i
PREDICTION OF ULTIMATE LOAD BEARING CAPACITY OF DRIVEN PILES
WONG CHARNG CHEN
A project report submitted in partial fulfillment
of the requirements for the award of the degree of
Master of Engineering (Civil – Geotechnic)
Faculty of Civil Engineering
Universiti Teknologi Malaysia
NOVEMBER 2006
iii
To my beloved family members
And all of my friends in UTM and KUiTTHO
iv
ACKNOWLEDGEMENTS
I would like to phrase my heartfelt gratefulness to my project supervisor,
Assoc. Prof. Dr. Aminaton Marto for her undivided attention, guidance and supports
that had been given throughout the duration of this project.
Besides, I would like to take this opportunity to thank all lecturers and staff of
UTM, my friends especially Mr. Michael Choy (Taisei Corporation), Mr. Sridar
Krishnan (Jimah Energy Venture), Mr. Selvam and Mr. Ngui Wei Chiun and to all
whom had been involved in the success of the completion of this report.
Last but not least, I would like to convey my thanks to my beloved parents
for their guidance and support throughout my studies.
v
ABSTRACT
Due to variation in soil layers, it is not easy for engineer to be assured that
theoretical design of piles comply with the actual site condition. Thus, every design
of piled foundations carries its own uncertainty and risk. This project evaluates the
applicability of eight methods to predict the ultimate bearing capacity of spun driven
friction piles. Analyses and evaluations were conducted on four piles of different
sizes and lengths that failed during pile load testing. The load test interpretation
methods, pile driving formulae, as well as the Meyerhof method (static analysis)
were used to estimate the bearing capacities (Qp) of the investigated piles. The
failure loads were the maximum measured load carrying capacities (Qm) from pile
load test. The pile capacities determined using the different methods were compared
with the measured pile capacities obtained from pile load tests. Three criteria were
selected as basis of evaluation: the best fit line for Qp versus Qm, the arithmetic mean
and standard deviation for the ratio of Qp/Qm, and the cumulative probability for
Qp/Qm. Results of the analyses show that the best performing method is Butler and
Hoy method (load test interpretation method). This method is ranked number one
according to the mentioned criteria.
vi
ABSTRAK
Adalah susah bagi seseorang jurutera untuk memastikan rekaan asas
cerucuknya secara teori adalah sama dengan keadaan di tapak disebabkan oleh
perbezaan lapisan tanah.
Oleh itu, setiap rekaan asas cerucuk mempunyai
ketidakpastian dan risiko yang tersendiri.
Projek ini dijalankan untuk menilai
kesesuaian lapan jenis kaedah menentukan keupayaan muktamad cerucuk geseran
terpacu terputar. Analisis dan penilaian telah dijalankan ke atas empat cerucuk
terputar yang berlainan saiz dan panjang dan telah gagal dalam ujian beban. Kaedah
interpretasi ujian beban, formula-formula penanaman cerucuk dan kaedah Meyerhof
(analisis statik) telah diguna untuk menentukan keupayaan muktamad (Qp) cerucuk
berkaitan. Beban gagal merupakan beban maksimum (Qm) yang telah diukur semasa
ujian beban dijalankan. Nilai yang ditentukan oleh kaedah-kaedah yang dinyatakan
telah dibandingkan dengan beban maksimum yang telah diukur dari ujian beban.
Tiga jenis kaedah penilaian telah dikenalpasti iaitu: garisan lurus terbaik untuk Qp
melawan Qm, pengiraan purata dan taburan normal piawai untuk nisbah Qp/Qm dan
kebarangkalian kumulatif untuk Qp/Qm. Keputusan analisis menunjukkan kaedah
Butler and Hoy (kaedah interpretasi ujian beban) merupakan kaedah paling baik.
Kaedah ini terletak pada tahap nombor satu mengikut kriteria yang dinyatakan.
vii
TABLE OF CONTENTS
CHAPTER
1
2
TITLE
PAGE
DECLARATION
ii
DEDICATION
iii
ACKNOWLEDGEMENT
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
xi
LIST OF FIGURES
xii
LIST OF SYMBOLS
xiv
LIST OF APPENDICES
xvi
INTRODUCTION
1
1.1
Background of the study
1
1.2
Objectives
2
1.3
Scope of study
3
1.4
Importance of study
4
LITERATURE REVIEW
5
2.1
Foundations on Problematic Soils
5
2.2
Deep Foundations
6
2.2.1 Driven Piles
7
2.2.2 Changes in Cohesive Soils
7
2.2.3
8
2.3
Changes in Granular Soils
Pile Load Testing
9
viii
2.3.1
Static Pile Load Test
11
2.3.1.1 Normal Maintained Load Test
(SM Test)
11
2.3.1.2 Quick Maintained Load Test
(QM Test)
2.4
2.5
2.3.2
Advantages of Static Load Test
12
2.3.3
Disadvantages of Static Load Test
12
Interpretation of the Results from Static Load Test
13
2.4.1
Davisson’s Method
13
2.4.2
Chin’s Method
14
2.4.3 De Beer’s Method
15
2.4.4 Brinch Hansen’s 80 Percent Criterion
16
2.4.5
Mazurkiewicz’s Method
18
2.4.6
Fuller and Hoy’s Method
18
2.4.7
Butler and Hoy’s Method
19
Analytical Analysis for Driven Piles
2.5.1
2.5.2
2.5.3
2.5.4
2.5.6
in Granular Soils
20
2.5.1.1 Meyerhof Method
20
2.5.1.2 Other Methods
22
Skin Resistance, Qs in Granular Soils
23
2.5.2.1 Meyerhof Method
23
2.5.2.2 Other Methods
23
Load Carrying Capacity at Pile Point, Qt
in Cohesive Soils (Meyerhof Method)
24
Skin Resistance, Qs in Cohesive Soils
25
27
Comparison of Static Analysis Result with
Pile Load Test Results
2.7
20
Load Carrying Capacity at Pile Point, Qt
2.5.5 Downdrag Force
2.6
11
28
Standard Penetration Test (SPT) Results for Design
29
2.6.1
Granular Soils
30
2.6.2
Cohesive Soils
31
Pile Driving Formulae
32
2.7.1
33
Janbu’s Formula
ix
2.7.2
2.8
36
2.8.1
Strength Requirement
37
2.8.1.1 Geotechnical Strength Requirements
37
2.8.1.2 Structural Strength Requirements
37
Serviceability Requirements
37
2.8.2.1 Settlement
38
2.8.2.2 Heave
39
2.8.2.3 Tilt
40
2.8.2.4 Lateral Movement
40
2.8.2.5 Durability (Corrosion)
40
METHODOLOGY
42
3.1
Introduction
42
3.2
Data Collection
42
3.3
Compilation of Data
43
3.3.1
Soil Data
44
3.3.2
SPT Data
44
3.3.3
Piling Records
44
3.3.4
Pile Load Tests Reports
44
3.4
Data Analysis
45
3.5
Comparison of the Results
45
3.6
Evaluation of Methods
46
3.6.1
Best Fit Line Equation
46
3.6.2
Cumulative Probability
47
3.6.3
Mean (µ) and Standard Deviation (σ)
of Qp/Qm
3.7
4
34
Failure in Foundation Engineering
2.8.2
3
Engineering News Record (ENR) Formula
Conclusion and Recommendation
48
49
CASE STUDY
50
4.1
Location of Study
50
4.2
Piled Foundations
52
4.3
Static Pile Load Test
53
4.4
Pile Instrumentation
53
x
5
4.5
Pile Movement Monitoring System
54
4.6
Loading Arrangement and Test Programs
55
ANALYSIS OF RESULTS
56
5.1
General Presentation
56
5.2
Characterization of the Investigated Piles
56
5.3
Failure Criteria
57
5.4
Predicted Versus Measured Pile Capacity
57
5.5
Evaluation of Methods
62
5.5.1
Best Fit Line Equation
62
5.5.2
Cumulative Probability (CP)
65
5.5.3
Mean (µ) and Standard Deviation (σ)
5.5.4
5.6
6
of Qp/Qm
70
Overall Performance
70
Discussion
70
CONCLUSION AND RECOMMENDATION
75
5.1
General
75
5.2
Conclusion
75
5.3
Recommendations
76
REFERENCES
APPENDICES
78
84-114
xi
LIST OF TABLES
TABLE NO.
TITLE
2.1
Values for earth pressure coefficient, K in granular soils
2.2
Values of soil-pile friction angle, δ φ in different types of
PAGE
24
piles
24
2.3
Summary of Briaud et al’s statistical analysis for H-piles
28
2.4
Variation of CN with γ’v
30
2.5
Variation of undrained shear strength, cu with SPT N-value 32
2.6
Value of C for different types of hammers
35
2.7
Value of ε for different types of hammers
35
2.8
Value of n for different types of hammers
36
2.9
Allowable total settlements, δa for foundation design
38
2.10
Allowable angular distortion, θa
39
4.1
Spun pile properties
52
5.1
Summary of pile failure criterion
57
5.2
Summary of piles investigated
59
5.3
Evaluation of the performance of the prediction methods
5.4
considered in this study
69
Summary of discussion
73
xii
LIST OF FIGURES
FIGURE NO.
TITLE
PAGE
2.1
Load settlement curve
10
2.2
Load-movement curve of Davisson’s Method
14
2.3
Load-movement curve of Chin’s Method
15
2.4
Load-movement curve of De Beer’s Method
16
2.5
Load-movement curve of Brinch Hansen’s 80 Percent
Criterion
17
2.6
Load-movement curve of Mazurkiewicz’s Method
19
2.7
Load-movement curve of Fuller and Hoy’s, and Butler and
Hoy’s Method
2.8
Critical embedment ratio and bearing capacity factors for
various soil friction angles
2.9
19
21
Variation of bearing capacity factor, Nq and earth pressure
coefficient, K with L/D
22
2.10
Variation of α with undrained cohesion of clay
26
2.11
Variation of λ with pile embedment length
27
3.1
Methodology flow chart
43
3.2
Best fit line
47
3.3
Cumulative probability curve
48
4.1
Site location plan
51
4.2
Site geological cross-section
51
4.3
Instrumentation details for static axial compression load tests 54
4.4
Typical static axial compression load tests setup
55
5.1
Comparison of measured and predicted pile capacity (Chin)
58
5.2
Comparison of measured and predicted pile capacity
(Brinch Hansen)
58
xiii
5.3
Comparison of measured and predicted pile capacity
(Fuller and Hoy)
5.4
Comparison of measured and predicted pile capacity
(Butler and Hoy)
5.5
60
60
Comparison of measured and predicted pile capacity
(De Beer)
60
5.6
Comparison of measured and calculated pile capacity (Janbu) 61
5.7
Comparison of measured and calculated pile capacity (ENR)
5.8
Comparison of measured and calculated pile capacity
(Meyerhof)
61
61
5.9
Predicted (Chin’s method) versus measured ultimate capacity 62
5.10
Predicted (Brinch Hansen Criterion) versus measured pile
capacity
5.11
Predicted (Fuller and Hoy’s Method) versus measured pile
capacity
5.12
63
63
Predicted (Butler and Hoy’s Method) versus measured pile
capacity
63
5.13
Predicted (De Beer’s Method) versus measured pile capacity
64
5.14
Calculated (Janbu’s Formula) versus measured pile capacity
64
5.15
Calculated (ENR’s Formula) versus measured pile capacity
64
5.16
Calculated (Meyerhof’s Method) versus measured pile
capacity
65
5.17
Cumulative probability plot for Qp/Qm (Chin’s Method)
66
5.18
Cumulative probability plot for Qp/Qm (Brinch Hansen’s
Criterion)
5.19
Cumulative probability plot for Qp/Qm (Fuller and Hoy’s
Method)
5.20
66
66
Cumulative probability plot for Qp/Qm (Butler and Hoy’s
Method)
67
5.21
Cumulative probability plot for Qp/Qm (De Beer’s Method)
67
5.22
Cumulative probability plot for QP/Qm (Janbu’s Formula)
67
5.23
Cumulative probability plot for QP/Qm (ENR’s Formula)
68
5.24
Cumulative probability plot for QP/Qm (Meyerhof’s Method)
68
xiv
LIST OF SYMBOLS
A, Ap
=
Pile cross-sectional area
cu
=
Undrained cohesion of the soil
C
=
Coefficient for different types of hammers
CN
=
Correction factor with variation of vertical overburden stress
CV
=
Coefficient of variation
D
=
Diameter/width of pile
E
=
Modulus elasticity of pile material
fav
=
Unit friction resistance at any given depth
H
=
Drop of hammer
ID
=
Identification
K
=
Earth pressure coefficient
L
=
Pile length
Lb
=
Length of pile embedded into bearing stratum
n
=
Coefficient of restitution
N
=
Average standard penetration number
Ncor
=
Corrected average standard penetration resistance values
Nq, Nc
=
Bearing capacity factor
p
=
Perimeter of pile
pa
=
Atmospheric pressure
P50
=
50 percent cumulative probability
P90
=
90 percent cumulative probability
Q, Qva
=
Applied load during pile load test
Qm
=
Maximum measured bearing capacity of pile
Qp
=
Predicted failure/ultimate load
Qs
=
Skin resistance of pile
Qt
=
Ultimate point resistance
R2
=
Coefficient of determinations
xv
∆
=
Correspond settlement of each applied load
∆u
=
Failure settlement
S
=
Final set
Sc
=
Column spacing
ue
=
Excess pore water pressure
Wp
=
Weight of pile
WR
=
Weight of the ram
γ’v
=
Vertical effective/overburden stress
φ
=
Soil friction angle
α
=
Empirical adhesion factor
λ
=
Empirical adhesion factor
η
=
Efficiency factor (Janbu formula)
ε
=
Efficiency factor (ENR formula)
δ
=
Total settlement
δφ
=
Soil-pile friction angle
δa
=
Allowable total settlement
δD
=
Differential settlement
δDa
=
Allowable differential settlement
θa
=
Allowable angular distortion
ω
=
Tilt
µ
=
Mean
σ
=
Standard deviation
xvi
LIST OF APPENDICES
APPENDIX
A1
TITLE
Summary of Average Pile Top Settlement for
Test Pile TP3C
A2
104
Bearing Capacity of Test Pile TP9 from Static
Analysis (Meyerhof Method)
D1
101
Bearing Capacity of Test Pile TP9 from Pile
Driving Formulae
C4
100
Bearing Capacity of Test Pile TP9 from Load
Test Interpretation Method
C3
97
Summary of Average Pile Top Settlement for
Test Pile TP9
C2
96
Bearing Capacity of Test Pile TP5 from Static
Analysis (Meyerhof Method)
C1
93
Bearing Capacity of Test Pile TP5 from Pile
Driving Formulae
B4
92
Bearing Capacity of Test Pile TP5 from Load
Test Interpretation Method
B3
89
Summary of Average Pile Top Settlement for
Test Pile TP5
B2
88
Bearing Capacity of Test Pile TP3C from Static
Analysis (Meyerhof Method)
B1
85
Bearing Capacity of Test Pile TP3C from Pile
Driving Formulae
A4
84
Bearing Capacity of Test Pile TP3C from Load
Test Interpretation Method
A3
PAGE
105
Summary of Average Pile Top Settlement for
Test Pile TP10
108
xvii
D2
Bearing Capacity of Test Pile TP10 from Load
Test Interpretation Method
D3
Bearing Capacity of Test Pile TP10 from Pile
Driving Formulae
D4
109
112
Bearing Capacity of Test Pile TP10 from Static
Analysis (Meyerhof Method)
113
1
CHAPTER 1
INTRODUCTION
1.1
Background of Study
Deep foundations are usually referred to as pile foundations. Pile foundations
are normally used due to some situation as follows (Henry, 1986):
(i)
When upper soil layers are weak and unable to support the structural loads.
