normalization and prediction properties using the cone ... · the late 1960s, his acceptance of the...
TRANSCRIPT
AD-A285 193 Tech-nical Report GL-94-29
I! II ~II I'il I 1.1 I ! ""August 1994
US Army Corpsof EngineersWaterways ExperimentStation
Normalization and Prediction of GeotechnicalProperties Using the Cone PenetrometerTest (CPT)
by Rich 3rd S. Olsen
S-' -"A
IB
Approv ed For Public R ,ldeace; Distribution Is U olmited
94-31531
Prepared for Headquarters, U.S. Airny Corps of qginruurs_
The contents of tkis repc,rt arc not to be used for advertising,publication, or promotiilal purpos)s. Citatiot of trade namesdocs not constitute an official endorsement or approval of-the useof such commercial products.
PRINTED ON RECYCLED PAPER
Technical Report GL-94-29A jgust 1994
Normalization and Prediction of GeotechnicalProperties Using the Cone PenetrometerTest (CPT)
by Richard S. Olsen Accesion For
U.S. Army Corps of Engineers C , ,&IWaterways Experiment Station u -, " A3909 Halls Ferry RoadVicksburg, MS 39180-6199
Ly .. ... .......I • U. ir
DUt i , . .. Id
Final Report
Approved for public release; distribution is unlimited
Prepared for U.S. Army Corps of Engi,,eersWashington, DC 20314-1000
US Army Corpsof Engineers N
Waterways ExperimentStation
• IORY U. S-OA RDA y EGN
WAERAS E[OTE"" IATO
HEA.FOARrERS
VBU-SBRG VJS;SPI31•69
" KY-AL -O TL DZrWEE'RR
MAK I 7 ' EU01rrE
ENTRANCE - I
Waterways Experiment Station Cataloging-in-Publication Data
Olsen, Richard S.
Normalization and prediction of geotechnical properties using the coneponetrometer test (OPT) / by Richard S. Olsen ;prepared for U.S. ArmyCorps of Engineers.
322 p. :il. ; 28 cm.-- (Technical repo0. ;GL-94-29)
Includes bibliographic references.1. Soils - Testing -- Statistical methods. 2. Soil penetration test. 3.
Probability measures. 4. Penetrometer. I. United States. Army. Corpsof Engineers. II. U.S. Army Engineer Waterways Experiment Station.IV. Geotechnical Laboratory (U.S.) V. Title. VI. Series: Technical report(U.S. Army Engineer Waterways Experiment Station) GL-94-29.
TA7 W34 no.GL-94-29
Preface
The Doctor of Philosophy (Ph.D.) dissertation replicated in this report was written by
Dr. Richard S. Olsen, In Situ Evaluation Branch (ISEB), Earthquake Engineering and
Geosciences Division (EEGD), Geotechnical Laboratory (GL), Waterways Experiment
Station (WES). Dr. Olsen is under the direct supervision of Mr. M. A. Vispi, Chief,
ISEB, and general supervision of Dr. A. G. Franklin, Chief, EEGD, and Dr. W. F.
Marcuson Ifl, Director, GL.
The dissertation committee chairman at the University of California at Berkeley (UCB)
was Prof. James K. Mitchell and the other committee members were Prof. Raymond
B. Seed and Prof. H. Frank Morrison. Dr. Olsen was on WES sponsored Long Term
Training (LIT) from August 1988 to September 1989 at the UCB campus (he also
received his Master of Science degree from UCB in 1977). He passed his written
Preliminary Examination in May 1989 and Oral Qualifying Examination in April 1991.
He was advanced to candidate tor the Ph.D. degree in April 1991 and tie final
dissertation was submitted to the University on May 20, 1994.
At the time of publication of this report, Director of WFS was Dr. Robert W. Whalin.
Commander was COL Bruce K. Howard, EN.
UPq1
The contents of this report are no! to be used for advertising, publication,or promotional purposes. Citation of trade names does not constitute anofficial endorsement or approval for the usc of such commercial products.
Normalization and Predictionof Geotechnical Properties
Using the Cone Penetrometer Test (CPT)
by
Richard Scott Olsen
B.S.C.E. (Oregon State University) 1976M.S. (University of California, Berkeley) 1977
A dissertation submitted in partial satisfaction of therequirements for the degree of
Doctor of Philosophy
'1 in
Engineering-Civil Engineering
in the
GRADUATE DIVISION
of the
UNIVERSITY of CALIFORNIA at BERKELEY
Committee in charge:
Professor James K. Mitchell, ChairProfessc; Raymond B. SeedProfessor H. Frank Morrison
1994
I]I
The dissertation of Richard Scott Olsen is approved:
61-Chair Dt
f Date
Date
University of California at Berkeley
1994
Abstract
Normalization and Prediction
of Geotechnical Properties
Using the Cont ,enetrometcr Test (CPT)
by
Richard Scott Olsen
Doctor of Philosophy in Civil Engineering
University of California at Berkeley
Professor James K. Mitchell, Chair
The objectives of thiis research were to develop techniques for (1) stress
normalization of CPT measurements (and geotechnical properties) and (2) CPT
prediction of geotechnical properties using cone and sleeve friction resistance values.
Stress normalization allows a variable geotechnical property to be reduced to an
equivalent vdue at a standard confining stress.
A new concept, the Stress Focus, was identified which provides a basis for
understanding soil strength as a function of confining stress. This study
demonstrated that sand friction angles for different initial relative densities converge
to a Stress Focus at high confining stress (approximately 100 atm), where the
strength behavior is similar to that of a sedimentary rock. Dilation of dense sands
decreases with incre-ased confining stress until the Stress Focus is reached, as
confinrmed using historic high pressure triaxial test data as well with CPT
measurements from laboratory chamber tests and uniform soil layers. The paths of
convergence to the Stuess Focus are exponentially related to confining stress and are
the basis for development of CPT cone and sleeve firiction resistance normalization
techniques. The overburden stress at the Stress Focus is soil type dependent.
The stress exponent for SPT normalization was shown to be equal to the CPT
derived stress exponent.
