Saha,
2005)

43

3.6

Response Spectrum

An estimation of the peak linear structural response to dynamic motion can be obtained byanalysing its response spectrum. This estimate can be presented in the formof displacement, velocity, as well as acceleration spectrum. In most cases, it is utilized in
the process of response analysis to seismic events. It makes the assumption thatthe response system is linear in order for it to be examined in the frequency domain
utilizing the system's natural modes, which have to be extracted in a step that comes before
the eigenfrequency extraction stage (i.e., natural frequency extraction). For the purpose ofgenerating the surface response spectrum, equivalent linear (EL) and nonlinear (NL)
approaches will be utilized with the help of DEEPSOIL software.
3.7

Peak Ground Acceleration (PGA)

A measurement of the maximum acceleration of the surface during an earthquake isreferred to as the Peak Ground Acceleration (PGA). For the sake of designing, it is the mostsignificant parameter that can be considered. It is possible to calculate the PGA value atthe bedrock level by conducting a Probabilistic Seismic Hazard Assessment at the location
using the appropriate Ground Motion Prediction Equations. It is possible to express peakground acceleration as a percent of g, which is the standard acceleration due to the gravityof the Earth and is comparable to g-force. With the aid of the DEEPSOIL program, EL and
NL techniques will be used to generate the surface PGA.
3.8

Modulus Reduction and Material Damping Curves

Due to the lack of material-specific test findings for the area under investigation, modulus
reduction and material damping curves were taken from the relevant body of publishedresearch. The normalized material damping and modulus reduction curves that weredeveloped by Darendeli (2001), were employed in this study to estimate the Nonlinear(NL) behavior of the soft sedimentary layers of Rangpur City Corporation. These curves
shown in Figure 3.2 were used to model the behavior of the soil deposits. It is necessary tohave the following soil properties in order to use the relationships found in Darendeli(2001): the vertical stresses under the optimum condition in the starting state, theinitial lateral earth pressure's coefficient, the loading cycle numbers, the loading
frequency, the plasticity index and the OCR ratio (Ansary and Jahan, 2021).
44

(a) Normalized shear modulus vs strain curve(b) Material damping vs shear strain curve
Figure 3.2: A representative example of Darendeli (2001) reference curves for the (a)normalized shear modulus reduction and (b) material damping (after Ansary et al., 2022).

45

3.9

Software for Site Response Analysis: DEEPSOIL

Hashash et al. (2020) created the DEEPSOIL software for the purpose of conducting a onedimensional (1-D) site response study. This program may analyze the site response in asingle dimension using linear, equivalent linear, or nonlinear methods. DEEPSOIL
software provides options for time-domain linear and frequency-domain linear site
response analysis, as well as frequency-domain equivalent-linear analysis and time-domain
nonlinear analysis. DEEPSOIL is able to do the nonlinear site response analysis both withor without pore pressure generation. The software undergoes consistent updates that
include the addition of new features as well as the correction of bugs in an effort to makethe results more accurate.
3.9.1 Linear Analysis
There are two approaches to solving a model in Linear Analysis, one is the frequency
domain and the other is the time domain. Both of the linear site response studies take into
account the highest soil stiffness for the entirety of the time history, in addition tomaintaining a constant damping ratio.
3.9.2 Equivalent Linear Analysis
An iterative process is utilized in the Equivalent Linear model for the purpose of selecting
the shear modulus and damping ratio soil parameters. This methodology was initiallydeveloped by the program called SHAKE. Either discrete points or the soil parameters that
constitute the core curve of one of the NL methods can be used to establish these features.
Discrete points are the more common method. In order to observe the maximal
amplification of seismic waves, a linear response analysis with equivalent parameters was
carried out in this research.
3.9.3 Non-Linear Analysis
Non-linear analysis, often known as NL analysis, is used to solve equations of motion
only in the time domain by employing either the Newmark β approach (implicit) or the
Heun method (explicit). Users can choose from a number of different soil models such as
the General Quadratic/ Hyperbolic Model (GQ/H), Pressure-Dependent Modified Kondner
Zelasko (MKZ), User-Defined (UMAT), Discrete Points etc. It is possible to carry out the46

analysis either with or without the generation of porewater pressure. Whenever a nonlinear
site response analysis is performed, the user has the option of automatically retrieving theresults of the site response using the equivalent linear approach.
In this study General Quadratic/ Hyperbolic Model (GQ/H) was used as the soil model anda non-massing re/unloading formulation was used. As a reference curve, Darendeli's
proposed curve was used. The time-domain was used to do the calculations for the
nonlinear model. The ground motion at the soil column base was accounted for using theaccelerogram of the matching bedrock spectral acceleration during the response analysis.
3.10 Summary of the Method of the Work
The approach that was used in this study is outlined in the form of a flow chart, which isshown in Figure 3.3. It is not possible to determine site amplification parameters using site
response analysis without the properties for dynamic study of soils, such as shear wave
velocities (Vs), accelerograms of earthquakes, shear modulus reduction curves andmaterial damping.
In order to accomplish this goal, it is necessary to consider additional soil properties suchas the over-consolidation ratio, the internal friction angle, the unit weight and the plasticity
index. In order to conduct the site response analysis, the information required is acquired
from 24 different borehole locations across the study site.
The liquefaction analysis employing various methods (such as Seed and Idriss simplified
method, Chinese method and Japanese method) can be performed utilizing the surface PGA
generated from the Nonlinear (NL) technique.

47

Figure 3.3: Flow chart of the methodology employed in this research48

4

Chapter 4

RESULTS AND DISCUSSION
4.1

Introduction

The site amplification and response spectra of the city of Rangpur have been analysed withthe aid of the DEEPSOIL program. To learn more about the soil at the site of theinvestigation, this chapter presents the location and SPT findings from a single borehole.
For the purpose of demonstration, the DEEPSOIL software is used to perform an analysis
on a single representative borehole. In this section, a number of comparison graphs (depth
versus PGA, and PSA versus time) are illustrated. This chapter also includes the target
response spectrum, a proposed design spectral acceleration curve, an estimate of thelikelihood of liquefaction, and a map depicting the potential danger caused by such an
event.
In the Rangpur city corporation, the borehole 1 (BH1) of ward 16 named as RP-1 in thisstudy is located at the side of the Agricultural tools-making factory, the right side of themain road. It has a latitude of 25°46.855΄ and a longitude of 89°13.121΄. It has agroundwater level of 4.42 meter from the existing ground level (EGL). The location of theborehole is presented in Figure 4.1 and the standard penetration test result of RP-1 areshown in Table 4.1. During each boring, a standard penetration test (SPT) was carried out
at intervals of nominally 1.5 meters, and the N values (the number of blows recorded foreach standard penetration) were noted down. The standard penetration test result of all 24
boreholes used in this study is presented in Appendix A.
4.2

DEEPSOIL Analysis

The analysis has been carried out using DEEPSOIL Software. In this Analysis theNonlinear method has been chosen as Analysis Method, the time domain is selected as thesolution type, General Quadratic/Hyperbolic Model (GQ/H) is selected as the default soilmodel, the Non-Masing Re/Unloading is selected as Default Hysteretic Re/Unloading
Formulation, the Metric unit is selected as Unit System, and Equivalent Linear – frequency
domain is selected as Complementary Analysis as shown in Figure 4.3.

49

Figure 4.1: Location of RP-1 (Ward 16_BH1)

50

Table 4.1: Standard Penetration Test (SPT) result of RP-1 (Ward 16_BH1)

Depth (m)Thickness(m)

Soil Description

1.5

6

3.0

5

4.5
6.0

9.0

Grey, loose to medium dense, silty FINE SAND,

10

trace mica

14

7.5

15

9.0

17

10.5

1.5

Light grey, FINE SAND and SILT, trace mica

5

12.0

1.5

Light grey, loose, silty FINE SAND, trace mica

7

13.5

19

15.0

28

16.5

29

18.0
19.5

12.0

Grey to light brown, medium dense to dense, silty

33

FINE SAND, trace mica

40

21.0

34

22.5

43

24.0

47

25.5

50

27.0
28.5

6.0

Light brown, very dense, silty FINE SAND, trace

50

mica

50

30.0
4.3

SPT-N

50

Basic Soil Properties Used in DEEPSOIL Software

The basic soil properties used in this research are the thickness of soil layer, unit weight,
shear wave velocity, effective vertical stress, shear strength etc. The unit weight is takenfrom the soil test report and effective vertical stress is calculated using the following
equation 4.1.
Effective vertical stress = γ * h(4.1)

Here, γ = unit weight of soil and h = height of the soil layer.
51

4.3.1 The Thickness of the Soil Layer
The thickness of the layer has been chosen in such a way that, the maximum frequency
should not be less than 30 Hz (i.e., the minimum value of the frequency should be 30 Hz)
and this is only applicable for time domain analysis. The formula for determining the
maximum frequency, which is the highest frequency of the layer that is capable ofpropagating, is shown in the following equation 4.2. The maximum frequency (fmax) canbe increased by lowering the layer's thickness (Hashash et al., 2020). If the maximum
frequency of any layer is less than 30 Hz, then the layer should be divided to sublayers withsmaller thickness with some properties to increase the frequency (fmax) value.
fmax =

Vs
4H

(4.2)

4.3.2 Determination of Shear Wave Velocity (Vs)
In this research, the shear wave velocity is determined from the standard penetration test
(SPT) value. The empirical relation that has been shown here will be utilized to convert theSPT value into shear wave velocity. This is necessary since the program DEEPSOIL
requires the shear wave velocity as one of the input parameters. The relation is adopted
from Tasmiah and Ansary (2022). The relation is shown in the following equation 4.3. The
shear wave velocity profile of RP-1 located in the Rangpur City Corporation Area is shownin Figure 4.2. From the shear wave velocity profile, it is clear that up to a depth of 55
meters, there is a significant amount of fluctuation. The reduction in the thickness of thesoil layer, which was done in order to keep the minimum frequency of 30 Hz as describedin section 4.3.1, causes this variation to take place. The shear wave velocity is around 800
m/sec at a depth of 160 m. So, it can be assumed that the bedrock is located 160 m below
the ground level in the study location.
Vs = 63.068 * D0.3597551 * N0.1194517(4.3)

Where, Vs = Shear Wave Velocity (m/sec); D = Soil Depth (m); and N = SPT blow count.

52

Figure 4.2: Shear wave velocity profile for RP-1 located in Rangpur city Corporation
4.3.3 Determination of Shear Strength (τ)
When attempting to characterize the large-strain characteristics of the soil with the GQ/H
model, it is necessary to enter the shear strength of the soil stratum. The Mohr-Coulomb
equation is used to determine the desired shear strength for a given nonlinear shear modulus
reduction.

53

τtarget, implied = cvs + σ΄v * tan (φ)(4.4)

Where, σ΄v = effective vertical stress, φ = angle of internal friction, cvs = shear strengththat a linear elastic material with 80% of its maximum shear modulus is assessed to haveat 0.1% shear strain (Hashash et al., 2020).
4.3.4 Reference Curve
The Darendeli (2001) curve is selected as a reference curve with some parameters like
Plasticity Index (PI) = 0, Over Consolidation Ratio (OCR) = 1, and the coefficient of earthpressure at rest (K0) which is calculated using the following equation 4.5.
K0 = [1 – sin(φ)] * OCRsin(φ)(4.5)

Here, φ = Angle of internal friction and φ = √(20*SPT) + 15 (Hatanaka et al., 1998). φ canbe found using the SPT N value.
The Modulus Reduction and Damping Curve Fitting (MRDF) with UIUC reduction factor
are used as the fitting procedure in curve fitting. GQ/H Model is set up for a shear strain
range of up to 0.05%, based on the Modulus Reduction Curve, as long as the shear stresses
reach 95% of the target shear strength. All the soil profile definitions, shear strength inputs,
and reference curve inputs are shown in Figure 4.4. GQ/H model fitting is shown in Figure4.5. Soil profile plot such as depth wise shear wave velocity, maximum frequency, small
strain damping ratio, implied shear strength, normalised implied shear strength, implied
friction angle is shown in Figure 4.6.

54

Figure 4.3: Analysis type definition for RP-1

Figure 4.4: Soil Profile Definition and Dareldeli’s Reference Curve Input for RP-1

55

Figure 4.5 :GQ/H model fitting and soil model properties

Figure 4.6: Soil Profile Plot
56

4.3.5 Input Motion Selection
RSN3976_SANSIMEO_CMR090_0.19g has been selected from Pacific Earthquake
Engineering Research Centre (PEER) as input motion for the purpose of analysis (PEERGround-Motion-Data-Base-Reader). The design basis earthquake (DBE) ground motion ischosen at a level of ground shaking equal to 2/3 (two-thirds) of the maximum considered
earthquake (MCE) ground motion (BNBC-2020). The design basis earthquake for thisstudy is determined to be 0.19 g, and it is obtained by multiplying the maximum earthquake
considered (0.28 g) by 2/3. So, the input’s PGA value has been scaled as 0.19 g in the
single motion view. The peak ground acceleration (PGA) at the surface is calculated bymultiplying the bedrock peak ground acceleration (PGA) by a calculated site coefficient(which is 0.19 g for Rangpur). Previous researchers did not evaluate the surface PGA value
for this site and instead relied on BNBC
4.3.6 Analysis Control Definition
The number of iterations on the frequency domain is 15, the effective shear strain ratio(SSR) is 0.65, and the frequency independent is selected as a complex shear modulus
formulation. In the case of time domain analysis, the step control is flexible, the maximum
strain increment is 0.005%, the Newmark Beta method is selected as the integration
scheme, and the time history interpolation method is zero-padded in the frequency domain.
4.3.7 Results
The time history plots showing the EL (Blue line) and NL (Gray line) are shown in Figure
4.7, and the response spectra summary is shown in Figure 4.8.
4.4

Earthquake Input Motions

For the purpose of DEEPSOIL analysis in this study, data for ten (10) earthquakes has beencollected from the PEER-Ground-Motion-Data-Base-Reader. All their record sequence,earthquake name, year, station name, magnitude, mechanism, the closest distance to therupture surface (RRUP), the Joyner - Boore distance (RJB), shear wave velocity value,
horizontal-1 filename and horizontal-2 filename, etc. are shown in the following Table 4.2.
These ten earthquakes input motion data have been selected for the nonlinear and57

equivalent linear analysis of each borehole. The average of 10 earthquakes' data has beentaken for the comparison of depth vs. PGA, and PSA vs. period.

Figure 4.7: Time History Plots (for both NL and EL)

Figure 4.8: Spectral Acceleration for 5% damping (for both NL and EL)

58

Table 4.2: Time histories Input Motion (PEER-Ground-Motion-Data-Base-Reader)

59

4.5

Comparison of Depth and Average PGA

The data analysis is carried out using equivalent linear and nonlinear methods. Individual
analysis has been performed for 10 (ten) time histories for Nonlinear (NL) and EquivalentLinear (EL) analysis shown in Figure 4.9 (a and b). The values of the PGA for the NL
analysis range from 0.185 g to 0.494 g, and the values of the PGA for the EL analysis range
from 0.241 g to 0.653 g. Following that step, the data from ten earthquakes were averaged
for both the NL and EL analyses. The depth against peak ground acceleration (PGA) (forthe average of ten earthquakes) is shown in Figure 4.9 (c). For RP-1 the value of the PGA
measured at the surface is 0.50 g as a result of the equivalent linear analysis, while thevalue is 0.35 g as a result of the nonlinear analysis.

(a) Depth (m) vs PGA (g) plots for NL
analysis(b) Depth (m) vs PGA (g) plots for
EL analysis

60

(c) Depth (m) vs PGA (g) plots (Average of 10 (ten) time histories for both NL andEL)
Figure 4.9: Depth against Peak Ground Acceleration plots. (a) for NL analysis, (b) for EL
analysis and (c) Average of 10 (ten) time histories for both EL and NL analysis
4.6

Comparison of PSA and Time

Figure 4.10 (a) and (b) depict nonlinear (NL) and equivalent linear (EL) assessments
performed separately for each of the 10 (ten) time histories. The comparison between
pseudo spectral acceleration (PSA) and period by averaging 10 (ten) time histories fornonlinear and equivalent linear analysis is shown in 4.10 (c). It is shown that the plot of
PSA for equivalent linear analysis is greater than the nonlinear PSA. The value of spectral
acceleration is maximum at the period of 0.38 seconds for equivalent linear analysis, andthe value of spectral acceleration is maximum at the period of 0.61 seconds for nonlinear
analysis. In addition to this, it has been demonstrated that the value of the spectral
61acceleration is decreasing as time goes on, and the PSA value is very close to being zero at
the time period of 10 seconds.

(a) PSA (g) vs Period (sec) plots for NL analysis(b) PSA (g) vs Period (sec) plots for EL analysis
62

(c) PSA (g) vs Period (sec) plots (Average of 10 time histories for both NL and EL)
Figure 4.10: Variation of Peak Spectral Acceleration against Period plots (a) for NL
analysis, (b) for EL analysis and (c) Average of 10 time histories for both EL and NL
analyses.
The comparison curves between NL and EL for other 15 boreholes used in this study arepresented in Appendix-C, and the comparison of the variation of spectral acceleration withBNBC are shown in Appendix-D.

4.7

Site Classification

The standard penetration values are obtained from the SPT test and are gathered for thisinvestigation. After doing the necessary calculations for the top 30 m of soil equation 2.4
̅ (blows/30 cm) values
was used (details calculation shown in Table 4.3) to determine the N
and the depth of the RP-1 borehole, it has been discovered that the N value is 14.94, whichplaces it in the site class SD according to BNBC (discussed in Table 2.5 in chapter 2).

