AUT:Geo-CPT&Pile Database Geotechnic records, Cpt...

AUT;GEO-CPT&PILE DATABASE

GEOTECHNICAL INFORMATION, CPT AND CPTU DATA AND PILE LOADING TESTS RECORDS

June 2017

Amirkabir University of Technology Department of Civil and Environmental Engineering

Developed by:

Engr. Sara Moshfeghi

Dr. Abolfazl Eslami

Dr. S. Majdeddin MirMohammad Hosseini

Finalized by:

Dr. Abolfazl Eslami

Dr. Abbas Soroush

Engr. Sara Moshfeghi

Engr. AmirHossein Vojgani

Outline

Introduction

Cone Penetration Testing (CPT) –Piezocone (CPTu) Applications

History of Databases in Geotechnical Engineering (GE)

Review of Current Databases for Piling and CPT

AUT;Geo-CPT&Pile Database

Typical Application in Data Processing

Summary and Concluding Remarks

1

2

3

4

5

6

7

Outline

Introduction

Geotechnical Engineering (GE)

Sources of Data in GE

In-situ Testing vs. Laboratory Testing

Different In-situ Tests

Applicability of in-situ tests

1


Geometricals: Soil,Rock,Ground Water

Geosynthetics: Geotextile,Geogrid,Geonet,Geomembrane,…

Geometricals: Soil,Rock,Ground Water

Geosynthetics: Geotextile,Geogrid,Geonet,Geomembrane,…

1. Introduction

4 /114

1. Data Collection

2. Site Visit & Non-Destructive Testing (NDT)

3. Drilling Operations & In-Situ Testing

4. Laboratory Tests

5. Information Synthesis & Geotechnical Report

6. Instrumentation & Monitoring

Specific Data in Foundation Engineering:

Geomaterial Strength & Stiffness Parameters

Geotechnical Investigation Steps: Geotechnical Investigation Steps:


1. Introduction

5 /114


Foundation

Engineering

1. Introduction

6 /114

Multidisciplinary: Structural, Geotechnical and Construction Multidisciplinary: Structural, Geotechnical and Construction

Sources of Data in GE

1. Introduction

1. Site visit and maps

2. Geophysical Tests

3. In-situ testing

4. Laboratory Testing

5. Physical Modeling

6. Instrumentation and

Monitoring

Sources of Data: Sources of Data:

7 /114

In-situ Testing vs. Laboratory Testing

Laboratory Tests Problems Laboratory Tests Problems

Difficulties in preparing undisturbed sample

Soil disturbance

Soil volume change

Omitting confinement pressure

Size effect and size limits

In Situ Tests In Situ Tests

Laboratory and In-Situ testing approaches are complementary in Geotechnical Engineering Practice

Laboratory and In-Situ testing approaches are complementary in Geotechnical Engineering Practice

Overcome sampling difficulties

Simple and fast

Economical

Generally applicable in foundation

engineering

1. Introduction

8 /114

Standard Penetration Test (SPT)

Standard Penetration Test (SPT)

Piezo Penetrometer (CPTu)

Piezo Penetrometer (CPTu)

Dilatometer (DMT)

Dilatometer (DMT)

Persumeter (PMT)

Persumeter (PMT)

Vane Shear Test (VST)

Vane Shear Test (VST)

Cone Penetration Test (CPT)


Common Penetrating In-Situ Tests Common Penetrating In-Situ Tests

In-situ Testing

1. Introduction

9

…

…

/114

test

Parameters and specifications

So

il c

lass

ific

ati

on

Verti

ca

l so

il p

rofi

lin

g

Rela

tive d

ensi

ty, D

r

Fric

tio

n a

ng

le, φ

Un

dra

ined

sh

ea

r

stre

ng

th, S

u

Po

re p

ress

ure

, u

Str

ess

his

tory

, O

CR

an

d K

0

Es a

nd

G m

od

ulu

s

Co

mp

ress

ibil

ity

facto

rs,

mv a

nd

Cc

Co

nso

lid

ati

on

fa

cto

rs,

cv a

nd

ch

Perm

ea

bil

ity, k

Str

ess

-str

ain

dia

gra

m

Liq

uef

act

ion

res

ista

nce



A: high application B: medium application C:limited application 10 /114

Outline

Cone Penetration Testing (CPT) –Piezocone (CPTu) Applications


Piezocone (CPTu)

Equipment

Graphical Presentation of Records

Special Piezocones

Applications

2

• ASTM D 5778 procedures

• No boring, No samples, No spoil

• Hydraulic Push at 20 mm/s

• Range of sizes:10 cm2 and 15 cm2 probes

Cone Penetrometer (CPTu) Probes and Terminology Cone Penetrometer (CPTu) Probes and Terminology

Advantages:

• Fast and continuous profiling

• Repeatable and reliable

• Continuous records of qc, fs, u per 2.5 cm

• Strong theoretical basis for interpretation

Disadvantages:

• High capital investment

• Requires skilled operators

• Limitation of use in gravel or cemented soils

Cone Penetration Test (CPT) and Piezocone (CPTu)

2. Cone Penetration Testing (CPT) –Piezocone (CPTu) Applications

12 /114

Cone Tracks, Trucks and Special Rigs Cone Tracks, Trucks and Special Rigs



13

CPTu Performance and Records CPTu Performance and Records



14 /114


Typical CPTu Profile , Vancouver, BC, Canada (Campanella, 1988)



15 /114


Typical CPTu Profile , Mexico City Clay (Mayne, 1990)



16 /114

Resistivity Cone Penetration Test (RCPTu)

Seismic Cone Penetration Test (SCPTu)

Piezovibrocone

Ultra violet induced fluorescence Cone Penetration Test (UVIF CPT)

Dynamic Cone Penetration Test (DCPT)

Cone Pressuremeter (CPMT)

…

Special Piezocones


17 /114

Soil Behavior Classification and Profiling

APPLICATION OF CPT IN GEOTECHNICS

Foundation Engineering

Estimating soil strength and stiffness

parameters

Soil improvement assessment

Problematic soils recognition

Evaluating liquefaction potential

Direct approaches

Indirect approaches

Applications


18

Geo-environmental Engineering

/114

19 19/91

Begemann (1963) Douglas & Olsen(1981)