(ii)
When underground water level is not constant.
(iii)
When upper soil layers are susceptible to large settlement.
(iv)
When the structure is subjected to lateral loads.
The principal function of a pile foundation is to transfer load to lower levels
of the ground which are capable of sustaining it with an adequate factor of safety and
without settling under normal working conditions by an amount detrimental to the
structure (Henry, 1986).
There are many different types of pile in use today, such as timber piles,
concrete piles, steel piles, composite piles and others. The choice of pile type for a
particular job depends upon the combination of all the various soil conditions and the
magnitude of the applied load; for example, timber piles are usually used in water
structure while precasted concrete piles are usually used in housing estate.
2
Current practice of pile design is based on the static analysis for example
Meyerhof Method, Vesic Method and Coyle & Castello methods.
Due to the
uncertainties associated with pile design, field tests (pile load tests) are usually
conducted to verify the design loads and to evaluate the actual response of the pile
under loading. Static pile load tests are a verification tool for pile design and they
cannot be a substitute for the engineering analysis of the pile behavior. Maintained
Load Test Method (ML Test) is considered as the standard method by Jabatan Kerja
Raya (JKR). This test however takes 2-3 days to complete. Due to the long period
of time needed to conduct ML Test, it contradicts with the current construction
industry practice which is time-saving. Hence, Dynamic Load Test (DLT) especially
Pile Driving Analyzer (PDA) is gaining popularity in construction industry.
However, ML Test should have the final say on the ultimate bearing capacity of
piles.
Due to variation in bearing stratum, it is not easy for engineer to be assured
that theoretical design of piles comply with the actual site condition. Thus, every
design of piled foundations carries certain amount of uncertainty and risk. This
report presented the effort undertaken to identify the most appropriate methods for
predicting the axial bearing capacity of piles driven to set. These methods include
static analysis, pile driving formulae, and interpretation method. The static analysis
is the Meyerhof Method. Five interpretation methods selected are Chin’s Method,
De Beer’s Method, Brinch Hansen’s 80 Percent Criterion Method, Butler and Hoy’s
Method, and Fuller and Hoy’s Method. These methods are described in detail by
Nor Azizi (2003).
1.2
Objectives
The aim of this study is to identify the most appropriate interpretation
methods to estimate the ultimate axial bearing capacity of piles. The objectives of the
study are:
3
(i)
To determine the ultimate bearing capacity of piles from illustrated full-scale
pile load tests.
(ii)
To predict and calculate the bearing capacity of pile from static analysis, pile
driving formulae, and interpretation method.
(iii)
To identify the most accurate method to predict pile bearing capacity by
comparing the predicted and calculated results with the actual results from
pile load tests.
1.3
Scope of Study
This study is only considering the carrying capacity of spun piles of different
sizes driven to set. Other pile types such as timber piles and steel pipes were not
covered in the analyses. Four sets of data were acquired from Taisei Corporation.
Their testing program was conducted in Mukim Jimah power plant on November
2005.
Square concrete piles are obsolete in this study due to different load
transferring mechanism (Hani and Murad, 1999). Only spun friction piles that tested
to failure are considered in this study.
Data acquired includes soil investigation reports, piling reports and pile load
tests reports. Soil investigation reports revealed the soil strata at the site and the
soils’ parameters, piling information and depth at which the piles set was revealed
from piling records while pile load tests reports gave the actual carrying capacity of
the piles.
This study focused on the applicability of proposed methods to predict the
ultimate axial compression load carrying capacity of piles.
Data from soil
investigation reports was used in static analysis while pile load tests data is essential
in interpretation method. Information from piling records was used in pile driving
formulae. All of the methods are described in detail in the literature review section
of this report.
The predicted capacity was compared with the actual carrying
capacity of piles from pile tests based on mentioned criteria. The method which
4
ranked number according to mentioned criteria is considered as the most accurate
method and is recommended for pile design practice.
1.4
Importance of Study
Static analysis formulae and pile driving formulae are not recommended as
the sole means of determining the acceptability of a pile, except on small jobs
(Fleming, 1985). These analyses do not describe the complex mechanics of pile
driving in rational way and interaction between pile and the surrounding soil is
poorly modeled. Thus, it is important to determine accuracy from these formulae
through comparison with actual bearing capacity from site. The differences can be
used as a guideline when pile load tests are not able to be conducted.
The problems with many of the interpretation methods are that they are either
empirical methods or are based on set deformation criteria. Several methods are also
sensitive to the shape of the load-settlement curve and it is preferable to use a
considerable number of load increment to define the shape clearly; for example,
Chin’s Method assumes the load-deformation curve is hyperbolic and is an empirical
method. An engineer may have difficulty in choosing the best method to interpret
the static load test data. This study is able to help an engineer to identify the
suitability of the proposed interpretation methods to predict the ultimate bearing
capacity of spun piles driven to set. Moreover, through the analyses, the most
appropriate method is identified.
5
CHAPTER 2
LITERATURE REVIEW
2.1
Foundations on Problematic Soils
The most common of these problematic soils are the soft, saturated clays and
silts often found near the mouths of rivers, along the perimeter of bays, and beneath
wetlands. These soils are very weak and compressible, and thus are subject to
bearing capacity and settlement problems.
These soils also frequently include
organic material in which will aggravate these problems.
Areas underlain by soft soils frequently below mean sea level, and thus are
subjected to flooding. Therefore, it is necessary to raise the ground by placing fill.
However, the weight of the fill frequently causes large settlement. For example,
Scheil (1979) described a building constructed on fill underlain by varved clay in the
Hackensack Meadowlands of New Jersey. About 250 mm of settlement occurred
during placement of the fill, 12 mm during construction of the building, and an
additional 100 mm over the following ten years.
In seismic areas, loose saturated sands can become weak through the process
of liquefaction. Moderate to strong ground shaking can create large excess pore
water pressures in these soils, which temporarily decrease the effective stress and
shear strength. Seed (1970) described the phenomenon occurred in Niigata, Japan
during 1964 earthquake.
Many buildings settled more than 1 m, and these
settlements were often accompanied by severe tilting.
6
However, engineers have developed several methods to alleviate the effects
of problematic soils which include supporting the structure on deep foundations that
penetrate through the weak soils.
2.2
Deep Foundations
Deep foundations are usually referred to as pile foundations.
Piles are
relatively long and generally slender structural foundation members that transfer load
to lower levels of the ground which are capable of sustaining it with an adequate
factor of safety and without settling under normal working conditions by an amount
detrimental to the structure. In geotechnical engineering, piles usually serve as
foundations when soil conditions are not suitable for the use of shallow foundations.
Moreover, piles have other applications in deep excavations and in slope stability
such as they can be installed to form retaining walls.
There are many types of pile in use today, with varying geometry which
depends upon imposed loading and soil conditions. Generally, piles are classified
according to the nature of load support (friction and end-bearing piles), the
displacement
properties
(full-displacement,
partial-displacement,
and
non-
displacement piles), and the composition of piles (timber, concrete, steel, and
composite piles).
The choice of pile for a particular job depends upon the
combination of all the various soil conditions and the magnitude of the applied load.
Besides its technical aspects, economical factor should also be a consideration.
The behavior of the pile depends on many different factors, including pile
characteristics, soil conditions and properties, installation method, and loading
conditions. The performance of piles affects the serviceability of the structure they
supported. In this study, only driven piles (displacement piles) are discussed.
7
2.2.1
Driven Piles
Most piles are driven into the ground by hammer or vibratory drivers. In
special circumstances, piles can also be inserted by jetting or pre-boring. In the
driving operation, a cap is attached to the top of the pile. A cushion may be used
between the pile and the cap. This cushion has the effect of reducing the impact
force and spreading it over a longer time. Pile is driven until it finds its bearing
layer. Usually, the driving is halted when the penetration is less than 25 mm per 10
blows.
Driven piles also known as displacement piles based on the nature of their
placement.
Driven piles caused some soil to move laterally; hence, there is a
tendency for the densification of soil surrounding them. Concrete piles and closedended pipe piles are high-displacement piles. However, steel H-piles displace less
soil laterally during driving, and so they are low-displacement piles.
2.2.2
Changes in Cohesive Soils by Pile Driving
Piles wobble during driving, thus creating gaps between them and the soil.
Tomlinson (1987) observed the gap extending to a depth of 8 to 16 diameters below
the ground surface. Piles subjected to applied lateral loads also can create gaps near
the ground surface. Therefore, the side friction in this zone may be unreliable,
especially in stiff clay (Coduto, 2001)
As a pile is driven into the ground, the soil below the toe must move out of
the way.
This motion causes both shear and compressive distortions.
These
distortions are greatest around large displacement piles. Cooke and Price (1973)
observed the distortion in London Clay as a result of driving a 168 mm diameter
closed-end pipe pile. The soil within radius of 1.2 pile diameters from the edge of
the pile was dragged down, while that between 1.2 and 9 diameters moved upward.
8
Besides, this remolding of the clay changes its structure and reduces its strength to a
value near its residual strength.
Pile driving also compresses the adjoining soils.
If saturated clays are
present, this compression generates excess pore water pressure.
The greatest
compression occurs near the pile toe, so the ratio of excess pore water pressure over
original vertical effective stress (ue/γ’v) in that region may be as high as 3 to 4
(Airhart et al., 1969). Poulus and Davis (1980) also suggest that ue/ γ’v may be as
high as 1.5 to 2.0 near the pile, gradually diminishing to zero at a distance of 30 to 40
pile radii.
For most clay, the excess pore water pressures that develop around a single
isolate pile completely dissipate in less than one month, with corresponding increases
in load capacity (Soderberg, 1962).
This is due to the dissipation of water,
thixotropic effect and consolidation. However, in pile groups, the excess pore water
pressures may require a year or more to dissipate.
2.2.3
Changes in Granular Soils
Soil compression from the advancing pile will generate excess pore water
pressures in loose saturated sands. However, sands have a much higher permeability
than clays, so these excess pore water pressures dissipate very rapidly. Thus, the full
pile capacity develops almost immediately.
Based on the observation by Coduto (2001), some local soil expansion can
occur when driving piles through very dense sands. This temporarily generates
negative pore water pressures that increase the shear strength and make the pile more
difficult to drive. This effect is especially evident when using hammers that cycle
rapidly.
Suggestion by Coduto to partially or wholly negate this effect is by
predrilling or jetting to install the pile.
9
2.3
Pile Load Testing
Pile load testing in Malaysia is normally based on the specification developed
by Jabatan Kerja Raya (JKR), Malaysia. Pile load test is carried out to determine the
relationship between load and settlement. It is to ensure the failure does not occur
before the ultimate design load has been reached. Pile load test also being carried
out with the purpose of determine the ultimate bearing capacity of the pile and so
define the maximum design factor of safety. Finally, pile load test can be used to
check the workmanship of any randomly selected pile is satisfactory.
The pile load test program should be considered as part of the design and
construction process, and not carried hurriedly in response to an immediate
construction problem (Fleming, 1985). Pile tests may be performed at various stages
of construction, i.e. prior to construction and during construction. A large amount of
information can be obtained from properly planned tests. This useful information
may lead to refinement of the foundation design with consequent possible cost
saving and certainly greater assurance of the satisfactory performance of the
foundation.
Three types of tests have been recommended by the JKR, namely Maintained
Load Test (ML Test), Constant Rate of Penetration Test (CRP Test) and Pile Driving
Analyzer (PDA). These tests are performed based on the JKR specification or BS
8004. The standard procedures are explained in the later part of the report.
The period of time which the test should be carried out in various soils is
mentioned by Bowles (1996). Piles in granular soil are often tested 24 to 48 hrs after
driving when load arrangements have been made. This time lapse is sufficient for
excess pore water pressure to dissipate. Pile in cohesive soils should be tested after
sufficient lapse for excess pore water pressure to dissipate.
This time lapse is
commonly in the duration of 30 to 90 days in order for cohesive soil to gain some
additional strength from thixotropic effects.
10
The failure of load test happened when either/all the following conditions are
observed at the site:
(i)
Residual settlement at design load exceeds 6.5mm;
(ii)
Residual settlement at working load exceeds 12.5mm;
(iii)
Total settlement exceeds 38mm or 10% of pile diameter or width whichever
is lower.
Residual
Settlement
Total
Settlement
Figure 2.1
Load settlement curve (Spronken, 1998)
11
2.3.1
Static Pile Load Test
2.3.1.1 Normal Maintained Load Test (SM Test)
This test method is commonly considered as the ASTM Standard Test
method and is generally used for site investigation prior to installing contract piles
and writing specifications. In this test, the pile is loaded in eight equal increments of
design load (25%, 50%, 75%, 100%, 125%, 150%, 175% and 200%) to 200% of the
design load. Each load increment is maintained until the rate of settlement has
decreased to 0.25mm/h (0.01 in/h) but no longer than 2 hours.
200% load is
maintained for 24 hours. After the required holding time, the load is removed in
decrements of 25% with one hour maintained period between decrements.
After the load has been applied and removed, as above, the pile is reloaded to
the test load in increments of 50% of the design load until two times the design load.
20 minutes are lapsed between load increments. Then the load is increased in
increments of 10% of design load until failure, allowing 20 minutes between load
increments. The main disadvantage of this test is that it is time consuming. A typical
test period may last 40 to 70 hours or more.
2.3.1.2 Quick Maintained Load Test (QM Test)
In this test method, the pile is loaded in 20 increments to 300% of the design
load (each increment is 15% of the design load). Each load is maintained for a
period of 5 minutes with reading taken every 2.5 minutes. Load increments is added
until continuous jacking is required to maintain the test load or test load has been
reached. After a 5 minutes interval, the full load is removed from the pile in four
equal decrements with 5 minutes between decrements.
This method is fast and economical. Typical time of test by this method is 3
to 5 hours. This test method represents more nearly undrained conditions. This
method cannot be used for settlement estimation because it is a quick method.
12
2.3.2
Advantages of Static Load Test
According to Han (1999), the static test is considered as the reference test
because it is the one that corresponds the most with the way that the load is applied
in reality (duration, loading rate and type of loading). The static test is generally
regarded as the definitive test against which other types of tests are compared. These
elements are obviously the best advantages of this kind of tests.