CPT correlations to geotechnical properties were established using both CPT
cone resistance and friction ratio. These correlations were based on a large database
which was developed for this research effort. Statistical evaluation during the
development of these correlations concentrated on excluding biased data. CPT
based correlations were established for the following geotechnical properties: SPT
blow count, unconsolidated undrained triaxial test strength, field vane shear test
strength, and shear wave velocity.
es K. MitchellDissertation Committee Chairman
2
Dedication
I wish to thank Professor James K. Mitchell and acknowledge the late H. Bolton
Seed for being two of the greatest teachers that I have known. While preparing zo
return to UC Berkeley for PhD studies from 1982 to 1988 and while attending
classes during 1988 and 1989, 1 was in nearly constant communication with the late
H. Bolton Seed. After the death of Professor Seed in 1989, Professor Mitchell
became my dissertation chairman and I am very thankful that it was a seamless
transition. A special gratitude to goes to Professor Mitchell during my class work
studies, PhD examinations, research phase and dissertation preparation from 1988 to
1994. He was also instrumental in securing project funding from the Department of
Energy. lie also read through the massive first draft, providing valuable insight
toward shorter final versions. A sincere thanks goes out to Dr. Joseph P. Koester
and Dr. A. G. Franklin (Waterways Experiment Station) for their in-depth detailed
t... :I .,.VY , , L.L L11101 UI 41(. U'.-,,^%, 1• IC.lU ld ",! r, );1- tvA ,
express my gratitude to the other members of the committee, Professors Ramond B.
Seed and H. Frank Morrison, for their review of this manuscript.NII dedicate this dissertation to my father, Irving E. Olse'a, for his contributions to
my career. Hie introduceA1 me to world of geotechnical engineering as a small child.
I worked summers on the drafting table, then in the lab, and finally in the field on
inspection jobs and logging borcholes while still in high schooi. I'm sure that he
would have supported any occupation that I picked, but I enjoyed geotechnical
engineering. As the principle-in-charge of the Poitiand office of Dames & Moore inRthe late 1960s, his acceptance of the mechanical Dutch cone penetrometer allowed
two contractors to start busine-ss in the Northwest. It also started my working
exposure to Cone Penetrometer Test (CPT) technology. I worked as a helper on both
of these CPT rigs during the 1972 to !974 surmners of my high school and college
years. My father also planted a secd in my head that the Unified Soil Classification
System (USCS) was no. enough; the professin needed a good index for soil
iii-
strength. I believe that this dissertation points toward the futurc of using the CPT as
a rapid tool for indexing soil strength.
Christine, my enduring partner, best frierd Lnd devoted wife, would always
re~mind me that there is an end to the PhD work. She has had to live as the wife of
a P"') student and the wife of a full time research engineer. She loves music but
would turn it off at night while I worked at this computer. She has gone on
aiumerons vacations and trips by hersclf, leaving me at home to work on the
dissertation.
To Erin, my daughter, for her willingness to adjust to a new school when we
moved to Berkeley for my PhD studies and always having to turn down the TV. She
understands rny needs because she is a good student.
And finally Jonathan, my son, who was two when I went back to school for PhD
studies and is now seven. He always wants to be my buddy, to sit on my lap, or to
be at my side. He has only known his dad as always needing to work on the
dissertation. During the weekends, I would work foi : hours then 0re would play for
1/2 an hour. His vocabulary is now filled with words such as data, PC, digitizer,
scainner, unstable soil, CPT, and dad's study. I hope that he has seen the effort of
hard work-education is what you make of it and it can be fun. Your brain is the
most powerful part of the body-exercise it and life becomes fascinating.
This dissertation is also for my professional career. CPT is my profession and
the opportunity to write this dissertation has allowed me to revisit fundamental
theory to discover new concepts and prove old ideas.
Richard S. Olsen
May 1994
iV
Table of Contents
Abstract ... ...................................................
D edication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1ii
Table of Contents .. ............................................ v
L ist of Figures . ... .... .... ... .... ... ...... ... ... .. ... .. ... ... . x
List of Tables . .............................................. xxii
List of Sym bols ............................................ xxiii
Chapter 1 - Introduction .. ........................................ 1
• G eneral . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I
The CPT Test .. ......................................... 2
The CPT Measurements . .................................. 4
i-CTT Pp~,'aA,.in". A,1,~.4.~ ,~.( t;-,, ~,rii
Stratigraphic Influences on CPT Correlations .................... 5
Accounting jbr Factors that Influence Geotechnical Properties ....... 6Using CPT based Soil Classification .......................... 6
Accounting for Stress Effects in CPT Correlations ................. 8
* Outline of Dissertation ...................................... 10
Chapter 2 - Mohr Envelope Curvature and Development of the Stress Focus
Concept .. ............................................. 12
• Introduction .. . .. . . . . . .. . . .. . . .. .. . . .. . . . . . . . . . . . . .. . . .. 12
- Baligh Formulation of Curvature Envelope . ...................... 12
New Strength Normalization Based on Failure Envelope Curvature ...... 15
• The Stress Focus Concept. ..................................... 16
• Rock Mechanics and Friction Angle at High Confining Stresses ........ 18
v
Chapter 3 - Stress Normalization . ................................. 28
"* Introduction ............................................... 28
"* The Stress Exponent for Geotechnical Engineering . ................ 29
"* The Stress Focus and Stress Exponent Interrelationship ............... 34
"* Stress Type and Stress Normalization ............................ 34
"* The Atmospheric Pressure Standard . ........................... 38
Chapter 4 - Developing the Cone Resistance Normalized Formulation ....... 39
"* Introduction .......... ................................ 39
"• Comparison of Limit Equi -urn and Cavity Expansion Theories ...... 40
"• Exponential Behavioj of the _one Resistance ...................... 40
"* Development of the Cone Resistance Normalization Formulation ....... 44
Development of the Bearing Capacity Formulation for Clay ........ 47
"* Modification to the Bearing Formulation for Non-linear Exponential
Behavior ................................................ 49
"• Bearing Stress Formulation for All Soil Types .. .................. 50
Chapter 5 - Cone Resistance Stress Focus--Confirmation Using CPT Chamber
Test Data .. ............................................ 51
"* Introduction ............................................... 51
"* Interpretation of Large Diameter Test Chamber Data ................ 53
Explanation of the Conc Resistance Stress Focus ................ 54
Shallow and Deep Bearing Stress in Terms of the Stress Focus ..... .57
"• Using Chamber Data to Establish Trends of Stress Exponent and the Stress
F ocus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Evaluation of the Chamber Data ...... : .................... 60
"CPT Stress Exponent Evaluation . ........................... 61
Overconsolidation Effects on the Stress Exponent ................. 67
vi
. Chamber Boundary Effects for Dense Sands .................... 69
* SPT Chamber Evaluation ........ ............................ 76
* SPT Chamber Data Plotting ............................... 77
* SPT Stress Focus and Sand Type ............................ ! .