Eslami & Fellenius (1997) Olsen & Mitchell (1995)

Jefferies & Davies (1991) Schmertmann (1978)

Robertson (1990)

CPT-Based Soil Classification Charts Evaluation- Eslami & Fellenius (2004)

CPT-Based Soil Classification Charts Evaluation- Eslami & Fellenius (2004)

Soil Behavior Classification


Robertson (2010) Robertson (2016)

Analysis of Problematic soils in Robertson (1990) Classification Chart (Alimirzaei and Eslami, 2017)

Analysis of Problematic soils in Robertson (1990) Classification Chart (Alimirzaei and Eslami, 2017)

1.00

10.00

100.00

1000.00

0.10 1.00 10.00

EXPANSIVE

1.00

10.00

100.00

1000.00

0.10 1.00 10.00

LIQUEFIABLE

1.00

10.00

100.00

1000.00

0.10 1.00 10.00

PEAT

1.00

10.00

100.00

1000.00

0.10 1.00 10.00

SENSITIVE

DOUGLAS &

OLSEN

JEFFERIES

& DAVIS

ROBERTSO

N 1986

ROBERTSO

N 1990

ESLAMI &

FELLENIUS

ROBERTSO

N 2010

CLAY 70 65 60 75 25 30

CLAYEY SILT 40 20 40 45 20 30

COLLAPSIBLE 10 100 50 100 90 95EXPANSIVE 60 50 35 55 40 10

LIQUEFIABLE 10 100 30 40 70 70

PEAT 100 60 60 90 100 55

SAND 5 30 40 40 20 40

SANDY SILT 60 30 45 40 70 55

SENSITIVE 80 100 50 97 35 85

SILT 80 40 60 30 30 30SILTY CLAY 40 40 45 50 20 20SILTY SAND 40 60 30 30 20 30

AVERAGE 50 58 45 58 45 46

Out of Zone %

Problematic Soils Classification


Analysis of Explosive Compaction (Shakeran et al., 2016) Analysis of Explosive Compaction (Shakeran et al., 2016)

A

B

C

Before EC After EC Recommended Zones

Soil Improvement: Design and Assessment


21 Schematic view of EC procedure /114

Characterization of the correlation structure of residual CPT profiles in sands (Eslami Kenarsari et al., 2012) Characterization of the correlation structure of residual CPT profiles in sands (Eslami Kenarsari et al., 2012)

Data Variation


22 /114

Application of piezocone (CPTu) data for liquefaction analysis (Robertson and Wride, 1997; Kangarani et al., 2011) Application of piezocone (CPTu) data for liquefaction analysis (Robertson and Wride, 1997; Kangarani et al., 2011)

Zone for non-liquefied

soils according to

u2/qt index

Analysis of Qtn index

proposed by

Campanella (1988)

for liquefaction

assessment

Liquefaction Analysis


23 /114

Estimating soil shear strength: Mayne and Kulhawy (1982) Kulhawy and Mayne (1990) Motaghedi and Eslami (2014)

Estimating soil shear strength: Mayne and Kulhawy (1982) Kulhawy and Mayne (1990) Motaghedi and Eslami (2014)

Input Data Input Data

c’ , φ’ c’ , φ’

Output Output

qc, fs, u2 qc, fs, u2

𝐶 + 0.000789 1 − 𝑠𝑖𝑛ϕ 𝜎𝑣0′ 𝑡𝑎𝑛

2

3ϕ

𝑞𝑐 −𝜎𝑣0 − 2𝜎ℎ0

3

𝜎𝑣0′ − 2𝜎ℎ0

′

3

1.44

= 𝑓𝑠

𝑡𝑎𝑛2𝜋

4+

ϕ

2𝑒𝜋𝑡𝑎𝑛ϕ − 1 𝐶 𝑐𝑜𝑡ϕ + 𝑞 . 𝑡𝑎𝑛2

𝜋

4+

ϕ

2𝑒𝜋𝑡𝑎𝑛ϕ +

𝛾𝐵 𝑡𝑎𝑛2𝜋

4+

ϕ

2𝑒𝜋𝑡𝑎𝑛ϕ + 1 𝑡𝑎𝑛ϕ = 𝑞𝐸 + 𝑁𝑢∆𝑈

Estimating Soil Parameters


24

Motaghedi and Eslami (2014)

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1. Shallow foundations

2. Soil improvement

3. Semi-deep foundations

4. Deep foundations

General Classification of Foundtions

Foundation Design


25

Shallow

foundation

Semi deep foundation Deep foundation

Fill with

improved soil

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1. Static Methods

How can we estimate the bearing capacity of piles?

2. In-situ Tests

4. Dynamic Methods

3. Static Loading Test

5. Numerical Analysis

Foundation Design


26 /114

Applications of CPT and CPTu Data in Pile Design: Fellenius (1972, 1988) Bustamante and Gianeselli (1982) ….

Applications of CPT and CPTu Data in Pile Design: Fellenius (1972, 1988) Bustamante and Gianeselli (1982) ….

1- Direct Approaches:

2- Indirect Approaches:

fs

rt qc

rs

c, qult fs qc,

Similarities between the cone penetrometer and piles

Penetrometer can be realized as a model pile.

qt

fs

Foundation Design: Bearing Capacity


27 /114

28

Current direct CPT and CPTu-

based methods for determining

the bearing capacity of piles

(Niazi and Mayne, 2013)

Method/ Reference Method/ Reference

Begemann (1963, 1965, 1969) Fugro-05 (Kolk et al. 2005)

Meyerhof (1956, 1976, 1983) UCD-05 (Gavin and Lehane 2005)

Aoki and Velloso (1975) ICP-05 (Jardine et al. 2005)

Nottingham (1975), Schmertmann (1978) UWA-05 (Lehane et al. 2005)

Penpile (Clisby et al.1978) NGI-05 (Clausen et al. 2005)

Dutch (de Ruiter & Beringen 1979) Cambridge-05 (White & Bolton 2005)