The data obtained are directly interpretable because they are linked to the
acceptance criteria (maximum settlement and authorized stiffness and/or design
load). Another reason is that the main interpretations were created with respect to
this kind of test. As such, all the other methods tried to predict response comparable
to the load settlement produced by the static load test. Finally, the measurements are
generally independent of the pile material properties.
2.3.3
Disadvantages of Static Load Test
Since the static load test is very closely related to the reality, the time needed
to carry out is relatively long (Han, 1999). This duration is costly in term of money
and contract planning.
Besides, to create the actual condition of loading slow
loading rate is imposed. The load is applied high enough to get closer to the real
load to be applied to the foundation. So the mobilization of this load and of this
associated reaction is strongly expensive regarding to the obtained result (one pile
tested).
The reaction supplied for the applied loading (kentledge, reaction piles,
ground anchors) generates some associated effects or interaction with pile that
perturb the interpretation of the results. These stresses will increase the shaft friction
and the base capacity. The pile settlement is reduced and the pile head stiffness is
also overestimated.
13
There are many procedures for static pile load testing. Due to the different
loading paths, any pile subjected to the various tests will exhibit a different loadsettlement response influencing the conclusions because the results are influenced by
loading history (steps and duration).
2.4
Interpretation of the Results from Static Load Test
The ultimate load of pile is usually not well defined. Based on Fleming
(1985), two simple criteria which can be used to define ultimate load are “the load at
which settlement continues to increase without further increase in load” and “the
load causing settlement of 10% of the pile diameter (base diameter)”. The latter limit
is likely to give a low estimate of the ultimate load as it is unlikely that general
yielding of the soil around the pile will have been initiated.
There are many methods that can be used to predict the ultimate load of piles.
The procedure of these methods is discussed at the latter part of the report.
2.4.1
Davisson’s Method
Davisson’s Method or also known as Davisson’s Criterion was introduced in
1972 (Tolosko, 1999). The procedures for obtaining predicted failure load, Qp, by
this method consist of the following steps. First, the load-movement curve is drawn.
Elastic movement, ∆ = (Qva)L / AE of the pile is obtained where Qva is the applied
load, L is pile length, A is pile cross-sectional area, and E is modulus of elasticity of
the pile material. A line OA is drawn based on the equation for elastic settlement, s,
as identified in previous step. A line BC is drawn parallel to OA at a distance x
where x = 0.15 + D/120 in, (D = diameter of pile in inch). The failure load is then at
the intersection of BC with load-movement curve (i.e., point C) (Davisson, 1972).
Figure 2.2 depicts the load-movement curve of Davisson’s method.
14
Figure 2.2
Load-movement curve of Davisson’s Method (Nor Azizi, 2003)
This method was originally recommended for the QM test method. The main
advantage of this method is that the limit line BC can be drawn before starting the
test. Therefore, it can be used as one of the acceptance criteria for proof-tested
contract pile.
Based on the study by Tolosko (1999) on 63 piles, he found out that the ratio
of Davisson’s Method and designated static analysis is in the range of 0.9 to 1.1.
According to Bachand (1997), Davisson’s Method has the advantage of deterministic
(and hence objective), while being able to consider pile properties and geometry,
hence the tip size on failure zone.
2.4.2 Chin’s Method
Chin’s Method was first introduced in 1971 (Tolosko, 1999). This method is
shown in Figure 2.3 and consists of the following steps. The ∆/Qva (settlement/load)
versus ∆ (settlement) plot is drawn, where ∆ is the settlement and Qva is the
corresponding applied load. The predicted failure load, Qp is then equal to 1/C1
15
where 1/ C1 is the gradient of the slope. The relationships given in the Figure 2.3
assume that the load movement curve is approximately hyperbolic.
Figure 2.3
Load-movement curve of Chin’s Method (Nor Azizi, 2003)
This method of ultimate load interpretation is applicable for both the QM and
SM tests, provided that the constant time increments are used during the test. In
selecting the straight line from the points, it should be understood that the data points
do not appear to fall on the straight line. This method may not provide realistic
failure for tests carried out as per ASTM Standard Method because it may not have
constant time load increments.
Tolosko (1999) conducted the comparison on predicted ultimate bearing
capacity of 63 piles with the designated bearing capacity from static analysis. The
average ratio of Chin’s Method and designated bearing capacity is 1.69.
This
indicates that Chin’s Method overpredicted the bearing capacity by more than 50
percent.
2.4.3 De Beer’s Method
De Beer’s Method or De Beer’s Log-Log Method was first introduced in
1971 (Tolosko, 1999). As seen in Figure 2.4, this method consists of the following
16
steps. Load and movement is drawn on logarithmic scales. These values then will
fall on two straight lines. The predicted failure load, Qp is then defined as the load
that falls at the intersection of these two straight lines (De Beer, 1971). This method
was originally proposed for maintained load test, such as SM and QM test.
Figure 2.4
Load-movement curve of De Beer’s Method (Nor Azizi, 2003)
Tolosko (1999) has suggested that De Beer’s Method generally
underpredicted the designated bearing capacity of piles by 0.2. Bachand (1997)
concluded that the two slopes are especially visible for piles that experienced
plunging failure, yet on piles that undergone local failure, the results may be a range
of values.
2.4.4 Brinch Hansen’s 80 Percent Criterion
In 1963, Brinch and Hansen developed a method in which failure is obtained
based on assumption that hyperbolic relationship exists between the load and the
displacement (Tolosko, 1999). This method of interpretation is shown in Figure 2.5
and consists of the following steps. The
∆
Qva
and ∆ curve is drawn, where ∆ is the
settlement and Qva is the load. Predicted failure load ,Qp and failure movement ∆u are
then given as follows:
17
Qp =
1
C1C 2
2
∆u = C2/C1
(2.1)
(2.2)
All the terms are defined in Figure 2.5. This method assumes that the loadmovement curve is approximately parabolic. The method is applicable for both QM
and SM tests. The failure criteria agree well with the plunging failure. However, the
plot and calculations could not be performed in advance of the test loading. This
method interpretation is not suitable for test methods that include unloading cycles
where plunging failure is not achieved (Nor Azizi, 2003).
Figure 2.5
Load-movement curve of Brinch Hansen’s 80 Percent Criterion (Nor
Azizi, 2003)
Tolosko (1999) conducted the comparison on predicted ultimate bearing
capacity of 63 piles with the designated bearing capacity from static analysis. The
average ratio of Brinch Hansen’s Method and designated bearing capacity is 0.99.
This indicates that this method can predict the bearing capacity near to the actual
value measured at the site.
18
2.4.5
Mazurkiewicz’s Method
Mazurkiewicz proposed his method on prediction of ultimate bearing
capacity of pile in 1972 (Spronken, 1998). As shown in Figure 2.6, this method
consists of the following steps. The load-movement curve is drawn. A series of
equal pile head movement is chosen and vertical lines that intersect on the curve is
drawn. Then horizontal line from these intersection points is drawn on curve to
intersect the load axis. From the intersection of each load, 45° line is drawn to
intersect with the next load line. These intersections will fall approximately on a
straight line. The point which is obtained by the intersection of the extension of the
line on the vertical (load) axis is predicted failure load, Qp.
This method assumes that load-movement curve is approximately parabolic.
The failure load values obtained by these method should be therefore be close to the
Brinch Hansen 80 percent criterion (Spronken, 1998).
Furthermore, all the
intersections of these lines do not always fall on straight line. Therefore, some
judgment may be required in drawing the straight line.
2.4.6 Fuller and Hoy’s Method
Fuller and Hoy’s Method or also known as single tangent method was first
proposed in 1976 (Spronken, 1998). This method consists of the following steps. A
load-movement curve is drawn as shown in Figure 2.7. The predicted failure load Qp
on the curve is determined where the tangent on the load-movement curve is sloping
at 0.1 mm/kN.
This method is applicable for QM and SM test. The main disadvantage with
this method may be that it penalizes the long piles because they will have larger
elastic movements and therefore 0.1 mm/kN slope will occur sooner (Spronken,
1998).
19
Figure 2.6
Load-movement curve of Mazurkiewicz’s Method (Nor Azizi, 2003)
Figure 2.7
Load-movement curve of Fuller and Hoy’s, and Butler and Hoy’s
Methods (Nor Azizi, 2003)
2.4.7
Butler and Hoy’s Method
Butler and Hoy’s Method or also known as double tangent method was first
proposed in 1977 (Spronken, 1998). As shown in Figure 2.7, this method consists of
the following steps. The load-movement curve is drawn. The failure load is then the
intersection of the 0.1 mm/kN slope line with either the initial straight portion of the
20
curve or the line parallel to the rebound curve or the elastic line starting from the
origin. This method is applicable for the QM and SM test.
Hani and Murad (1999) mentioned that Butler and Hoy’s Method is the
primary load test interpretation method used by Louisiana Department of
Transportation and Development (LDOTD).
They concluded that this method
generally underpredicted the bearing capacity of prestressed concrete piles based on
35 driven friction square concrete piles.
2.5
Analytical Analysis for Driven Piles
2.5.1
Load Carrying Capacity at Pile Point, Qt in Granular Soils
2.5.1.1 Meyerhof Method
Meyerhof has described an analytical method in 1976 (Das, 1999). He
recommended the following procedure for estimation of the point bearing capacity of
a pile in granular soil:
(i)
For sand, since cohesion, c is equal to zero, the equation for load carrying
capacity at pile point, Qt = Apγ’vNq where Ap is area of the pile, γ’v is
effective overburden stress and Nq is bearing capacity factor.
(ii)
Soil friction angle, φ is determined.
(iii)
The Lb/D ratio for the pile is determined in which Lb is length of pile
embedded into bearing stratum and D is the width or diameter of pile.
(iv)
(Lb/D)critical is obtained through Figure 2.8. Lb/D ratio should not exceed
(Lb/D)critical. If otherwise, (Lb/D)critical ratio will be used as design parameter.
(v)
The appropriate value of Nq corresponding to the given Lb/D ratio or
(Lb/D)critical ratio is determined from Figure 2.8.
(vi)
The Nq value calculated in Step (v) is used to obtain the Qt.
21
(vii)
The value of Qt obtained in Step (vi) should not exceed the limiting load
carrying capacity at pile point given as Ap50Nq φ .
Figure 2.8
Critical embedment ratio and bearing capacity factors for various soil
friction angles (after Meyerhof, 1976)
Based on field observations, Meyerhof (1976) also suggested that the ultimate
point resistance, Qt, in a homogeneous granular soil (L = Lb) can be obtained from
standard penetration numbers as
Qt = 40NL/D ≤ 400N
(2.3)
where N is an average standard penetration number (about 10D above and 4D below
the pile point).
22
2.5.1.2 Other Methods
Coyle and Castello (1981) have analyzed 24 large-scale field load tests of
driven piles in sand. They have shown that equation Qp = Apγ’vNq + favpL can
predict the ultimate load with an error band ± 30% with a majority falling within an
error band of ± 20%. Based on this study, Coyle and Castello correlated Nq with
embedment ratio (L/D). Figure 2.9 shows the values of Nq for various of embedment
ratios (L/D) and friction angle ( φ ) of the soil.
Figure 2.9
Variation oh bearing capacity factor, Nq and earth pressure
coefficient, K with L/D (Coyle and Castello (1981) in Nor Azizi,
2003)
23
2.5.2 Skin Resistance, Qs in Granular Soils
2.5.2.1 Meyerhof Method
The frictional or skin resistance of a pile can be written as
Qs = ∑ pLf av
(2.4)
where p is perimeter of the pile section, L is the pile length of the soil boundary and
fav is unit friction resistance at any given depth.
Meyerhof indicated that the average unit frictional resistant for driven highdisplacement piles can be obtained from corrected average standard penetration
resistance values as fav = 2Ncor. Thus,
Qs = ∑ pL 2 N cor
(2.5)
where Ncor is corrected average standard penetration resistance values of the soil
layer.
2.5.2.2 Other Methods
There are several more researchers studied on the average frictional resistance
such as Broms (1965), Aas (1966) and Meyerhof (1976). All of them agree that
average frictional resistance can be represented by Kσ’vtanδ φ where K is earth
pressure coefficient, γ’v is average effective overburden pressure and δ φ is soil-pile
friction angle. However, the values of the parameters are varies from one researcher
to another researcher.
24
Coyle and Castello (1981) correlated that earth pressure coefficient, K with
embedment ratio (L/D) and friction angle ( φ ) of the soil as shown in Figure 2.9.
This chart is designed based on assumptions that δ φ = 0.8 φ .
Broms (1965) suggested the values for K in granular soils as in Table 2.1
while Aas (1966) proposed the values of δ φ as in Table 2.2:
Table 2.1 : Values for earth pressure coefficient, K in granular soils (Broms, 1965)
Type of Pile
Loose Sand
Dense Sand
Steel
0.5
1.0
Concrete
1.0
2.0
Timber
1.5
3.0
Table 2.2 : Values of soil-pile friction angle, δ φ in different types of piles
(Aas, 1966)
Type of Pile
Soil-Pile friction angle, δ φ
Steel
20°
Concrete
0.75 φ
Timber
0.66 φ
Note : φ is the friction angle of soil
2.5.3 Load Carrying Capacity at Pile Point, Qt in Cohesive Soils (Meyerhof
Method)
The procedure for estimation of the point bearing capacity of a pile in
cohesive soil is similar as in granular soil. However, the equation for estimating load
carrying capacity at pile point, Qt = Ap(cNc + γ’vNq) where c is cohesion of the soil
supporting the pile tip and Nc is bearing capacity factor. Nc is also obtained through
Figure 2.8.
25
For piles in saturated clays in undrained condition ( φ = 0),
Qt = 9 c u A p
(2.6)
where cu is undrained cohesion of the soil below the pile tip.
2.5.4 Skin Resistance, Qs in Cohesive Soils
The equation favpL is generally accepted by most of the researchers.
However, the proposed procedure to obtain unit skin friction (fav) is different from
one researcher to another researcher.
Tomlinson (1967) suggested a method known as ‘α method’ to estimate the
skin resistance in clayey soils. According to this method, the unit skin resistance can
be represented by the equation
f = αc u
(2.7)
where α is empirical adhesion factor.
The approximate variation of the value of α is shown in Figure 2.10. For
normally consolidated clays with cu is about 50 kN/m2, α is equal to one. Thus, skin
resistance is Qs = ∑ αcu pL .
Flaate (1968), after a comprehensive analysis on a number of pile loading
tests suggested that α depended not only on the average undrained shear strength of
the clay, but also on the plasticity index.
26
Tomlinson (1971) showed that the adhesion factor is influenced by other soils
overlying the stiff London Clay. Overlying soft clay results in smaller adhesion
factors, whereas overlying granular soils give greater factors.