63

Table 4.3: Calculation for determining site class

Depth (m)

d (m)

SPT N

d/SPT-N

0
1.5
3
4.5
6
7.5
9
10.5
12
13.5
15
16.5
18
19.5
21
22.5
24
25.5
27
28.5
30

0
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5

0
6
5
10
14
15
17
5
7
19
28
29
33
40
34
43
47
50
50
50
50

0.25
0.30
0.15
0.11
0.10
0.09
0.30
0.21
0.08
0.05
0.05
0.05
0.04
0.04
0.03
0.03
0.03
0.03
0.03
0.03
∑ d/SPT-N
=2.01

∑d=30

4.8

̅
SPT value, N(blows/30 cm)

̅
N

=

∑d
d
SPT−N

∑

= 14.94
Site
= SD
Class

Target Response Spectrum

The normalized design acceleration response spectrum for different site classes according
to BNBC (2020) is shown in Figure 2.4 (Chapter 2). The surface hazard spectrum wascalculated by multiplying the normalized design acceleration response spectrum (for soil
type SD) by 0.19 g as recommended by BNBC (2020). After that, the spectral acceleration
for the SD site class has been plotted in the PSA vs. period curve. Figure 4.11 shows theComparison of the variation of spectral acceleration with BNBC for the site class SD(0.19g). The graph shows that the site class SD (0.19 g) is much lower than the PSA
obtained from the analysis.

64

Figure 4.11: Comparison of the variation of spectral acceleration with BNBC (SD 0.19g)

4.9

Proposed Design Acceleration Response Spectrum for Rangpur

̅ values, and the site class has been determined in accordance with
Based on the SPT N
̅ values for Rangpur City Corporation
BNBC (2020). A significant majority of the SPT N
are less than 15 (following Table 2.5). The site class of 12 of the 16 boreholes is determined
to be SD, whereas the site class of 4 of the boreholes is determined to be SC, as shown in
Table 4.4. When considering the total number of boreholes in the Rangpur area, the site̅ values.
class is determined to be an SD site class by taking the average of all boreholes’ N
One conclusion that might be drawn from this is that the site class of the soil in the Rangpur
area is classified as SD.

65

Table 4.4: Site class for all the boreholes

Site Class (According

Borehole No.

̅
SPT value, N

RP-1

14.94

SD

RP-2

11.08

SD

RP-3

17.7

SC

RP-4

12.69

SD

RP-5

16.97

SC

RP-6

10.08

SD

RP-7

11.62

SD

RP-8

16.55

SC

RP-9

10.83

SD

RP-10

11.88

SD

RP-11

11.95

SD

RP-12

12.83

SD

RP-13

16.17

SC

RP-14

9.43

SD

RP-15

7.79

SD

RP-16

6.58

SD

to BNBC-2020)

Figure 4.12 demonstrates that the average spectral acceleration plot of all sixteen boreholes
is significantly greater than the BNBC site class SD (0.19 g). Even though the spectral
acceleration for SD soil is low in BNBC (2020), the computation shows that SD soil issignificantly higher for Rangpur City. A design acceleration response spectrum has beenpresented for site class SD (0.19 g), which may be seen in Figure 4.12. The solid black line
illustrates the average nonlinear spectral acceleration for all boreholes, the dasheddotted blue line depicts the BNBC site class SD (0.19 g), and the solid red line illustrates
the recommended PSA for the SD site class in Rangpur City.

66

Figure 4.12: Proposed design Spectral Acceleration Response Spectrum for Rangpur City

4.10 Soil Profiles for the Study Area
The borehole location and cross-sectional direction of Rangpur City Corporation are shownin Figure 4.13, and two cross-sections showing the soil profile of the study site are shownin Figure 4.14. According to the cross-sectional profile (section 1-1), it is clearly visiblethat the soil of the study site is mostly composed of silty fine sand on the top few meters,
and dense silty fine sand with trace mica is present in the soil up to a depth of 30 meters.
Based on the cross-sectional profile (section 2-2), it can be said that the top soils of thestudy site consist of loose to medium dense fine sand, and up to a depth of 36 meters, thesoil is medium dense to very dense fine sand with trace mica. It may be possible to draw
the conclusion, based on the cross sections 1-1 and 2-2, that the soil has a liquefaction
susceptibility when an earthquake occurs.

67

Figure 4.13: Rangpur City Corporation Area showing the borehole location and crosssectional direction.

68

(a) Typical Cross Section 1-1 for the study site (with SPT N value)69

(b) Typical Cross Section 2-2 for the study site (with SPT N values)
Figure 4.14: Typical cross section of the soil profile with SPT values of Rangpur a) section 1-1, b) section 2-2
70

4.11 Estimation of Liquefaction Susceptibility
In this study, the liquefaction susceptibility has been carried out by using the Seed andIdriss simplified method, the Japanese method, and the Chinese method. For the assessmentof the liquefaction susceptibility SPT N values, and Fineness Content (FC) are required. N
values have been found from the standard penetration test (attached in Appendix A), andFC has been taken from the grain size distribution curve (attached in Appendix B). As
discussed in the literature review (Article 2.11), the liquefaction tendency of an underlying
soil may be evaluated using geological data and the soil's current features.
The factor of safety for all boreholes is less than 1, based on the three liquefaction methods
that have been carried out in this study (Using the equation 2.5 to 2.23 that have been
discussed in Chapter 2). FL<1.0 implies that the shear stress induced by the earthquake
exceeds the liquefaction resistance of the soil, and hence liquefaction will occur. For
FL>1.0, liquefaction will not occur. So, it can be said that liquefaction will occur at the
study site at the time of an earthquake. Figure 4.15 depicts the depth versus factor of safety
plot at RP-11 for the three different approaches when the PGA value is 0.3238 g and themagnitude (Mw) value is 7.5.

Figure 4.15: Variation of factor of safety with depth (for the three different approaches)71

From the DEEPSOIL analysis, it is found that the surface PGA value for the Rangpur City
Corporation area is 0.3238 g (for NL) by averaging all the borehole data. Equation 2.24
was utilized in the calculation of LPI values for the simplified method and the Japanesemethod, while equation 2.29 was utilized for the Chinese method. The LPI values for thethree approaches as well as the different scenarios of earthquakes with varying levels of
GWT are presented in Table 4.5, Table 4.6, Table 4.7, Table 4.8, Table 4.9, and Table 4.10.
From the tables it can be noticed that the LPI value is increasing with the increase inmagnitude.
Table 4.5: Scenario of Earthquake (PGA = 0.3238 g and Magnitude, Mw = 6.5) for different
groundwater table depth
Borehole

GWT Depth

No.

(m)

RP-1
RP-2
RP-3
RP-4
RP-5
RP-6
RP-7
RP-8
RP-9
RP-10
RP-11
RP-12
RP-13
RP-14
RP-15
RP-16
BT-13
BT-4
BT-2
BT-17
BT-18
BT-1
BT-7
BT-8

4.42
2.74
2.13
4.12
2.59
0.76
1.52
2.29
3.66
3.13
2.44
2.44
3.35
2.74
2.44
3.51
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5

Liquefaction Potential Index (LPI)
Japanese
Method
3.49
1.41
6.57
4.74
1.18
21.96
8.77
2.59
6.1
9.38
10.75
12.23
3.84
12.42
16.1
8.46
9.98
10.75
14.27
9.23
5.57
8.09
7.74
8.12

Chinese Method
19.15
32.25
13.88
37.62
19.88
56.98
38.9
13.43
46.27
35.9
37.69
35.03
16.54
47.61
60.8
49.77
30.18
35.58
55.05
29.97
33.31
30.42
31.4
33.12

Seed & Idriss
Method
10.26
17.84
15
20.61
12.3
36.27
19.9
7.47
15.38
17.6
17.7
17.83
7.48
22.75
26.42
16.93
29.01
24.39
29.06
19.59
14.63
26.75
20.13
18.71

72

Table 4.6: Scenario of Earthquake (PGA = 0.3238 g and Magnitude, Mw = 6.5) for samegroundwater table depth
Liquefaction Potential Index (LPI)
BoreholeNo.

GWT Depth(m)Japanese
MethodChinese Method

Seed & Idriss
Method

RP-1

1.5

32.41

30.57

20.88

RP-2

1.5

5.14

38.03

23.82

RP-3

1.5

11.32

15.73

18.25

RP-4

1.5

16.77

50.43

31.12

RP-5

1.5

7.28

24.22

17.69

RP-6

1.5

13.31

54.77

30.76

RP-7

1.5

8.77

38.98

19.9

RP-8

1.5

5.98

15.95

10.59

RP-9

1.5

16.7

54.49

25.39

RP-10

1.5

15.49

44.21

25.48

RP-11

1.5

14.23

42.29

22.46

RP-12

1.5

15.56

38.32

21.63

RP-13

1.5

11.53

23.42

16.17

RP-14

1.5

16.88

52.72

28.85

RP-15

1.5

20

63.52

30.03

RP-16

1.5

19.76

55.77

26.03

BT-13

1.5

9.98

30.18

29.01

BT-4

1.5

10.75

35.58

24.39

BT-2

1.5

14.27

55.05

29.06

BT-17

1.5

9.23

29.97

19.59

BT-18

1.5

5.57

33.31

14.63

BT-1

1.5

8.09

30.42

26.75

BT-7

1.5

7.74

31.4

20.13

BT-8

1.5

8.12

33.12

18.71

73

Table 4.7: Scenario of Earthquake (PGA = 0.3238 g and Magnitude, Mw = 7.5) for different
groundwater table depth

Borehole

GWT Depth

No.

(m)

Liquefaction Potential Index (LPI)
Japanese
MethodChinese Method

Seed and Idriss
Method

RP-1

4.42

3.49

34.05

21.82

RP-2

2.74

1.41

48.29

29.11

RP-3

2.13

6.57

30.29

25.68

RP-4

4.12

4.74

53.27

32.85

RP-5

2.59

1.18

35.42

24.71

RP-6

0.76

21.96

67.64

44.08

RP-7

1.52

8.77

54.12

32.05

RP-8

2.29

2.59

29.09

18.99

RP-9

3.66

6.1

59.75

28.9

RP-10

3.13

9.38

51.27

29.69

RP-11

2.44

10.75

53.34

30.7

RP-12

2.44

12.23

47.55

27.6

RP-13

3.35

3.84

31.87

20.47

RP-14

2.74

12.42

60.46

33.97

RP-15

2.44

16.1

70.51

36.86

RP-16

3.51

8.46

62.06

28.3

BT-13

1.5

9.98

42.63

38.92

BT-4

1.5

10.75

51.08

34.99

BT-2

1.5

14.27

65.07

38.51

BT-17

1.5

9.23

46.84

32.14

BT-18

1.5

5.57

45.22

27.52

BT-1

1.5

8.09

43.73

36.81

BT-7

1.5

7.74

48.03

31.25

BT-8

1.5

8.12

48.39

30.09

74

Table 4.8: Scenario of Earthquake (PGA = 0.3238 g and Magnitude, Mw = 7.5) for samegroundwater table depth
Liquefaction Potential Index (LPI)

Borehole

GWT Depth

No.

(m)

RP-1

1.5

32.41

44.16

32.55

RP-2

1.5

5.14

53.09

33.59

RP-3

1.5

11.32

33.69

28.04

RP-4

1.5

16.77

62.85

40.31

RP-5

1.5

7.28

40.28

29.46

RP-6

1.5

13.31

65.95

40.2

RP-7

1.5

8.77

54.19

32.05

RP-8

1.5

5.98

33.31

22.93

RP-9

1.5

16.7

65.88

36.4

RP-10

1.5

15.49

58.2

36.21

RP-11

1.5

14.23

56.78

34.3

RP-12

1.5

15.56

50.01

31.13

RP-13

1.5

11.53

42.32

29.57

RP-14

1.5

16.88

64.56

38.75

RP-15

1.5

20

72.54

39.44

RP-16

1.5

19.76

66.82

35.7

BT-13

1.5

9.98

42.63

38.92

BT-4

1.5

10.75

51.08

34.99

BT-2

1.5

14.27

65.07

38.51

BT-17

1.5

9.23

46.84

32.14

BT-18

1.5

5.57

45.22

27.52

BT-1

1.5

8.09

43.73

36.81

BT-7

1.5

7.74

48.03

31.25

BT-8

1.5

8.12

48.39

30.09

Japanese
MethodChinese Method

Seed and Idriss
Method75

Table 4.9: Scenario of Earthquake (PGA = 0.3238 g and Magnitude, Mw = 8.5) for different
groundwater table depth

Borehole

GWT Depth

No.

(m)

Liquefaction Potential Index (LPI)
Japanese
MethodChinese Method

Seed and Idriss
Method

RP-1

4.42

3.49

44.17

32

RP-2

2.74

1.41

58.63

36.77

RP-3

2.13

6.57

44.25

33.6

RP-4

4.12

4.74

62.61

40.71

RP-5

2.59

1.18

48.36

33.54

RP-6

0.76

21.96

74.07

48.91

RP-7

1.52

8.77

63.28

40.11

RP-8

2.29

2.59

43.32

28.47

RP-9

3.66

6.1

67.77

37.88

RP-10

3.13

9.38

61.01

38.23

RP-11

2.44

10.75

62.66

39.2

RP-12

2.44

12.23

55.01

36.94

RP-13

3.35

3.84

45.51

31.55

RP-14

2.74

12.42

68.34

41.56

RP-15

2.44

16.1

76.35

43.6

RP-16

3.51

8.46

69.61

36.7

BT-13

1.5

9.98

52.78

45.17

BT-4

1.5

10.75

60.85

41.56

BT-2

1.5

14.27

71.63

44.87

BT-17

1.5

9.23

57.1

40.21

BT-18

1.5

5.57

52.51

36.82

BT-1

1.5

8.09

52.94

43.63

BT-7

1.5

7.74

58.43

38.39

BT-8

1.5

8.12

58.04

38.63

76

Table 4.10: Scenario of Earthquake (PGA = 0.3238 g and Magnitude, Mw = 8.5) for samegroundwater table depth

Borehole

GWT Depth

No.

(m)

Liquefaction Potential Index (LPI)
Japanese
MethodChinese Method

Seed and Idriss
Method

RP-1

1.5

32.41

55.32

39.79

RP-2

1.5

5.14

62.46

40.27

RP-3

1.5

11.32

46.99

35.76

RP-4

1.5

16.77

70.24

46.17

RP-5

1.5

7.28

52.24

37.35

RP-6

1.5

13.31

72.71

46.1

RP-7

1.5

8.77

63.33

40.11

RP-8

1.5

5.98

46.68

31.34

RP-9

1.5

16.7

72.66

43.34

RP-10

1.5

15.49

66.53

43.06

RP-11

1.5

14.23

65.4

41.82

RP-12

1.5

15.56

56.97

39.51

RP-13

1.5

11.53

53.87

38.37

RP-14

1.5

16.88

71.61

45.05

RP-15

1.5

20

77.98

45.52

RP-16

1.5

19.76

73.41

42.62

BT-13

1.5

9.98

52.78

45.17

BT-4

1.5

10.75

60.85

41.56

BT-2

1.5

14.27

71.63

44.87

BT-17

1.5

9.23

57.1

40.21

BT-18

1.5

5.57

52.51

36.82

BT-1

1.5

8.09

52.94

43.63

BT-7

1.5

7.74

58.43

38.39

BT-8

1.5

8.12

58.04

38.63

77

From the above six tables, it is clearly visible that a variation may occur when themagnitude is changed. It can be observed that the liquefaction potential index value
increases as the earthquake magnitude increases from 6.5 to 8.5. So, it can be seen that thehigher the magnitude, the greater the liquefaction potential index value. The groundwatertable (GWT) is another important factor that affects the LPI value. If the GWT depth is low
from the existing ground level (EGL), the LPI value increases. So, it can be observed thatthe lower the GWT from EGL, the higher the liquefaction susceptibility.

4.11.1 Liquefaction Contour Map
As described in Chapter 2, when the LPI value is greater than 15, the risk of liquefaction
is very high; when the LPI value is between 15 and more than 5, the risk of liquefaction ishigh; when the LPI value is between 5 and more than 0, the risk of liquefaction is low; andwhen the LPI value is equal to 0, the risk of liquefaction is very low. Due to the fact that
the LPI values for both the simplified method developed by Seed and Idriss and the Chinese
method are greater than 15, the potential for liquefaction is extremely high in accordancewith the limit, as shown in the above four tables of different scenarios that were presented
earlier in this article. As all the LPI values are greater than 15 for the simplified and Chinese
methods, the liquefaction contour maps for all the scenarios (different moments and GWTvariations) will be the same as shown in Figure 4.16. The Japanese method is lessconservative than the other two methods that’s why the LPI values for Japanese method
vary with different scenarios as illustrated in Figure 4.17. It has been demonstrated thatwhen the magnitude increased, there was also an increase in the LPI values. As thesimplified and Chinese methods are more conservative than the Japanese method, the entireliquefaction contour map for Rangpur city can be represented by Figure 4.16. The predicted
LPI contours reveal that nearly 100 percent of the overall area is vulnerable to liquefaction.

78

Figure 4.16: LPI based microzonation map for the Rangpur city corporation area for a PGA
value of 0.3238 g (for both Chinese and Seed & Idriss methods).