Philipponnat ( 1980) German (Kempfert and Becker 2010)

LCPC (Bustamante & Gianeselli 1982) UCD-11 (Igoe et al. 2010, 2011)

Cone-m (Tumay & Fakhroo 1982) V–K (Van Dijk and Kolk 2011)

Price and Wardle (1982) SEU (Cai et al. 2011, 2012)

Gwizdala (1984) HKU (Yu and Yang 2012)

UniCone (Eslami & Fellenius 1997) UWA-13 (Lehane et al., 2013)

KTRI (Takesue et al. 1998) Modified UniCone (Niazi and Mayne, 2016)

TCD-03 (Gavin and Lehane 2003)



Bearing Capacity of Piles Bearing Capacity of Piles

Scale Effect for Correlation CPTu Data and Deep Foundation (Rezazadeh et al., 2013)



29 /114

Pile Shaft Capacity (Lotfi et al., 2014) Pile Shaft Capacity (Lotfi et al., 2014)



30 /114

Analytical model for ultimate bearing capacity of foundations by CPT

Bearing Capacity of Shallow Foundations Bearing Capacity of Shallow Foundations

(Eslami and Gholami, 2003, 2006)



31 /114

Bearing capacity of piles in sand: stress characteristics (Veiskarami et al., 2011) Bearing capacity of piles in sand: stress characteristics (Veiskarami et al., 2011)

Directions of the stress characteristics on Mohr’s circle of

stress and the major and minor principal stresses

Boundary conditions of Bolton and Lau

(1993) with a straight rigid cone



32 /114

Bearing capacity of piles in sand: stress characteristics (Veiskarami et al., 2011) Bearing capacity of piles in sand: stress characteristics (Veiskarami et al., 2011)

Stress characteristics and

variation of soil friction

angle at failure



33 /114

Ground Improvement and Foundation Practice for Persian Gulf Bridge (Causeway) (Asadi et al., 2016) Ground Improvement and Foundation Practice for Persian Gulf Bridge (Causeway) (Asadi et al., 2016)

Geotechnical Site Characterization


34

The view of the cable part

implemented in the sea

Particle size distribution of the soil close to Qeshm

coastline and main land

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Ground Improvement and Foundation Practice for Persian Gulf Bridge (Causeway) (Asadi et al., 2016) Ground Improvement and Foundation Practice for Persian Gulf Bridge (Causeway) (Asadi et al., 2016)

Geotechnical Site Characterization


35

The model geometry in FLAC 3D

Displacement contours (a) before subsoil improvement and (b) after improvement

(a) (b)

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CPT-Based Investigation for Pile Toe and Shaft Resistances Distribution (Eslami et al., 2016) CPT-Based Investigation for Pile Toe and Shaft Resistances Distribution (Eslami et al., 2016)

Normalized curve

for the values of

ultimate resistance

Comparison of pile

bearing capacities



36 /114

Settlement analysis of shallow foundations Schmertmann (1978) Malekdoost and Eslami (2010) Valikhah and Eslami (2016)

Settlement analysis of shallow foundations Schmertmann (1978) Malekdoost and Eslami (2010) Valikhah and Eslami (2016)

Foundation Design: Settlement Estimation


37

1.Sensitive Fine-Grained Soil

2.Organic Soil

3.Clay

4.Silty Clay to Clay

5.Clayey Silt to Silty Clay

6.Sandy Silt to Silty Clay

7.Silty Sand to Sandy Silt

8.Sand to Silty Sand

9.Sand

10.Sand to Gravelly Sand

11.Very Stiff Fine-Grained Soil

12.Overconsolidated or Cemented

Sand to Clayey Sand

(a) Robertson et al. (1986) and (b) Eslami-Fellenius (1997) soil behaviour

classification chart with proposed “j” values

(a) (b) Comparison of the predictive methods

for settlement estimation using the

cumulative probability approach

𝑗 =𝑞𝑡 1 + 0.05 𝑙𝑜𝑔𝑞𝑡 × 𝑅𝑓

2

5𝑙𝑜𝑔𝑞𝑡(11 𝑅𝑓 + 𝑅𝑓2)

Outline

History of Databases in Geotechnical Engineering (GE)

Databases

Examples of Databases in Geotechnics

Mayne et al. (2011)

Berkeley Liquefaction Investigation

USGS Earthquake Hazards Program

Iowa State University Database

Driven Pile Ground Vibration Case History Database

Iranian geotechnical data bank- Building and Housing

Research Center (BHRC)(2000-2002)

3

Databases are collections of data which are organized in order to facilitate

access and retrieving data when they are needed.

Examples of Databases in Geotechnical Engineering:

1. Pile loading test

2. Pile loading test under lateral load

3. Retaining walls and displacement due to deep excavation

4. In-situ tests

5. Specifications of geotechnical boreholes

6. Settlement of shallow foundations

7. …

Databases

39

3. History of Databases in Geotechnical Engineering

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Advantages and Applications:

I. Cost saving and project execution time

II. Optimization of design methods

III. Evaluation of design methods

IV. Development of new methods

V. Improvement of geotechnical studies

Databases

40

Data banks of deep foundation are a powerful tool for designing,

analyzing, developing and evaluating predictive methods.


/114

41/91

Correlation between CPT and soil unit weight

Includes records of 44 sites

A wide range of soil type (sand, clay, chalk, tilts, …)

Mayne et al. (2011)


41 Estimated versus measured unit weight (Mayne et al., 2011)

Records of earthquakes:

Adapazari (1999) in Turkey

Chi Chi (1999) in Taiwan

Includes records of CPT and SPT

Aimed at investigation of liquefied

soils during earthquake

Berkeley Liquefaction Investigation


42 /114

CPT records performed all over

the North America

1500+ tests carried out from

1979 to 2011

Seismic investigation and soil

liquefaction assessment

USGS Earthquake Hazards Program


43 /114

Database for PIle LOad Test (PILOT)

Comprising both static and dynamic data for driven piles back to 1966

Is intended for use in the establishment of resistance factors for LRFD and a reliable construction-control method for driven pile foundations and their future developments