Figure 2.10
Variation of α with undrained cohesion of clay (Das, 1999)
Vijayvergia and Focht (1972) assumes that displacement of soil caused by
pile driving results in a passive lateral pressure at any depth, and the average unit
skin resistance can be given as
fav
= λ(γ’v + 2cu)
(2.8)
where γ’v is mean effective vertical stress for the entire embedment length, cu is the
mean undrained shear strength ( φ = 0 concept) and the value for λ can be estimated
from Figure 2.11.
27
Figure 2.11
2.5.5
Variation of λ with pile embedment length (Das, 1999)
Downdrag Force
Construction on sites underlain by soft soil often requires placement of fills to
raise the ground surface elevation to provide protection against flooding from nearby
bodies of water. The weight of these fills causes consolidation in the underlying
soils, so the fill and the soft soil move downward. Because of this downward
movement of the soil with respect to the foundations, the side friction force in the
upper zone now acts downward instead of upward and becomes a load instead of
resistance. This load is known as the downdrag load, or the negative skin friction
load. It can be very large and may cause excessive settlements in the foundation
(Bozozuk, 1981).
Downdrag force can cause differential settlement, and, in severe cases, these
loads may pull some of the piles out of their caps (Bozozuk, 1981) because of the
variations in soil properties, fill thickness, and other factors. Downdrag force is
more pronounced in the soft soils and the overlying fills. One of the method to
reduce this effect is by coating the bitumen in downdrag zone.
28
The bitumen acts like a rubber to reduce the coefficient of friction. This
method is very effective, so long as the pile is not driven through an abrasive soil,
such as sand, that might scrap off the bitumen coating.
However, this method will present another problem which is reduced the skin
friction of the pile. Hutchinson and Jensen (1968) described a reinforced concrete
test piles driven into soft silty clays at Khorramshar, failed to reach predicted pile
bearing capacity by wide margin. They made the interesting observation that the
skin friction at the pile/soil interface had been considerable weaken by the 1-2 mm
thick soft bitumen applied to the piles to protect them from acid attack. The skin
friction developed on the coated piles was only 30 to 80% of that on uncoated piles.
Thus, Engineers should investigate before any method is implemented.
2.5.6 Comparison of Static Analysis Results with Pile Load Test Results
Briaud et al. (1989) reported the results of 28 axial load tests performed by
the U.S. Army Engineering District (St. Louis) on impact-driven H-piles and pipe
piles in sand during the construction of the New Lock and Dam No. 26 on the
Mississippi River. Briaud et al. made a statistical analysis to determine the ratio of
theoretical ultimate load to measured ultimate load. The results are summarized in
Table 2.3.
Table 2.3 : Summary of Briaud et al.’s statistical analysis for H-piles (Das, 2004)
Method
Coyle and Castello
Qs
Qt
Qu
µ
σ
CV
µ
σ
CV
µ
σ
CV
2.38
1.31
0.55
0.87
0.36
0.41
1.17
0.44
0.38
1.79
1.02
0.59
0.81
0.32
0.40
0.97
0.39
0.40
4.37
2.76
0.63
0.92
0.43
0.46
1.68
0.76
0.45
(1981)
Briaud and Tucker
(1984)
Meyerhof (1976)
Note : µ is mean, σ is standard deviation, and CV is coefficient of variation
29
A perfect prediction would have a mean of 1.0, a standard deviation of 0, and
a coefficient of variation of 0. Based on the results, there is no method that gave a
perfect prediction. The most accurate method is Briaud and Tucker method. In
general, load carrying capacity at pile point, Qt was overpredicted and skin
resistance, Qs was underpredicted. This shows the uncertainty in predicting the
bearing capacity of piles.
Meyerhof (1976) also provided the results of several field load tests on long
piles (L/D ≥ 10), from which the derived values of Qt were calculated. He concluded
from the results that for a given friction angle, φ the magnitude of Qt can deviate
substantially from that given in the static analysis method. Again, this shows the
uncertainty in predicting the bearing capacity of piles.
2.6
Standard Penetration Test (SPT) Results for Design
Besides obtaining soil samples, standard penetration tests provide several
useful correlations.
Although the correlations are approximate, with correct
interpretation the standard penetration test provides a good evaluation of soil
properties (Das, 1999).
The current practice in using the N-value for design is to use an average Nvalue but in the zone of majoring stress. For pile foundations, there may be merit in
the simple average of blow count N for any stratum unless it is very thick. It is more
accurate better to subdivide the thick stratum into several strata and average the N
count for each division (Ramli, 2005). Average corrected N-value can be computed
and then averaged. The average N-value is correlated with empirical formula to
obtain the soil parameters and finally the bearing capacity.
30
2.6.1 Granular Soils
Kovac and Salomone (1982) found that the energy impact to the sampler
range about 30 to 80% while Riggs (1983) obtained energy input from 70 to 100%.
Therefore, the raw SPT data need to be improved by applying certain correction
factors.
In granular soils, the N-value is affected by the effective overburden pressure,
γ’v. For that reason, the N-value obtained from field exploration under different
effective overburden pressure should be changed to correspond to a standard value of
γ’v. Peck, Hanson and Thornburn (1974) have recommended the following method
for correcting the standard penetration numbers obtained from the field:
Ncor
= 0.77 N log
20
0.0105γ ' v
(for γ’v ≥ 23.9 kN/m2)
(2.9)
where Ncor is corrected N-value to a maximum value of γ’v = 95.6 kN/m2, N is Nvalue obtained from the field and γ’v is effective overburden pressure in kN/m2. For
γ’v ≤ 23.9 kN/m2, they suggested
Ncor
= CNNcor
(2.10)
where CN is a correction factor, the variation of which with γ’v is given in Table 2.4.
Table 2.4 : Variation of CN with γ’v (Das, 1999)
γ’v (kN/m2)
CN
0
2
6
1.8
15
1.6
31
There is a weakness in this method in which the overburden stress is not
allowed to be greater than 95.6 kN/m2. Therefore, some other researchers have come
out with other formula.
9.78
Liao and Whitman (1986) recommended that CN =
1
2
while Skempton (1986) porposed CN =
.
γ 'v
1 + 0.01γ , v
For granular soils, the corrected N-value can be used to estimate the effective
friction angle of the soil, φ ’. Wolff (1989), based on research by Peck, Hanson and
Thornburn in 1974 has produced an empirical formula to correlate friction angle with
Ncor. The formula is shown as:
2
φ = 27.1 + 0.3 N cor − 0.00054 N cor
(2.11)
Kulhawy and Mayne (1990), based on the work by Schmertmann in 1975 has
approximate an empirical formula to estimate the friction angle:
⎡
⎢
Nf
φ = tan −1 ⎢
γ 'v
⎢
⎢12.2 + 20.3 p
a
⎣
⎤
⎥
⎥
⎥
⎥
⎦
where pa is the atmospheric pressure in the same unit as γ’v.
(2.12)
More recently,
Hatanaka and Uchida (1996) suggested φ = 20 N cor + 20 .
2.6.2
Cohesive Soils
Based on Code of Practice for Site Investigation (BS 5930), an approximation
can be made between stiffness and undrained shear strength, cu as shown in Table
2.5.
32
Table 2.5 : Variation of undrained shear strength, cu with SPT N-value (BS 5930)
SPT N-value
Consistency
Undrained shear
strength, cu (kN/m2)
Less than 4
Very soft
Less than 20
4-10
Soft
20-40
10-30
Firm
40-75
30-50
Stiff
75-150
More than 50
Very stiff
More than 150
Besides BS 5930, Stroud (1974) based on the results of undrained triaxial test
suggested that cu = KN where K is a constant in the range of 3.5 – 6.5 kN/m2. Stroud
found that the average value for K is about 4.4 kN/m2. Hara et al. (1971) also
suggested that cu = 29N0.72.
2.7
Pile Driving Formulae
Many attempts have been made to determine the relationship between the
dynamic resistance of pile during driving and the static load-carrying capacity of the
pile. These intended relationships are called pile driving formulae and have been
established empirically or theoretically. According to Simon nad Menzies (2000).
Much discussion has been generated, for example, ASCE (1951), Chellis (1941),
Cummings (1940), and Greulich (1941). Conflicting opinions have been expressed.
The relationship between dynamic and static resistance of pile should be
independent of time if the formula is to have any validity (Simons and Menzies,
2000). This is clearly not the case with clays and, therefore, pile driving formulae
should not, in general, be applied to cohesive soils, but only to granular soils, that is,
sands and gravel.
Simons and Menzies (2000) suggest that the Janbu formula and the Hiley
formula are convenient to use and give reasonable predictions of the ultimate bearing
33
capacity of driven piles in granular soils. Das (1986) also suggested Engineering
News Record (ENR) formula besides above mentioned formulae. His reason is that
ENR formula which was introduced during nineteenth century has gone through
several revisions over the years and is acceptable for prediction of the ultimate load.
Das also suggested a factor of safety (FOS) of 4 - 6 should be recommended to
estimate the allowable load. However, McCarthy (1998) has different opinion. He
suggested that the use of ENR formula should be discouraged because it does not
have application for existing pile driving methods.
A detailed investigation into the validity of pile driving formulae in granular
soils by Flaate (1964) suggests that there is little to choose between the Hiley and
Janbu Formulae. In order to obtain a minimum factor of safety of 1.75 for any pile,
Flaate showed that it is necessary to use FOS = 2.7 with Hiley formula and FOS =
3.0 for Janbu Formula. Flaate also found out that Janbu formula gave a slightly
better correlation between tested and calculated bearing capacity and also the lowest
arithmetic mean value of the factor of safety.
2.7.1
Janbu’s Formula
Janbu’s Formula was first introduced in 1953 (Das, 1999). The ultimate
bearing capacity can be calculated based on the following formula:
Qp
=
ηW R H
Ku S
(2.13)
where Qp is calculated ultimate bearing capacity, WR is weight of the ram, H is drop
of hammer, and S is final set (penetration / blow) while Ku is determined by the
following formulae:
34
Ku
Cd
0.5
⎡ ⎛ λe
⎤
⎞
= C d ⎢1 + ⎜1 +
⎟ ⎥
C
d ⎠
⎣ ⎝
⎦
= 0.75 + 0.15
λe
=
Wp
WR
ηW R HL
Ap E p S 2
(2.14)
(2.15)
(2.16)
where Cd and λe are constant, L is length of pile, Ap is cross-sectional area of pile, Ep
is modulus elasticity of pile material, and Wp is weight of pile.
The efficiency factor, η, is dependent on the pile driving equipment, the
driving procedure adopted, the type of pile, and the ground conditions. Values of η
can be chosen as follows:
η = 0.70 for good driving conditions
η = 0.55 for average driving conditions
η = 0.40 for difficult or bad conditions
A factor of safety of 4 to 5 is generally recommended for this formula.
2.7.2 Engineering News Record (ENR) Formula
ENR formula is derived on the basis of the work-energy theory. This means
that energy imparted by the hammer per blow is the summation of pile resistance
times penetration per hammer blow (Das, 1999).
35
The original ENR Formula has been revised for several times due to its
irrational prediction on ultimate bearing capacity. The Michigan State Highway
Commission (1965) undertook a study to obtain a rational pile-driving equation. At
three diverse sites, a total of 88 piles were driven. Based on these results, a modified
ENR had been adopted. According to the revised ENR formula (Das, 1999), the pile
resistance is the calculated ultimate load, Qp and can be expressed as:
Qp
=
εW R H W R + n 2W P
S +C
x
(2.17)
WR + W p
where ε is hammer efficiency, WR is weight of the ram, H is drop of hammer, Wp is
weight of pile, S is final set (penetration / blow), C is a constant and n is coefficient
of restitution between the ram and the pile cap.
The values of C recommended are shown in Table 2.6 while the efficiencies
of various pile driving hammers, ε, are given in Table 2.7.
Table 2.6 : Value of C for different types of hammers (Das, 1999)
For drop hammers:
C = 2.54 cm (if the units of S and H are in centimeters)
C = 1 in (if the units of S and H are in inches)
For steam hammers:
C = 0.254 cm (if the units of S and H are in centimeters)
C = 0.1 in (if the units of S and H are in inches)
Table 2.7: Value of ε for different types of hammers (Das, 1999)
Hammer Type
Efficiency, ε
Single and double-acting hammers
0.7 to 0.85
Diesel hammers
0.8 to 0.9
Drop hammers
0.7 to 0.9
36
Representative values of the coefficient of restitution, n, are given in Table
2.8.
Table 2.8 : Value of n for different types of hammers (Das, 1999)
Hammer Type
Coefficient of Restitution, n
Cast iron hammer and concrete piles
0.4 to 0.5
Wood Cushion on steel piles
0.3 to 0.4
Wooden piles
0.25 to 0.3
A factor of safety 4 to 6 is generally recommended for the Modified ENR
Formula.
2.8
Failure in Foundation Engineering
Many people think it is a failure when foundation is incapable of supporting
the necessary loads and fail catastrophically.
This “it’s either black or white”
perspective is easy to comprehend but it is not correct.
Leonard (1982) defined failure as “an unacceptable difference between
expected and observed performance.” For example, an expected settlement for a
building is not more than 25 mm when loaded. If the actual, settlement is 27 mm, an
engineer will probably not consider it is a failure because the different between
observed and predicted is small and within design factor of safety. However, if the
actual settlement is 50 mm, it would probably classify as failure.
Coduto (2001) explains that the foundation should not only based on strength
requirements but also the serviceability requirements. The following sections will
discuss on these requirements.
37
2.8.1
Strength Requirement
2.8.1.1 Geotechnical Strength Requirements
Geotechnical strength requirements are those that address the ability of the
soil or rock to accept the loads imparted by the foundation without failing. The
strength of soil is governed by its capacity to sustain shear stresses. In other words,
if the shear strength of the soils is greater than the shear stresses, then the foundation
is safe. Geotechnical strength analyses are almost always performed using allowable
stress design (ASD) methods.
2.8.1.2 Structural Strength Requirements
Structural strength requirements address the foundation’s structural integrity
and its ability to safely carry the applied loads. For example, pile foundations made
from steel are designed to carry certain amount of load. Thus, the thickness of the
steel should be chosen such that the stresses induced should not exceed the allowable
value.
Foundations that are loaded beyond their structural capability will, in
principle, fail catastrophically.
Structural strength analyses are almost always
performed using allowable stress design (ASD) methods.
2.8.2
Serviceability Requirements
Foundation that satisfies strength requirements will not collapse, but they still
may not have adequate performance. For example, they may experience excessive
settlement. Therefore, there are second performance requirements, which are known
as serviceability requirements.
38
2.8.2.1 Settlement
Most foundation experienced some downward movement as a result of the
applied loads. This movement is called settlement.
Keeping settlements within
tolerable limits is usually the most important foundation serviceability requirement.