* Chamber Test Stress Exponent Discussion ...................... 87
* Conclusion ... ........................................... 92
Chapter 6 - CPT Prediction of CPT Normalization Parameters-Developed using
Uniform Soil Layer Data .. ................................. 93
"• Introduction ............................................... 93
"* Limitations and Merits of Using In Situ Data for Stress Normalization . .. 94
"• Establishing In Situ Uniform Layer Trends . ...................... 95
"* Establishing Cone Resistance Stress Exponents using the CPT Soil
Characterization Chart . .............................. 97D s,�s~�JC "•. ,TC..,J,,- -.. ,,.T- $11,, /-PT C-•.i
"tJ tý61t "I.)*L~t~ ýXr r§*W 1.-1 A LJ'.J$
Characterization Chart ................................ 99
"* Establishment of the Sleeve Friction Resistance Stress Exponent ....... 115
. Direct Correlation of Sleei e and Cone Stress Exponents ........... 115
"* Determining the Soil Type Dependent Stress Focus using Uniformn Soil
Layer D ata . ...................................... 119
* Developing ihe Stress Foct's RelationshipIfor Different Soil Types . . . . 119
* Soil Tvpe Dependent Trend of the Stress Focus ................. 125
- Conclusions .............................................. 127
Chapter 7 - Normalization of Selected Geotechnical Properties ............ 130
- Introduction .............................................. 130
- Standard ['enetration Test (SPTl) Normalization ................... 130
Historical SPT Blow Count Normalization .................... 131
SPT Blow Count Normalization ............................. 133
* Stresses at the SP' Sanpler.. ............................. 133
vii
* Mud Stress Influence at the SPT Sampler . .................... 136
* Stresses at the SPT Sampler for Field In Situ conditions ............ 137
Stresses at the SPJ' Sampler for Chamber Testing Conditions ....... 140
* C onclusion . .. . . .. . .. . .. . . ... . . . . . .. . . . . . .. . . . . . . . . . . 146
• Nornalization of the Shear Wave Velocity ...................... 148
Introduction ....... ...... .... ... .... . ... . ... .... ... .. 148
Definition of Normalized Maximum Shear Modulus ............... 149
Relating Maximum Shear Modulus to Shear Wave Velocity .......... 149
Relationships of Shear Wave Velocity Stress Exponent to Soil Type . .. 152
Shear Wave Velocity Stress Exponent trend from a Sand Site ....... 153
Relating Stress Exponents for Shear Wave Velocity & Cone Resistance 155
Conclusions .......................................... 158
Chapter 8 - Development of Correlations for CPT Prediction of Geotechnical
• Introduction . . ... .... ....... . ...... ..... ... ... . ... . ... .. 159
- T'he CPT and soil sample database ............................ 161
- Using the CPT Soil Characterization Chart to Predict Properties ........ 161
- Statistics and CPT Correlations .............................. 162
Bias Error Results from Stratigraphy ........................ 164
The Academic Quality Index (AQI) .......................... 164
- Developing CPT Predictive Contours .......................... 168
Use oJ the AQifor Developing Predictive Contours .............. 170
- CPT Prediction of the SPT blow count ......................... 174
Introduction . .. ... .... ... ..... .. .... .... ... . ... . .. . .. 174
J SPT Prediction using Both CPT' Measurements ................ 175
CPT Prediction of N, using the CPT Soil Characterization Chart .... 178
Discussion of CP'T Prediction of the SI'T Blow Count ............ 178
viii
"* CPT Prediction of Clay Undrained Strength, S. ................... 199
introduction . ......................................... 199
CP7' Prediction o.j... .................................... 199
Historical Means oJ Estimating NA for CPT Prediction of S,.. ....... 200
Determining Sul using CPT Soil Characterization Chart ........... 201
Establishment of Sul contours on the CPT soil characterization chart . . 203
Conclusions . ......................................... 234
"° CPT Prediction of Shea" Wave Velocity (Vs) ..................... 239
Introduction . ......................................... 239
* Minimal Stratigraphic Error when V, Measured by CPT sounding .... 239
* Historical use of both CPT Measurements to Predict Vs or Gm,.,a..... 240
* CPT Prediction of Ps, using Both CPT Measurements ............ 240
* Discussion of CPTprediction of V•. ......................... 248
Chapter 9 - Conclusions .. ....................................... 260
Reference . ................................................. 265
Appendix .. ................................................. 282
ix
List of Figures
Figure 1.1 The Cone Penetrometer Test (CPT) system .................. 3
Figure 1.2 The CPT soil characterization (Olsen, 1988) ................ 7
Figure 1.3 Using of stress normalization for CPT prediction of
geotechnica' properties ................................. 9
Figure 2.1 Failure envelope curvature effects for different relative densities
and sand types (Baligh, 1976) ... ...................... 14
Figure 2.2 Simplified representation of the Stress Focus using the
Mohr envelope curvature ............................... 1_
Figure 2.3 Strength Stress Focus described for Chatahoochee sand in terms of
friction angle and overburden sticss (data from Baligh, 1976) . . . 19
Figure 2.4 Strength Strcss Focus described for Sacramento sand in terms of
friction angle and overburden stress (data from Baiigh (i976)) . . 20
Figure 2.5 Effect of sand type on Stress Focus location ................ 21
Figure 2.6 Sacramento sand plotted in terms of strength versus
confining stress . ................................... 22
Figure 2.7 Components of shear strength in granular soils
(After Mitchell, 1993, and Rowe, 1962) ................... 25
Figure 2.8 Proposed interaction of friction angle effects and the
Stress Focus concept . ............................... 26
Figure 3.1 Representing geotechnical properties in tenns of exponential
behavior ........................................... 30
Figurc 3.2 Illustrating the paramneters to describe the curvatuic of the failure
envelopc for geotecctical engincering . ................... 33
Figure 3.3 Stress Focuts expressed using the stress exponent and
norm alized value .. .................................. 35
Figure 4.1 Comparison of the Classical Linmit Equilibrium based bearing
failure to Cavity Expansion bearing failure ................. 41
x
Figure 4.2 Approximately combining the classical limit equilibrium bearing