An electronically organized assimilation of geotechnical and pile-load test data for 274 piles of various types (e.g., steel H-shaped, timber, pipe, Monotube, and concrete) driven within the state of Iowa

Iowa State University Database (Roling et al., 2011)


44 /114

Hajduk et al. (2009)

An important first step towards future examining

of the environmental effects of pile driving on

adjacent structures and residents

Incorporates available data from the technical

literature and data provided by professionals

within the pile driving industry

Driven Pile Ground Vibration Case History Database


45

Summary of initial database case histories

(Hajduk et al., 2009)

Outline

Review of Current Databases for Piling and CPT

Briaud and Tucker (1988)

Alsamman (1995)

Eslami and Fellenius (1997)

Abu-Farsakh & Titi (2004) Database

UWA (2005) Database

Hassani et al. (2010) Database

Van Dijk & Kolk (2011) Database

Eslami et al. (2011) Database

ZJU-ICL (2015) Database

4

Evaluating Performance of 13 methods for determining the bearing capacity and settlement of piles based on the results of standard penetration tests (SPT), cone penetration test (CPT), pressure meter test and dynamic formulas

98 case studies of steel and concrete piles with square, H, circular cross sections

Pile lengths between 3 and 25 m with the average of 12.2 m

The ultimate loads range from 307 to 2536 kN with the average of 1213 kN

Briaud and Tucker (1988) Database

4. Review of Current Databases for Piling and CPT

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95 case records of axial load testing on bored piles

29 sites from 8 countries

48 loading tests in granular soils, 16 in cohesive soil and 31 in mixed soils

The diameter of the piles is between 300 and 2130 mm

The embedment depth of the piles is between 4.6 to 42 m

Alsamman (1995) Database


48 /114

Results from 102 case studies from 40 sites and 13 countries

Sites include clay, silt and sand deposits

The majority of the records are square or circular in sections

Piles are made from steel and concrete materials

The bearing capacity of the piles is 80 to 8000 kN

Eslami and Fellenius (1997) Database


49 /114

Performance of 8 methods for determining bearing capacity using CPT

35 prestressed concrete piles with square cross section

The embedment length between 9 and 38 m

The section size between 356 and 762 mm

29 piles driven in clay and 9 in layered soils

Abu-Farsakh & Titi (2004) Database


50 /114

77 tensile and compressive loading tests

Driven concrete piles in sand

CPT records digitized in 0.1 m intervals or less

The length of the piles is between 5 and 80 meters,

mostly from 10 to 20 m

The majority of the records were less than 800 mm in

diameter

The bearing capacity of the piles mainly less than 5 MN

UWA (Lehane et al., 2005) Database


51 /114

Includes information from 70 piles from 12

countries

The buried depth of the pile is between 5.5 and

67m

Provides an artificial intelligence model to

determine the bearing capacity of piles

Hassani et al. (2010) Database


52 /114

33 steel pipe piles from 15 sites

Investigating the effect of soil plasticity,

overconsolidation ratio, the length and

slenderness ratio as well as the time

interval between driving the piles and

performing the loading tests

Van Dijk & Kolk (2011) Database


53 /114

CPTu Based Piles Capacity Methods in Urmiyeh Lake Causeway CPTu Based Piles Capacity Methods in Urmiyeh Lake Causeway

CPTu the major source of subsoil data in this project. CPTu the major source of subsoil data in this project.

CPTu soundings were performed in 12 locations, down to 100 m

below the lake-bed.

CPTu soundings were performed in 12 locations, down to 100 m

below the lake-bed.

Super Soft Deposits Super Soft Deposits



54 /114

CPTu Based Piles Capacity Methods in Urmiyeh Lake Causeway

CPTu Based Piles Capacity Methods in Urmiyeh Lake Causeway

Case

No Pile Name

Pile

Shape

Pile Size Measured

Type of Test Length

(m)

Diameter

(mm)

Thickness

(mm)

Ru

(KN)

1 UCA4 Circular 66 813 38.1 5400

Dynamic

Test

Pile driving

Analyzer

2 UCA5 Circular 66 813 38.1 4700

3 UCA7 Circular 66 813 38.1 5500

4 UCB3 Circular 75 813 38.1 7300

5 UCB4 Circular 75 813 38.1 5500

6 UCB5 Circular 75 813 38.1 7000

7 UCB7 Circular 75 813 38.1 6300

8 UCB8 Circular 75 813 38.1 8000

9 UCA4-C Circular 30 356 12 760 Pile Load

Test 10 UCA5-T Circular 70 305 16 3200



55 /114

CPTu Based Piles Capacity Methods in Urmiyeh Lake Causeway CPTu Based Piles Capacity Methods in Urmiyeh Lake Causeway

Soil Profiling Soil Profiling

Robertson (1990) Eslami-Fellenius (2004)

Pile Capacity by Different CPT/CPTu Methods- Site Specific Design Pile Capacity by Different CPT/CPTu Methods- Site Specific Design



56 /114

Pore Pressure (MPa) Pore Pressure (MPa)

Sensitivity Sensitivity

100

10 10 10 3 4 3



57 /114

ZJU-ICL Database


58

Zhejiang University/Imperial College London (ZJU-ICL) database

Developed by Yang et al. (2015)

115 records of driven piles in sand

Openly accessible

/114

ZJU-ICL Database


59 /114

No. Database Number of records Installation Soil

1 Briaud and Tucker (1988) 98 Driven, bored Clay, Sand

2 Alsamman (1995) 95 Drilled shaft Clay, Sand

3 Eslami and Fellenius (1997) 102 Driven, bored Clay, Sand

4 Abu-Farsakh & Titi (2004) 35 Prestressed driven Clay

5 UWA (2005) 77 Driven Sand

6 Van Dijk & Kolk (2010) 33 Circular driven Clay

7 Hassani et al. (2010) 70 Driven, bored Clay, Sand

8 Eslami et al. (2011) 10 Driven Clay

9 ZJU-ICL (2015) 115 Driven Sand

Summary of Databases


60 /114

Outline

AUT;Geo-CPT&Pile Database

Data statistics

Soil properties

CPT data

Piles characteristics

Piles loading test information

Database structure

5

Records of pile axial loading tests along with adjacent CPT or CPTu profiles

Includes 466 case records from 48 sources and from 23 countries

AUT:Geo-CPT&Pile Database (Moshfeghi and Eslami, 2016)

5. AUT:Geo-CPT&Pile Database

62 /114

Digitizing load-displacement diagrams derived from loading tests

and CPT profiles using the GetData Graph Digitizer 2.2 software



63 /114

Soil Properties Includes a wide range of clayey, silty

and sandy soils.