Total settlement, δ, is the change in foundation elevation from the original
unloaded position to the final loaded position. Structure that experience excessive
total settlements might have some problems in connections with existing structure,
utility lines, surface drainage, access and aesthetics. Table 2.8 presents typical
design values for the allowable total settlement, δa. These values already include a
factor of safety, and thus may be compared directly to the predicted settlement. The
design meets total settlement requirements if the following condition is met:
δ ≤ δa
(2.18)
where δ is total settlement of foundation.
Table 2.9 : Allowable total settlements, δa for foundation design (Coduto, 2001)
Type of structure
Allowable total settlement, δa (mm)
Office building & house
12 – 50 (25 is the common value)
Heavy industrial building
25 – 75
Bridges
50
The differential settlement, δD, is the difference in total settlement between
two foundations or between two points on a single foundation.
Differential
settlements are generally more troublesome than total settlements because they
distort the structure. This causes cracking in walls and other members, jamming in
the doors and windows, and other problems. If allowed to progress to an extreme,
differential settlements could threaten the integrity of the structure.
39
Table 2.10 presents synthesis of Skempton and MacDonald (1956), Polshin
and Tokar (1957), and Grant et al (1974), expressed in terms of the allowable
angular distortion, θa. These values already include a factor of safety of at least 1.5.
The allowable differential settlement, δDa is computed as follows:
δDa = θaSc
(2.19)
where Sc is column spacing (horizontal distance between columns).
Table 2.10 : Allowable angular distortion, θa (Coduto, 2001)
Type of structure
Allowable angular
distortion, θa
Steel tanks
1/25
Bridges with simply-supported spans
1/125
Bridges with continuous spans
1/250
Buildings that are very tolerant of differential settlements,
such as industrial buildings with corrugated steel siding and 1/250
no sensitive interior finishes
Typical commercial and residential buildings
1/500
Overhead traveling crane rails
1/500
Buildings that are especially intolerant of differential
settlement, such as those with sensitive wall or floor finishes 1/1000
Machinery
1/1500
Buildings with unreinforced masonry load-bearing walls
~ Length/height ≤ 3
1/2500
~ Length/height ≥ 5
1/1250
2.8.2.2 Heave
Sometimes foundations move upward instead of downward. This kind of
movement is called heave. It may be due to applied upward loads, but more often it
is the result of external forces, especially those from expansive soils. The design
40
criteria for heave are the same as those for settlement. However, if some foundations
are heaving while others are settling, then the differential is the sum of two.
2.8.2.3 Tilt
Excessive tilt is often a concern in tall, rigid structures.
To preserve
aesthetics, the tilt, ω from the vertical should not more than 1/500 (Tower of Pisa has
tilt of about 1/10). Greater tilts would be noticeable, especially in taller structures
and those that are near other structures (Coduto, 2001).
2.8.2.4 Lateral Movement
Foundations subjected to lateral loads have corresponding lateral movements.
These movements also have tolerable limits.
For bridge foundations, Bozozuk
(1978) recommended maximum lateral movements of 25 mm.
2.8.2.5 Durability (Corrosion)
Studies of waterfront structures have found that steel is lost at rate of 0.075 to
0.175 mm/yr (Whitaker, 1976). This corrosion occurs most rapidly in the tidal and
splash zones and can also be very extensive immediately above the sea floor. It
becomes almost negligible at depths of more than about 0.5 m below the sea floor.
Such structures may also prone to abrasion from moving sand, ships, floating debris,
and other sources. It is common to protect such foundations with coatings or jackets.
The situation in land environments is quite different.
Romanoff (1970)
observed that no structural failures have been attributed to corrosion of steel piles.
The explanation is that the natural soils contain very little oxygen and other
ingredients for the corrosion process. One of the most likely places for corrosion on
land piles is immediately below concrete pile cap. This is caused by local electric
currents that develop. Concrete will act as cathode and soil as an anode.
41
However, piles penetrates through fill may be subjected to corrosion as fills
do contain sufficient free oxygen. Tomlinson (1987) found out that steel is lost at
rate up to 0.8 mm/yr.
42
CHAPTER 3
METHODOLOGY
3.1
Introduction
This chapter will discuss on methodology used of this study as shown in
Figure 3.1. The methodology used in this study includes data collection, compilation
of data, data analysis, comparison of the results, evaluation of methods, and finally
conclusion and recommendation. The methodology used is essential in order to
achieve the study’s aim which is to identify the most appropriate interpretation
methods to estimate the ultimate axial bearing capacity of piles.
3.2
Data Collection
The collected data include soil investigation reports, piling records, and pile
load test records. Data was acquired from Taisei Corporation. They conducted their
tests in Mukim Jimah Power Plant on November 2005. Spun piles of different sizes
driven to set were considered in this study.
43
Data Collection
Compilation of Data
a)
b)
c)
d)
soil data
SPT data
piling records
pile tests data
Data Analysis- Prediction of Pile Capacities
Load Test
Interpretation Method
Pile Driving Formulae
Static Analysis
Comparison- Actual Versus Predicted Pile Capacities
Evaluation of Methods
Best Fit Line
Arithmetic
Calculations
Cumulative Probability
Conclusion
Figure 3.1
3.3
Methodology flow chart
Compilation of Data
The information from the data collected was compiled. The information and
data regarding the project, soil stratification and properties, pile characteristics, load
test data, SPT profiles, etc. were processed and transferred from each load test report
to tables, forms, and graphs.
44
3.3.1
Soil Data
The soil data consists of information on the soil boring location (station
number), soil stratigraphy and other information.
From soil stratification, the
predominant soil type was qualitatively identified (cohesive or cohesionless). The
importance of this identification is addressed in the analysis section.
3.3.2
SPT Data
The standard penetration soundings information includes test location (station
number), date, soil description and lithology, water level, N value and the depth the
test halted.
3.3.3
Piling Records
Piling records consist of pile characteristics (pile identification, material type,
cross-section, total length, embedded length), and installation data (location of the
pile, date of driving, driving record, hammer type, etc.).
3.3.4
Pile Load Tests Reports
Pile load test report consist of date of loading, applied load with time, pile
head movement, pile failure under testing, and etc.
45
3.4
Data Analysis
Data collected was first analyzed by Meyerhof method. Information was
extracted from soil investigation reports (soil description and lithology, water level,
N value, and etc) and piling records (depth at which pile driven to set). This
information was useful to determine the soil parameters. From the soil parameters,
the skin resistance, end bearing resistance and finally the ultimate load of the piles
were able to be calculated by Meyerhof method.
The data collected was then analyzed using interpretation methods.
Information from pile load test reports (applied load and pile head movement) were
used. In this study, since the proof test used is slow and quick maintained pile load
test, the Chin, Butler and Hoy, Fuller and Hoy, De Beer, and Brinch Hansen method
were chosen because these are the methods applicable for both maintained load tests.
The analyzing process was carried out based on the steps recommended by the
respective methods.
Information was extracted from piling records (pile identification, material
type, cross-section, total length, embedded length), and installation data (date of
driving, driving record, hammer type, penetration of set, etc.).
The extracted
information was then substituted into the equation of proposed pile driving formulae.
The end product is the predicted ultimate load carrying capacity of pile by the
respective formula.
3.5
Comparison of the Results
This section presents an evaluation of the ability of the proposed methods to
predict the ultimate load carrying capacity of spun piles driven to set. The
performance of the different methods was evaluated based on criterion that is
evaluation of the predicted and measured pile capacity. The analyses were conducted
46
only on friction piles that failed (plunged or showed large settlement) under load
testing.
3.6
Evaluation of Methods
In this study, an evaluation scheme using three different criteria was
considered in order to rank the performance of different methods for predicting the
ultimate axial capacity of piles. These criteria are:
(i)
R1 - the equation of the best fit line of predicted versus measured capacity
(Qp/Qm) with the corresponding coefficient of determinations (R2);
(ii)
R2 – Qp/Qm at 50 and 90 percent cumulative probability (P50 and P90);
(iii)
R3 – mean (µ) and standard deviation (σ) calculations of Qp/Qm
3.6.1
Best Fit Line Equation
For each prediction method, analysis was conducted to obtain the best fit line
for the predicted/measured pile capacities (Figure 3.2). The relationship Qp/Qm and
the corresponding coefficient of determination (R2) were determined for each
method. In this criterion, the method is better when Qp/Qm is closer to unity. If there
are two or more methods that produced the same answer, the method with R2 closer
to one will be considered as the better method.
47
Figure 3.2
3.6.2
Best fit line (Hani and Murad, 1999)
Cumulative Probability
Long et al. (1999) used the cumulative probability (CP) value to quantify the
ability of different methods to predict the measured pile capacity. The concept is to
sort the ratio Qp/Qm for each method in an ascending order. The smallest Qp/Qm is
given number i = 1 and the largest is given i = n where n is the number of piles
considered in the analysis. The cumulative probability value for each Qp/Qm is given
by:
CPi =
i
n +1
(3.1)
The cumulative probability curves were used to determine the 50 percent and
90 percent cumulative probability values (P50 and P90) (Figure 3.3). The pile capacity
prediction method with P50 value closer to unity and with lower P50 – P90 range is
considered the best. P50 is considered as the average value of Qp/Qm while P50 – P90
is considered as the value examining the consistency of the data.
48
Figure 3.3
Cumulative probability curve (Hani and Murad, 1999)
3.6.3 Mean (µ) and Standard Deviation (σ) of Qp/Qm
The ratio of predicted to measured ultimate pile capacity (Qp/Qm) was the
main variable considered in the analyses. This ratio (Qp/Qm) ranges from 0 to α with
an optimum value of one. The methods underpredicts the measured capacity when
Qp/Qm < 1 and it overpredicts the measured capacity when Qp/Qm > 1. The mean and
standard deviation of Qp/Qm are indicators of the accuracy and precision of the
prediction method. An accurate and precise method gives mean (Qp/Qm) = 1 and
standard deviations (Qp/Qm) = 0, respectively, which means that for each pile, the
predicted pile capacity equals to the measured one. This case is ideal, however, in
reality the method is better when mean (Qp/Qm) is closer to one and standard
deviation (Qp/Qm) is closer to 0.
In order to calculate the mean (µ) and standard deviation (σ) of Qp/Qm, the
following equations are used (Long et al., 1999):
49
⎛ Qp
⎝ Qm
µ ⎜⎜
σ
Qp
Qm
=
⎞ 1 n ⎛ Qp
⎟⎟ = ∑ ⎜⎜
⎠ n i =1 ⎝ Qm
⎞
⎟⎟
⎠
⎞
1 n ⎛ Qp
⎜⎜
− µ ⎟⎟
∑
n − 1 i =1 ⎝ Qm
⎠
(3.2)
2
(3.3)
where n is number of piles being considered.
3.7
Conclusion and Recommendation
The method with the lowest rank index is considered as the most accurate
method and recommended for pile design practice. Recommendations regarding the
proposed methods and further improvement for the study were also included in this
section.
50
CHAPTER 4
CASE STUDY
4.1
Location of Study
The site of this study is located at Mukim Jimah. Mukim Jimah is located
east of the mouth of the Sepang River and off the Kuala Lukut shoreline in the state
of Negeri Sembilan in west peninsular Malaysia. It lies at an elevation of between 0
m and 5 m below the Malaysian Land Survey Datum (MLSD, approximate Mean
Sea Level).
Reference to the geological map of the site and its surroundings
(Geological Survey Malaysia, 1985) shows that the site is underlain by very soft to
soft clays, organic soils and very loose to loose sands presumably deposited during
the Pleistocene and Holocene Epochs of the Quaternary Period. The solid geology of
the site consists of meta-sedimentary rocks (Phyllite, Schist, Slate and Sandstone) of
the Devonian Period (Krishnan and Lee, 2006).
Based on description above, it is clear that the site is seated on the
problematic soils where bearing capacity and settlement problems are expected.
Besides, the site lies below mean sea level, and thus is subjected to flooding.
Therefore, fill materials are necessary to raise the level before any works can
commence.
51
Figure 4.1
Site location plan (Krishnan and Lee, 2006)
Figure 4.2
Site geological cross-section (Krishnan and Lee, 2006)
52
4.2
Piled Foundations
Piles are chosen to support the structure to be built.
Before actual
installation, comprehensive pile testing program was implemented to determine the
load-displacement relationship and the suitability of installation method. Only four
of the test piles are taken into account as the other piles are not in the scope this
study. These piles are TP3C, TP5, TP9, and TP10. All of the mentioned piles are
spun pile.
In the site, the spun piles were driven by 11 tonne BSP hydraulic hammer
(pile no. TP3C) and 9 tonne Junttan hydraulic hammer (pile no. TP5, TP9, and
TP10). Pre-boring was also carried out on upper 12 m of piles TP3C and TP5. Table
4.1 summarized the properties of the mentioned piles.
Table 4.1 : Spun pile properties (Krishnan and Lee, 2006)
Pile No.
Nominal Diameter
Wall
Pile Length
Prestresing
(mm)
Thickness
(m)
Bar
(mm)
(D = 9mm)
TP3C
600
100
38.9
14 no.
TP5
500
90
38.1
10 no.
TP9
400
80
41.7
8 no.
TP10
400
80
17.5
8 no.
Construction on Mukim Jimah sites requires placement of fills to raise the
ground surface elevation to provide protection against flooding from nearby bodies
of water. However, placement of fills presents another problem – negative skin
friction load or downdrag load. This load may cause excessive settlements in the
foundation (Bozozuk, 1981). Therefore, engineers had coated the pile with bitumen
at downdrag zone in order to alleviate or neglect the downdrag force.
53
4.3
Static Pile Load Test
Two types of static pile load test had been conducted on the site. They are
normal maintained load test and quick maintained load test. Normal maintained load
tests were conducted on three piles in the site (TP3C, TP5 and TP9) while quick
maintained load test was conducted on TP10. The detail procedures for these tests
had been elaborated in Sections 2.3.1.1 and 2.3.1.2 respectively.
4.4
Pile Instrumentation
For the instrumented test spun piles (TP3C, TP5 and TP9), pile
instrumentation was conducted using Vibrating Wire (VW) Extensometers
monitoring system for determining axial loads and movements at various levels
down the pile shaft including the pile base level using Global Strain Extensometer
(GloStrExt) Instrumentation method (Mukim Jimah Site Report, 2005).
VW GloStrExt Strain Gauges were installed at seven designated levels while
VW Extensometers were installed at eight designated anchored intervals (housed in
the hollow internal diameter of test pile). The instrumentation details are illustrated
in Figure 4.3.
During static load testing, the load intrigued pile deformation resulted in
relative movement between each and every two anchored intervals. The relative
movement causing changes in strain gauge wire tension and corresponding change in
its resonant frequency of vibration. To measure the resonant frequency, Glostrext
strain gauge wire was plucked using electromagnetic coil connected through a signal
cable to data logger, which also measures the frequency and displays the shortening
reading and strain reading. The strain reading is essential for calculation of stress
value at each anchor level.
54
Figure 4.3
Instrumentation details for static axial compression load tests
(Krishnan and Lee, 2006)
4.5
Pile Movement Monitoring System
The pile top settlement was monitored using two different instruments,
survey precise level instrument (Figure 4.4) and Linear Vertical Displacement
Transducers (LVDT).