(a) Magnitude = 6.5 and different GWT depth (Japanese)79

(b) Magnitude = 6.5, and GWT depth = 1.5 m (Japanese)(c) Magnitude = 7.5 and different GWT depth (Japanese)80(d) Magnitude = 7.5, and GWT depth = 1.5 m (Japanese)(e) Magnitude = 8.5 and different GWT depth (Japanese)442

(f) Magnitude = 8.5, and GWT depth = 1.5 m (Japanese)
Figure 4.17: LPI based microzonation map for the Rangpur city corporation area for a PGA
value of 0.3238 g (for the Japanese method). (a) Magnitude = 6.5 and different GWT depth,(b) Magnitude = 6.5, and GWT depth = 1.5 m (c) Magnitude = 7.5 and different GWT
depth, (d) Magnitude = 7.5, and GWT depth = 1.5 m, (e) Magnitude = 8.5 and different
GWT depth, and (f) Magnitude = 8.5, and GWT depth = 1.5 m

443

PART-VII

ESTIMATION OF LIQUEFACTIONSUSCEPTIBILITY OF A NEW
INTERNATIONAL AIRPORT SITE IN SYLHET,BANGLADESHBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By:

Mehedi Ahmed Ansary

INTRODUCTION
For important sites like airports, power plants etc. estimation of liquefaction potential isimportant owing to the existence of several important infrastructures. Resistance of soil toliquefaction has turned into an essential condition to be estimated before any major
construction during recent time. Liquefaction is the alteration of 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 sandy type and 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 toenhance, which causes the soil mass to perform as a fluid. The 1964 Alaska, USA and
Niigata, Japan earthquakes are the major examples where liquefaction played a 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 prior to any new important
construction takes place. Also, wide-ranging investigation has been done in this field to avoid
any such catastrophic damages in the future. The findings of many researchers (Ansary,
2003; Ansary and Sharfuddin, 2002; Ansary and Arefin, 2020; Rahman et al., 2021) advocatethat important cities of Bangladesh have been struck by numerous historical large
earthquakes, that is why the current study is important.
The simplified procedure for the determination of the liquefaction susceptibility based on
SPT-N value provided by Seed and Idriss (1971) has been authenticated and amended byvarious researchers (Youd and Idriss, 2001; Idriss and Boulanger, 2006; Juang et al., 2000;
Lee et al., 2007) over the years. Iwasaki et al. (1984) has suggested a technique to estimate
the liquefaction potential index for the entire depth of a 20m deep borehole, which is popularfor seismic microzonation of an area.
In this research, the under-construction new international airport site at a neighborhood in
Sylhet City, Bangladesh has been considered. The soil of the eastern part of the project site
mainly composed of loose to medium dense silty fine sand within the top few meters which isunderlain mainly by hard clay soil up to a depth of 45m (sometimes medium to dense sandcan be found there) and the western part of the project site mainly composed of medium stiffto hard clay up to a depth of around 30m which is underlain by very dense sand up to a depthof 45m.
444

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
hazard. 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
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 and445

Thallak (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, 2565 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
locations 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. Finally for theassessment 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 that PGA.
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 61 borehole locations

3and seven PS-Log locations of the study site as shown in Figure 3 to carry out the site
response analysis.
SPT and Shear-wave Velocity Profile
Figure 5 presents two cross-sectional profiles (section 2-2 and 9-9 according to Figure 3) of
the study site. The soil of the eastern part of the project site (based on section 2-2) mainlycomposed of loose to medium dense silty fine sand within the top few meters which isunderlain mainly by hard clay soil up to a depth of 45m (sometimes medium to dense sandcan be found there) and the western part of the project site mainly composed of medium stiffto hard clay up to a depth of around 30m which is underlain by very dense sand up to a depthof 45m. Similarly, the soil of the southern part of the project site (based on section 9-9)
mainly composed of loose sand within the top few meters which is underlain by soft tomedium stiff clay, dense sand and hard clay up to a depth of 45m and the northern part of the
project site mainly composed of loose to medium dense sand up to a depth of around 8m
which is underlain by soft to medium stiff clay, dense sand and hard clay up to a depth ofaround 45m.
The shear wave velocity (Vs) information from the study location has been compiled fromthe ground level up to a depth of maximum 55 m from the seven PS-logs carried out at the
airport site (Figure 6). The data has been determined utilizing a suspension PS-log system.
The Vs data from 55 m to 200 m depth have been gathered using array microtremor
measurements (AMT) from CDMP (2009) in nearby Sylhet city as shown in Figure 7. The
bedrock (when the shear-wave velocity is larger than 760 m/s) is located at 150 m below theground level. So, the bedrock for this site is also assumed to be at 150m depth. Figure 8
shows the shear-wave velocity model used for the airport site.
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 andAnbazhagan, 2020) to utilize the existing standard curves may be followed. Several damping
ratio and shear modulus reduction relations can be found in different available literature (suchas Seed and Idriss, 1970; Sun et al., 1988; Darendeli, 2001) to estimate the dynamic
4

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 55 m deep is mostly consisting of sandy soils in the eastern part of the siteand mixture of clay and sandy soil in the western part of the site (Figure 5). 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 9).
Bedrock and surface hazard spectra
The normalized design acceleration response spectrum proposed in BNBC (2020) for groundcondition (Vs > 760 m/s) [soil type SA] has been considered in this study as shown in Figure
10a. This spectrum for soil type SA has been multiplied by PGA for a return period of 475
years (in this case, it is 0.30g) to obtain the target spectrum, which is here referred as thehazard spectra at the bedrock (UHS). In this particular site, the mean shear-wave velocity forthe initial 30m of a soil column is 188 m/s (using Figure 8), which falls in soil type C (SC)category. The normalized design acceleration response spectrum for soil type SC as per
BNBC (2020) has been multiplied by 0.30g to obtain the surface UHS. Both these UHSs areshown in Figure 10b.
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 thispurpose, freely available ten worldwide data are used: the 1961 Hollister (USA) earthquake(USGS station 1028), the 1976 Friuli (Italy) earthquake [Tolmezzo (000)], the 1979 Imperial
Valley USA (USGS station 5115), the 1983 Trinidad (USA) earthquake (090 CDMG station
1498), the 1989 Loma Prieta USA (090 CDMG station 47381), the 1992 Landers (USA)earthquake (000 SCE station 24), the 1994 Northridge USA (090 CDMG station 24278), the51995 Kobe Japan (Kakogawa CUE90), the 1999 Kocaeli Turkey (Yarimca, Koeri330) andthe 1999 Chi-chi Taiwan (TCU045) earthquakes.
The spectral acceleration of the earthquake accelerograms is fitted to the target bedrock
response spectra to generate time history data compatible with the target spectra (Figure 11).
The matching of spectra has been done by using the SEISMOSOFT software to adapt thetime history data by fitting its spectral acceleration with the target response spectrum (Figures12). The spectral response of 10 earthquake acceleration time histories is fitted with the target
spectra for a return period of 475 years (Figures 13 and 14). The time versus acceleration dataof the fitted spectral acceleration curve have been applied for the site assessment (see Figure12).
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 soilmodel for response analysis requires material damping and shear modulus reduction relationin normalized form. The relations suggested by Darendeli (2001) have been utilized in thisresearch. To utilize the relationships of Darendeli (2001), the following soil parameters areneeded: vertical stress under effective condition in initial state, initial coefficient of lateralearth pressure, loading frequency, loading cycle numbers, OCR ratio, and plasticity index(Figure 9).
DEEPSOIL has numerous soil models to carry out the site assessment analysis. 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 soil column with thebenchmark relations of Darendeli (2001) for certain shear strength. This model consists of
non-Masing reloading-unloading hysteretic set up based on the general quadratic/hyperbolicmodel (GQ/H). The effective shear strength condition has been applied for all calculations byconsidering the water table at the top of the surface. According to Groholski et al. (2016), the
GQ/H form has the capability to depict the relatively big shear stress strain characteristics ofthe materials to precisely approximate the motion of the ground at the surface for relatively
big strains. Viscous damping term which has been frequency-independent has been utilized
for nonlinear response assessment in time domain. During response analysis, theaccelerogram of the matched bedrock spectral acceleration have been applied for motion of6the ground at the bottom of the soil column. Figure 15 shows the depth versus average PGA
plots using equivalent-linear and nonlinear ground response analysis. The PGA value at thesurface due to the nonlinear analysis is 0.39g and due to the equivalent-linear analysis is
0.65g.
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 in
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. After the detailed assessment, liquefaction severity is evaluatedbased 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
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 16). 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 slightly larger to relatively larger at relatively low periods (less than 0.20 s) andbigger at large periods (more than 0.20 s) in comparison with the spectral accelerations of thehazard spectra at the bedrock during equivalent-linear response assessment. The spectral
acceleration of the hazard spectra at the surface are smaller at low periods (from 0.03 s to
0.30 s) and larger at large periods (0.30 s and 4 s) in comparison with the spectral
7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 theequivalent-linear, and nonlinear models with respect to 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 thecases. 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 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 0.39g using nonlinear assessment technique.
Liquefaction susceptibility estimation
In this study, the liquefaction susceptibility at each layer of 1.5m interval where SPT-N value
exist and liquefaction potential index (LPI) values have been estimated for 61 boreholes
located all over the site up to a depth of 20m. The locations where borehole data are notpresent, LPI have been estimated by Kriging method. LPI estimation have been made for thethree methods Seed and Idriss (1971) method, Japanese method (Tatsuoka et al., 1980) andChinese method (Sun et al., 2015) for two cases: (a) A lower bound value of PGA=0.29g (for23% probability of exceedance in 50 years or for a return period of 200 years) and M w = 7.5
and (b) a upper bound value of PGA=0.39g (estimated through nonlinear site assessment fora return period of 475 years) and Mw = 8.15 which has been estimated with the help of past
seismic data. Figure 17 shows the factor of safety versus depth plot at BH-168 for the threemethods for PGA=0.29g 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, thethree levels of hazard as described by Iwasaki et al. (1984), have been utilized as shown in
Figure 18 for both the lower bound and the upper bound cases. The estimated LPI contours
show that 80% to 90% of the total area will be highly susceptible to liquefaction and the restof the area will be lowly susceptible.

8

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 shallow foundation for this site may be recommended only if the entire soil up to a depthof 20m is fully improved by suitable ground improvement techniques. Alternatively, lengthof pile greater than 20m below EGL may be recommended along with ground improvementof the top 5m of the loose sand soil zone. In this research, borehole data of 61 locations withSPT have been utilized for a relatively small area. The large number of borehole for a
relatively small area of the site would generally produce dependable results in the assessmentof LPI.
CONCLUSIONS
During the whole design lifecycle, the assessment of Liquefaction Potential Index (LPI) is
important for the development of a new international airport site in inferior quality soils forproper working condition of the facility. The PGA value at bedrock level has been evaluatedutilizing past seismic data, seismo-tectonical details and suitable GMPE relations. To
approximate the time history at the surface in a site where the relatively loose or soft soil
deposits of larger than 30 m thick is located on top of the bedrock, 1D nonlinear site
assessment is needed. For these sites, the ground motion depending on Vs 30 based site
amplification at low periods is relatively higher and the ground motion at large periods is
relatively lower. The nonlinear site assessment determines the motion at the ground surface
better than the linear or equivalent-linear analyses, since the soils properties are nonlinear
too. 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 the site
under study has been assessed utilizing the SPT-N value data at 61 locations of the site
applying three methods and two sets of PGA values and magnitudes up to a depth of 20m.
Approximately 80% to 90% of the total area of the site has been found to be highly
vulnerable to liquefaction up to a depth of about 20 m. For this reason, two alternative
foundation solutions are recommended for this site. The first one is providing shallow
foundation above an improved ground up to a depth of 20m or alternatively providing 20m
deep piles. Also, the LPI contours will be helpful for future development in the vicinity of thecurrent site.

9

Airport Site

Figure 1 Tectonic map of the area.

Figure 3 Proposed airport area showing borehole locations

13

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 Real Earthquakes
and Match them with TRS for Rockto obtain 10 Input Motions for the
Soil Model based on the PGA Value
obtained for Rock Using 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 study

14

West

East

Figure 5 (a) Typical cross-sectional profile (2-2) of the study site with SPT-N values

15NorthSouth

Figure 5 (b) Typical cross-sectional profile (9-9) of the study site with SPT-N values
16Shear-wave Velocity Vs (m/s)

Shear-wave Velocity Vs (m/s)
0050 100 150 200 250 300 350 400 450

0

-10

-10

-20

-20

Depth (m)

-30

-30

-40

-40

-50

-60

50 100 150 200 250 300 350 400 450

Depth (m)0

BH-058
BH-064
BH-075
BH-085-50(a)

BH-087
BH-091
BH-099-60(b)Figure 6 Shear-wave velocity profiles at seven borehole location at the airport site

17

Depth (m)S-velocity (m/s)

(a)

(b)
Figure 7 (a) Array microtremor measurements (AMT) configuration: array sizes: 125 m, 250 m, and 500 m; seismometers used: 10 with natural
frequency of 0.5 Hz, sampling rate of 10 ms and sampling duration 60 min and (b) an example of shear wave velocity structure up to the depthof 200 m obtained from array microtremor measurements (AMT) data at borehole site SMT-1, Sylhet (CDMP 2009)18

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

100 200 300 400 500 600 700 800

0-25Depth (m)

-50

-75

-100

-125

-150

Figure 8 Shear wave velocity (Vs) model for the airport site

19

RefCurve at15m
1

Reference Curve
Curve Fit
0.8

G/Gmax

0.6

0.4

0.2

0
0.0001

0.001

0.01

0.1

1

10

1

10

Strain (%)
RefCurve
at15m
25

Damping ratio (%)

20

15

10

5

0
0.0001

0.001

0.01

0.1

Shear Strain (%)

Figure 9 Sample of normalized shear modulus reduction and material damping curves where
the reference curves are taken from Darendeli (2001)

20

(a)
1

Spectral Acceleration (g)

0.8

0.6

0.4

0.2

Bedrock UHS
Surface UHS using Vs30 based site coefficient
00.02

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 10 (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

21

1TargetMatchedInitialSpectral Acceleration (g)

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)Figure 11 Spectral matching of the response spectrum of the earthquake time history withtarget response spectra for a return period 475 years. Initial is the response spectrum of theearthquake time history (orange), and green is the matched response spectra with target
response spectra (black) of bedrock ground condition

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

40

45

50

Time (s)Figure 12 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

22

3.5

Target Response Spectrum
ChichiFriuli
HolisterImperial Valley
Kobe
Kocaeli
Landers
Loma Prieta
Northridge
Trinidad3

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 13 Response spectra of 10-time histories from real earthquakes with target response
spectrum for a return period 475 years at the site
1.2

TargetChichiFriuliHollister
ImperialValley
Kobe
Kocaeli
Landers
LomaPrieta
Northridge
TrinidadSpectral Acceleration (g)

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)Figure 14 Matched response spectra of 10-time histories with target response spectrum for a
return period 475 years at the site

23

PGA (g)
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0

-25

Depth (m)

-50

-75

-100

-125

Nonlinear
Equivalent-linear
-150
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Figure 15 Depth versus average PGA plots using equivalent-linear and nonlinear groundresponse analysis
2.4

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

2.2
2

Spectral Acceleration (g)

1.8
1.6
1.4
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)Figure 16 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
24Factor of Safety (FL)

Factor of Safety (FL)
2

4

0

6

2

4

0

0

0

5

5

5

10

15

20

25

Simplified
IdrissDepth from EGL (m)0Depth from EGL (m)Depth from EGL (m)0Factor of Safety (FL)

10

15

20

4

10

15

20

Chinese
Criterion

2

Japanese
Code…

25

25

Figure 17 Factor of safety versus depth plot at BH-138 of the three methods for PGA=0.29g and Mw=7.5

466

(a)

(b)

Figure 18 LPI contour of the site for (a) PGA=0.29g and Mw=7.5 and (b) (a) PGA=0.39g and
Mw=8.15467

PART-VIII

ASSESSMENT OF SOIL-BUILDINGRESONANT EFFECT FOR DMDP AREA INBANGLADESHBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Mehedi Ahmed Ansary