Classified within three categories:

Sand

Clay

Mixed

Sand 35%

Clay 42%

Mixed 23%

Classification based on the type of soil around

pile toe as well as the dominant soil type along

the pile (70% of pile embedment depth)

Classification based on the type of soil around

pile toe as well as the dominant soil type along

the pile (70% of pile embedment depth)



64 /114

CPT Data Digitizing CPT and CPTu profiles in

0.05, 0.1, 0.2, 0.3 and 0.5 m

intervals.

0

50

100

150

200

250

qc qc, fs qc, fs, u qc, u

Nu

mb

er o

f C

ase

Rec

ord

s

28%

45%

23%

4%

qc qc, fs qc, fs, u qc, u

An example of CPT (Sandpoint in the United States)

(Fellenius et al., 2004)



65 /114

Piles Specifications

68

146

111

70

34

16 8 13

0

20

40

60

80

100

120

140

160

≤5 5-10 10-15 15-20 20-30 30-40 40-50 >50

Nu

mb

er

of

Ca

ses

Embedment Depth (m)

Embedment Depth Embedment Depth

Slenderness Ratio Slenderness Ratio

Cross Section Cross Section

Mainly between 5 to 75 m



66

Cross Section Shape Cross Section Shape

Material Material

Installation Method Installation Method

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Cross Section Cross Section Mainly between 100 to 900 mm

34 21

55

156

91

36 21 20 17 15

0

20

40

60

80

100

120

140

160

180

Nu

mb

er

of

ca

ses

Diameter (mm)



67


Material Material


/114





23

112

93

56 64

42

10 13 18

35

0

20

40

60

80

100

120

Nu

mb

er

of

ca

ses

Slenderness ratio



68


Material Material


/114

200

122

73

41 25

5 0

50

100

150

200

250

round pipe square helical H other

Nu

mb

er o

f ca

se r

ecord

s



Material Material


Round

Square

Pipe

Triangle

Octagonal

H

X

Helical



69




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195

266

5 0

50

100

150

200

250

300

steel concrete other

Nu

mb

er o

f C

ase

Rec

ord

s

Steel

Concrete

Composite (steel and concrete)

CFG (Cement, Fly ash, Gravel)



70


Material Material





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Material Material Driven

Bored

PGDS (Pressure Grouted Drilled Shaft)

APGD (Augured Pressure Grouted Displacement)

DCIS (Driven Cast in-situ)

224

58 55 41

22 21 13 32

0

50

100

150

200

250

driven DD bored helical pressed CFA jacked other

Nu

mb

er

of

Ca

se R

eco

rd

s Atlas (DD) Fundex (DD) Olivier (DD)

Omega (DD)

De Waal (DD)

Jacked

Vibro

CFA

Pressed

Helical



71





/114


Loading Tests and Bearing Capacity Loading Tests and Bearing Capacity

-5

0

5

10

15

20

0 500 1000 1500

Dis

pla

cem

ent

(mm

)

Load (kN)

0

20

40

60

80

100

0 3 6 9 12

Load

(k

N)

Displacement (mm)

0

500

1000

1500

2000

2500

0 20 40

Load

(kN

)

Displacement (mm)

Static Head- Down Static O-Cell

Statnamic

-4500

-3000

-1500

0

-15-10-50

Load

(k

N)

Displacement (mm)



72 /114 Dynamic


Loading Tests and Bearing Capacity Loading Tests and Bearing Capacity

356

74 42

14

0

50

100

150

200

250

300

350

400

static

(compression)

static (tension) dynamic statnamic

Nu

mb

er o

f C

ase

Reco

rd

s

119

173

107

43 24

0

20

40

60

80

100

120

140

160

180

200

≤500 500-1500 1500-3000 3000-5000 >5000

Nu

mb

er

of

ca

se R

eco

rd

s

Bearing Capacity (kN)



73 /114

Database structure

Using Microsoft Access 2010 to organize and classify data

Naming the data:

Assign a Case ID to each of the records based on the reference

107-TOKYO PORT : Reference 107

Operation place: Tokyo harbor (TOKYO PORT)

The name of the pile is TP1 in the original reference



74 /114

Database structure

General Records Form



75

Database structure

CPT Data Form



76

Database structure

Piles Information



77

Database structure

Piles Information



78

Database structure

Sources



79 /114

Database structure

Search



80 /114

Database structure

Search Results



81 /114

82 /114

Database structure

Details



Outline

Typical Application in Data Processing

Assessment of load test interpretation criteria

Evaluation of methods performance

Risk analysis and optimum safety factor

Examining wasted capacity

Reliability-based analysis

Neural networks modeling

Bearing capacity of special foundations: helical piles

Bearing capacity of special foundations: drilled displacement

piles

6

Studying effects of different soil types on piles performance

Back analysis of load-displacement diagrams

Comparing soil behavior classification methods with geotechnical logs

Evaluating efficiency of methods for estimating the pile bearing capacity

Validation of static and dynamic methods

Interpretation of the ultimate capacity of piles with existing methods

Applications of Database (Moshfeghi and Eslami, 2015 a,b)

6. Typical Application in Data Processing

84 /114

Evaluation of performance of current CPT-based methods

Performing Reliability-based analyses to estimate the optimum safety

factor for each method

Performing risk analyses to assess piles failure

60 compression Loading

Tests 30 tension

56 steel Material

34 concrete

44 pipe

Cross

section

shape

6 circular

26 square

12 H

2 octagonal

Study was carried out on 90 case records of driven

piles in sand

Typical Application of Database in Data Processing (Moshfeghi, 2015)