In the first instrument, pile top was affixed with vertical scale rule and
sighted by a survey precise level instrument with the use of TP3B and TP4 as
temporary benchmark reference for correction purposes. JKR specification
mentioned that the apparatus should be placed on the stable ground and six meters
from the reaction system.
Four LVDTs were mounted to reference beams, with plunger pressing
vertically against glass plates fixed to pile top. Vertical scales were also provided on
reference beams to monitor frame movement during load testing for correction
purposes.
55
4.6
Loading Arrangement and Test Programs
As mentioned in Section 4.2, normal and quick maintained load tests were
conducted on the test piles. The tests were conducted using kentledge reaction
system (Figure 4.4). In this method, kentledge was placed onto a test frame and cribs
which rest upon the ground.
In the setup, a hydraulic jack was used to provide the load by acting against
the main beam. The hydraulic jack was operated by electric pump. Calibrated VW
Load Cell was used to indicate the applied load. The load cell was placed between
the jack and the kentledge framework and a pressure gauge linked to the hydraulic
pump.
Besides manual precise level survey level, all other instruments were logged
automatic using Micro-10x Datalogger and Multilogger software, at 2 minutes
interval during loading and unloading steps. All the instruments were calibrated
before were used in the test programs.
Figure 4.4
Typical static axial compression load tests setup (Krishnan and Lee,
2006)
56
CHAPTER 5
ANALYSIS OF RESULTS
5.1
General Presentation
This section presents an evaluation of the ability of the investigated methods
to predict the ultimate load carrying capacity of spun piles driven into Mukim Jimah
soils. The performance of the different methods was evaluated based on criteria that
include evaluation of the predicted/measured pile capacity and cumulative
probability. Each method was given a rank based on its performance according to
the selected criterion. The final rank of each method was obtained by adding the
ranks of all criteria.
5.2
Characterization of the Investigated Piles
Four spun piles were considered in the current study. However, the analyses
were conducted on the piles that were failed during the pile load test. A summary of
the characteristics of the investigated pile is presented in Table 5.2. All the piles are
friction piles based on the data given.
57
5.3
Failure Criteria
The failure criteria are based on JKR specification as mentioned in Section
2.3. Based on the mentioned criteria, Table 5.1 summarizes the failure condition of
the test piles.
Table 5.1 : Summary of pile failure criterion
Pile No.
TP3C
Diameter
600 mm
Failure Criterion
Total settlement exceeds 38mm (actual settlement is
40.70 mm)
TP5
500 mm
Total settlement exceeds 38mm (actual settlement is
41.12 mm)
TP9
400 mm
Total settlement exceeds 38mm (actual settlement is
46.66 mm)
TP10
400 mm
Residual settlement exceeds 12.5 mm (residual settlement
is 17.52 mm)
5.4
Predicted Versus Measured Pile Capacity
Table 5.2 summarizes the results of the analyses conducted on the
investigated piles. Among the data presented in Table 5.2 are: the pile size, type,
length, the measured ultimate load carrying capacity, and the predicted ultimate
bearing capacity. The graphs and calculations to predict ultimate bearing capacities
are given in Appendix A, B, C and D.
The predicted ultimate bearing capacity (Qp) is the sum of pile tip capacity
(Qt) and pile shaft resistance (Qs). The pile capacities Qt, Qs, and Qp predicted by the
interpretation methods, pile driving formulae, and Meyerhof method are compared
with Qm in Figures 5.1 to 5.8. Based on the graph, it is observed that prediction of
pile ultimate bearing capacities by Fuller and Hoy’s, and Butler and Hoys method are
58
near to the exact bearing capacities measured at the site whereas the other six
methods showed deviation from the measured bearing capacitites.
14000
Capacity (kN)
12000
10000
8000
Actual
6000
Predicted
4000
2000
0
TP3C
TP5
TP9
TP10
Pile Number
Comparison of measured and predicted pile capacity (Chin)
Figure 5.1
7000
Capacity (kN)
6000
5000
4000
Actual
3000
Predicted
2000
1000
0
TP3C
TP5
TP9
TP10
Pile Number
Figure 5.2
Comparison of measured and predicted pile capacity (Brinch Hansen)
59
Table 5.2 : Summary of piles investigated
Pile No.
TP3C
TP5
TP9
TP10
Pile ID
600 mm diameter
500 mm diameter
400 mm diameter
400 mm diameter
Pile and Soil
Pile Classification
Friction
Friction
Friction
Friction
Identification
Predominant Soil*
Cohesive
Cohesionless
Cohesionless
Cohesionless
Pile Length (m)
42
48
48
18
Types of Load Test
Normal
Normal
Normal
Quick
Working Load (kN)
2200
1700
1150
100
Actual Ultimate Load (kN)
Qs
Qt
Qu
Qs
Qt
Qu
Qs
Qt
Qu
Qs
Qt
Qu
5116
1457
6573
4053
1051
5104
2692
671
3363
-
-
442
Predicted Ultimate Load (kN)
Qs
Qt
Qu
Qs
Qt
Qu
Qs
Qt
Qu
Qs
Qt
Qu
Chin
-
-
12500
-
-
8333
-
-
5582
-
-
524
Load Test
Brinch Hansen
-
-
2760
-
-
2532
-
-
2051
-
-
360
Interpretation
Fuller and Hoy
-
-
6600
-
-
5400
-
-
3300
-
-
420
Method
Butler and Hoy
-
-
6400
-
-
5200
-
-
3200
-
-
390
De Beer
-
-
4300
-
-
3000
-
-
2100
-
-
230
Pile Driving
Janbu
-
-
3787
-
-
2682
-
-
1545
-
-
350
Formulae
ENR
-
-
2392
-
-
1875
-
-
1078
-
-
272
Static
Meyerhof
1258
2566
3824
352
376
728
607
1917
2524
71
101
172
Measured Field Results
Analysis
*Cohesive (mainly clayey and silty clay soils) and cohesionless (mainly sandy soils): Qs: Pile skin resistance; Qt: Pile tip capacity; Qu: Total
ultimate capacity (Qs + Qt)
60
7000
Capacity (kN)
6000
5000
4000
Actual
3000
Predicted
2000
1000
0
TP3C
TP5
TP9
TP10
Pile Number
Comparison of measured and predicted pile capacity (Fuller and Hoy)
Figure 5.3
7000
Capacity (kN)
6000
5000
4000
Actual
3000
Predicted
2000
1000
0
TP3C
TP5
TP9
TP10
Pile Number
Comparison of measured and predicted pile capacity (Butler and Hoy)
Figure 5.4
7000
Capacity (kN)
6000
5000
4000
Actual
3000
Predicted
2000
1000
0
TP3C
TP5
TP9
TP10
Pile Number
Figure 5.5
Comparison of measured and predicted pile capacity (De Beer)
61
7000
Capacity (kN)
6000
5000
4000
Actual
3000
Calculated
2000
1000
0
TP3C
TP5
TP9
TP10
Pile Number
Comparison of measured and calculated pile capacity (Janbu)
Figure 5.6
7000
Capacity (kN)
6000
5000
4000
Actual
3000
Calculated
2000
1000
0
T3C
TP5
TP9
TP10
Pile Number
Comparison of measured and calculated pile capacity (ENR)
Figure 5.7
7000
Capacity (kN)
6000
5000
4000
Actual
3000
Calculated
2000
1000
0
TP3C
TP5
TP9
TP
Pile Number
Figure 5.8
Comparison of measured and calculated pile capacity (Meyerhof)
62
5.5
Evaluation of Methods
A rank index (RI) is introduced in this study to quantify the overall
performance of all methods. The rank index is the sum of the ranks from the different
criteria, RI= R1+R2+R3. These evaluation methods are explained in Section 3.6.
5.5.1 Best Fit Line Equation
Figures 5.9 to 5.16 show the best fit equation and coefficient of determination
of each method. The summary of the results for each method and their ranks in this
P re d ic t e d P ile C a p a c it y , Q p (k N )
criterion is shown in Table 5.3.
14000
12000
QP= 1.7793 Qm
10000
R2 =0.98
Perfect fit
8000
6000
4000
2000
0
0
2000
4000
6000
8000
10000
12000
Meausred Pile Capacity, Qm (kN)
Figure 5.9
Predicted (Chin’s Method) versus measured pile capacity
14000
63
Predicted Pile Capacity, Qp (kN)
7000
6000
5000
Perfect fit
4000
3000
2000
Qp = 0.4721 Qm
R 2 =0.90
1000
0
0
1000
2000
3000
4000
5000
6000
7000
Meausred Pile Capacity, Qm (kN)
Figure 5.10
Predicted (Brinch Hansen Criterion) versus measured pile capacity
Predicted Pile Capacity, Qp (kN)
7000
6000
5000
Perfect fit
4000
3000
2000
Qp = 1.0182 Qm
R2 =0.99
1000
0
0
1000
2000
3000
4000
5000
6000
7000
Meausred Pile Capacity, Qm (kN)
Figure 5.11
Predicted (Fuller and Hoy’s Method) versus measured pile capacity
Predicted Pile Capacity, Qp (kN)
7000
6000
5000
Perfect fit
4000
3000
2000
Qp = 0.9849 Qm
R2 =0.99
1000
0
0
1000
2000
3000
4000
5000
6000
7000
Meausred Pile Capacity, Qm (kN)
Figure 5.12
Predicted (Butler and Hoy’s Method) versus measured pile capacity
64
Predicted Pile Capacity, Qp (kN)
7000
6000
5000
Perfect fit
4000
3000
2000
Qp = 0.6283 Qm
R 2 =0.99
1000
0
0
1000
2000
3000
4000
5000
6000
7000
Meausred Pile Capacity, Qm (kN)
Calculated Pile Capacity, Qp
(kN)
Figure 5.13
Predicted (De Beer’s Method) versus measured pile capacity
7000
6000
5000
Perfect fit
4000
3000
2000
Qp = 0.5061 Qm
1000
R 2 =0.92
0
0
1000
2000
3000
4000
5000
6000
7000
Meausred Pile Capacity, Qm (kN)
Calculated Pile Capacity, Qp
(kN)
Figure 5.14
Calculated (Janbu’s Formula) versus measured pile capacity
7000
6000
5000
Perfect fit
4000
3000
2000
Qp = 0.3596 Qm
1000
R 2 =0.99
0
0
1000
2000
3000
4000
5000
6000
7000
Meausred Pile Capacity, Qm (kN)
Figure 5.15
Calculated (ENR’s Formula) versus measured pile capacity
65
Calculated Pile Capacity, Qp (kN)
7000
6000
5000
Perfect fit
4000
3000
2000
Qp = 0.4633Qm
R 2 =0.62
1000
0
0
1000
2000
3000
4000
5000
6000
7000
Meausred Pile Capacity, Qm (kN)
Figure 5.16
Calculated (Meyerhof’s Method) versus measured pile capacity
Inspection of Figures 5.9 to 5.16 (Qp/Qm plots) shows that Butler and Hoy
method has best fit equation Qp = 0.9849Qm with R2 = 0.99. This method tends to
underpredict the measured pile capacity by an average of 1 percent. Therefore,
Butler and Hoy method ranks number one according to this criterion and is given R1
= 1 (R1 is the rank based on this criterion). The Fuller and Hoy method with Qp =
1.0182Qm (R2 = 0.99) tends to overpredict the measured capacity by 2 percents and
therefore ranks number 2 (R1 = 2). According to this criterion, Brinch Hansen, De
Beer, Janbu, ENR, and Meyerhof methods tend to underpredict the measured
ultimate pile capacity, while Chin method tends to overpredict the measured ultimate
pile capacity. The Chin method showed the inaccurate performance with Qp =
1.7793Qm (R2 = 0.98) and therefore was given R1= 8.
5.5.2 Cumulative Probability (CP)
Figures 5.17 to 5.24 show the values of P50 and P90 of each method. The
summary of the results for each method and their ranks in this criterion is shown in
Table 5.3.
66
2.5
2.10
2
Qp/Qm
1.65
1.5
1
0.5
0
0
20
40
60
80
100
Cumulative probabiity (%)
Cumulative probability plot for Qp/Qm (Chin’s Method)
Qp/Qm
Figure 5.17
0.97
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0.55
0
20
40
60
80
100
Cumulative probabiity (%)
Cumulative probability plot for Qp/Qm (Brinch Hansen’s Criterion)
Figure 5.18
1.2
1.12
1
1.00
Qp/Qm
0.8
0.6
0.4
0.2
0
0
20
40
60
80
1 00
Cumulative probabiity (%)
Figure 5.19
Cumulative probability plot for Qp/Qm (Fuller and Hoy’s Method)
67
1.2
1.08
1
0.96
Qp/Qm
0.8
0.6
0.4
0.2
0
0
20
40
60
80
100
Cumulative probabiity (%)
Cumulative probability plot for Qp/Qm (Butler and Hoy’s Method)
Qp/Qm
Figure 5.20
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0.68
0.62
0
20
40
60
80
100
Cumulative probabiity (%)
Cumulative probability plot for Qp/Qm (De Beer’s Method)
Qp/Qm
Figure 5.21
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0.92
0.51
0
20
40
60
80
Cumulative probabiity (%)
Figure 5.22
Cumulative probability plot for QP/Qm (Janbu’s Formula)
100
Qp/Qm
68
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0.75
0.36
0
20
40
60
80
1 00
Cumulative probabiity (%)
Cumulative probability plot for QP/Qm (ENR’s Formula)
Qp/Qm
Figure 5.23
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0.83
0.50
0
20
40
60
80
1 00
Cumulative probabiity (%)
Figure 5.24
Cumulative probability plot for QP/Qm (Meyerhof’s Method)
The cumulative probability curves (Figures 5.17 to 5.24) were used to
determine the 50 percent and 90 percent cumulative probability values (P50 and P90).
The pile capacity prediction method with P50 value closer to one and with lower P50 P90 range is considered the best. Based on this criterion, the Butler and Hoy method
with P50 = 0.96 and P90 = 1.28 ranks number one (R3 = 1) followed by de Fuller and
Hoy with R3 = 2. The Chin method has highest P50 and P90 values and therefore
ranks number eight.