capacity formulation with non linear Mohr enVwlopc behavior . .. A
Figure 5.1 Proposed relotionship of cone resistance versus vertical eftective
stress trending fer a given sand (or soil) type .............. 52
Figure 5.2 Trends of cone resistance versus vertical effective stress for Ticino
sand (Baldi, et.al., 1981) .. ............................. 55
Figure 5.3 Replotting of Baldi, et.al., 1981 data curves fiom Figure 5.2 in
terms of Log1 0 net cone resistance versus
Logio vertical effective stress . ......................... 56
Figure 5.4 Annotated description of the cone resistance Stress Focus together
with bearing stress divided into vertical expression failure and
cavity expansion failure ... .......................... 58
Figure 5.5 Correlations between cone resistance and friction angle based on
limit equilibrium theories and laboratory chamber tests
(Campaneila and Robertson, 1983) ....................... 59
Figure 5.6 Net Cone resistance versus vertical effective stress for
Hokksand sand .. ................................... 62
Figure 5.7 Net cone resistance versus vfrtical effective stress for
Ticino sand (batch #1) . .............................. 63
Figure 5.8 Net cone resistance versus vertical effective stress for
Ticino sand (batch #2) . .............................. 64
Figure 5.9 Net cone resistance versus vertical effective stress for
Ticino sand (batch #4) . .............................. 65
Figure 5.10 Stress Focus locations for Hokksund and Ticino sands based on
evaluation of laboratory chamber tests .................... 66
Figure 5.11 CPT stress exponent range for several sands in terms of the
Relative density and CPT cone resistance stress exponent ...... 68
Figure 5.12 Relationship of the cone resistance stress exponent for
ovei consolidated sands in chamber tests ................... 70
Figure 5.13 Overconsolidation effects illustrated by comparing the conventional
xi
consolidation representation to the observed relationship of cone
resistance versus vertical effective stress ................... 71
Figure 5.14 Boundary effects on the measured cone resistance level in
laboratory chamber test in sand (Parkin and Lunne, 1981) ...... 72
Figure 5.15 The reduced cone resistance for dense sands due to "chamber size
effects" can be represented with h*,,her stress exponents because
all relative densities appear to have a common Stress Focus..... 74Figure 5.16 'Possible modification of the chamber based stress exponent for
dense and very dense sands ............................ 75
Figure 5.17 Cone resistance chamber data for a relative density of 33% for
Reid Bedford sand . ................................. 78
Figure 5.18 Cone resistance chamber data for a relative density of 45% for
Reid Bedford sand . ................................. 79
Figure 5.19 Cone resistance chamber data for a relative density of 67% for
Reid Bedford sand ................................. . 80
Figure 5.20 Cone resistance chamber data for all relative densities for Reid
Bedford sand together with the Stress Focus ................ 81
Figure 5.21 Cone resistance chamber data for Standard Concrete sand together
with the corresponding Stress Focus ..................... 82
Figure 5.22 Cone resistance chamber data for Platte River sand together with
the corresponding Stress Focus ........................ 83
Figure 5.23 Cone resistance chamber data for one relative density range of
O ttaw a sand . ..................................... 84
Figure 5.24 Cone resistance chamber data trends for Gibbs & Holtz data . .. 85
Figure 5.25 Comparison of SPT Stress Focus locations for different -ands to
the resulting trends o" Feldspar percentage and D5 . . . . . . . . . .. 86
Figure 5.26 Relationship between relative density and SPT stress exponent for
different sands from SPT chamber tests .................. 88
Figure 5.27 Comparison of the ranges for CPT and SPT stress exponents from
evaluation of chamber ciata ........................... . 89
xii
Figure 5.28 Relationship between SPT stress exponent and Feldspar percentage
at a relative density of 36% for chamber tests .............. .90
Figure 5.29 Interrelation of the Stress Focus and the stress exponent (for a very
loose sand condition) based on evaluation of CPT cone resistance
chamber data for increasing feldspar content ................ 91
Figure 6.1 Determining the cone resistance nonnalization value (q,,,) and
corresponding stress exponent (c) using uniform soil layers ..... .96
Figure 6.2 Example of in situ cone resistance data having a uniform soil layer
with the stress exponent, c, and normalized cone resistance,
qc., defined ..... .... .... . . ... . .. . . .... . .... . ... . 98
Figure 6.3 Using uniform soil layer data to establish cone resistance stress
exponent data points on the CPT soil characterization chart .... 100
Figure 6.4 Uniform sand layer at the Holmen, Norwiy
(N G I research site) ................................. 101
Figure 6.5 Uniform unstable silty clay layers for a Hong Kong Bay deposit
(airport replacement projeca) .......................... 102
Figure 6.6 Uniform sandy silt layer in the core of Ririe dam
(Corps of Engineers) ............................... 103
Figure 6.7 Uniform sand layer for project code DE-S-R ............... 104
Figure 6.8 Uniform silty sand layer it the Aftchafalaya River
(dredging study) .................................. 105
Figure 6.9 Uniform silty clay layer in the Aftchafalaya River
(Dredging study) .. ................................ 106
Figure 6.10 Uniform silt)y clay layers of the foundation
for Lucky Peak Dam (Corps of Engineers) ................ 107
Figure 6.11 Uniform sand layer segment at the McDondalds Farm, Sea Island,
C anada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Figure 6.12 Uniform silty sand layer at Salinas (Old Hilltown), California
(U SGS research project) ............................. 109
Figure 6.13 Uniform foundation clay layer (Leiee failure investigation) ..... 110
xiii
Figure 6.14 Establishing contours of cone resistance stress exponent using CPT
data from in situ uniform soil layers with constant relative strength 111
Figure 6.15 Comparing soil types from uniform soil layers to the CPT soil
classification line (from Olsen, 1988) ..................... 112
Figure 6.16 Annotated version of the cone resistance stress exponent chart
showing soil zones (and strength character) together with CPT soil
characterization line ...................................