1 Introduction
Bangladesh is located in a significantly active seismic region, most of the people andpolicymakers do not consider the seismic risk to be important. Bangladesh has not faced any
damaging major earthquakes in the recent years; although, during the last few centuries,
numerous major seismic events have taken place in this region. Most of the seismic events
have taken place far away from the key settlements, and have caused distress to relatively
small population. Several researchers (Ansary et al. 2013; Morino et al. 2014; Steckler et al.
2016; Rahman et al. 2020) have shown that a future major seismic event may happen in the
Himalayan or Burmese front at any moment and source of significant distress to all type ofstructures in Bangladesh, especially in Dhaka.
Earthquakes are one of such disasters that are associated with ongoing tectonic processes. It
unexpectedly happens for a few seconds and can be the basis of enormous loss to life andassets. Therefore, earthquake disaster prevention and mitigation strategy are of global
concern today. According to Gallipoli et al. (2020), earthquake hazard alleviation comprisesof a set of plans targeted at decreasing the harmful consequences of seismic events on allsusceptible components. Distress due a seismic event is generally managed by threeinterdependent issues - local geological and geotechnical conditions, source and pathcharacteristics, and type of structures (Mucciarelli et al. 2001). According to Gullu and Pala(2014), major distress at great distances may happen owing to the effects of local site
condition and double resonance (it is the resonance of the frequency of the body wave of theground and also resonance with the predominant frequency of a building). Apparently, all of
this would involve the study and arrangement of a huge quantity of geological, geotechnical,
and seismological information.
Experimental and numerical are the two techniques for studying the effect of ground due toearthquakes. The key goal of investigational techniques is to estimate the predominantfrequency of the ground through observations of earthquakes or microtremor, or noise data
(Pinzon et al. 2019). The microtremor Horizontal-to-vertical spectral ratio (HVR) method is
primarily applied to understand the effect of local sites and for microzonation studies. The
findings of those studies are afterward expanded to recognize the predominant periods ofstructures (Nakamura et al. 2000; Gallipoli et al. 2004; Bindi et al. 2015; Petrovic and Parolai2016). Gosar (2010) and Gallipoli et al. (2004) have studied soil and structure interaction as
well as their distress observing microtremors. Also resonance between structure and soil has
been identified using the microtremor method. The soil-building relations for URM buildings468

and various kinds of surface soil have been numerically assessed by Piro et al. (2019).
Additionally, every time the predominant vibration period of a structure is relatively near tothat of the surface soil, the soil-structure resonance issue is activated. According to Bard etal., (1996) and other researchers (Tsogka and Wirgin, 2003; Mucciarelli et al., 2011) thisissue can initiate the distress of the structure in case of a seismic event.
Mucciarelli et al. (2004) has studied the reasons behind high damage to two RC buildings in
the town of Bonefro during the 2002 seismic sequence in Molise (Italy). One of them is afour-storied building with a damage grade of 4 in European Macroseismic Scale (EMS) andthe other is a three-storied building with a damage grade of 2 in EMS scale. These buildings
are located on soft sediments, close to each other and very similar in design and construction.
The recorded data has been analyzed by four different techniques: short-time fouriertransform (STFT), wavelet transform (WT), horizontal-to vertical spectral ratio (HVSR), andhorizontal-to-vertical moving window ratio (HVMWR). To test if the soil–building resonanceeffect could have increased the damage, they also evaluated the soil fundamental frequency
by three different techniques: noise HVSR, strong motion HVSR of seven aftershocks, and
1D modeling based on a velocity profile derived from noise analysis of surface waves(NASW) measurements. The results are in good agreement, showing that resonancefrequencies of the soil and of the more damaged building are very close. Navarro et al. (2004)
has assessed the dynamic behavior of RC building structures in Granada city. The map ofprobable resonance phenomena in Granada city, comparing predominant period of soil andnatural period of RC buildings, shows that a significant number of buildings be able to havedominant periods close to the ground motion ones and consequently resonant phenomena
would be able to appear if an earthquake occur in the zone. Gallipoli et al. (2020) has
undertaken a study aiming to recognize the interaction eﬀect between near surface geology
and all overlying buildings in the urban area of the city of Matera, Italy. Microtremor
measurements have been performed on the main lythologies and on the principal building
typologies. Soil and building measurements allowed estimating the main frequencies andrelative amplitudes of the soil fundamental peaks as well as the ﬁrst vibrational frequency ofbuildings. Matera presents an important case study because the ﬁrst vibration frequency formost of the buildings is quite close to those of the foundation soils. Tallini et al. (2020) hasstudied the soil-building resonance effect in the downtown of L'Aquila city, Italy. A very
heterogeneous building stock is present in this area: mainly consisting of two to four-storiedstone masonry, some brick and a few reinforced concrete buildings. They have showed thatthe buildings with possible seismic coupling due to the shallow geological setting and the469

fundamental building period, which is further supported by the areal distribution of seismicbuilding damages caused by the 2009 L’Aquila earthquake. As can be seen from the above
studies that for a few cities in the world soil-building resonance effect have been studied. The
Government of Bangladesh has recently initiated a project to retrofit some old schoolbuildings in the capital city Dhaka, where this study has been carried out. This kind of study
is a pre-requisite for taking decision to retrofit or demolish vulnerable buildings in a city.
This is essential since retrofitting is expensive. If we know beforehand that there is a chanceof soil-building resonance to take place, either we need to take additional measure to avoid
that or take decision to demolish the building.
In order to learn the consequence of resonance between the nearby ground and structures inthe Dhaka Metropolitan Development Plan (DMDP) area, microtrremor measurement has
been done to assess the site effect and characteristics of the buildings. In this study, 114
educational institutions site has been selected considering the availability of free field and theexistence of past SPT and PS logging data as compared to other facilities. Microtremor
measurements have been performed in each of those selected 114 buildings and free-field
locations.
In this research, the consequence of resonance between the nearby ground and structures inthe DMDP area has been experimentally evaluated. An effort has been made to identify thepotential areas of resonance between structure and soil within the study area by putting theprincipal vibrational frequencies of the structures on the frequency contour map based on the
predominant frequencies of the soil.
2

Geological background

Dhaka Municipal Corporation and the surrounding Thanas (the lowest administrative unit
among four administrative tiers of Bangladesh), is combinedly known as Dhaka Metropolitan
Area (DMA), having an area of 300 km2 with a population density of 23,234 people/ km2(World Population Review 2021). Dhaka marked by the Dhaka Metropolitan Development
Plan (DMDP) area is a megacity that spreads over 4 other districts covering an area of over1500 km2 with a population of around 15 million. DMDP area is situated in a central locationof Bangladesh as shown in Figure 1.
According to Jain et al. (2020), within Indian subcontinent Bangladesh, which is located in
the northeastern side, shares the geology of the Bengal Basin with some part of India. The
entire country has been cramped within the Brahmaputra–Ganga–Meghna Delta, is underlain
by the alluvial recent deposits of those rivers. The sediments of Bangladesh Geology can be
3divided into six principal groups (Jain et al. 2020). These are Coastal deposits, Deltaic
deposits, Paludal deposits, Alluvial deposits, Alluvial Fan deposits, and Residual deposits(Persits et al., 2001). Figure 2 shows the geological map of Bangladesh and the study area.
Figure 3 presents the Standard Penetration Test (SPT) and Seismic Downhole Test (SDHT)
locations within the DMDP area. Figures 4 and 5 show the lithology of the horizontal andvertical cross-sections of the study area based on the SPT profile. The Madhupur Clay
Residuum is the main soil deposit in the top (which is part of Pleistocene terrace deposit: very
stiff soil shown by red color in Figures 4 and 5) and then Alluvial Sand, Silt and Clay, andtheir various combinations. According to the SDHT data, the engineering bedrock of Dhaka
city (Shear-wave velocity ≥ 400 m/s) is situated around 70 m below the existing ground level.
Dhaka is located between the Meghna and Brahmaputra Flood Plains. Two characteristic
geological units cover the DMDP area and the surroundings: Madhupur clay deposit (MCD)of the Pleistocene age and alluvial Flood plain deposits (FPD) of the recent age can be seenfrom Figure 2b.
3

Materials and methods

3.1

The built environment

To estimate the vulnerability and risk of Dhaka’s critical facilities and develop a prioritizedinvestment plan through an analytical approach, 3252 individual facilities have been assessed
recently using Rapid Visual Assessment (RVA) technique combining FEMA P-154 (2015)
and ASCE 41 (2017). Figure 6 presents the spatio-temporal divisions of 3252 structures
divided based on their types, construction years, and floor numbers. The RVA methodology
applied to the buildings has two major components: structural and nonstructural vulnerability.
In the seismic risk prioritization approach, seismic hazard and other vulnerability indicatorssuch as building importance, urban context and economic impact have been included inaddition to RVA results. The principal level seismic prioritization methodology issummarized in Figure 7. The total number of the prioritized buildings for Preliminary
Engineering Assessment (PEA) is 611.
3.2

Microtremor Measurements on Soils and Buildings

To develop a Risk-Sensitive Land Use Planning (RSLUP) map for the DMDP area, 500
single station microtremor measurements have been carried out by dividing the study area
into 2km by 2km grids and the fundamental frequency, amplification and seismic
vulnerability index variation of the study area have been mapped (Ansary et al. 2019). A total
number of 400 locations have also been selected to perform Standard penetration test (SPT)and Seismic downhole test (SDHT) based on the homogeneity and non-homogeneity of the4study area based on the microtremor measurements. Those SPT and SDHT locations areshown in Figure 3. In this study, during the selection of the educational institutions out of theprioritized 611 buildings, the institutions close to the SPT and SDHT are given priority. Thisway, 114 buildings are selected for this study. Figure 8 shows the number of study sites
located on MCD and FPD geological units. Figure 9 presents those buildings according totheir construction years and floor numbers.
In this study, microtremor measurements have been carried out on ground and structures inthe DMDP area at 114 locations. Site selection and microtremor observations have been
executed according to the guideline of SESAME (2004). The microtremor observation on
nearby ground and structures have been made by utilizing the digital seismographmanufactured by “OYO International” (McSEIS-MT-NEO-1134) and have been analyzed
following the procedures suggested by SESAME (2004). The system has an internal 12V
rechargeable battery having the ability to record 5 hour continuously. Surveys have been
carried out at 100 samples per second for about 30 minutes.
Measurements have been performed at 114 selected buildings of different height (1 to 10
storied, but most of the buildings are less than 5-storied). Microtremor has been observed on
the top floor of the buildings. Two horizontal directions of the sensor have been positioned
along the two main axes of the buildings. The sensor has been located as near as possible tothe mass center of the structure. Microtremor observations on the soils have been made atleast 5m away from the buildings to avoid its influence. The measurements on the soils andbuildings, both lasted for 30 minutes with a sampling frequency of 100 Hz. Figure 10 shows
microtremor observations at a free field and at a rooftop of a building.
HVR technique for the free field has been executed according to the criteria of SESAME(2004). The data processing to obtain the HVR at each location has been carried out using thefollowing steps using the GEOPSY software: traced data have been visually observed forprobable errors; after that the total data has been divided into 41s wide windows petered out
with a 5% cosine function. A Fast Fourier Transform (FFT) has been performed for each split
data for each component. Konno and Ohmachi’s (1998) technique with a smoothing constantof 40 has been applied to smooth the data.
4
4.1

Data Analysis and results
Soil frequencies

The main resonant peak obtained from the data acquired at 114 sites using HVR techniquemainly ranges between 0.5 to 2 Hz (Figure 11). The average predominant frequency for
MCD and FPD deposit types do not vary significantly as can be seen from Figure 3.
5

Although surfacial geology varies for the MCD and FPD deposits but the average shear-wave
velocities for top 30 m of those sites vary between 160m/s and 320m/s (Ansary and Saidur
2013; Zillur et al. 2021). Most of the estimated HVRs show clear resonance peaks for bothtypes of soil deposits as can be seen from Figure 12 (ii)a for FPD deposits and Figure
12(ii)b for MCD deposits.
The soil frequency and soil amplitude maps (Figure 13) show that the soils for most of the
DMDP area are characterized by similar predominant frequencies with moderate
amplification values for both types of soil deposits. These iso maps are based on 614
microtremor data collected by Ansary et al. (2019) and the current study. The predominantfrequencies which have been found for most of the locations of the area under study clearly
indicate that the soil which exists below the DMDP area are not suitable for midrise tohighrise buildings of the city, in general.
4.2.

Building frequencies

The elevation of the 114 observed buildings vary from 3 and 30 m (most of the buildings arelower than 5-storied) and their principal vibrational frequency vary from 1.6 to 8.5 Hz(Figure 14). For the reinforced concrete buildings (RCC), the principal vibrationalfrequencies are considerably smaller and significantly inconsistent than the masonrybuildings (URM) with 3.5 Hz as the median values for both types of buildings (Figure 14a).
The average fundamental frequency values of buildings generally decrease with the increaseof the floor numbers of the building (Figure 14b). This relation can be taken as an indicationof superior statistics as it is an expected relation.
For the observed 107 RCC structures, linear regression with zero intercept in the shape
T=N (Figure 15a) has been used to develop the relation between the principal vibrational
period T(s) and the corresponding floor numbers (N). This developed relationship has been
estimated in period versus the number of floors to compare our results with those of otherresearchers (Figure 15b). The estimated  value is 0.0747, which is in accord with thosefound by Guler et al. (2008) for six buildings in Turkey; Michel et al. (2010) for sixty
buildings in France, and Gallipoli et al. (2020) for ninety-six buildings in Italy. Also, asimilar relation proposed in the BNBC (2020) [T=0.0466(3N)0.9] has been drawn in the same
figure, showing a similar trend.
Due to the availability of the number of floors (Figure 6c) for the assessed 3252 institutionalbuildings within the DMDP area, it has been feasible to estimate the principal vibrational
periods (T=0.0747N) for those structures. The projected principal vibrational frequencies for6most of the structures varied from 0.55 to 13.2 Hz. In this database, there are 40 buildings
having the number of floors greater than 10, 791 buildings are 2-storied and 514 buildings are
single-storied. Out of those 40 buildings, five buildings are more than 15-storied. Most of thebuildings having more than 10-storied are located within the city center.
4.3.

Development of soil-building resonance map

Figure 16 presents the univariate allotments of principal frequencies of the 3252 surveyed
structures and 614 soil locations for which microtremor data are available. The numbers of
the two allotments significantly overlap in the lower frequency range (<2 Hz) indicating that
relatively taller building stocks will be susceptible to resonance within the DMDP area. In
order to assess the probable resonance phenomena in the DMDP area, the predominantfrequency of the ground near the structures is compared with the principal vibrationalfrequency of the 3252 buildings. Figure 17 presents the average Fourier amplitude spectrum,
which has been computed for a 6-storied RCC-building and average HVR of the nearby soil
(FPD) showing that their predominant frequencies are relatively close. When both thefrequencies are close to one another, in this case, the ratio of the predominant frequency ofsoil and the principal vibrational frequency of buildings vary from 0.85 and 1.15; it has been
assumed that a strong soil-building resonance effect is likely to occur; these buildings aremarked in the soil-building resonance map (Figure 18) with red color. On the other hand, if
the ratio varies from 0.75 and less than 0.85 or greater than 1.15 and less than or equal to1.25; it has been assumed that a moderate soil-building resonance effect is likely to occur;these buildings are marked with violet color on the map (Figure 18). For other ratios, theresonance effect is considered to be low or none and is marked with yellow color on the map.
The analysis shows that for 73 buildings, the resonance is relatively high and for 48
buildings, it is moderate. One of the reasons why the effect of resonance is low is due to thefact that out of the 3252 buildings assessed, 80% are less than 5-storied having a principal
predominant frequency greater than 3 Hz, whereas the soil predominant frequency for mostof the DMDP area is less than 2 Hz. This finding is important since out of the total building
stock of 2.2 Million within the DMDP area, 5000 buildings are taller than 10-storied.
Soil frequency has been taken from the microtremor study of 614 free-field points scattered
within DMDP area (Figure 13). For a single building, all microtremor points around thatbuilding have been found using the GIS software as shown in Figure 19. For resonancepurpose, the microtremor point with the least distance has been considered. For more than
80% of buildings assessed, the least distance is less than 700m.
5 Conclusions
7

The resonance effect which may lead a building to vulnerable condition within the DMDP
area have been assessed and discussed in this paper. Results clearly indicate the importanceof site effects in the study area. It is found that the measured predominant soil frequencies
using HVR method within the DMDP area for 614 locations are in general below 2 Hz whichis expected for the geological conditions underlain by the study area. Also for 114 buildings,
the principal vibrational frequencies have been estimated from microtremor observations.
This investigation on structures permitted the estimation of the principal vibrational periods;
these data allowed developing a relation between the observed period (T) and number offloors (N). Applying this newly developed relation for the building of the DMDP area andascertaining the floor numbers of each building, the principal vibrational period or frequencyof the 3252 buildings has been obtained. The principal vibrational frequency range for theassessed buildings varies from 0.6 to 13.5 Hz with a median value of 4.4 Hz.
A building-soil resonance plot has been developed by matching up the variations offrequencies for the buildings with that of the underlying ground. A moderate to severe
resonance level has been obtained for 121 buildings (3.7%); the rest 94.3% of buildings(3131), there is almost no overlap, which implies that no resonance may occur between abuilding and the nearby ground. The DMDP area has around 2.2 Million building stocks,
around 0.5 Million are located within the city center. Out of these 0.5 Million, around 5000
are more than 10-storied high and vulnerable to the resonance effect since most of the areasof DMDP area has soil predominant frequency of less than 2 Hz.
This method allowed evaluating the effect of resonance between buildings and the underlying
ground. The finding of this study is a significant ingredient as it makes us to identify thoseareas of a metropolis where the building-soil resonance is more prone to occur causing
relatively more distress during a seismic event.
References
Ansary M.A., Rahman M.S. (2013). Site amplification investigation in Dhaka, Bangladesh,using H/V ratio of microtremor. Environmental Earth Sciences, ISSN 1866-6280, 70:559–
574.
Ansary M.A., Helaly A.L., Hassan M., Khair A., Bhuiya M.M.R., Saha S., Helaly SM(2019). Assessment of Seismic Vulnerability Index of RAJUK Area in Bangladesh Using
Microtremor Measurements. The 18th International Symposium on New Technologies for
Urban Safety of Mega Cities in Asia, USMCA 2019, December 9-10, 2019 Yangon,
Myanmar.

8

Petrovic, B., Parolai, S., 2016. Joint deconvolution of building and downhole strong- motion
recordings: evidence for the seismic waveﬁeld being radiated back into the shallow
geologicallayers.

Bull.

Seismol.

Soc.

Am.