69
Table 5.3 : Evaluation of the performance of the prediction methods considered in this study
Pile Capacity
Prediction Methods
Best fit calculations
QP/Qm
R2
Chin
1.7793
Brinch Hansen
Arithmetic calculations
µ
Σ
0.98
Rank,
R1
8
1.595
0.4721
0.90
5
Fuller and Hoy
1.0182
0.99
Butler and Hoy
0.9849
De Beer
Cumulative probability
calculations
P50
P90
0.0861
Rank,
R2
8
1.65
0.590
0.0317
5
2
0.998
0.0022
0.99
1
0.955
0.6283
0.99
3
Janbu
0.5061
0.92
ENR
0.3596
Meyerhof
0.4633
2
Rank of the methods based on
their performance
Rank Index,
RI
24
Rank
2.10
Rank,
R3
8
0.55
0.97
6
16
5
1
1.00
1.12
2
5
2
0.0034
2
0.96
1.08
1
4
1
0.598
0.0035
3
0.62
0.68
3
9
3
4
0.560
0.0286
4
0.51
0.92
5
13
4
0.99
7
0.418
0.0187
6
0.36
0.75
7
20
7
0.62
6
0.465
0.0502
7
0.50
0.83
4
17
6
R
= Coefficient of determination
µ
= Mean
σ
= Standard deviation
RI
= R1 + R2 + R3
8
70
5.5.3
Mean (µ) and Standard Deviation (σ) of Qp/Qm
The summary of the results for each method and their ranks in this criterion is
shown in Table 5.3. In this criterion, the arithmetic mean (µ) and standard deviation
(σ) of the ratio Qp/Qm values for each method were calculated. The best method is
the one that gives a mean value closer to one with a lower standard deviation, which
is the measure of scatter in the data around the mean. According to this criterion,
Fuller and Hoy method with µ = 0.998 and σ = 0.0022 ranks number one (R2 = 1)
followed by the Butler and Hoy method (R2 = 2). Brinch Hansen, De Beer, Janbu,
ENR, and Meyerhof methods have µ < 1, which means that these methods on
average are underpredicting the measured pile capacity. On the other hand, Chin
method has µ > 1, which means that these methods on average are underpredicting
the measured pile capacity.
5.5.4
Overall Performance
In order to evaluate the overall performance of the different prediction
methods, all criteria were considered in a form of an index. The Rank Index (RI) is
the algebraic sum of the ranks obtained using the three criteria. Considering Butler
and Hoy method, the RI equals to four as evaluated from RI = R1 + R2 + R3 + R4.
The Rank Index values for all other methods are presented in Table 5.3. Inspection of
Table 5.3 demonstrates that Butler and Hoy method ranks number one. This method
showed the best performance according to the evaluation criteria and therefore
considered the best methods. The Fuller and Hoy method ranks number two. The
Chin method showed the worst performance as it ranks number eight.
5.6 Discussion
The results of this study demonstrated the capability of the mentioned
methods in predicting the ultimate load carrying capacity of spun piles driven into
Mukim Jimah soils. Butler and Hoy method methods showed the best performance
71
in predicting the ultimate measured load carrying capacity of spun piles. It is strongly
recommended that this method is implemented in design and analysis of spun piles.
Although Butler and Hoy, and Fuller and Hoy showed accuracy in predicting
the ultimate load carrying capacity of spun piles, it is recommended that a factor
should be introduced due to uncertainties and variations in soil profiles. The factor
recommended is 1.1 as Fuller and Hoy’s method overpredicted the ultimate bearing
capacity by 2 percent. Besides, one should be careful in determine the 0.1 mm/kN
slope on load-movement curve as it is not clearly defined especially in longer piles.
It is recommended that the same personnel should be responsible in determining the
tangent when these two methods are implemented as the judgment will be consistent.
De Beer method defined the ultimate load falls at the intersection of the two
straight lines. However, not all the intersections of these lines are clearly defined.
Therefore, some judgment may be required in determine these intersections. It is
recommended that the same personnel should be responsible in determining the
intersection point as the judgment will be consistent. This method may be used as
supplementary method when the load is more than 1000 kN (accuracy is around
60%).
Brinch Hansen’s 80 percent criterion is not suitable for test methods that
include unloading cycles or where plunging failure is not achieved. The result of this
study support the statement as the performance of this method is average (accuracy
of 60%). Therefore, this method is not recommended for load tests that include
unloading cycles. However, it can be used as an additional method when the load is
not more than 1000 kN as the accuracy is relatively higher (83%) than the average
accuracy.
Chin method shows least competency in predicting the ultimate load of spun
piles driven into Mukim Jimah soils. Part of the reason is that the load tests carried
out in the site did not have constant time load increments. As a result, it affected the
accuracy of this method as Chin method is understood dependant on the time load
72
increments. Hence, it is not recommended for load tests that have different time load
increment. However, the suitability of this method for load tests which have constant
time load increments is subjected to further study. A factor of 2 is recommended as
Chin’s method overpredicted the ultimate bearing capacity by 78 percent.
Among the two pile driving formulae evaluated in this study, Janbu formula
shows better accuracy than ENR formula. However, both showed low accuracy with
accuracy less than 55%. The sources of this problem may include the followings:
(i)
The pile, hammer, and soil types used to generate the formula may not be the
same as those at site where it is being used. This is probably one of the major
reasons for the inaccuracies in ENR Formula.
(ii)
The hammers do not always operate at their rated efficiencies.
(iii)
The energy absorption properties of cushions can vary significantly.
(iv)
The formulae do not account for flexibility in the pile.
(v)
There is no simple relationship between the static and dynamic strength of
soils.
Because of these difficulties, there is little need to continue using pile driving
formulae unless there are some correction in these formulae. For recommendation,
the formula may be modified to suit the condition of the site or at least the particular
area. Besides, the coefficient of efficiencies for Janbu and ENR formula should be
restudied as the equipments which are used today are certainly more efficient.
Finally, the formulae should include some parameters on pile flexibility and
relationship between static and dynamic strength of soils. However, pile driving
formulae may be used for initial design as it gives engineer some idea on the pile
bearing capacity.
Based on the data, the piles are considered as friction piles.
However,
calculations based on Meyerhof method suggested that the piles are end bearing
piles. Meyerhof method overpredicted the end bearing of piles but on the other hand,
underpredicted the skin resistance. These differences were down to the soil
73
parameters used in the design procedure. As mentioned, these soil parameters were
obtained from empirical formulae based on average SPT N-values. These empirical
formulae may not be suitable for Mukim Jimah soils as the parameters are irrelevant.
Laboratory tests should be conducted to obtain the actual soil parameters or at least
proven empirical formulae in Malaysian soils should be implemented. Meyerhof
method with the soil parameters based on the average N-value may only be used as
the preliminary design. This method is found to underpredict the ultimate load.
Table 5.4 summarized the results of discussion and comments.
Table 5.4 : Summary of discussion
Methods
Chin
Qp/Qm
1.78
Comments
~least accurate due to the fact that the data did not
have constant time load increment.
~factor of 2 is recommended.
Brinch Hansen
0.47
~underpredicted the bearing capacity (conservative).
~part of the reason is that this method is not suitable
for the load tests that have unloading cycle.
~showed better accuracy when the load is lower (less
than 1000 kN).
Fuller and Hoy
1.02
~accurate but slightly overpredicted the bearing
capacity.
~factor of 1.1 is recommended
~judgment needed to determine 0.1 mm/kN slope at
load-deformation curve.
Butler and Hoy
0.99
~most accurate.
~recommended for design procedure in Mukim Jimah
~judgement needed to determine 0.1 mm/kN slope at
load-deformation curve.
De Beer
0.63
~ underpredicted the bearing capacity (conservative).
~ judgement needed to determine the intersections of
the two straight lines.
~showed better accuracy when the load is greater
(more than 1000 kN)
74
Janbu
0.51
~ underpredicted the bearing capacity (conservative).
~showed better accuracy than ENR formula.
~not recommended for design procedure unless pile
load test is unable to be conducted.
ENR
0.36
~ underpredicted the bearing capacity (conservative).
~not recommended for design procedure unless pile
load test is unable to be conducted.
Meyerhof
0.46
~ underpredicted the bearing capacity (conservative).
~contradict with the field result in term of type of
pile.
~not recommended for design procedure detailed
laboratory tests are not conducted.
75
CHAPTER 6
CONCLUSION AND RECOMMENDATION
5.1
General
This study presented an evaluation of the performance of eight methods in
predicting the ultimate load carrying capacity of spun piles driven into Mukim Jimah
Power Plant.
Four pile load test reports, which have soil investigation report
adjacent to the test pile, were collected from Taisei Corporation. Prediction of pile
capacity was performed on four friction piles that failed during the pile load test.
5.2
Conclusion
(i)
Based on the results of this study, Butler and Hoy method shows the best
capability in predicting the measured load carrying capacity of spun piles.
Fuller and Hoy method also shows competency in predicting the ultimate
load carrying capacity of piles. Other methods such as De Beer, Brinch
Hansen showed an average accuracy in predicting the ultimate carrying
capacity of spun piles. Chin method is found to be the least suitable in
predicting ultimate load carrying capacity.
(ii)
It is concluded that six out of eight methods considered in the study
underpredicted bearing capacity of spun piles. These methods are Butler and
Hoy, Brinch Hansen, De Beer, Meyerhof, Janbu, and ENR method. Except
76
for Butler and Hoy method, the other five methods tend to underpredict the
ultimate load in the range of forty to sixty percent. Butler and Hoy method
underpredicts the ultimate load by one percent.
The two methods that
overpredict the ultimate carrying capacity of piles are Fuller and Hoy and
Chin method. The margin of error by Fuller and Hoy is small (around two
percent).
However, Chin method overpredicted almost two times the
measured ultimate load.
(iii)
Fuller and Hoy, Butler and Hoy and De Beer method show its consistency in
predicting the ultimate bearing capacity of the spun piles. It is shown in
standard deviation (σ) column as all of these methods have σ less than 0.004.
Meyerhof and Chin method shows less consistency in predicting the ultimate
load as σ for meyerhof method is 0.05 while the standard deviation for Chin
method is 0.09.
(iv)
Butler and Hoy method is the recommended method for pile design practice
as it is precise and consistent in predicting the spun piles capabilities
5.3
Recommendation
Some recommendations for further studies are listed as follows:
(i)
At least 10 data are needed for this type of study. This is essential for
cumulative probability calculations (CP) as CP at ninety percent is needed for
analysis. For the current study, the value of CP ninety percent is based on
interpolation.
(ii)
For further studies, driven square precasted concrete piles and bored piles
may be included. End bearing piles may be useful for improvement of this
study.
(iii)
Other load test interpretation methods such as Davisson’s, Brinch Hnasen
90% Criterion and Mazurkiewicz Methods may be included in the discussion.
(iv)
Pile driving formula used by various companies in the industry such as
Pilecon and Hiley’s formulae may be included for further discussion.
77
(v)
Other static analysis formulae such as Vesic, and Coyle and Castello may be
included for further investigation.
(vi)
Detail laboratory tests reports should be included for further studies.
(vii)
Other evaluation methods such as histogram and log normal probability
distribution may be included to further evaluation of the methods.
78
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84
Appendix A1
Summary of Average Pile Top Settlement for Test Pile TP3C
85
Appendix A2
Bearing Capacity of Test Pile TP3C from Load Test Interpretation Method
Chin's Method
0.008
Settlement/Load (mm/kN)
0.007
y = 0.00008x + 0.00367
0.006
0.005
0.004
0.003
0.002
0.001
0
0
5
10
15
20
25
30
35
40
45
Settlement (mm)
Ultimate Load (Qu) = 1/0.00008 = 12500 kN
Brinch Hansen's 80% Criterion
Settlement^0.5/Load (mm^0.5/kN)
0.003
0.002
y = -0.00002x + 0.00169
0.001
0
0
10
20
30
40
Settlement (mm)
Ultimate Load (Qu) = 0.5/√(0.00002x0.00169) = 2720 kN
50
86
Fuller and Hoy's Method
Qp
7000
6000
Load (kN)
5000
4000
3000
2000
1000
0
0
10
20
30
40
50
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 6600 kN.
Butler and Hoy's Method
Qp
7000
6000
Load (kN)
5000
4000
3000
2000
1000
0
0
10
20
30
40
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 6400 kN.
50
87
De Beer's Method
10000
Load (kN)
Qp
1000
100
1
10
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 4300 kN.
100
88
Appendix A3
Bearing Capacity of Test Pile TP3C from Pile Driving Formulae
Weight of ram, WR
= 107.91 kN
Weight of Pile, Wp
= 165.47 kN
Area of pile, Ap
= 0.16708 m2
Young modulus of pile, Ep
= 43.25 x 106 kN/m2
Drop of hammer, H
= 1.2 m
Penetration of pile per, S
= 0.0012 m
hammer blow
Efficiency, η (Janbu)
= 0.70 (good driving condition)
Efficiency, ε (ENR)
= 0.9 (assuming the efficiency is maximum)
Restitution factor, n
= 0.5 (assuming the restitution is maximum)
Constant, C
= 0.0254 m
Janbu Formula
Janbu formula, Qp
=
ηW R H
Ku S
= 3787 kN
where Ku
0.5
⎡ ⎛ λe
⎤
⎞
= C d ⎢1 + ⎜1 +
⎟ ⎥
C
d ⎠
⎣ ⎝
⎦
Cd
= 0.75 + 0.15
λe
=
Wp
WR
ηWR HL
=
εWR H WR + n 2WP
S +C
= 0.98
= 366
Ap E p S 2
Engineer News Record (ENR) Formula
ENR formula, Qp
= 19.9
x
= 2392 kN
WR + W p
89
Appendix A4
Bearing Capacity of Test Pile TP3C from Static Analysis (Meyerhof Method)
0 – 9.0 m
Loose sand, average unit weight, γavg = 16.5 kN/m2
Navg = 3
9.0 m – 25.8 m
Soft clay, average unit weight, γavg = 17.5 kN/m2
Navg = 4
Cu = 20 kN/m2
25.8 m – 38.7 m
Medium dense sand, average unit weight, γavg = 18.75 kN/m2
Navg = 17
38.7 m – 42.0 m
Very dense sand, average unit weight, γavg = 18.75 kN/m2
Navg = 176
For Loose Sand
Based on result from TP9, Navg is 3.
Effective overburden stress, γ’v
= (16.5 – 9.81) x 9
= 60.2 kN/m2
90
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
20
0.0105γ 'v
= 3.5
Based on Meyerhof (1976)
Skin resistance, qs1
= 2NcorpL
= 2 x 3.5 x 0.6π x 9
= 119 kN
For Soft Clay
Skin resistance, qs
= αcupL
From Figure 2.15, α = 1.0
Thus, qs2
= 1.0 x 20 x 0.6π x 16.8
= 633 kN
For Medium Dense Sand
Effective overburden stress, γ’v
= (16.5 – 9.81) x 9.0 + (17.5 – 9.81) x 16.8
+ (18.75 – 9.81) x 12.9
= 304.7 kN/m2
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
20
0.0105γ 'v
= 10.4
Based on Meyerhof (1976)
Skin resistance, qs3
= 2NcorpL
= 2 x 10.4 x 0.6π x 6.8
= 506 kN
Total skin resistance, Qs = qs1 + qs2 + qs3 = 1258 kN
91
For Hard Layer
Effective overburden stress, γ’v
= 304.7 + ( 20.5 – 9.81) x 3.3
= 340 kN/m2
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
20
0.0105γ 'v
= 89
Based on Wolff (1989)
2
φ = 27.1 + 0.3N cor − 0.00054 N cor
= 52° > 45°. Assume friction angle is 45°.