85 /114

Selecting appropriate interpretation criterion for load-displacement

diagrams

0.0

0.2

0.4

0.6

0.8

1.0

1.2

(Qp

/Qm

)aver

ag

e

10%B 80% Brinch Hansen



86 /114

Evaluating the performance of the methods using different statistical

approaches

y = 0.8632x R² = 0.6959

0

2000

4000

6000

8000

0 2000 4000 6000 8000

Qc

(kN

)

Qm (kN)

LCPC-1982 00.20.40.60.8

11.21.4

μg

0

0.5

1

1.5

2

2.5

σg



87

Risk analyses and optimum safety factor

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0 1 2 3

Ris

k (

%)

Safety Factor

Unicone-1997

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 1 2 3 4

Cost

(xT

L.β

/Qp

)

Safety Factor

Construction Cost

Failure Cost

Total cost

Unicone-1997



88

Value Engineering Value Engineering

/114

Evaluation of

wasted capacity



89

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0.0 1.0 2.0 3.0 4.0

WC

I (%

)

Qp/Qm

Meyerhof Schmertmann LCPCUnicone UWA-05 NGI-05Fugro-05 ICP-05 German

/114

Risk and reliability

Min. S.F. for

Risk=0

Safety Factor Method

3.5 3 2.5 2 1.5

2.4 0 0 0 5.7 15.9 Meyerhof-1976

2.3 0 0 0 2.3 5.7 Schmertman-1978

1.5 0 0 0 0 0 Dutch-1979

2 0 0 0 0 15.9 LCPC-1982

2.5 0 0 0 2.3 17.0 Unicone-1997

2.2 0 0 0 1.1 7.9 UWA-2005

3 0 0 1.1 7.9 15.7 NGI-2005

2.4 0 0 0 4.5 14.6 Fugro-2005

3.1 0 1.1 3.4 4.5 12.4 ICP-2005

2.2 0 0 0 4.5 16.8 German-2010

FSopt Method

2.4 Meyerhof-1976

1.5-2.3 Schmertman-1978

1.4, 1.5 Dutch-1979

2.0 LCPC-1982

1.6-2.5 Unicone-1997

1.7, 2.2 UWA-2005

1.8,2.5 NGI-2005

2.4 Fugro-2005

1.6-3.1 ICP-2005

2.2 German-2010



90 /114

Piles shaft capacity from CPT: Polynomial neural networks (GMDH)

Typical Application of Database in Data Processing (Ardalan et al., 2008; Eslami et al., 2014)


91

Different proposed design curves for shaft resistance

Experimental and predicted unit shaft capacities

/114

92

y = 1.06x

R² = 0.996

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0.00 0.50 1.00 1.50 2.00 2.50 3.00

FO

RM

Rel

iab

ilit

y I

nd

ex

FOSM Reliability Index

FS=2

FS=2.5

FS=3

Reliability index for different dead to live load ratio and

different factors of safety

CPT-based methods attained greater reliabilities and

followed by SPT-based methods and static analyses.

The sensitivity of reliabilities to the dead/live load ratios

is negligible.

FORM Reliability index is slightly greater than FOSM

reliability index.

Greater factors of safety result in greater reliabilities.

Reliability index does not perceive the conservatism of a

method.

Typical Application of Database in Data Processing (Heidari et al., 2017)


Reliability-based Assessment of Pile Foundation Bearing Capacity:

Static analysis, SPT and CPT-based Methods

/114

93





0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

deRuiter and

Beringen

UniCone

LCPC

Meyerhof(CPT)

Schmertmann

Bazaara and

Kurkur

Briaud and

Tucker

Decourt

Meyerhof(SPT)

Shioi and Fukui

CFEM

API

FORM Resistance factor -- β=2

QD/QL=1 QD/QL=2 QD/QL=3 QD/QL=4

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

deRuiter and

Beringen

UniCone

LCPC

Meyerhof(CPT)

Schmertmann

Bazaara and

Kurkur

Briaud and

Tucker

Decourt

Meyerhof(SPT)

Shioi and Fukui

CFEM

API

FORM Resistance factor -- QD/QL=1

Beta=2 Beta=2.5 Beta=3βtarget=2 βtarget=2.5 βtarget=3

FORM resistance factors for different methods for (a) different

dead to live load ratios (b) different target reliability indices

FORM resistance factors are insensitive

to dead/live load ratios.

Greater target reliabilities result in

smaller resistance factors.

Conservatives methods attain greater

resistance factors.

/114

94





0.54 0.52 0.51 0.50

0.43 0.41 0.40 0.39

0.34 0.33 0.32 0.31

0.0

0.1

0.2

0.3

0.4

0.5

0.6

1 2 3 4

Eff

icie

ncy

Rati

o

QD/QL

βtarget=2 FOSM Approach:

FORM Approach:

0.360.34

0.33 0.33

0.250.24 0.24 0.23

0.19 0.18 0.17 0.17

0.0

0.1

0.2

0.3

0.4

1 2 3 4

Eff

icie

ncy R

ati

o

QD/QL

βtarget=3

Efficiency ratio for different reliability approaches and different groups of methods (a) βtarget=2 (b) βtarget=3

Efficiency ratio is a better means for measuring the reliability by considering both resistance factor and the resistance

bias factor.

/114

/114 95

Typical Application of Database in Data Processing (Askari Fateh et al., 2016&2017)


Bearing Capacity of Special Foundations: Helical piles

Design optimization

Failure mechanism assessment

96

Typical Application of Database in Data Processing (Moshfeghi and Eslami, 2017)


Bearing Capacity of Special Foundations:

Drilled displacement piles

Drilling displacement procedure of Atlas piles

(Basu et al., 2010)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

Scre

w s

ha

ped

Sm

ooth

Scre

w s

ha

ped

Sm

ooth

Scre

w s

ha

ped

Sm

ooth

Scre

w s

ha

ped

Sm

ooth

Scre

w s

ha

ped

Sm

ooth

Scre

w s

ha

ped

Sm

ooth

Method A(2002; 2005)

Method B(1998)

Eslami andFellenius (1997)

UWA (2005) Togliani (2008) German Method(2010)

PR

ED

ICT

ED

TO

ME

AS

UR

ED

CA

PA

CIT

Y

Upper 95% Confidence Limit Lower 95% Confidence Limit Arithmetic Mean

Evaluation results of CPT-based methods based on shaft shapes

/114

Outline


Geotechnical engineering

In-situ testing

Cone and piezocone penetration test (CPT, CPTu)

CPT and CPTu Applications

CPT and Pile

Databases

AUT;Geo-CPT & Pile database

7

1. Geotechnical Engineering: A branch of civil engineering which deals with design, analysis and

construction of any systems that are made of or supported by soil or rock (Geomaterial).