Figure 6.!7 Relationship of sleeve friction resistance stress exponent (s) to the
cone resistance stress exponent (c) using uniform soil layer data . 116
Figure 6.18 Correlation of the s/c ratio (sleeve to cone stress exponents) to the
normalized sleeve friction resistance (f,1,) ................. 118
Figure 6.19 Proje, ions of trends for uniform in situ clay layers in terms of log
net cone resistance versus log vertical effective stress ......... 120
Figure 6.20 Compression curves for several clays and silty clays (from
Mitchell, 1993; Lambe & Whitman, 1969) ................ 122
Figure 6.21 Replot of selected soil types from Figure 6.20 in using stress
normalization format to show that clays have an approximate
Stress Focus . ..................................... 123
Figure 6.22 Projections of trends for uniform sand layers in tenns of log net
cone resistance versus log vertical effective stress ........... 124
Figure 6.23 Projections of trends for uniform soil mixture layers in terms of
Log cone resistance versus Log vertical effective stress ....... 126
Figure 6.24 The soil type dependency trend for the Stress Focus based on
uniform soil layer and laboratory chamber test evaluation ...... 128
Figure 6.25 Inferences concerning the soil type dependent Stress Focus ..... .129
Figure 7.1 Cn versus vertical effective stress (Kips/ft2) relationship developed
by Seed ct al. 1983 (Note: 2 Kips/ft2 = I atm) ............. 134
Figure 7.2 Back-calculated SPT C. parameters from field and laboratory
chamber test (Skempton, 1986) ........................ 135
Figure 7.3 Mud pressure effects on the SPT sampler .................. 138
xiv
Figure 7.4 Drilling mud pressure effects for the SPT sampler in
field boreholes ..................................... 139
Figure 7.5 Stress effects on the SPT sampler for historical laboratory chamber
tests due to a constant drilling mud stress at differing
confining stress levels . .............................. 141
Figure 7.6 Comparison of confining stress surrounding the SPT sampler
(or CPT probe) for chamber and field conditions ............ 145
Figure 7.7 Comparison of the ranges for CPT and SPT stress exponents from
evaluation of chamber data ............................ 147
Figure 7.8 Shear wave velocity versus depth for intermediate and saturated
firm natural soils (Lee and Campbell, 1985) ............... 154
Figure 7.9 Comparing the stress exponent ranges for shear wave velocity and
cone resistance . ................................... 157
Figure 8.1 Using CPT measurements to predict geotechnical properties .... 160
Figure 8.2 CPT Soil Characterization chart in terms of the normalized cone
resistance and normalized friction ratio (Olsen, 1988) ......... 161
Figure 8.3 Hypothetical example showing that soil lenses of differing soil
type (or stiength) can bias correlations .................... 165
Figare 8.4 Definition of a stratigraphic AQI of 76% (i.e. 76% of the soil
layers are continuous between the boring and CPT sounding) . . . 167
Figure 8.5 Description of a response surface ........................ 169
Figure 8.6 An illustration of the iterative technique for removing bias data
using the AQI index ................................. 172
Figure 8.7 Example using the Academic Quality Index (AQI) toward
establishing the best correlation line by excluding biased data . . . 173
Figure 8.8 Comparison of forces on the SPT and CPT devices (Schmertmann,
1979a) . ......................................... 176
Figure 8.9 Prediction of the SPT blow count, N, using both CPT
measurements (Olsen, 1988) .......................... 177
Figure 8.10 Prediction of the N,=2 contour on the CPT Soil Characterization
xv
C hart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Figure 8.11 Prediction of the N,=4 contour on the CPT soil
characterization chart . ............................... 180
Figure 8.12 Prediction of the N,=7 contour on the CPT Soil
Characterization Chart . .............................. 181
Figure 8.13 Prediction ofthe NI=15 contour on the CPT Soil
Choracterization Chart ... ....................... ... .. 182
Figure 8.14 Prediction of the N,=25 contour on the CPT Soil
Charactenization Chart . .............................. 183
Fi, ure 8.15 Piediction of the N1=35 contour on the CPT Soil
Characterization Chart . .............................. 184
Figure 8.16 Prediction of the N1=50 contour on the CPT Soil
Characterization Chart . .............................. 185
Figure 8.17 Final plot of the best fit SPT N, contours on the CPT Soil
Characterization Chart . .............................. 186
Figure 8.18 Contours of constant normalized sleeve friction resistance on the
CPT soil characterization chart ........................ 188
Figure 8.19 Example of CPT Prediction of SPT blow count with comparison
data (Barkley dam seismic evaluation study,
data from Olsen, et al, 1989) ........................... 190
Figure 8.20 CPT predicted versus measured SPT N, for the Barkley darn
seismic evaluation study (data from Olsen et al., 1989) ....... 19i
Figure 8.21 CPT predicted versus measured N, for sites on the East coast of
the US (data from project code LE-JN) ................... 192
Figure 8.22 CPT predicted versus measured N, for a CPT sounding through
the hydraulic core of Sardis dam ........................ 193
Figure 8.23 CPT predicted versus measured SPT N1 for a stiff/dense dirty sand
site (project code DE-S-R) ........................... 194
Figure 8.24 CPT predicted versus measured SPT N, for a site composed of soil
mixtures in Tracy California (project code WC-TSS) ......... 195
xvi
Figure 8.25 CPT predicted versus measured SPT N, for McDonalds Farm, Sea
Island, Richmond, British Columbia, Canada (University of British
Columbia research site)(data from Campanella, et al, 1982) ..... 196
Figure 8.26 CPT predicted versus measured SPT N, for the Arcadia Dam
seismic evaluation study ............................. 197
Figure 8.27 CPT predicted versus measured SPT N, at the Coyote North site
(near San Jose) California (data from Martin & Douglas, 1980) . . 198
Figure 8.28 Establishing Sul (i.e. c/p) contours on the CPT soil characterization
chart based on bearing theory for clay penetration ........... 204
Figure 8.29 Predition of the (Su1)Tuu=O.l contour on the
CPT Soil Characterization Chart ....................... 206
Figure 8.30 Prediction of the (SD)T1 uu=0.25 contour on the
CPT Soil Characterization Chart ....................... 207
Figure 8.31 Prediction of the (SUI)TxUU=0. 3 1 contour on the
CPT Soil Characterization Chart ....................... 208
Figure 8.32 Prediction of the (S0)TxUU=0. 3 9 contour on the
"CPT Soil Characterization Chart ........................ 209
Figure 8.33 Prediction of the (SuI)TxUU=0. 5 4 contour on the
CPT Soil Characterization Chart ....................... 210
Figure 8.34 Prediction of the (SuO)-xU0=0. 80 contour on the
CPT Soil Characterization Chart ....................... 211
Figure 8.35 Prediction of the (Sul)TUu 2 contour on the
CPT Soil Characterization Chart ...................... 212
Figure 8.36 Contours of normalized (Sul)TxUu (i.e. (Su)iuju/',,) on the CPT