The depth of penetration in bearing stratum, Lb is 0.2.
Thus, Lb / D = 0.3 and is less than (Lb / D)critical. The value for (Lb / D)critical is around
24 (from Figure 2.8). Take (Lb / D).
From Figure 2.8, bearing capacity factor, Nq is around 240.
Ultimate point load, Qtu
= Ap γ’v Nq
= 0.16708 x 340 x 240
= 13634 kN
However, limiting point load, Qtl
= Ap50Nqtan φ
= 0.16708 x 50 x 240 x tan 52°
= 2566 kN
Since Qtl < Qtu, the point bearing capacity, Qt is 2566 kN.
Thus, the bearing capacity of pile, Qp = Qt + Qs
= 2566 + 1258
= 3824 kN
92
Appendix B1
Summary of Average Pile Top Settlement for Test Pile TP5
93
Appendix B2
Bearing Capacity of Test Pile TP5 from Load Test Interpretation Method
Chin's Method
0.01
Settlement/Load(mm/kN)
0.009
y = 0.00012x + 0.00385
0.008
0.007
0.006
0.005
0.004
0.003
0.002
0.001
0
0
10
20
30
40
50
Settlement (mm)
Ultimate Load (Qu) = 1/0.00012 = 8333 kN
Brinch Hansen's 80% Criterion
0.003
0.002
y = -0.00002x + 0.00195
0.5
0.5
Settlement^ /Load (mm^ /kN)
0.004
0.001
0
0
10
20
30
40
Settlement (mm)
Ultimate Load (Qu) = 0.5/√(0.00002x0.00195) = 2532 kN
50
94
Fuller and Hoy's Method
Qp
6000
Load (kN)
5000
4000
3000
2000
1000
0
0
10
20
30
40
50
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 5400 kN.
Butler and Hoy's Method
Qp
6000
Load (kN)
5000
4000
3000
2000
1000
0
0
10
20
30
40
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 5200 kN.
50
95
De Beer's Method
10000
Load (kN)
Qp
1000
100
1
10
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 3000 kN.
100
96
Appendix B3
Bearing Capacity of Test Pile TP5 from Pile Driving Formulae
Weight of ram, WR
= 88.29 kN
Weight of Pile, Wp
= 131.21 kN
Area of pile, Ap
= 0.115925 m2
Young modulus of pile, Ep
= 43.25 x 106 kN/m2
Drop of hammer, H
= 1.1 m
Penetration of pile per, S
= 0.00024 m
hammer blow
Efficiency, η (Janbu)
= 0.70 (good driving condition)
Efficiency, ε (ENR)
= 0.9 (assuming the efficiency is maximum)
Restitution factor, n
= 0.5 (assuming the restitution is maximum)
Constant, C
= 0.0254 m
Janbu Formula
Janbu formula, Qp
=
ηW R H
Ku S
= 2682 kN
where Ku
0.5
⎡ ⎛ λe
⎤
⎞
= C d ⎢1 + ⎜1 +
⎟ ⎥
C
d ⎠
⎣ ⎝
⎦
Cd
= 0.75 + 0.15
λe
=
Wp
WR
ηWR HL
=
εWR H WR + n 2WP
S +C
= 0.97
= 11299
Ap E p S 2
Engineer News Record (ENR) Formula
ENR formula, Qp
= 105.6
x
= 1875 kN
WR + W p
97
Appendix B4
Bearing Capacity of Test Pile TP5 from Static Analysis (Meyerhof Method)
0 – 10.5 m
Loose sand, average unit weight, γavg = 16.5 kN/m2
Navg = 3
10.5 m – 26.0 m
Soft clay, average unit weight, γavg = 17.5 kN/m2
Navg = 2
Cu = 10 kN/m2
26.0 m – 43.0 m
Dense sand, average unit weight, γavg = 18.75 kN/m2
Navg = 32
For Loose Sand
Based on result from TP9, Navg is 3.
Effective overburden stress, γ’v
= (16.5 – 9.81) x 10.5
= 70.2 kN/m2
98
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
20
0.0105γ 'v
= 3.3
Based on Meyerhof (1976)
Skin resistance, qs1
= 2NcorpL
= 2 x 3.3 x 0.5π x 10.5
= 109 kN
For Soft Clay
Skin resistance, qs
= αcupL
From Figure 2.15, α = 1.0
Thus, qs2
= 1.0 x 10 x 0.5π x 15.5
= 243 kN
Total skin resistance, Qs = qs1 + qs2 = 352 kN
For Medium Dense Sand
Effective overburden stress, γ’v
= (16.5 – 9.81) x 10.5 + (17.5 – 9.81) x 15.5
+ (18.75 – 9.81) x 17.0
= 341 kN/m2
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
20
0.0105γ 'v
= 18.4
Based on Wolff (1989)
2
φ = 27.1 + 0.3N cor − 0.00054 N cor
= 33°
99
The depth of penetration in bearing stratum, Lb is 12.1.
Thus, Lb / D = 24.2 and is less than (Lb / D)critical. The value for (Lb / D)critical is
around 7 (from Figure 2.8). Take (Lb / D)critical.
From Figure 2.8, bearing capacity factor, Nq is around 100.
Ultimate point load, Qtu
= Ap γ’v Nq
= 0.115925 x 341 x 100
= 3953 kN
However, limiting point load, Qtl
= Ap50Nqtan φ
= 0.115925 x 50 x 100 x tan 33°
= 376 kN
Since Qtl < Qtu, the point bearing capacity, Qt is 187 kN.
Thus, the bearing capacity of pile, Qp = Qt + Qs
= 376 + 352
= 728 kN
100
Appendix C1
Summary of Average Pile Top Settlement for Test Pile TP9
101
Appendix C2
Bearing Capacity of Test Pile TP9 from Load Test Interpretation Method
Chin's M e thod
0.02
Settlement/Load (mm/kN)
y = 0.00017x + 0.00630
0.01
0
0
5
10
15
20
25
30
35
40
45
50
Settlement (mm)
Ultimate Load (Qu) = 1/0.00017 = 5882 kN
Brinch Hansen's 80% Criterion
0.006
0.004
0.003
y = -0.00002x + 0.00297
0.5
0.5
Settlem
ent^ /Load(m
m
^ /kN)
0.005
0.002
0.001
0
0
10
20
30
40
Settlement (mm)
Ultimate Load (Qu) = 0.5/√(0.00002x0.00297) = 2051 kN
50
102
Fuller and Hoy's Method
Qp
4000
3500
3000
Load (kN)
2500
2000
1500
1000
500
0
0
10
20
30
40
50
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 3300 kN.
Butler and Hoy's Method
Qp
4000
3500
3000
Load (kN)
2500
2000
1500
1000
500
0
0
10
20
30
40
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 3200 kN.
50
103
De Beer's Method
10000
Load (kN)
Qp
1000
100
1
10
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 2100 kN.
100
104
Appendix C3
Bearing Capacity of Test Pile TP9 from Pile Driving Formulae
Weight of ram, WR
= 88.29 kN
Weight of Pile, Wp
= 91.03 kN
Area of pile, Ap
= 0.080425 m2
Young modulus of pile, Ep
= 43.25 x 106 kN/m2
Drop of hammer, H
= 0.6 m
Penetration of pile per, S
= 0.002 m
hammer blow
Efficiency, η (Janbu)
= 0.70 (good driving condition)
Efficiency, ε (ENR)
= 0.9 (assuming the efficiency is maximum)
Restitution factor, n
= 0.5 (assuming the restitution is maximum)
Constant, C
= 0.0254 m
Janbu Formula
Janbu formula, Qp
=
ηW R H
Ku S
= 1545 kN
where Ku
0.5
⎡ ⎛ λe
⎤
⎞
= C d ⎢1 + ⎜1 +
⎟ ⎥
C
d ⎠
⎣ ⎝
⎦
Cd
= 0.75 + 0.15
λe
=
Wp
WR
ηWR HL
=
εWR H WR + n 2WP
S +C
= 0.9
= 128
Ap E p S 2
Engineer News Record (ENR) Formula
ENR formula, Qp
= 12
x
= 1078 kN
WR + W p
105
Appendix C4
Bearing Capacity of Test Pile TP9 from Static Analysis (Meyerhof Method)
0 – 6.8 m
Loose sand, average unit weight, γavg = 16.5 kN/m3
Navg = 3
6.8 m – 19.0 m
Soft clay, average unit weight, γavg = 17.5 kN/m3
Navg = 2
cu = 10 kN/m2
19.0 m – 39.0 m
Medium dense sand, average unit weight, γavg = 18.75 kN/m3
Navg = 13
39.0 m – 45.0 m
Very dense sand, average unit weight, γavg = 20.5 kN/m3
Navg = 165
For Loose Sand
Effective overburden stress, γ’v
= (16.5 – 9.81) x 6.8
= 45.5 kN/m2
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
= 3.7
20
0.0105γ 'v
106
Based on Meyerhof (1976)
Skin resistance, qs1
= 2NcorpL
= 2 x 3.7 x 0.4π x 6.8
= 63 kN
For Soft Clay
Skin resistance, qs
= αcupL
From Figure 2.15, α = 1.0
Thus, qs2
= 1.0 x 10 x 0.4π x 12.2
For Medium Dense Sand
Effective overburden stress, γ’v
= (16.5 – 9.81) x 6.8 + (17.5 – 9.81) x 12.2
+ (18.75 – 9.81) x 20
= 318.1 kN/m2
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
20
0.0105γ 'v
= 7.8
Based on Meyerhof (1976)
Skin resistance, qs3
= 2NcorpL
= 2 x 7.8 x 0.4π x 6.8
= 391 kN
Total skin resistance, Qs = qs1 + qs2 + qs3 = 607 kN
For Hard Layer
Effective overburden stress, γ’v
= 318.1 + ( 20.5 – 9.81) x 6
= 382.2 kN/m2
107
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
20
0.0105γ 'v
= 89
Based on Wolff (1989)
2
= 50° > 45°. Assume friction angle is 45°.
φ = 27.1 + 0.3N cor − 0.00054 N cor
The depth of penetration in bearing stratum, Lb is 2.8.
Thus, Lb / D = 6.8 and is less than (Lb / D)critical. The value for (Lb / D)critical is around
24 (from Figure 2.8). Take (Lb / D).
From Figure 2.8, bearing capacity factor, Nq is around 400.
Ultimate point load, Qtu
= Ap γ’v Nq
= 0.080425 x 382.2 x 400
= 12295 kN
However, limiting point load, Qtl
= Ap50Nqtan φ
= 0.080425 x 50 x 400 x tan 50°
= 1917 kN
Since Qtl < Qtu, the point bearing capacity, Qt is 1917 kN.
Thus, the bearing capacity of pile, Qp = Qt + Qs
= 1917 + 607
= 2524 kN
108
Appendix D1
Summary of Average Pile Top Settlement for Test Pile TP10
109
Appendix D2
Bearing Capacity of Test Pile TP10 from Load Test Interpretation Method
Chin's Method
0.06
Settlement/Load (mm/kN)
0.05
y = 0.00191x + 0.01116
0.04
0.03
0.02
0.01
0
0
5
10
15
20
25
Settlement (mm)
Ultimate Load (Qu) = 1/0.00191 = 524 kN
Settlement^0.5/Load (mm^0.5/kN)
Brinch Hansen's 80% Criterion
0.025
0.024
0.023
0.022
0.021
0.02
0.019
0.018
0.017
0.016
0.015
0.014
0.013
0.012
0.011
0.01
0.009
0.008
0.007
0.006
0.005
0.004
0.003
0.002
0.001
0
y = -0.00015x + 0.01242
0
5
10
15
20
Settlement (mm)
Ultimate Load (Qu) = 0.5/√(0.00015x0.01242) = 366 kN
25
110
Fuller and Hoy's Method
500
QP
450
400
Load (kN)
350
300
250
200
150
100
50
0
0
5
10
15
20
25
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 420 kN.
Butler and Hoy's Method
500
QP
450
400
Load (kN)
350
300
250
200
150
100
50
0
0
5
10
15
20
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 390 kN.
25
111
De Beer's Method
1000
Load (kN)
QP
100
10
1
10
Settlement (mm)
From the graph, it is estimated the ultimate bearing capacity is 230 kN.
100
112
Appendix D3
Bearing Capacity of Test Pile TP10 from Pile Driving Formulae
Weight of ram, WR
= 88.29 kN
Weight of Pile, Wp
= 34.14 kN
Area of pile, Ap
= 0.080425 m2
Young modulus of pile, Ep
= 43.25 x 106 kN/m2
Drop of hammer, H
= 0.2 m
Penetration of pile per, S
= 0.0208 m
hammer blow
Efficiency, η (Janbu)
= 0.70 (good driving condition)
Efficiency, ε (ENR)
= 0.9 (assuming the efficiency is maximum)
Restitution factor, n
= 0.5 (assuming the restitution is maximum)
Constant, C
= 0.0254 m
Janbu Formula
Janbu formula, Qp
=
ηW R H
Ku S
= 350 kN
where Ku
0.5
⎡ ⎛ λe
⎤
⎞
= C d ⎢1 + ⎜1 +
⎟ ⎥
C
d ⎠
⎣ ⎝
⎦
Cd
= 0.75 + 0.15
λe
=
Wp
WR
ηWR HL
=
εWR H WR + n 2WP
S +C
= 272 kN
= 0.8
= 0.15
Ap E p S 2
Engineer News Record (ENR) Formula
ENR formula, Qp
= 1.7
x
WR + W p
113
Appendix D4
Bearing Capacity of Test Pile TP10 from Static Analysis (Meyerhof Method)
0 – 7.8 m
Loose sand, average unit weight, γavg = 16.5 kN/m2
Navg = 3
7.8 m – 19.0 m
Soft clay, average unit weight, γavg = 17.5 kN/m2
Navg = 3
cu = 15 kN/m2
19.0 m – 41.2 m
Medium dense sand, average unit weight, γavg = 18.75 kN/m2
Navg = 26
41.2 m – 46.0 m
Very dense sand, average unit weight, γavg = 18.75 kN/m2
Navg = 178
For Loose Sand
Effective overburden stress, γ’v
= (16.5 – 9.81) x 7.8
= 52.2 kN/m2
Based on Peck, Hanson and Thornburn (1974)
Ncor
= 0.77 N f log
= 3.6
20
0.0105γ 'v
114
Based on Meyerhof (1976)
Skin resistance, qs1
= 2NcorpL
= 2 x 3.6 x 0.4π x 7.8
= 71 kN
For Soft Clay
Skin resistance, qs
= αcupL
From Figure 2.15, α = 1.0
Thus, qs2
= 1.0 x 15 x 0.4π x 11.2
= 101 kN
Total skin resistance, Qs = qs1 + qs2 = 172 kN
This pile is carry by skin resistance alone as the soft clay is not capable of generating
end bearing for the pile. Thus, Qp = Qs.