Sources of acquiring data:

Site visit and maps

Geophysical Testing

In-situ testing

Laboratory testing

Physical modeling

Instrumentation and monitoring

2. In-situ Testing: SPT, CPT, DCPT, PMT, PLT, DMT, FVST, ….

Provides accurate and reliable information

Supplement of laboratory testing


7. Summary and Concluding Remarks

98 /114

3. Cone and Piezocone Penetration Test (CPT, CPTu):

Simple

Fast

Economical

Supplies continuous records of soil with depth

Allows a variety of sensors to be incorporated with the penetrometer

4. CPT and CPTu Applications:

Soil behavior classification

Soil strength and stiffness parameters

Liquefaction analysis

Soil improvement assessment

Foundation Engineering: bearing capacity and settlement



99 /114

5. CPT and Pile:

Considered as a model pile

Facilitates Installation

Direct and indirect approaches for bearing capacity

Bearing capacity methods: currently used more than 25 direct methods

Settlement estimation

6. Databases:

Appropriate tools for design, analysis, and provide trend of optimum design

Necessity of assessment of methods performance



100 /114

7. AUT;Geo-CPT & Pile database:

Records of pile loading tests & adjacent CPT or CPTu profiles

466 case records from 48 sources and from 23 countries

Sand, clay and mixed soils

Various piles types including: driven, bored, jacked, drilled displacement, helical,

pressed, CFA, vibro, PGDS, APGD and driven cast in-situ piles.

Embedment length: mainly between 5 to 75

Section size: mainly between 100 to 900 mm



101 /114


Section shape: round, square, triangle, pipe, octagonal, H, X, helical

Piles material: steel, concrete, composite, CFG

Data were organized using Microsoft Access 2010 software and consist of various

forms for presentation of data including general records form, CPT test results, pile

information, resources and search forms.



102 /114




103

Applications:

Study the effects of different soil types on piles performance

Back analysis of load-displacement diagrams

Comparing soil behavior classification methods with geotechnical logs

Evaluating efficiency of methods for estimating the pile bearing capacity

Validation of static and dynamic methods

Interpretation of the ultimate capacity of piles with existing methods

Safe, Optimized and Sustainable

Designs

Safe, Optimized and Sustainable

Designs Value Engineering Value Engineering

/114

References

References

Abu-Farsakh, M. Y., & Titi, H. H. (2004). Assessment of direct cone penetration test methods for predicting

the ultimate capacity of friction driven piles. Journal of Geotechnical and Geoenvironmental Engineering,

130(9), 9

Alsamman, O. M. (1995). The use of CPT for calculating axial capacity of drilled shafts (Doctoral

dissertation, University of Illinois at Urbana-Champaign).

Ardalan, H., Eslami, A., & Nariman-Zadeh, N. (2009). Piles shaft capacity from CPT and CPTu data by

polynomial neural networks and genetic algorithms. Computers and Geotechnics, 36(4), 616-625.

Asadi, F., Eslami, A., and Valikhah, F.,. "Ground improvement and foundation practice for Persian Gulf Bridge

(causeway); Bandar Abbas Harbor–Qeshm Island." Marine Georesources & Geotechnology 35, no. 4 (2017): 538-

547.

Askari Fateh, A. M., Eslami, A., & Fahimifar, A. (2017). Direct CPT and CPTu methods for determining

bearing capacity of helical piles. Marine Georesources & Geotechnology, 35(2), 193-207.

Askari Fateh, A. M., Eslami, A., & Fahimifar, A. (2017). A study of the axial load behaviour of helical piles

in sand by frustum confining vessel. International Journal of Physical Modelling in Geotechnics, 1-16.

105 /114

References

Basu, P., Prezzi, M., & Basu, D. (2010). Drilled displacement piles–current practice and design. DFI

Journal-The Journal of the Deep Foundations Institute, 4(1), 3-20.

Begemann, H. P. (1963). The use of the static soil penetrometer in Holland.New Zealand

Engineering, 18(2), 41.

BHRC, Building and Housing Research Center (2000-2002), Iranian geotechnical data bank

Briaud, J. L., & Tucker, L. M. (1988). Measured and predicted axial response of 98 piles. Journal of

Geotechnical Engineering, 114(9), 984-1001.

Bustamante, M., & Gianeselli, L. (1982, May). Pile bearing capacity prediction by means of static

penetrometer CPT. In Proceedings of the 2nd European symposium on penetration testing, Amsterdam

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Campanella, R. (1988). Current status of the piezocone test. In Proc. 1st Int. Symp. on Penetration

Testing (Vol. 1, pp. 93-116). ISOPT.

Campanella, R. G., Robertson, P. K., Davies, M. P., & Sy, A. (1989, August). Use of in-situ tests in pile

design. In Proceedings 12th International Conference on Soil Mechanics and Foundation Engineering,

ICSMFE, Rio de Janeiro, Brazil (Vol. 1, pp. 199-203). 106 /114

References

Clausen, C. J. F., Aas, P. M., & Karlsrud, K. (2005, September). Bearing capacity of driven piles in sand,

the NGI approach. In Proceedings of International Symposium. on Frontiers in Offshore Geotechnics, Perth

(pp. 574-580).

De Ruiter, J., & Beringen, F. L. (1979). Pile foundations for large North Sea structures. Marine

Georesources & Geotechnology, 3(3), 267-314.

Douglas, B. J. (1981). Soil classificaion using electric cone penetrometer. InSymp. on Cone Penetration

Testing and Experience, Geotech. Engrg. Div.(pp. 209-227). ASCE.