soil characterization chart for theunconsolidated undrained triaxial strength test .............. 2i3
Figure 8.37 Prediction of the (-Sul)Fv,, = 0.25 contour on the CPT soil
characterization char't ............................... 214
Figure 8.38 Prediction of the (SI,1)F:van = 0.31 contour on *he CPT soil
characterization chart ............................... 21 5
xvii
Figure 8.39 Prediction of the (S1)Fvanc = 0.54 contour on the CPT soil
charactei ization chart ............................... . 216
Figure 8.40 Prediction of the (Sul)FV.e = 0.80 contour on the CPT soil
characterization chart ............................... . 217
Figure 8.41 Prediction of the (Sul)f:vae = 2 contour on the CPT soil
characterization chart ............................... . 218
Figure 8.42 Contours of (S.)6 , (i.e. (Su)FV., /aG'V) for the field vane shear
on the CPT soil characterization chart ................... 219
Figure 8.43 CPT predicted versus measured (Su0)Txt for silty clays from a
Fraser Ri, !r site, Vancouver i. -national Airport, Canada
(data from Konrad, et al., 1985) ....................... . 220
Figure 8.44 CPT predicted versus measured (SUI)Tuu for silty clay fromr_
Limma Mellosa, Sweden (40 km north of Stockholm)
(data from Larsson & Mulabdic, 1991) .................. 221
Figure 8.45 CPT predicted versus measured (SUI)TU for San Francisco Bay
mud at the Mumi Met-o tumnaround facility (the measured strength
data are located at 10 different elevawtons) (data from Dames &
M oore, 1992) .................................... 222
Figure 8.46 CPT predicted versus measured (SUO)Ttr for the Onsoy site in
Norway (NGI research site) (the mne•,surcd trength data are at
four different depths)
(data from Rad, et al, 1985, Gillespie, et al., 1985) .......... 223
Figure 8.47 CPT predicted versus measuredi (Su1)-ruu for San Franciszo Bay
mud at H-amilton AFB (University of California at Berkeley
research site) (data from projcc;,. code ET-SE) .............. 224
Figure ,8.,8,, CPT piedi'tcd vr-sus measured ( from Norrkoping,
Sweden (with measurements at 11 dif•kmnt depths) (a Swedish
Geotechnical Institute r,'sodrch site)
(data fron Larsson a..d Mulabdic, 1991) .................. 225
Figore 8.49 CPT predicted verus measured (Suj1Y1 Uu from the HXibernia
xviii
offshore investigation (data from Konrad, et al., 1991) ........ 226
Figure 8.50 CPT predicted versus measured (StOrxu for San Francisco bay
mud at the muni metro turnaround facility (with measurements
from 17 different depths) (data from Dames & Moore, 1985) . . . 227
Figure 8.51 CPT predicted versus measured (Sul)fv.e for a conference pile load
test at Northwestern University in 1988 (with measurements from
12 different depths) (data from Stratigraphics, Inc, 1988) ...... .228
Figure 8.52 CPT predicted versus measured (Sul)Fv,. for a foundation clay
layer for the Nerlerk Berm liquefaction slide study .......... 229
Figure 8.53 CPT predicted versus measured (SuI)Fva at the Fraser River Delta
Bridge, 25 km SW of Vancouver, Canada (with measurements
from 11 different depths)
(Data from Crawford & Campanella, 1991) ................ 230
Figure 8.54 CPT predicted versus measured (Sve for bay sediments at the
Hong Kong Airport replacement at Chek Lap Kok
(data from Dames & Moore, 1982) ..... ....... ....... 231
Figure 8.55 CPT predicted versus measured (Sul)Fv., at cower 232 Street,
Langley, British Columbia, Canada
(data from Campanella, et al., 1991) .................... 232
Figure 8.56 CPT predicted versus measured (Sul)FV,, at Barkley dam within
clay lenses (data from Olsen, et al, 1989) ................. 233
Figure 8.57 Illustration on how to calculate the Bjerrum V. correction factor
using the predicted Sul contours ....................... 235
Figure 8.58 Calculated contours of (3U)TxUU/(Su)FV on the CPT soil
characterization chart by taking a ratio of contours on Figure 8.36
to Figure 8.42 ..................................... 236
Figure 8.59 Correlation of PI to the Bjerrum p correction factor for
determining the undrained strength from field vane shear results
(Bjerrum, 1972) .................................... 237
Figure 8.60 Correlation of (Sul)Fv to PI to establish the overconsolidation
xix
character and then to get the Bjerrum [i correction factor
(Aas, Lacasse, Lunne, and Hoeg, 1985) .................. 238
Figure 8.61 CPT prediction of the maximum shear modulus using both of the
CPT measurements (Olsen, 1988) ...................... 241
Figure 8.62 Prediction of V,, = 150 ft/sec contour on the CPT soil
characterization chart ................................ 242
Figure 8.63 Prediction of the VS1 = 400 ft/sec contour on the CPT soil
characterization chart . ............................... 243
Figure 8.64 Prediction of the Vs1 = 650 if/sec contour on the CPT soil
characterization chart ....................... ........ 244
Figure 8.65 Prediction of the V,1 = 900 ft/sec contour on the CPT soil
characterization chart ................................ 245
Figure 8.66 Prediction of the Vs, = 1200 fl/sec contour on the CPT soil
characterization chart ................................ 246"L-• , r " ' -•... : . .I-^-•-. . .........-------- -- ;,-1! .f /'T x -_.. ,I u LL .U•, .VJ)I C no sflIL -lJUIlL UIL IIUIIII on ILdLIaII -,11 -W -•--V V- iU.,.;CLy I V] .; UII o It' LI- I
soil characterization chart ............................. 247
Figure 8.68 CPT predicted versus measured V.l for the Holmen site,
Drammen, Norway (NGI research site) (data from Christoff -sen
and Lunne, 1982; Gillespie, Lunne, and Eidsmoen, 1985) ...... 249
Figure 8.69 CPT predicted versus measured VS1 for a stiff/dense dirty sand site
in the U.S. (project code DE-S-R) ....................... 250
Figure 8.70 CPT predicted versus measured V,, for the Barkley dam seismic
evaluation study (data from Olsen, et al., 1989) ............... 251
Figure 8.71 CPT predicted versus measured V., for a site at Tuktoyaktule,
Bugmallit Bay, Beaufort Sea, Canada
(data from Campanella, et al., 1987) .................... 252
Figure 8.72 CPT predicted versus measured V,1 for a uniformly compacted
sand (data from project code DN-11J2) ................... 53
Figure 8.73 CPT predicted versus measured Vs1 for a site at Onsoy, Norway
(NGI research site) . ................................ 254
xx
Figure 8.74 CPT predicted versus measured V. 1 a, Treasure Island, San
Francisco, California (data from Hryciw, 1990) ............. 255
Figure 8.75 CPT predicted versus measured Vsl at the parameter levee area of
Santa Cruz, California (data from Hryciw, 1990) ............ 256
Figure 8.76 CPT predicted versus measured Vsi for the compacted silt core,
Lucky Peak dam , Idaho ............................. 257
Figure 8.77 Illustration why the predicted shear wave velocity contours on the
CPT Soil Characterization chart arc cui'ved ............... 259
xxi
List of 'Fables
Table 2.1 High pressure friction angles for sedimentary materials
(B arton, 1976) . ............ .................. ... ... 23
Table 7.1 Showing the equivalent (Gm.,), from historic Gmx formulations 150
"Table 7.2 Shear wave velocity pxirarneters determined from data presented by