106,

1720–1732.

https://doi.org/

10.1785/0120150326.
Pinzóna, LA, L. G. Pujadesa, A. Macaub, S. Figuerasb (2019); Increased seismic hazard in
Barcelona (Spain) due to soil-building resonance effects, Soil Dynamics and Earthquake
Engineering 117 (2019) 245–250
Piro, A., de Silva, F., Parisi, F., Scotto di Santolo, A., Silvestri, F., 2019. Efects of soilfoundation-structure interaction on fundamental frequency and radiation damping ratio of
historical masonry building sub-structures. Bull. Earthq. Eng. 18 (4), 1187–1212.
Rahman MZ, Siddiqua S, Kamal ASMM (2020) Probabilistic Seismic Hazard Analysis for
Bangladesh. Nat Hazards 103: 2489-2532
Rahman MZ, Siddiqua S, Kamal ASMM (2021) Site Response Analysis for Deep and Soft
Sedimentary Deposits of Dhaka City, Bangladesh. Nat Hazards DOI: 10.1007/s11069-02104543-w
SESAME European research project, (2004). Guidelines for the implementation of the h/v
spectral ratio technique on ambient vibrations, measurements, processing and interpretation.
European commission-research general directorate project no. CT2000--00026 SESAME.
Steckler MS, Mondal DR, Akhter SH, Howe M (2016) Locked and loading megathrust
linked to active subduction beneath the Indo-Burman Ranges. Nat Geosci 9: 615-618.
Tallini, M., Sardo, LL, Spadi, M (2020). Seismic site characterisation of Red Soil and soilbuilding resonance effects in L’Aquila downtown (Central Italy). Bulletin of Engineering
Geology and the Environment. 79:4021–4034. https://doi.org/10.1007/s10064-020-01795-x.
Tsogka, C., Wirgin, A. (2003). Simulation of seismic response in an idealized city. Soil Dyn.
Earthq. Eng. 23, 391–402. https://doi.org/10.1016/S0267-7261(03)00017-4.
World Population Review (2021). https://worldpopulationreview.com/world-cities/dhakapopulation ((last accessed 26 February 2021)

496

Figure 1: DMDP area with and its surrounding region

12Figure 2: (a) Geological Map of Bangladesh (Alam et. al. 1990) (b) Geological map of the study area showing sites where data have beenacquired in this study

13

Figure 3: SPT and SDHT locations within the DMDP area

14

Figure 4: The lithology of the horizontal cross-section

15

Figure 5: The lithology of the vertical cross-section

16

(a)
Figure 6: Spatial distributions of buildings classified according to (a) year of construction; (b)built typology; (c) number of floors of total 3252 buildings

17

(b)

Figure 6 (contd.): Spatial distributions of buildings classified according to (a) year of
construction; (b) built typology; (c) number of floors of total 3252 buildings.

18

(c)

Figure 6 (contd.): Spatial distributions of buildings classified according to (a) year of
construction; (b) built typology; (c) number of floors of total 3252 buildings.

19

Figure 7: Flowchart of Level 1 risk prioritization procedure

70
60

Count

50

Average

1.17

Number
1.15

40
30
20
10
0
MCD

FPD

Geological Types
Figure 8: Number study sites on Madhupur Clay Deposit (MCD) and flood plain deposit(FPD) with average predominant frequency

20

Year
45

40

41

36

40

35

35

32

30

NumberNumber

25
22
20
17
15

25
20
15
10

10
6
5

29

30

26

3

2

5

5

3

6

1

1

0

0
<1950

1950-<19601960-<19701970-<1980

1980-<1990

1990-<2000

2000-<20101

2010-<2020

2

3

4

5

6

Number of Floors

Year

Figure 9: Year of construction and number of floors of the selected 114 buildings

21

10

(a)

(b)

(c)
(d)
Figure 10: Microtremor recording (a) at a free-field, (b) at roof top of a building, (c) sketch of sensor’s map for one location and (d) channels
showing time history data

22

5

FPD
1. Donia
2. Dhaka Ud
4. Sk Rasel
5. Murapara
7. Jangir
9. Sonargaon
10. Charail
11. Battali
12. Dhaka Sik

Average HVR

4

3

2

1

0
0.1

0.2

0.3

0.4

0.5 0.6 0.7 0.8

1

2

3

4

5

6

7 8 9 10Frequency (Hz)(a)

Average HVR

3MCD
47. Satarkul
49. Kalachandpur
50. Tongi Pilot
56. Sataish
57. Rani Bilas
61. Bakshi
62. Nayatola

2

1

0
0.1

0.2

0.3

0.4

0.5 0.6 0.7 0.8

1Frequency (Hz)

2

3

4

5

6

7 8 9 10

(b)
(i)
(ii)
Figure 12: (i) Spatial Distribution of test sites as per MCD and FPD deposit type and (ii) comparison between HVSRs obtained on (a) FPD and(b) MCD deposits
23

(a)

(b)

Figure 13: (a) Soil frequency contour and (b) soil amplification contour maps of DMDP area
24

(a)

(b)
Figure 14: Empirical distributions of the principal vibrational frequency of the 114 buildings
versus (a) construction typology and (b) number of ﬂoors
The lower and upper part of the grey rectangular box correspond to the first and third
quartiles (the 25th and 75th percentiles); the black square box is the median (50th percentile)25

Fundamental Period (s)

1
0.8
0.6
0.4
0.2
0
0

1

2

3

4

5

6

7

8

9

10

11

Number of Storey

Fundamental Period (s)1(a)

Current Study
Galipolli 2020
Guler 2008
Michel 2010
BNBC 2020

0.8
0.6
0.4
0.2
0
0

2

4
6
Number of Storey

8

10
b)

(

Figure 15: Experimental relation between building period and the number of floors for (a) the
107 sampled buildings and (b) other studies. In (a), the thin black line represents thepredicted values (T = 0.0747N), and in (b) the thick black line represents the prediction
interval of the regression
26

Figure 16: Distributions of the fundamental frequency for soils and buildings27

Amplitude for Building or HVR for Soil

200

Soil (2.0 Hz)
Building (2.26 Hz)

100
70
50
30
20
10
7
5
3
2
1
0.7
0.5
0.3
0.2
0.1
0.5

0.6

0.7 0.8 0.9 1

2

3

4

5

6

7

8

9

10

Frequency (Hz)(a)(b)
Microtremor Sensor(c)Figure 17: (a) Fourier amplitude functions estimated on the top-floor of the 6-storied
reinforced concrete building and HVR on the nearby soil; (b) microtremor observation of thebuilding resting on FPD; (c) location of building on the googlemap28

Figure 18: Soil-building resonance map of 3252 buildings495

Figure 19: Nearest microtremor stations for an individual building

496

PART-IX

DEVELOPMENT OF CORRELATIONEQUATIONS BETWEEN SHEAR WAVEVELOCITY AND STANDARDPENETRATION TEST VALUES FOR
DIFFERENT SOIL TYPES FOR
DMDP AREA OF BANGLADESH USINGMULTIVARIATE ANALYSISBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA
Prepared By: Anikah Tasmiah
Mehedi Ahmed Ansary

Introduction
Shear wave velocity Vs is an essential metric when assessing the dynamic properties ofshallow subsurface soil [1, 2]. Design seismic movements, wave amplification, and soil
structure interaction are all major issues in earthquake engineering and these necessitate
understanding of shear wave velocities in soil deposits in order to be solved[3]. The usage of
Vs became widespread and is now widely employed in practice due to the fact that it is aquantitative index that can be quantified using geophysical techniques [4].
Correlation equation of Vs with various soil indexes has been established by numerous
researchers over the years in various geographical locations because direct determination ofshear-wave-velocity is expensive [1, 5] and requires leading-edge instrument and appropriate
industrial and traffic noise free environment [6]Numerous studies have established correlations between Vs and soil indexes such as depth,
SPT-N (or N), geological epoch and soil type [3, 7, 8]. The geologic influence could be
attributed to geologic age or the sedimentary environment[7] .Adopting a similar technique tothe one described above may be advantageous for previously bored boreholes, as they often
have just data on N and the accompanying depths, but no measured Vs [8].
Hamilton[9], Boore and Joyner[10] , Klimis et al. [11] , Wang and Wang [12] establisheddepth based regression equations in the past. Empirical correlation equation between shearwave-velocity and penetration resistance or N value from SPT has been established by lots ofresearchers over the years in different geographical locations. For example in Japan research
was conducted by, Imai et al.[13], Imai and Yoshimura [14], Imai [15] and Imai andTonouchi [16] & Dikmen [17] in Turkey, Fauzi [18] in Indonesia, Sun et al.[19] in Korea,
Maheswari [20] , Thokchom et al. [1] and Bandyopadhyay et al. [5] in India. However the
shear wave velocity cannot be well characterized by the N-value alone. Several approaches
have been proposed to improve such empirical equations by incorporating other elements
such as type of soil and depth estimated from the ground surface [3].
The study of Ohta and Goto [3] first proposed multivariable analysis technique in Vs
empirical equations. Multiple studies considered depth and N based correlation equations intheir studies [3, 7, 21] and resorted to multiple regression analysis. Both Ohta and Goto[3]and Lee [22] discovered that the essential parameter in a regression equation is “depth”
rather than the N-value, assuming the type of soil and effect of geology are initially studied.
The equation of

Chapman et al. [21] incorporated effective overburden pressure (σv).

However, Kuo et al. [8] advised in their study that the model for regression should be chosen
based on the highest coefficient of correlation R2 between Vs and N or depth.
498

The purpose of this paper is to create multivariate regression equations of Vs based on depth
and SPT-N for various soil types in the 1530-square-kilometer Dhaka Metropolitan
Development Plan (DMDP) Area. A total of 400 boreholes were drilled throughout the
research area. N levels were assessed using SPT at 1.5m depth intervals and PS logging was
performed in all 400 boreholes, resulting in a total of 9334 data pairs for all soils (6159 forsand; 3175 for clay).
Existing Shear Wave Velocity Equations
Ohta and Goto [3] adopted four soil indexes namely the soil depth, the Standard Penetration
Test N-value, soil type(grain size) & geological period and established 15 sets of empiricalequation in order to approximate low-strain level shear wave velocity by use of about 300
data. Since the indexes can be both quantitative and qualitative type they resorted to scaleclassification where above mentioned indexes were categorized into few clusters by theirfeatures. Since the N-value and depth were matric variables derivation was done by means ofmultivariate analysis. The depth and SPT-N based equation of shear wave velocity hadcorrelation coefficient larger than 0.8.
Lee [7] used 491 sets of data from the Taipei basin, including SPT N-value, shear wave
velocity, and “depth.” To identify the most rational model of the shear-wave-velocity, aside
from simple linear model, the multiple regression models & the intrinsically linear models arealso investigated. In addition, a method for examining the problem of multicollinearity in a
multiple regression equation was proposed. When type of soil and geological influence aretaken into account in the regression model (𝑉 = 𝑎𝑁 𝐷 ), he concludes that the multiple
regression model yields the highest coefficient of determination (R2). However, because“depth” and “N” are not mutually exclusive, a multicollinearity problem may develop. The“rule of thumb” test, which states that the correlation coefficient R between any two variables
ought not to be greater than 0.70, is one way for avoiding the problem suggested by Lee [7]from Anderson et al., [23]. Additionally, he found that the multiple regression model,
𝑉 = 𝑎𝑁 𝐷 overcome the disadvantages of the single variable regression equation, 𝑉 =𝑎𝐷 or 𝑉 = 𝑎(𝐷 + 1) , by presenting the variations amongst soils at the same depth in thesame area. According to his analysis, one disadvantage of intrinsically linear regression
model where depth (D) is the principal parameter is that the shear-wave-velocities will be all
the same in depth throughout the investigated area. Thus, the equations cannot reflect the
weaker strata, and multiple regression equations without the multicollinearity problem would
prevail in this case.
499

In his previous study, Lee [22] pointed that the fundamentally linear form of equation withthe depth factor was appropriate when the indigenous soils were originally categorizedaccording to type of soil and the effect of geology; its value of R-square was comparable tothe value of R-square of the multiple regression equation. In this paper, 88 data sets of SPT N
value, shear wave velocity, and depth were examined in the Taipei basin from fifteen
borelogs. To select the finest model for the shear wave velocity, the linear, the intrinsicallylinear, the multiple regression and the second-order polynomial models are evaluated.
In the study of Kuo et al. [8] empirical-regression-equations were assessed utilizing over 641
sets of data from Ilan area as well as 719 sets of data from Taipei Basin area based on thecorrelation between Vs and soil indicators. In this study, multivariable analysis was employed
to improve the precision of regression models. To analyze the regression equations,specimens with N less than 50 and depth less than or equal to 50 m were chosen. Due to thisreason, 56 and 38 locations in Taipei and Ilan, respectively, were used. For boreholes that had
only N values and had not been drilled to a depth of 30 meters, empirical equations for Vs
were performed, and extrapolations for Vs30 were utilized.
Table 1 Regression Equations established in previous studies
Author(s)Ohta andGoto(1978) [3]Lee (1989) [22]

No of
Data
Point
300

88

126

Soil Type
All

𝐻 .

0.820

CL/AllCL/Keelung
CL/Tanshuei

𝑉 = 74.44𝑁 . 𝐷 .
𝑉 = 71.52𝑁 . 𝐷 .

0.78
0.83

𝑉 = 58.56𝑁 . 𝐷 .

0.92

ML/AllSM/AllSM

𝑉 = 73.70𝑁 . 𝐷 .
𝑉 = 57.97𝑁 . 𝐷 .
𝑉 = 76.16𝑁 . 𝐷 .

0.88
0.86
0.776

𝑉 = 61.62𝑁 .

𝑉 = 68.77𝑁 .
Lee (1992) [7]

Kuo et al.
(2011) [8]3R2Equation

265

CL

100

ML

365

CL/ML

719

Sand
Clay/Silt(𝐷 + 1 ) .

0.779

.

0.785
0.788
0.829
0.830
0.798
0.801
0.671
0.685

.

𝑉 = 95.72𝑁
𝐷
𝑉 = 86.10𝑁 . (𝐷 + 1) .
𝑉 = 90.57𝑁 . 𝐷 .
𝑉 = 82.79𝑁 . (𝐷 + 1) .
𝑉 = 93.54𝑁 . 𝐷 .
𝑉 = 84.53𝑁 . (𝐷 + 1) .
𝑉 = 93.11𝑁 . 𝐷 .
𝑉 = 114.55𝑁 . 𝐷 .

Database Used for Conducting Study
SPT was used to conduct borehole drilling at 400 places throughout the DMDP area. A downhole
seismic test was carried out at each location. The borehole log displays the N-values derived from
SPT with depth and the Vs profiles established from seismic downhole testing. Fig. 1 presents anillustration of test results at a site in Hemayatpur, Savar of DMDP area.
For all soil types, downhole tests provided 9334 pairs of data points. In the past, N values produced
from SPT tests were corrected for rod length, overburden stress, and equipment type, as well as
borehole diameter. [19]. Correlations are calculated in the current study using uncorrected N values.

In-situ test is a widely used means for site characterization in geotechnical engineering [14,20]. In present study SPT is used for in-situ geotechnical test. The SPT process is describedin ASTM D 1586 [24]. Both seismic and electromagnetic techniques are used for in-situ
geophysical tests to estimate subsurface properties[19]. Vs can be estimated both in laboratory
tests as well as in-situ tests [6, 19]. In this study seismic downhole test is done in the same
borehole where SPT has been performed to determine the shear-wave-velocity of soil. This
test procedure is described in ASTM D 7400 [25].

Fig. 1 . A sample set of SPT and downhole test results along with soil description in DMDP
Area
Fig. 2 shows the data statistics for sand, clay, and all soils. Considering all soil type data, it is foundthat 75% of the values of N fall below 40, maximum data point is around 400 and minimum data
point is 1. The median in the mid-point of the box implies symmetric or normal distribution. Theinterquartile range is 15-40. For clay, data is left skewed or negatively skewed but for sand, data is
4

symmetric for SPT-N values. In case of clay interquartile range is around 8-20 whereas in case ofsand it is 20-50 which indicates for sand layers higher SPT-N value was found. Also, N for sand ismore dispersed than clay.
In case of all type of soils shear-wave-velocity data, it is observed to be negatively skewed and 75%of the data falls below 300. Maximum value found is around 750 and minimum value found is around
15. For clay, Vs data is observed to be symmetric and interquartile range is 150-300 whereas for sandit is 200-350 and data is negatively skewed. So, we can state that dispersion of Vs data is almost
similar for clay and sand soil.

Geological Review of the Study Area
Our research focus is the DMDP area, which comprises Dhaka, Gazipur, Narayanganj, andNarshingdi districts. It covers approximately 1530 square kilometers in total, and it is evident
that the greater the number of data points, the more accurate and dependable the output. The
geomorphologic map of the DMDP area is depicted in Fig. 3.
The area is level topographically, with elevations ranging from 1 to 14 meters. The majorityof metropolitan areas are located anywhere between 6 and 8 meters above sea level[26].
Dhaka is at high risk when it comes to earthquake sensitivity. The city is located between-theEurasian and the Indian Plates, next to the seismically active convergent plate-boundary [27,28]. The city and its environs were covered by two distinct geologic units, namely current
alluvial deposits and Pleistocene Madhupur Clay. The principal geomorphic units arefloodplains, abandoned canals, depressions, and the Dhaka terrace, or high land. Othersignificant topographic characteristics are low-lying swamps and marshes found throughout
the DMDP area.
For describing the reliance of a response variable on a number of independent factors,
regression analysis is one of the most popular methods [29, 30]. Every time we want to model
the link between one response variable and more than one regressor variable, we employ
multiple linear regression analysis[31].
According to [32] mathematically Multiple Linear Regression can be defined as a regression analysis
where independent variable Y linearly depends on many independent variables X1, X2,...,Xk
The form of a multiple linear regression can be as below:
𝑌 = 𝑓(𝑋 , 𝑋 , … … , 𝑋 )Here 𝑓(𝑋 , 𝑋 , … … , 𝑋 ) is a linear function of 𝑋 , 𝑋 , … … , 𝑋 .