Eslami, A., & Fellenius, B. H. (1997). Pile capacity by direct CPT and CPTu methods applied to 102 case

histories. Canadian Geotechnical Journal, 34(6), 886-904.

Eslami, A., & Fellenius, B. H. (2004). CPT and CPTu data for soil profile interpretation: review of methods

and a proposed new approach. Iranian journal of science and technology, 28(B1), 69-86.

Eslami, A. and Gholami, M. 2006. Analytical Model for Ultimate Bearing Capacity of Foundations from

Cone Resistance. International Journal of Science & Technology, Scientia Iranica, Sharif University of

Technology, July. Vol. 13, No. 3, pp 223-233.

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References

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estimation methods using Urmiyeh lake Causeway piling records, Scientia Iranica transaction a-civil

engineering, 19 October. Vol.18, No.5, pp.1009 - 1019.

Eslami, A., Mola-Abasi, H., & Shourijeh, P. T. (2014). A polynomial model for predicting liquefaction

potential from cone penetration test data. Scientia Iranica. Transaction A, Civil Engineering, 21(1), 44.

Eslami, A., Alimirzaei, M., Aflaki, E., Molaabasi, H. (2015), "Deltaic Soil Behavior Classification (SBC)

Using CPTu Rec-ords- Proposed Approach and Applied to Fifty-Four Case Histories”, Marine georesources

& geotechnology.

Eslami, A., Valikhah, F., Veiskarami, M., Salehi, M., (2017). "CPT-Based Investigation for Pile Toe and Shaft Resistances

Distribution." Geotechnical and Geological Engineering: 1-15.

Eslami Kenarsari, A., Jamshidi Chenari, R., & Eslami, A. (2013). Characterization of the correlation

structure of residual CPT profiles in sand deposits. International Journal of Civil Engineering.

Fellenius, B. H. (1972). Down-drag on piles in clay due to negative skin friction. Canadian Geotechnical

Journal, 9(4), 323-337. 108 /114

References

Fellenius, B. H. (1988). Unified design of piles and pile groups.Transportation Research Record, (1169).

Hajduk, E. L., Bower, K. C., Mays, T. W., Falatok, D. A., & Perkins, T. S. (2009). Development of a driven

pile ground vibration case history database. In Contemporary Topics in Deep Foundations (pp. 351-358).

Heidari, S., Eslami, A., Jamshidi Chenari, R., (2017), Reliability based assessment of pile foundation

bearing capacity: static analysis, SPT and CPT-based methods, Probabilistic Engineering Mechanics,

submitted.

http://earthquake.usgs.gov

http://peer.berkeley.edu

Jardine, R. J., Chow, F., Overy, R., & Standing, J. (2005). ICP design methods for driven piles in sands and

clays (p. 112). London: Thomas Telford.

Jefferies, M. G. & Davies, M. P., (1991). Soil classification using the cone penetration test: Discussion.

Canadian Geotechnical Journal, 28(1), 173–176.

Kangarani Farahani, M.R., Ahmadi, M.M., Eslami, A. (2011), Application of piezocone (CPTu) data for

liquefaction analysis", Sharif Journal of Engineering, 26(2-3), pp. 13-21 (2011) 109 /114

References

Kempfert, H. G., & Becker, P. (2010). Axial pile resistance of different pile types based on empirical

values. Proceedings of Geo-Shanghai, 149-154

Kolk, H. J., Baaijens, A. E., & Senders, M. (2005, September). Design criteria for pipe piles in silica sands.

In Proc., 1st Int. Symp. on Frontiers in Offshore Geotechnics (pp. 711-716). Perth, Australia: Balkema.

Kulhawy, F. H., & Mayne, P. W. (1990). Manual on estimating soil properties for foundation design (No.

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driven piles in sand. Frontiers in Offshore Geotechnics: ISFOG, 683-689.

Malekdoost, M., Eslami, A., 2011. application of CPT data for estimating foundations settlement-case

histories, Sharif Journal of Engineering, Sharif University of Technology, 18 April.Vol.2-27, NO.1, pp.75 -

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References

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Foundations Division, 108(6), 851-872.

Mayne, P. W., Peuchen, J., & Bouwmeester, D. (2011). Soil unit weight estimated from CPTu in offshore

soils. Front. Offshore Geotech, 2, 371-376.

Moshfeghi, S. (2015). Compiling a data bank including CPT, CPTu and pile load test records for

comparison of bearing capacity methods, M. Sc. Thesis, Dept. of civil and environmental engineering,

Amirkabir University of Technology (AUT).

Moshfeghi, S., Eslami, A., Mir Mohammad Hosseini, S. M. (2015a). AUT- CPT&Pile database- CPT data

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Tehran, Iran, 24-26 Jan.

Moshfeghi, S., Eslami, A., Mir Mohammad Hosseini, S. M. (2015b). AUT-CPT&pile database for piling

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Moshfeghi, S., Eslami, A., (2016). Study on pile ultimate capacity criteria and CPTbased direct methods,

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from CPT and CPTu Data. Arabian journal for science and engineering, Vol39., PP.4363-4376.

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Schneider, J. A., Xu, X., & Lehane, B. M. (2008). Database assessment of CPT-based design methods for axial capacity of driven piles in siliceous sands. Journal of geotechnical and geoenvironmental engineering, 134(9), 1227-1244.

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Van Dijk, B. F. J., & Kolk, H. J. (2011). CPT-based design method for axial capacity of offshore piles in clays. In Proceedings of the International Symposium on Frontiers in Offshore Geotechnics II. Edited by S. Gourvenec and D. White. Taylor & Francis Group, London (pp. 555-560).

Veiskarami, M., Eslami, A., and Kumar, J. (2011). End-bearing capacity of driven piles in sand using the stress characteristics method: Analysis and implementation, Canadian Geotechnical Journal, 24 September. Vol.48, No.0, pp.1570-1586.

Valikhah, F., Eslami, A., (2016). CPT-Based approach to estimate foundation settlement on sand, 5th International Conference on Geotechnical Engineering and Soil Mechanics, Tehran, Iran, 15-17 Nov. 2016.

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