Lee and Cmnpbell (1985) for differing soil conditions ........ 153
Table 7.3 Published strtss exponents for shear wave velocity .......... 156
Table 8.1 Typical Nk values for estimating the unconsolidated undrained
strength of clays using the CPT cone resistance (Olsen, 1994) . . 202
xxii
List of Symbols
DefinedSymbol Defifliioon npageC71,, Vertical effective stress 15
Gtota! Total vertical stress 47
atm Atmospheric pressure designation 38
(approximately 1 ton,/ft2 or 100 KPa)
Fmca Multiplication factor for a,' to convert to o 36
e General exponent val ue 32, 35
V Vertical axes, overburden stress 32, 35
1-1 Horizontal axes, geotechnical property 32, 35
III Normalized H property 32, 35
Hf H at the Stress Focus 34, 35
Yfll Confining stress at the Stress Focus for H 34, 35
qc Measured cone resistance 2, 3
qcl, Normalized cone resistance using stress exponent 49, 96
based on soil character at O,= I atm
(qc)nct net cone resistance 47
c Cone resistance stress exponent 49, 96, 113
f, Measured sleeve friction resistance 2, 3
'sic Normalized measured sleeve friction resistance 115
based on soil character at 0,= 1 atm
s Sleeve friction resistance stress exponent 115, 118
FR R- Friction ratio (%) (calculated) 6
FR1 = Rn, Normalized friction ratio using q, 1, and f,,, 100
qcf Cone resistance at the Stress Focus 54, 58
afc Vcrtical effective stress at the 54, 58
cone resistance Stress Focus
xxiii
qcn Normalized cone resistance Stress Focus 54, 58
ZC & Z4 General bearing factors 46
Drained friction angle 13
Drained friction angle at the Stress Focus 16
Vertical effective stress at 16
the friction angle Stress Focus
"" Normalized shear strength, atm units 15
t shear strength stress exponent 15
ýp Material friction angle 24
a Balighs' Mohr failure envelope curvature parameter 13
N Standard Penetration Test (SPT) blow count 76, 132
N1 SPT blow count normalized at o',= I atm 132
CN SPT normalization factor 67, 132
(a 5 C)C Vertical effective stress surrounding the 138
,31 1 san-..111 ei ULf .. P1 I chll icrt eýll~ L;,Ls
(USC)f Vertical effective stress surrounding the 138
SPT sampler for field situations
(as), Stress that influences the SPT blow count for 138
SPT chamber tests
(USA Stress that influences the SPT blow count for 138
field situations
n SPT stress exponent for normalization 88, 132
(from SlI1 chamber evaluation)
b Calculated Sl1T stress exponent relating (cS1), to (o•), 144
(for field SPT blow count normalization) (equals c)
Rm Reduction of the confining stresses at the 144
SPI sampler due to the low mud pressure borehole
effects for SFT chamber tests (%)
xxiv
Vs Shear wave velocity (units must be specified) 149
VS1 Normalized shear wave velocity at a'= 1 atm 152
(units must be specified)
v Shear wave velocity stress exponent 152
fps feet per second 149
mps meters per second 149
max Maximum shear modulus (units must be specified) 149
(Gmax) I Normalized maximum shear modulus, atm units 149
m Shear modulus stress exponent 149
Su Undrained cohesive strength (units must be specified) 47, 200
(Su)TxlfU Undrained cohesive strength based on the 203
laboratory triaxial unconsolidated undrained (TxUU)
test (units must be specified)
field vane (FVane) shear test (units must be specified)
S Sul Normalized undrained cohesive strength at oa,= 1 atm 48, 201a,, P
.S.0 Normalized undrained cohesive strength based 203
on the laboratory triaxial unconsolidated undrained
(TxUU) test at (j,= I atm
..:.,o I•. Normalized undrained cohesive strength based 203
on the field vane (F Vane) shear test
at o(,= I atm
It- (SU) -XUU Bjerruin field vane shear correction factor 205, 236
xxv
Chapter 1
Introduction
General
Site characterization, in terms ot geotechnical properties, can be the single most
important task for geotechnical engineering investigations. Characterization is
defined as "To rL veal and separate into categories" (Webster's New Collegiate
Dictionary, 197/5). Once a site has been realistically characterized in terms of
geotechnical property distribution, to the needs of a project, the foundation design or
foundation performance evaluation (e.g. liquefaction evaluation) can be done with
greater economy and reliability. Site characterization by drilling and sampling is
economically limited because of the small proportion of the subsurface sampled and
the relatively high cost of laboratory tests.
When the Cone Penetrometer Test (CPT) is used for a site investigation, the
industry standard practice for CPT data reduction has generally been to use only the
CPT cone resistance and calculated friction ratio; The measured dynamic pore
pressure is become more common as an additional CPT measurement. Most
CPT-based theories are derived cith-er tor clay or sand and therefore are not directly
applicable in a world of soil mixtures, dirty sands, and silty clays. Use of
techmiques for CPT prediction of geoteclnical properties that arc applicable to all
soil types (Olsen 1984, 1988, Olsen and Farr, 1986) have been constrained by the
limited amount of published verification.
"The goal of this research program was to develop improved techniques for CPI"
prediction of geotechnical properties. This goal was achieved by creating a large
database (of CPT and soil test results), developing new stress normalization
techniques, accounting for bias error due to stratigra)hy changes (between CPT
soundings and borings), and finally, by using the CPT soil characterization chart
(Olsen, 1988) to develop predictive correlations for Standard Penetration Test (SPT)
blow count, clay undrained strengths (laboratory unconsolidated undrained triaxial
test and field vane shear test), and shear wave velocity.
The CPT Test
The CPT test is performed by pushing a 3.57 cm (1.4 inch) diameter
instrumented probe into the earth at 2 cm/second while simultaneously measuring the
cone r-.qiqtance 2nd sleeve frictinn reoiqtqnrce na illuztrated in Figure 1.1 Cone
resistance (q,) is the axial component (,f the stress acting on the tip of the probe (10
cm2 horizontal cross sectional area) and sleeve friction resistance (f,) is the sliding
stress developed on a short cylindrical section of steel just above the tip (surface area
of' 150 cm2). The electric CPT has received wide acceptance throughout the world
and its use continues to grow. The advantages of the electrical CPT are: fast rate of
penetration (production rate up to 600 ft per day), higher accuracy and repeatability
(compared to the Standard Penetration Test (SPT)), and use of a computer data
acquisition system which allows for computer based evaluation. While there are
numerous additional sensors (Figure 1.1) that can be added io a CPT probe
(Lieberman, ct.al, 1991, Cooper, et.al., 1988, Robertson, et.al., 1986, FUGRO, 1980),
approximately 60% of all CPT work in the U.S. is done using only the two basic
measurements (i.e. q, and f, ). The CPT is also becoming the geotechnical tool of
choice for investigations where therc are local ClI' contractors and the site is
composed of clays, sands, or soil mixtures containing little or no gravel.
20 ton"• '
reactiontruck
Fluorescence
Downhole Seismic '-Measurements,V & V ,
s P , Sleeve Friction7' Resistance,--. ,/ f.