According to [33] the model formulation, assumption and least square estimation can be
known

5

Fig. 2: Data statistics, showing minimum, maximum, and mean for sand, clay and all data
6

Fig. 3 Locations of downhole/SPT tests performed in the DMDP area
Mathematical Theory: Multiple Regression Analysis and Non-linear Regression
AnalysisAssuming p explanatory variables 𝑋 , 𝑋 , … … , 𝑋 that will be related to a dependent variable
Y. Assuming the data matrix derived from sample of n observations(𝑥 , 𝑥 , … … , 𝑥 , 𝑦 ),𝑖 = 1,2, … … , 𝑛, or equivalent to an 𝑛 × (𝑝 + 1) data matrix.
It is assumed that the (p+1) random variables will satisfy the following linear model𝑦 = 𝛽 +𝛽 𝑥 +𝛽 𝑥 +⋯+𝛽 𝑥 +𝑢

𝑖 = 1,2, … , 𝑛

Here
1. The 𝑢 , 𝑖 = 1,2, … , 𝑛 are the values of unobserved error term U and are identically
distributed and mutually independent
2. The unknown parameters namely 𝛽 , 𝛽 , 𝛽 ,……, 𝛽 are constants
Now a sample of n no. of observations on Y and 𝑋 , 𝑋 , … … , 𝑋 forms a [𝑛 × (𝑝 + 1)] data
matrix. The n equations provide equations linking the n observations.
𝑦 =𝛽 +𝛽 𝑥+𝛽 𝑥+ ⋯+ 𝛽 𝑥+𝑢𝑦 =𝛽 +𝛽 𝑥+𝛽 𝑥+ ⋯+ 𝛽 𝑥+𝑢.
7𝑦 =𝛽 +𝛽 𝑥

+𝛽 𝑥+ ⋯+ 𝛽 𝑥+𝑢This set of n equations can be expressed as follows using matrix notation:𝒚 = 𝑿𝜷 + 𝒖,
Where:
𝑦
𝑦
𝑦=
⋮
𝑦

1 𝑥
1 𝑥
;
⋮
1
1 𝑥
( × )

𝛽
⎡ ⎤
𝛽
⎢ ⎥
𝛽
𝛽=⎢ ⎥
⎢⋮⎥
⎣𝛽 ⎦(
𝑢
𝑢
𝑢=
⋮
𝑢

𝑥 …𝑥
𝑥 …𝑥
1 … 1
𝑥 …𝑥

;
)

×(

; and
)×

( × )

Starting from the model we can obtain the estimation of 𝛽 of the β vector by means of theleast-square technique [32][33] has explained the method of obtaining 𝛽 by using least square procedure, that minimizes
the sum of squares given by𝜁 =𝑦 − 𝛽 − 𝛽 𝑥 − 𝛽 𝑥 − ⋯− 𝛽 𝑥= (𝑦 − 𝑋𝛽 ) (𝑦 − 𝑋𝛽 )After utilizing calculus the resulting equation for β can be given by the following normal
equation written in matrix notation
𝑋 𝑦 = 𝑋 𝑋𝛽
Where:
⎡
⎢
⎢
⎢
⎢
⎢
𝑋𝑦=⎢
⎢
⎢
⎢
⎢
⎢
⎣
8

𝑦 ⎤
⎥
⎥
⎥
𝑥 𝑦⎥
⎥
⎥
𝑥 𝑦⎥
⎥
⋮
⎥
⎥
𝑥 𝑦⎥
⎦(

)×

⎡
⎢
⎢
⎢
⎢
⎢
⎢
′
𝑋𝑋=⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎣

𝑛

𝑥

𝑥

…

𝑥

𝑥

𝑥 𝑥

−

𝑥

𝑥 𝑥

𝑥

−

⋮

⋮

⋮

⋮

𝑥

𝑥 𝑥

𝑥 𝑥

…

⎤
⎥
⎥
⎥
𝑥 𝑥
⎥
⎥
⎥
𝑥 𝑥 ⎥
⎥
⎥
⋮
⎥
⎥
⎥
⎥
𝑥
⎦(
𝑥

)×(

)

Where the solution vector for the abovementioned normal equations is
𝛽 = (𝑋′𝑋) 𝑋′𝑦
The fitted model after obtaining 𝛽 can be written as𝑦̂ = 𝑋. 𝛽
And residuals denoted by vector e can be written as𝑒 = 𝑦 − 𝑦̂The error sum of squares or SSE is𝑦 − 𝑦̂

= 𝑦 − 𝑋𝛽𝑦 − 𝑋𝛽And the total sum of squares SST is(𝑦 − 𝑦̅)This value defines the total variation in y based on one or multiple x variables.The ration of
the SSR and SST value is coefficient of multiple determination and is denoted by R2 [33]We
can also derive the adjusted R2 value.
9The regression sum of squares SSR can be defined as follows

𝑦̂ − 𝑦̅An F-test in an analysis of variance (ANOVA) format can be used to evaluate the model's
overall goodness of fit[33]. It assists in testing the null hypothesis that𝐻 : 𝛽 = 𝛽 = ⋯ =𝛽 = 0. Under this hypothesis, the statistic MSR/MSE has an F distribution having p and np-1 degrees of freedom[32, 33]
Table 2 Analysis of Variancs or ANOVA table for Multiple Regression[ 33]Sourced.f

Sum of Squares

Mean SquareF

Regressionp

SSR

MSR=SSR/ p

MSR/MSE

Error

n-p-1

SSE

MSE=SSE/ n-p-1

Total

n-1

SST

In nonlinear regression, observational data are represented by a function that depends on one
or more independent variables and is a nonlinear combination of the model
parameters[29].Nonlinear regression may estimate models with arbitrary relationships
between independent and dependent variables, in contrast to classic linear regression, which
can only estimate linear models[29].
The general form of a nonlinear regression given by Yaser et al. [29] is as followed
𝑌=𝛼 𝑋

𝑋

… 𝑋

Here, 𝛼 − 𝛼 are the equation parameters for the relation.
Yaser et al. [29] has incorporated a method of moving nonlinear regression problems to alinear domain utilizing an appropriate transformation of the model formulation which is asfollowed
Taking the log of the aforementioned equation we get a linear relationshiplog(𝑌) = log(𝛼 ) + 𝛼 log(𝑋 ) + 𝛼 log(𝑋 ) + ⋯ + 𝛼 log(𝑋 )10And thus regression of log(𝑌) on log(𝑋 ), log(𝑋 ),…, log(𝑋 ) can be used to assess the α0,
α1… αn [29, 34]
Regression of the empirical equation/Data Analysis Process
The majority of researchers predicted that Vs had a power-law relationship with either thedepth or the in situ penetration test result N[8]. According to Kuo et al.[8], the most accurate
regression model can be determined by the greatest value of correlation coefficient or R
between Vs and depth or N. To minimize the problem of multicollinearity, some statisticians
advocated for a "rule of thumb" method where the correlation coefficient R between any twovariables ought not to exceed 0. 70 [7, 8].
When all of the variables are metric, or can be expressed as numbers, a simple-multivariate
analysis can be used easily [3]. Initially, SPT N-value, the shear wave velocity, and depth
value have been plotted on a logarithmic graph (Fig. 4) in order to understand the nature of
the data and to obtain a useful link between shear wave velocity and individual index.

Fig. 4 Visualizing relation of SPT N-value, shear wave velocity (Vs) and depth
We have hypothesized a nonlinear regression relationship between response variable shear
wave velocity (Vs ) and two regressor variables Depth (D) and SPT blow counts (N) . We
adopted the methodology mentioned in [29] and brought the logarithms of the variable to alinear domain to establish a multiple linear regression relationship among the response and11regressor variable and by means of inverse calculation established the nonlinear regression
equation correlating Vs with D & N.
By inspection of the graph and regression analysis, the we have hypothesized a linear relation
between log Vs and log N using 9334 data points for all types of soil, and the least squares
curve obtained this way is as follows:
𝑙𝑛 𝑉 =4.1442093 +0.3597551 𝑙𝑛 𝐷 + 0.1194517 𝑙𝑛 𝑁
This is equivalent to 𝑉 = 63.068 ∗ 𝐷 .

(1)(m/s). In Equation (1), the R2∗𝑁 .

value is 0.7171. In the same process the multiple regression equations for the soil of DMDP
area based on soil type are as follows
For sand𝑉 = 59.61 ∗ 𝐷 .

∗𝑁 .

(2)

For clay𝑉 = 63.29 ∗ 𝐷 .

∗𝑁 .

(3)

Fig. 5 demonstrates the summary of the regression analysis performed on the dataset for all
types of soil, sand and clay respectively including the value of equation parameters, R squarevalue and ANOVA table mentioned in Table 2

12

Fig. 5 Summary of Regression analysis of all type of soil, sandy soil and clayey soil
respectively performed in Excel’s Data Analysis Toolpack
In Equations (2) and (3), the R2 values are 0.6844 and 0.7428 as well as the standard errors
are 0.239394176 and 0.249327695, respectively. The three dimensional plots of the above
three equations are presented in Fig. 6.

13

(a)

(b)

(c)

Fig. 6 Three-dimensional illustrations of regression equations and data sets for DMDP area

14

Validation of the Proposed Equation
The regression outcomes in this investigation are within the range suggested by previous
researches. The R2 value obtained in multi-regression equation is the largest among othercombinations. This complies with the conclusion of Lee [7] that according to the theoreticalbasis of shear wave velocity, Vs =aNbDc has a specific physical meaning and also has thehighest R2 value. All the correlation models developed in this study with R2 are presented inTable 3.
Table 3 Regression Equations established in the current study
Soil TypeEquation TypeR2

All soils

𝑉 = 𝑎𝑁

0.5257Sand

0.5832Clay

0.3923All soils

𝑉 = 𝑎𝐷

0.6941Sand

0.6502Clay

0.7221All soils

𝑉 = 𝑎𝑁 𝐷

0.7171Sand

0.6844Clay

0.7428Besides it has been discovered by Ohta and Goto [3] and by Lee [22] that instead of "Nvalue”, “depth” is the most important parameter in a regression equation if the geologic effectand soil types are taken into account first in the regression equation. It also overcomes one
disadvantage of using intrinsically linear regression with depth (D). In this case, a multiple
regression equation without the multi-collinearity problem will be advantageous [7]. The
above table clearly shows that the hypothesis of Ohta and Goto and Lee is correct.
From statistical point of view we can further validate our equation by means of F-test in the
ANOVA table presented in Fig. 5 .As mentioned before F-test is used to evaluate thegoodness of fit of a model[33].As per [32] it allows us to test the null hypothesis which is
𝐻 =𝛽 =𝛽 =⋯=𝛽 =0513

against the alternative hypothesis:
𝐻 : 𝑎𝑡 𝑙𝑒𝑎𝑠𝑡 𝑜𝑛𝑒 𝑜𝑓 𝑡ℎ𝑒 𝑝𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟𝑠 𝛽 , 𝛽 , … , 𝛽 𝑖𝑠 𝑑𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑡 𝑓𝑟𝑜𝑚 𝑧𝑒𝑟𝑜In a regression model, significance F represents the probability that the null hypothesis
cannot be rejected.
In the ANOVA table the Significance F represents the p-value for the F-test that determines
whether our model's ability to explain the variability of the dependent variable is better thanthat of a model with no independent variables when all of our model's independent variables
are taken into account. Since our p-value is smaller than any possible value of significancelevel we can say that we obtained a statistically significant regression model.
Conclusions
This paper has attempted to establish a depth and SPT-N based empirical equation of shear
wave velocity in the DMDP area of Bangladesh by means of multiple regression analysis. It
has been found that multiple regression model yields higher value of R2 than one variable
regression equation and overcomes the disadvantage of one variable regression equations.
This paper has also produced a three dimensional diagram of regression equation including a
regression plane.

514

PART-X

EFFECT OF SURCHARGE PRESSURE ON
MODEL GEOTEXTILE WRAPPED-FACE
WALL UNDER SEISMIC CONDITIONBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Ripon Hore
Mehedi Ahmed Ansary

1.

Introduction

It is about four decades since the construction of first geosynthetic reinforced soil (GRS) walland it is now established as an adaptable soil retention technique (Latha & Manju 2016). The
GRS walls have several beneficial effects such as-saving in cost ease of construction, better
performance under seismic loads (Tafreshi et al., 2015; Hegde & Sitharam 2015), design
flexibility, capacity to sustain large deformations without structural distress and aesthetics
made them suitable for a variety of geotechnical engineering applications (Latha & Manju
2016). Over the year’s extensive research were carried out on stability and performance of
GRS and reinforce soil (RS) walls under different seismic events, for which a summary review
is provided in this section.
Seismic effect on soil structures assumed a significant part in the area of earthquake
geotechnical engineering and was discovered impressive turn of events in the recent past. In
this exploration, a wrap reinforced soil wall was fabricated on clay soil enclosed by a laminarbox and subjected to sinusoidal input motions through the shake table. In view of shaking table
tests, this study aims to explore the impact of surcharge on wrap faced geotextile reinforced
sand wall. The outcomes from this examination give helpful rules with respect to the relative
performance of reinforced soil under different test conditions with clear ramifications for plan.
Hatami et al. (2005) carried out parametric studies on model reinforced soil retaining wallswith a wide range of geometrical and material properties. Ling et al. (2005) reported full-scale
shaking table tests and observed that reinforcement spacing and the length of the top
reinforcement layer each had a significant influence on measured facing deformation.
Chakraborty et al. (2021) and Hore et al. (2020) conducted small scale shaking table tests toevaluate the response GRS walls under sinusoidal loading. Ehrlich et al. (2012) conductedfull-scale model tests on two walls and evaluated the influence of backfill compaction on themeasured reinforcement load. They showed that increased compaction effort could help reduce
the reinforcement connection loads and facing deformations resulting from surcharge loads
following construction. Ertugrul & Trandafir (2013) proved lightweight deformable geofoam
can reduce the earth pressure on the retaining wall. Bilgin & Mansour (2014) observed thatreinforcement type (e.g., geogrids, geotextiles, metal strips, and metal bar mats) can affect both
the required reinforcement length and governing design criteria.
Latha & Santhanakumar (2015) observed that denser backfill and reinforcement layers
improved the seismic performance of walls with modular facing significantly more than thosewith the full-height panel facing. Panah et al. (2015) conducted shaking table tests on
reinforced soil retaining walls with polymeric strips and investigated the effect of the length of515

reinforcement, the number of steps and shape of the reinforcement arrangement on the failuremode, the wall displacement, and the acceleration amplification factor, respectively. Wang etal. (2015) performed a large-scale shaking table tests of geogrid reinforced rigid retaining walls
and observed that geogrid layers can decrease the development of excess pore water pressuresand accelerate the dissipation of excess pore water pressures. Chaudhary et al. (2016)
performed a numerical analysis of reinforced soil retaining walls using FLAC and observedthat the reinforcement affects the earth pressure as well as lateral displacement of the retaining
wall significantly.
Yazdandoust (2017; 2018) carried out a series of 1-g shaking table tests was to investigate theinfluence of the peak acceleration, the loading duration, and the strip length on the dynamic
behaviour of steel-strip reinforced soil walls (SSWs). Huang (2019) performed shaking table
tests on geosynthetic-reinforced walls with a height of H = 0.6 m and described that maximum
tensile forces induced by shaking increase as the depth of reinforcement increases, generating a
trapezoidal shape rather than the inverted trapezoidal shape.
Goktepe et al. (2019) studied numerical and experimental research on scaled soil-structure
model for small shaking table tests and the structural behaviour is significantly affected by thefrequency content of the earthquakes considered in the soil-structure interaction (SSI) problem.
Gidday & Mittal (2020) and Hore et al. (2021a, b) conducted shaking table tests on geotextile
wrap faced reinforced soil walls and compared with the numerical results done by PLAXIS
software. They observed that, vertical crest settlement and horizontal displacement ofreinforced soil wall decrease with an increase in reinforcing layers. Xu et al. (2020) conducted
two shaking table tests on a full-height panel and modular block reinforced soil retaining wallmodels in order to examine the influence of facing type on the connected loads in the twomodels.
This paper describes, the results from twenty-four shaking table tests on geotextile wrap faced
reinforced soil retaining wall models, where the soil wall is resting on soft clayey soil
foundations. Sinusoidal harmonic motions were applied to the model; with different surchargepressure, frequency of shaking, and base acceleration, respectively. This research paper mainly
highlights the surcharge pressure effect on model walls for evaluating the reinforced wall
response and foundation soil at higher depths (higher vertical stress) under cyclic loadings.
Varied surcharge pressure was used on the model wall to evaluate the cyclic behaviour ofreinforced wall and foundation at same wall height. Different surcharge pressure conditions
were used in the tests not as a procedure to simulate different wall heights but to evaluate theresponse of each slice of reinforced sand wall. Moreover, the impact of surcharge wasevaluated for different conditions of frequency and acceleration, face displacements and porewater pressures were also discussed.
2.

Equipment and materials

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 is a square type, having 2 m×2 m dimension and approximate
payload capacity of 1000 kg, which was made from steel plates. The shaking table can be
operated over an acceleration range of 0.05g to 2g and frequency range 0.05 to 50 Hz with amaximum amplitude of ±200 mm. Maximum velocities are 0.3 m/s.
The ideal container is one that gives a seismic response of the soil model identical to thatobtained in the prototype. The laminar shear box developed at Bangladesh University ofEngineering Technology (BUET) has consisted of 24 hollow aluminium layers of frames asshown in Figure 1. Each layer consists of an inner frame with inside dimensions of 915 mm ×1220 mm × 1220 mm. The aluminium alloy is adopted for its sufficient strength and rigidity,
and it’s lightweight to minimize the effect of the inertia of the frame on the soil movements.
The gap between the successive layers is 2 mm. The layers are separated by linear roller
bearings arranged to permit relative movement between the layers in the longitudinal direction
with minimum friction.
In this study, Dhaka clay has been reconstituted by thoroughly mixing the oven dried clay
powder with an initial water content equal to the LL—a procedure described by Burland(1990). The thorough mixing of the slurry has been attained with the aid of a ‘Hobart’ rotary
mixer. With this slurry, a 300 mm thick reconstituted clay layer has been constructed within thelaminar shear box; and then one-dimensional consolidation were carried out under the drained
condition at loads: 15kPa, 20kPa, 25kPa, 30kPa, 40kPa, 60kPa, 80kPa, and 100kPa. The
consolidation process has been observed through the settlement versus time graph, plotted withthe aid of calibrated mechanical dial gauges, instrumented on either side of the laminar shear
box. A model soil with appropriately scaled stiffness and strength properties was developed forthe project and consisted of 75% kaolinite, 25% Illite (by weight). The model soil has a unit
weight of 14.8 kN/m3, a specific gravity of 2.64, undrained shear strength of 28 kPa, andultimate bearing capacity of 17.20 kPa. Undrained shear strength was determined by
Unconsolidated Undrain (UU) test. The ultimate bearing capacity was determined from CPT
test result by following (Meyerhof 1956) method. The water content (w %) of the collectedreconstituted Clay samples have been determined to be 27%. Average liquid limit (LL) andplastic limit (PL) were established to be 41% and 16%, respectively. It was observed that thePL points located above the A-line defined by PI = 0.73(LL-20), where PI is the plasticity
index. The soil was defined as Lean Clay (CL), as per as USCS. Locally available dry sand(called as Sylhet) was used as the backfill material. Figure 2 shows the particle size distributionof the sands. The sand is classified as poorly graded sand (SP) according to the Unified Soil
Classification System. General Geotechnical properties of the sands are presented in Table 1.
A woven polypropylene multifilament geotextile (DF50) was used for reinforcing the sand in
the tests. Here in DF50, DF stands for Dart Felt. The individual multifilament is woven
together so as to provide dimensional stability relative to each other. The ideal container is one
that gives a seismic response of the soil model identical to that obtained in the prototype. The
boundary conditions created by the model container walls have to be considered carefully,
otherwise the field conditions cannot be simulated properly. In this study, embankment with
soft Clay soil models was constructed in a laminar box to reduce boundary effects as far aspracticable. The boundary conditions for physical modelling in problems of earthquake
geotechnical engineering have a significant influence on the test results. In order to reduce theundesirable effects of boundaries on the model responses, the laminar shear boxes are used. In
laminar shear boxes, the stiffness of the walls is proportional to the stiffness of soil. For
increasing the flexibility of the box walls, depending on soil type, model dimensions and thestudied phenomena, setting each layer on the other, within the frame made of rigid lightmaterial which can easily move on each other. The tensile strength of the geotextile wasdetermined by the wide-width strip method (ASTM D4595) as 15.5 kN/m.
Table 1. Geotechnical properties of Sylhet Sand
Physical properties

Sylhet sandCoefficient of uniformity (Cu)

2.00

Coefficient of curvature (Cc)

0.95

Effective size, D10 (mm)0.400

Average size, D50 (mm)0.7Specific gravity (Gs)

2.65
3

16.4

3

13.494

Maximum dry density (kN/m )Minimum dry density (kN/m )Relative density (Dr%)

48

Friction angle (°)

31

Void ratio

0.524

Fineness modulus (FM)2.63

USCS soil classification

SPFigure 1. Laminar box mounted on the shake table.
100
90

Percent Passing (%)

80
70
60
50
40
30
20
10
0
10

1

0.1

Sieve Size (mm)Figure 2. Particle size distribution curve of the Sylhet sand.

0.01

3.

Testing process

One of the complications with laboratory tests, especially dynamic laboratory tests, is scalemodelling. Several approaches were considered to size the model walls by different researchers
over the years. One such scaling law was proposed by Kokusho (1980) and Yu & Richart(1984) wherein a reinforcement ratio is calculated based on the properties of the geotextile andthe stresses and strains in the soil were considered for this study. Table 2 presents the scaling
factors for this study, assuming α = 0.5 (Kokusho 1980 and Yu & Richart 1984) for sand andconsidering the prototype to model scale being N = 10.
Table 2. Prototype-Model Similitude (Sabermahani et al., 2009)
Description

Parameter

Scale

Scale

factorfactor M/PScale factor
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

G

1-α

0.32

3.125

α

0.32

3.125

2-α

0.031

32.25

1-α/2

5.62

0.18

F

3

1/N

0.001

1000

F/L

2

0.01

100

α/2

0.56

1.785

1-α/2

0.178

5.62

StrainStiffness
Displacement
Frequency
Force
Force/L
Shear Wave velocity
Time

G
D
F

Vs
T

1/N

1/N
1/N
N

1/N
1/N
1/N

*P-Prototype; M-Model

This paper describes, the results from twenty-four shaking table tests on geotextile wrap faced
reinforced soil retaining wall models, where the soil wall is resting on soft clayey soil
foundations. Sinusoidal harmonic motions were applied to the model; with different surchargepressure, frequency of shaking, and base acceleration, respectively. The model embankment
was constructed in a laminar box and each geotextile wrapped sand slice had the equal heightof 100 mm. In this study, a portable traveling pluviator developed and calibrated by Hossain &Ansary (2018) at BUET, was operated to maintain the corresponding relative density of sandlayer at 48%, 64% and 80% for Sylhet sand and 27%, 41% and 55% for Local sand dependingon height of fall of the soil. We have compared Sylhet Sand (48%) and Local Sand (41%). In
this research, used 60% relative density as sample based. To achieve uniform relative density(Dr), sand was placed in the laminar box using the pluviation (raining) technique. In this study

60% relative density was maintained for construction of the all models. As indicated in Figure
3, the surcharge load was also applied to the backfill material. Surcharge pressure values weretaken as close to the study of Krishna & Latha (2007) for comparing the result. Surchargepressure height in prototype to mode scale was not considered. In this study a concrete block
was used as surcharge pressure. The height of the concrete block was constant in all threedifferent conditions but the length and width of the concrete block was varied. Accelerometers(A1, A2, A3, A4, A5 and A6) were used to monitor the accelerations of the shaking table andthe soil along with a vertical array. The LVDT transducers were employed to monitor the
displacements of the sand model wall in the horizontal direction. Two Pore water pressure
sensors were placed in the clayey soil layer to determine the excess pore pressure response. 11
data channels were used in total. In details, sensors arrangement and model configuration arepresented in Fig.3 and Fig.4.

Figure 3. Schematic diagram of typical test wall configuration and instrumentation. (All thedimensions are in mm)

Figure 4. Completed test set-up.
4.

Results and discussions

For each test, the horizontal accelerations were applied with acceleration amplitudes of 0.1g, 0.2g, 0.3g,
0.4g and 0.5g for approximately 20 cycles. Effect of surcharge on the displacements, acceleration
amplifications and pore pressure of geotextile wrap faced sand walls (WFSW) was studied through aseries of tests on model walls as shown in Table 3. The frequency has been varied from 1 Hz, 3 Hz, 5
Hz, 10 Hz, 12 Hz, and 15 Hz, respectively. 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 heightof clayey soil and reinforced sand wall together (T) had been taken as the full model height is 1060 mm.
Each shake was applied to the newly constructed individual model walls.

Table 3. Shaking table model test matrix.
Test Set

Set-1

Set-2

Test

Base

Code

Acceleration (g)

ST1

0.1

ST31

Frequency (Hz)Surcharge

Pore pressure

Load (kPa)ratio (Pr%)

1

0.71

34.86

0.1

1

1.12

22.09

ST61

0.1

1

1.72

15.13

ST2

0.1

3

0.71

33.08

ST32

0.1

3

1.12

24.16

Set-3

Set-4

Set-5

Set-6

Set-7

Set-8

4.1

ST62

0.1

3

1.72

17.19

ST4

0.1

10

0.71

30.77

ST34

0.1

10

1.12

20.11

ST64

0.1

10

1.72

18.92

ST-8

0.2

3

0.71

49.38

ST-38

0.2

3

1.12

35.16

ST-68

0.2

3

1.72

14.55

ST-15

0.3

5

0.71

97.23

ST-45

0.3

5

1.12

69.80

ST-75

0.3

5

1.72

36.96

ST-22

0.4

10

0.71

78.58

ST-52

0.4

10

1.12

50.14

ST-82

0.4

10

1.72

23.22

ST-29

0.5

12

0.71

92.20

ST-59

0.5

12

1.12

56.70

ST89

0.5

12

1.72

29.68

ST30

0.5

15

0.71

87.56

ST60

0.5

15

1.12

59.78

ST90

0.5

15

1.72

34.47

Acceleration response

Effect of surcharge on acceleration amplification was studied by subjecting the model to ahorizontal shaking for each of the eight set. Results from set 1 are presented in Fig. 5 and 6.
Results of reinforced sand wall from set 1 to 8 are presented in Fig 7.
Figure 5 represents the surcharge pressure effect both for sand and clayey layer altogether. In
Figure 5 it is observed that in clayey soil layer at elevation z/T=0.43, for 0.7 kPa, 1.12 kPa and1.72 kPa surcharge pressures (from ST1, ST31, and ST61 tests), the acceleration amplitude
was 1.05, 1.02, and 1, respectively. Whereas, at elevation z/T=0.95 in the sand layer,
amplitudes increased to 1.7, 1.55, and 1.42, for the same surcharge pressures respectively. In
clayey soil layer acceleration amplified much less than reinforced sand layer. This has been
constant in all the test result. The range of acceleration amplitude of clayey layer was in
between 0.9 to 1.05 whereas the range of acceleration amplitude of reinforced sand wall was in
between 1 to 1.92.

1

Test no.
Surcharge
ST1
0.7 kPa
ST31 1.12 kPa
ST61 1.72 kPa

Normalised Elevation, z/T

0.8

0.6

0.4

0.2

0
0

0.5

1

1.5

2

2.5

Acceleration Amplification
fig 5.grf

Figure 5. Effect of Surcharge on acceleration amplification for Set-4 configuration(both for WFSW and clayey layer).
Figure 6 represents a comparison between the present studies with the study of Krishna &Latha (2007) for the reinforced sand wall only. Acceleration response against different
surcharge pressures in the model wall was presented from tests ST1, ST31 and ST61 of set-4. It
is observed from the figure that, the acceleration amplification values at elevation z/H=0.875
were 1.7, 1.55 and 1.42 for 0.7 kPa, 1.12 kPa and, 1.72 kPa surcharge pressures respectively.
Accelerations at the top of the wall were inversely proportional to the surcharge pressures for
all the tests. This observation is in concurrence with the results of Krishna & Latha (2007).
From Figure 7(a) to 7(h) it can be seen that, at the top of the wall acceleration amplification isgreater than any other elevation in all the test sets and also inversely proportional to thesurcharge pressures only for the top of the wall at all the test sets.

1

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

Normalized Elevation, z/H

0.8

0.6

0.4

0.2

0
0

0.5

1

1.5

2

2.5

Acceleration Amplification

Figure 6. Effect of Surcharge on acceleration amplification for Set-4 configuration (onlyfor WFSW)
1

Normalized Elevation, z/H

0.8

0.6

0.4

0.2

0
0

0.5

1

1.5

Set-1
Set-1
Set-1
Set-2
Set-2
Set-2
Set-3
Set-3
Set-3
Set-4

Set-4
Set-4
Set-5
Set-5
Set-5
Set-6
Set-6
Set-6
Set-7
Set-7

2

2.5

Set-7
Set-8
Set-8
Set-8

3

Acceleration Amplification

Figure 7. Effect of Surcharge on acceleration amplification (a) Set-1; (b) Set-2; (c) Set-3; (d)Set-4; (e) Set-5; (f) Set-6; (g) Set-7 and (h) Set-8 (only for WFSW)

4.2

Face displacement response

When the retaining walls are subjected to horizontal seismic shaking, they tend to slide or
overturn. Since the thickness of facing, in this case, is sufficient to overcome the sliding
movement at the base, deformations are seen only in terms of wall movement frontward.
However, overall forward movement of the backfill and the active thrust of the backfill on thegeotextile facing cause the wall to deform more at higher elevations. The results of facedisplacement response of all 8 sets are presented in figure 8. Displacements at all elevations of
the WFSW are decreased with an increase in surcharge pressure. It is also observed that for
figure 8 (set ‘h’) the maximum displacement of the wall was occurred. The maximum
displacement of the wall is 8 mm (δh/H = 2%) at a surcharge pressure of 0.71 kPa, whereas it isdecreased to 0.2 mm (δh/H = 0.05%) at a surcharge pressure of 1.72 kPa. Since the baseacceleration and frequency of set 8 is 0.5g and 15 Hz respectively. Also, it is noticeable that
displacement occurred more at the top elevation of the wall in all the sets. There is no clear
pattern for frequency response was observed except at low frequencies as it can be seen fromfigure 8 (set ‘a’ to set ‘c’) where displacement values were close for all the surcharge pressuresrespectively.
0.9

Normalised Elevation, z/H

0.8

0.7

0.6

0.5

0.4

0.3
1.6

1.7

1.8

1.9

Set-1
Set-1
Set-1
Set-2
Set-2
Set-2
Set-3
Set-3
Set-3
Set-4

Set-4
Set-4
Set-5
Set-5
Set-5
Set-6
Set-6
Set-6
Set-7
Set-7

2

2.1

Set-7
Set-8
Set-8
Set-8

2.2

Normalised face displacement,h/H (%)

Figure 8. Effect of Surcharge on displacement profile (a) Set-1; (b) Set-2; (c) Set-3; (d) Set-4; (e)Set-5; (f) Set-6; (g) Set-7 and (h) Set-8.

Deformation in the like of overturning of the facing was observed as shown in figure 9. The
overturning mode of failure was highly noticeable after 10 Hz, 12 Hz and 15 Hz. Although thedeformation was visible enough to notice after 1 Hz, 3 Hz and 5 Hz. The maximum visible
lateral displacement had occurred at the top of the wall and the reinforced zone moved
outwards of those layers.

a)

b)

c)

d)

Figure 9. Formation of overturning mode during shaking: (a) before shaking; (b) after shaking
by 1, 3 and 5 Hz; (c) after shaking by 12 Hz; (d) after shaking by 15 Hz.
4.3

Pore pressure response

Pore pressure responses were evaluated by considering the Set-8 configuration. The height ofthe clayey soil layer (C) was 610 mm and used to normalize the elevations. Fig. 10 depicts theeffect of surcharge on pore pressure in clayey soil layer. The maximum pore water pressure
0.30 kPa was determined at z/C=0.75 for surcharge load of 0.7 kPa. At z/C=0, the minimumpore pressure (0.06 kPa) was found. The maximum pore water pressure for model tests ST30,
ST60 and ST90 were 0.30 kPa, 0.21 kPa, and 0.09 kPa, respectively at z/C=0.75.
Excess pore pressure ratio and acceleration time histories are presented in the Fig. 11 byconsidering Set-1, 4, 5, 6, and 8, respectively. Moreover, Table 3 depicts the maximum valuesof Pr% (of each one of the 24 tested cases) to show the effects of the parameters evaluated on
the pore water pressure. To more clearly depict the change of pore pressures with surchargeand elevation, the excess pore pressure ratio (Pr%) was normalized and obtained by dividing
the measured excess pore pressure by the initial vertical effective stress at each pore pressure
cell depth. Peak to peak values of horizontal pressures is also high at higher base accelerations.
The 100% pore pressure ratio indicates complete liquefaction. It can be seen from Fig. 11 that,with increasing the surcharge load, the pore pressure is decreasing, though it was increasing
elevations wise. Moreover, the elevation wise change of pore pressure is very limited, or it canbe said that very negligible. According to Bishop and Morgenstern (1960) pore pressure ratio isdefined as 𝑅𝑢 = 𝑢/𝛾z, where e u is the pore-water pressure, γ is the unit weight of the soil
and z is the depth below ground. The excess pore pressure ratio (Pr%) is increasing with theincrease of the accelerations and the maximum pore pressure ratio (about 90%) was developedfor 0.5g acceleration. The average excess pore pressure ratio (Pr%) was within the range of
40-70%.
1

Test no. Surch.
ST30 0.7kpa
ST60 1.12kpa
ST90 1.72kpa

Normalised Elevation, z/C

0.8

0.6

0.4

0.2

0
0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

pore water pressure(kpa)

Figure 10. Variations of pore water pressure with respect to Elevation for set-8 (Effect ofSurcharge).

35

20

Test no. Surch.
P1 ST8
0.7kpaP2 ST8
0.7kpaP1 ST381.12kpa
P2 ST381.12kpa
P1 ST68
1.72kpa
P2 ST68
1.72kpa

40

Excess pore pressure ratio, (Pr%)

25

Excess pore pressure ratio, (Pr%)

50

Test no. Surch.
P1 ST1
0.7kpaP2 ST1
0.7kpaP1 ST311.12kpa
P2 ST311.12kpa
P1 ST61
1.72kpa
P2 ST61
1.72kpa

30

15
10
5
0
-5
-10
-15

30
20
10
0
-10
-20
-30

-20
-40

-25

-50

-30
0

2.5

5

7.5

10

12.5

15

17.5

0

22.5

2.5

5

7.5

10

12.5

Time(s)

a)

b)

60

17.5

0
-20
-40
-60

20

22.5

Test no. Surch.
P1 ST22
0.7kpaP2 ST22
0.7kpaP1 ST52
1.12kpa
P2 ST52
1.12kpa
P1 ST82
1.72kpa
P2 ST82
1.72kpa

40

Excess pore pressure ratio, (Pr%)

20

15

60

Test no. Surch.
P1 ST15 0.7kpa
P2 ST15 0.7kpa
P1 ST45 1.12kpa
P2 ST45 1.12kpa
P1 ST75 1.72kpa
P2 ST75 1.72kpa

40

Excess pore pressure ratio, (Pr%)

20

Time(s)

20

0

-20

-40

-60

-80
-100
0

2.5

5

7.5

10

12.5

15

17.5

20

22.5

-80

25

0

Time(s)

2.5

5

7.5

10

12.5

15

17.5

20

22.5

Time(s)0.3g.grf

c)

d)
80

Test no. Surch.
P1 ST29
0.7kpaP2 ST29
0.7kpaP1 ST59
1.12kpa
P2 ST59
1.12kpa
P1 ST89
1.72kpa
P2 ST89
1.72kpa

Excess pore pressure ratio, (Pr%)

60
40
20
0
-20
-40
-60
-80
-100
0

2.5

5

7.5

10

12.5

15

17.5

20

22.5

25

Time(s)e)
Figure 11. Excess pore pressure ratio at two depths versus time curves(a) Set-1; (b) Set-4; (c)Set-5, (d) Set-6 and (e) Set-8.

530

5.

Conclusions

The main conclusions from reduced scale shaking table model tests on wrap faced geotextile
retaining walls can be summarized as follows:

Acceleration amplifications at the top of the geotextile wall were inversely proportional
to the surcharge pressures for all the tests. Acceleration amplifications are not muchaffected by the change in surcharge loads, especially at lower elevations of the wall. In
clayey soil layer acceleration amplified less than geotextile sand wall in all the tests.

 Displacements along the facing were reduced due to an increase in the surchargepressure. This phenomenon was observed at all the elevations. Maximum 2%
displacements were observed for 0.7 kpa pressure. Because of overturning mode of
failure maximum displacement occurred at the top of the wall. In the overturning mode,
the reinforced zone of facing moved outwards like a rigid block. In general, facedisplacements are high for low surcharge pressures.
Pore water pressure gets intensified with decreased surcharge pressure. Peak to peakvalues of horizontal pressures is also high at higher base accelerations. Moreover, thevariation is not significantly shown in the higher elevations. As the excess pore pressure
ratio was found below the 100%, means no complete liquefaction occurred. The
outcomes from this examination give helpful rules with respect to the relative
performance of reinforced soil under different test conditions with clear ramifications
for plan.

531

PART-XI

RECENT MAJOR FIRE/OTHER INCIDENCES
IN BANGLADESHBANGLADESH NETWORK OFFICE FOR URBANSAFETY (BNUS), BUET, DHAKA

Prepared By: Mehedi Ahmed Ansary

49 KILLED, OVER 450 INJURED IN CHITTAGONG CONTAINER DEPOTFIRE (05.06.2022)
Large explosion have killed at least 49 people and injured hundreds more at a storage depot near
the city of Chittagong, Bangladesh. Hundreds of people had arrived to tackle the fire whena number of shipping containers exploded at the site in Sitakunda. It is thought thatchemicals were stored in some of the containers. Industrial fires are common in
Bangladesh, and are often blamed on poor safety regulations.
Many of the injured are said to be in a critical condition and the number of people killed
is expected to rise. Hospitals in the area are overwhelmed, with crowds of people
waiting in hallways for treatment. Medics have appealed for blood donations and militaryclinics are helping to treat the injured.

IMAGE SOURCE,GETTY IMAGES
Image caption,
Parts of the depot were still on fire on Sunday
The fire broke out at around 21:00 local time (15:00 GMT) on Saturday and hundreds offirefighters, police and volunteers quickly arrived on the scene. As they tried toextinguish the blaze a huge explosion rocked the site, engulfing many of the rescuers inflames and throwing debris and people into the air.

"The explosion just threw me some 10 metres from where I was standing. My hands
and legs are burnt," lorry driver Tofael Ahmed told AFP news agency. Volunteers, somewearing only sandals on their feet, continued to bring bodies from the smouldering
wreckage on Sunday morning. Pictures of the aftermath show the twisted remains ofmetal shipping containers and the collapsed roof of a warehouse. A local journalist told
the BBC that there was a pungent odour in the air. At least five firefighters were killed in
the blast and several more were injured. Many people are still missing, including
journalists who were reporting on the fire before the explosion.
The blast was so large it was heard several kilometres away and shattered the windows
of nearby buildings. One local shopkeeper told reporters that a piece of debris had flown
half a kilometre and landed in his pond. He described seeing "fireballs falling like rain"
after the explosion.

IMAGE SOURCE,GETTY IMAGES
Image caption,
Bodies were still being taken from the scene on Sunday
Many people in Bangladesh are comparing the explosion to the huge blast that hit
Beirut in 2020, says the BBC's Akbar Hossain in the capital, Dhaka. He says people
have reported hearing the blast from 30-40km (19-25 miles) away.

Firefighters were still struggling to put out the fire on Sunday, with continued explosions
making it more difficult, according to fire officials. The army has deployed sandbags toprevent chemicals flowing into the Indian Ocean.
Around 4,000 containers were stored at the depot in Sitakunda, which is around 40km
(25 miles) from Chittagong - Bangladesh's main sea port and second-largest city.
Sitakunda acts as a transit point for goods travelling through the port.

IMAGE SOURCE,REUTERS
Image caption,
The storage site held around 4,000 containers
A regional government official said the depot contained millions of dollars of garments
waiting to be exported to Western retailers.
Bangladesh is a major supplier of clothing to the West and has prospered over the past
decade to become the world's second largest exporter of garments.
But safety regulations are often ignored or poorly enforced, and there have been
several large fires and other incidents at factories in recent years.

GULSHAN BUILDING FIRE: DEATH TOLL 2 (FEB 2023)

At least two people were killed trying to save themselves by jumping from a high-rise building on fire in
Dhaka’s Gulshan on Feb 23. A couple on Feb 2 was killed in an explosion inside their kitchen. The
explosion and subsequent fire were caused by gas leaking from an LPG cylinder.
The modern apartment building in Gulshan that caught fire on Sunday lacked a "fire safety plan", a fireservice probe has found.
"This is a modern building but during our primary investigation, we found that it has different types ofproblems. We are not disclosing the details for the sake of investigation," said Lt Col Mohammad Tajul
Islam Chowdhury, head of a five-member probe committee, after visiting the fire-ravaged building.
The building authorities had a no-objection certificate from the fire service during construction, but theyfailed to get the fire safety plan which is required under the Fire Prevention and Extinction Act, he added.
Fire service-approved Fire Safety Plan indicates that a building has been inspected and working fire safetymeasures are in place as per the norms and regulations.
Replying to a query, he said the two died as they jumped off the building. "We repeatedly told them not tojump. After some time, our firefighters with breathing gear entered the building and rescued trapped victims
alive," he said. Meanwhile, another person who jumped off the building to avoid the blaze died yesterday,
raising the death toll to two.

Mohammad Raju, 30, who was a cook in an apartment on the 12th floor, died around 3:30am yesterday at
a hospital in Gulshan. On Sunday night, Anwar Hossain, 32, died.
Three people are under treatment at the Sheikh Hasina National Institute of Burn and Plastic Surgery.
The fire began around 7:00pm on the sixth floor and spread up to the 12th floor. It could be brought undercontrol around 11:00pm with the efforts of firefighters who were joined at one point by the air force andarmy personnel. Firefighters rescued 22 people, including 11 women and a child, from the building on
Road-104 of Gulshan-2.

CAUSE OF FIRE?
The fire could have originated from a short circuit inside the building's lift which then spread quickly due tothe wooden décor inside the lift, Brig Gen Md Main Uddin, director general of Fire Service and Civil
Defence, told The Daily Star. He said wood had been used a lot for interior decoration in the building andthat could be a reason for the fire spreading this quickly.
Two firefighters who conducted the search operation told this newspaper that ducts from the third to the11th floors were badly burnt and those had various electrical lines. The gas line was close by too. The
ducts were next to the lift. Engineer Mahfuzul Hasan, who worked at the building during construction,
claimed that the building had a central air conditioning system which helped the fire spread.
He also claimed that the 10th floor was damaged the most and that floors 10 and 11 belonged to a garment
factory owner.
Mohammad Sajal, a caretaker of a flat, told The Daily Star that he and his colleagues first heard the fire
alarm at 6:35pm and then they called the reception. "When the smoke was rushing in, we went downstairs[from the sixth floor] with a fire extinguisher. We first saw the fire near one of the two staircases … . We
somehow managed to get down from the building. The fire spread to the whole building through the central
air conditioning system," he suspected. Visiting the spot yesterday, Dhaka North City Corporation Mayor
Atiqul Islam claimed that the building was compliant and that it followed every code stipulated by Rajuk. But
unfortunately, the residents of the building did not have training on how to respond to fires.
The mayor said the extinguishing of the fire and the rescue efforts were hampered due to the huge crowd
blocking surrounding roads.

NO FIRE STATION IN GULSHAN, BANANIThere is no fire station in Gulshan and Banani areas which sometimes causes delays in firefightersreaching those areas, fire service officials said.
However, firefighters managed to reach the spot within 10 minutes of receiving the call. The
neighbourhoods need a fire station close by as unfavourable conditions in future could delay fire service
response, they said.
Brig Gen Main Uddin said they wrote to the DNCC for space to establish fire stations in Gulshan and
Banani but did not get any response.
Mayor Atiqul said the city corporation does not have any piece of land to allocate and it was Rajuk that
allocates plots. "The fire department should write to Rajuk, not the city corporation," he said.
Fire service officials said there are 20 fire stations in Dhaka north and south city corporation areas. As there
is no fire station in Gulshan and Banani, fire engines from Bhatara respond to incidents in those areas.
During a spot visit yesterday afternoon, police were seen guarding the building. Not even caretakers andguards were allowed in.

6 DEAD, SEVERAL INJURED IN BLAST AT OXYGEN PLANT INBANGLADESH’S CHITTAGONG (5TH MARCH 2023)
The explosion shook the buildings in the nearby area within a range of two square
kilometres. Several objects were seen flying from the oxygen plant in the Chittagongarea after the massive explosion.

Chittagong Oxygen Plant Blast: At least six people were killed while 30 others were
injured in an explosion at an oxygen plant in Kadam Rasul (Keshabpur) area of
Chittagong’s Sitakunda upazila in Bangladesh on Saturday afternoon. The explosion
shook the buildings in the nearby area within a range of two square kilometres. Several
objects were seen flying from the oxygen plant in the Chittagong area after the massive
explosion.
Those killed included, 5 people who were inside the plant at the time explosion occurred
while a 65-year-old Shamshul Alam, who was sitting at his shop Kadam Rasul Bazar –about a kilometre away from the oxygen plant – died after a metal object fell on him
following the massive explosion.
According to Alam’s brother Mowlana Obaidul Mostafa, a metal object, weighing around250-300kg, fell on top of him after the explosion and he was killed on the spot.

According to the fire officials, the explosion took place around 4:30 pm. On receiving
information, nine fire tenders from Sitakunda and Kumira Fire Service were collectively
rushed to the spot. It took the personnel more than an hour to bring the fire undercontrol. The cause of the explosion is yet to be ascertained.

CHATTOGRAM, March 6, 2023 (BSS) - The Investigators believe that the blast at
Sema oxygen plant in Sitakunda might have originated in its air separation
unit. Directorate of Explosives believes that the deadly blast occurred in air separation
column at Sema Oxygen Plant under Sitkakunda upazila. The investigation team of the
district administration also feels that the explosion may have occurred from the air
separation column. The fire service says that the fire did not cause the explosion, theexplosion caused by the fire. Earlier, members of district administration investigationcommittee visited the site and collected evidence on Sunday. “The inquiry committee
suspected the blast originated in the air separation column of the oxygen plant,” said
Rakib Hossain, Additional Deputy Commissioner, also head of the investigationcommittee.
Rakib Hossain said they need to carry out more investigation to find out the actual
cause of the accident. Another investigation committee member Dr Suman Barua,

chairman of applied chemistry of Chattogram University, said the blast was caused bypressure fluctuation in the air separation plant. They apprehended that the pressure
was not released properly. Rakib Hossain said the factory engineer could not provide
proper answers to questions from the committee as he did not have a clear idea about
the technical matters related to the plant. The committee would ask the owner Mamun
Uddin for the information, he said. Six people were killed and 25 others injured as a fire
broke out at a private oxygen plant following an explosion in Kadam Rasul (Keshabpur)
area of Sitakunda upazila of the district on Saturday.

BLAST IN SCIENCE LAB AREA: BUILDING HAD NO FIRE SAFETY
SYSTEM (TUE MAR 7, 2023 04:11 AM)

Shirin Mansion, the three-storey commercial building in the capital's Science Lab area, where adeadly explosion took place on Sunday, lacked any fire safety features or other means ofpreventing a fire, said a top fire service official. The walls and roof of the building caved in andprojectiles and glass shards shot across the area after the blast on the second floor around10:50am, killing three people and injuring at. There were offices of an insurance company and astationery product supplier on the second floor.
"There was no fire safety equipment or anything that could stop a fire in the building…Thesecond floor has been so damaged that it needs to be reconstructed," said Hafizur Rahman,deputy assistant director at Bangladesh Fire Service and Civil Defence, who led the rescue
operation at the scene on Sunday.
Fire service officials said they were yet to form a probe body over the incident.
"We primarily suspect gas accumulation to be the reason behind the blast. We are investigating it
further and looking into other possible reasons," Brig Gen Md Main Uddin, director general of
the fire service, said, while talking to reporters after attending an event in Mirpur yesterday.
The bomb disposal unit of Counter Terrorism and Transnational Crime found no sign of
explosive substances but found the presence of gas at the scene.
The CTTC suspect the explosion might have originated from the office of the insurancecompany.
Meanwhile, Dhaka South City Corporation (DSCC) declared the Shirin Mansion as "risky" andput up a banner, restricting entry to the building.
FIGHTING FOR THEIR LIVES
Six injured employees of the insurance company were admitted to the Sheikh Hasina National
Institute of Burn and Plastic Surgery.
Three of them -- Zahur Ali, with 44 percent burns, Ayesha Akter Asha, with 38 percent burns,
and Akbar Ali, with 37 percent burns, -- are in critical condition, said Dr Samanta Lal Sen,coordinator of the hospital.
A Dhaka University student Nur Nabi, 23, on whom parts of the wall collapsed, is fighting forhis life at the Dhaka Medical College Hospital.
"His condition is critical. We are doing our best," Dr Asit Chandra Sarkar, chief of DMCH's
neurosurgery department, told The Daily Star, after conducting surgery on his head yesterday.
Meanwhile, shop owners of the building are worried.
"There were goods worth Tk 50 lakh inside my two shops. Ramadan and Eid are coming up fast.
The frequent college student clashes on top of the Covid pandemic have already done enoughdamage to our business. Now, this is another massive blow," said Mahabub Mollick, proprietorof two shops in the market.
Shafiqul Gani Shabu, officer-in-charge of New Market Police Station, said, "As far as we've
come to know, the owner of the building -- Shirin Chowdhury lives abroad. We have yet tocontact her."DHAKA BLAST: 19 KILLED, OVER 100 INJURED AS EXPLOSIONROCKS SEVEN-STOREY BUILDING (TUE MAR 7)
A t least 14 people were killed and over 100 others injured on Tuesday in a powerful explosion at a sevenstorey building in Bangladesh's capital Dhaka, police said. Eleven firefighting units have been mobilised at
the spot after the blast, which occurred around 4:50 pm (local time) at Old Dhaka's crowded Gulistan area,
the fire service control room said. "Fourteen bodies have been found (so far) but the toll could rise as the
rescue operation is underway," a fire service official told reporters.
The cause of the explosion could not be known immediately, but local residents suspected chemicals
illegally stored inside the building, mostly used as an office and business complex, might have sparked theblast. "At first, I thought it was an earthquake. The entire Siddik Bazar area was shaken by the blast,"
eyewitness Safayet Hossain, a local shopkeeper, told The Daily Star newspaper.
"I saw 20-25 people lying in the road in front of a damaged building. They were seriously injured andbleeding. They were crying out for help. Some people were running around in panic," he said.
He added that the locals were carrying the injured in vans and rickshaws to the hospital.

Alamgir, who was close to the blast site, said, "After the loud noise, people quickly came out of the building.
There was panic on everyone's faces. The glass of the building's windows shattered and fell onto thestreet. Many pedestrians on the street were injured."
The Rapid Action Battalion's bomb disposal unit was rushed to the spot to inspect the buildings. Dozens of
injured were taken to Dhaka Medical College Hospital, said DMCH police outpost j+spector Bacchu Miah.
He added that all of them were receiving treatment at the hospital's emergency unit. The building has
several stores for sanitary products on the bottom floor and a branch of BRAC Bank was located in thebuilding adjacent to it. The blast shattered the glass walls of the bank and also damaged a bus standing on
the opposite side of the road, reports said.

Firefighters and rescue workers search for survivors and bodies at the site of an explosion in Dhaka,Bangladesh, on March 7, 2023.
An explosion ripped through a building in a crowded area of Bangladesh’s capital on Tuesday, killingat least 19 people and injuring more than 50 others, according to authorities in the South Asian
country.
Mahid Uddin Khondekar, additional commissioner of the Dhaka Metropolitan Police, said the causeof the blast was unknown but it may have been a gas explosion.
“We are not sure, but it seems accidental,” he said, adding that the number of casualties and scaleof the damage would become clearer after firefighters and rescue workers had completed theiroperations. Not many people were inside the building at the time of the blast, but its location on abusy road near a market meant pedestrians were impacted, Dhaka Metropolitan Police said.

Firefighters and rescue workers at the site of an explosion in Dhaka, Bangladesh, on March 7.
Photos show firefighters and emergency responders carrying out search and rescue operations after
dark. The damaged building has crumbling and missing walls; some units appear to have collapsed
completely and debris covers the ground outside. Relatives of the victims are seen mourning
outside. As of Wednesday morning, 22 people remain in hospital, according to fire service official
Dinomoni Sharma.