Resistivity -C--
Measured Dynamic I Resistane,Pore Pressure, u q
Optional Measurements Standard Measurements
CPT measurements
Figure 1.1 The Cone Penetrometer Test (CPT) system
3
The CPT can provide a large quantity of low-cost, repeatable, well-distributed
measurements distributed throughout a site. Alternatively, a few relatively
undisturbed soil samples may be tested in laboratory, but site va-iability generally
overshadows the benefits gained from a few specialty tests. CPT is becoming the
choice in situ exploration tool over the SPT because of the lower cust, repeatability,
continuous record, and quantitative nature of the data. The CPT is also easier to
interpret because the measurements are more fundamental. However, unlike the SPT,
it provides no soil sample.
The CPT Measurements
The two CPT measurements are remarkably unique. The cone resistance is
influenced by many geotechnical properties-it varies exponentially, in fact, with soil
frictiona lbehavinr For examp!,e, the cone resistnce cn be 200 tcn_/ft2 (tsf)
(20 MPa) in a sand, and as low as 3 tsf (300 KPa) in clays. The cone resistance can
therefore be considered an index of the sand skeleton strength (Douglas and Olsen,
1981). The CPT sleeve frictionl measurement is a high-strain sliding measurement
along a steel cylinder (after the soil has navigated around the cone tip) and is a good
indicator of loose or unstable soil structures (Olsen and Farr, 1986). While the cone
resistance has been the topic of extensive theoretical and experimental research (too
numerous to reference), there has only been limited research on sleeve friction
resistance (Olsen, 1984, 1988, Olsen and Farr, 1986, and Masood, 1990).
Developing CTPT Prediction Relationships for Geotechnical Properties
There are numerous means for establishing correlations of C111 measurements
with geotechnical properties. Laboratory chamber testing, while very useful, has
historically been. dane only on clean sands (silty sands have recently been tested in
4
laboratory chambers (Rahardjo, 1989)). Also, the results of CPT chamber tests are
sensitive to chamber boundary conditions. Theoretical formulations are typically
derived only for a particular soil type and must always be thoroughly verified with
laboratory and/or field test data. Laboratory-based correlations, while attractive for
pure sands and pure clays may be of limited usefulness in evaluating soil- composed
of mixtures o, these materials.
Historically, quantitative CPT correlations with geotechnical properties have been
based only on the cone resistance. CPT sleeve friction resistance was used only for
soil classification (Douglas and Olsen, 1981, Robertson and Campanella, 1984).
Researchers have typically compared CPT cone resistance (qc) and laboratory
strength test results (or field strength measurement results) in an X-Y scatter plot to
develop best fit correlations. CPI prediction of geotechnical properties should be
based on combination of the two basic CPT measurements (qc and f,) because these
measurements are always performed and each reflects different aspects of
geotechnical behavior.
Stratigraphic Influences on CPT Correlations
Using field data to correlate CPT results with geotechnical properties is an
attractive approach, however there are limitations. Stratigraphic vwiiation of soil
types and geotechnical properties between a CPT sounding and a nearby borehole
cani introduce major errors into a correlation. The use of uniform sites only would
significantly reduce correlation error, however, there are only a limited number of
well-documented uniform sites in the world, These uniform sites also do not
represent all soil types, and most importantly do not represent a wid2 range of
strengths (e.g. relative density for sand) for each soil type. It is therefore precfrable
to represent many soil types and relative strength levels by using sites with less than
perfect soil uniformity. Site stratigraphy (i.e. uniformity) must still be accounted for
5
when developing CPT correlations. A subjective quality index can be assig-led to
each CPT-to-boring comparison and used as a index for quantify'ing bias error
potential (e.g. a CPT encounters a clay layer but the nearby borehole encounters a
sand at the same elevation).
Accounting for Factors that Influence Geotechnical Properties
Many factors influence geotechnical properties and should be accounted for when
developing CPT-based correlations. The three factors of strongest influence are:
1) soil type, 2) soil state, and 3) confining stress level. Soil type and confining stress
are self explanatory. The soil state (i.e. void ratio at a standard confining stress
level) can be defined as the normalizcd geotechnical property level (e.g. Standard
Penetration Test (SPT) normalized blow count, N,). Therefore, a CPT technique for
predicting geotechnical properties must directly or indirectly account for all three of
these influencing factors.
Using CPT based Soil Classification
Soil type reflects the bulk soil composition in terms of sand and silt grain types
and sizes (if present) together with the clay type (if present). The CPT soil
characterization chart (Douglas and Olsen, 1981, Olsen, 1984, Olsen and Farr, 1986,
Olsen, 1988) can approximately predict soil type, primrily based on the observation
.hat the cone resistance is exponentially influenced by sand grain frictional behavior
and is therefore an index of the soil structure. The Olsen (1988) CPT soil
characterization chart, shown in Figure 1.2, represents the stale-of-thc-art for CPT
prediction of soil type from knowledge of the cone resistance (log scale) and friction
ratio (which is defined as the sleeve friction resistance a:; a percent of the cone
resistance level).
6
00- , O CPT Soil Characterizator- Number
600 IGP (SCN) for the displayed contour
400-N GRAVEL
20 AND v0 200- SANDS 6 •,'2•
E n%0. 40 ""•~ANDS ~~~
c 10 •CLEAN SAN(C
80 _SILTY SAND.
40- C
SAND MIXTURES C'20\/ SILTY SAND
ICLAYEY SANDI /\ SANDY SILT V it
CD
"• 10 \ SILT MIXTURESl:E 8^ \ " SANDY SILT -
8,ML CLAYEY SILT)
0 6 SILTY CLAY/
0 4- CL AYSexpenene t xponCLnAY
value (SILTY CLAY)
2-
S"/ LM•,,\'"•'•e'••O PEATS
Equivalent C
1-range1 - 1 o f ' . . . 1, " , ,
0.1 .2 04 0.6 0.8 1 2 4 6 8 10
Corrected Friction Ratio (%) in terms of tsf
f fsI1FR 1 = '1 100 = f 100 I00Li qc/(,)" qn ()(lfl)
Figure 1.2 The CP" soil characterization (Olsen, 1988)
7
Accounting for Stress Ljtkcts .4n CPT Ccrrelation.-
Confining stress influences CPT[ mea~suvements arid geotcchnical properties
differently. It will be shown that confining stress influences are dte),inderit on soil
type and relative strength. The. influenc- of confining stres-Z roust ber prop'ý-rly
accounied for when developing COrrelations of CPT to geoik.chnical vere.
Tceconfininig stress influwixces are also important du;ring prediction of grotechnical
properties using field CP1 data. If stress influences are not pr-operly considered,
geo'echnical properilies for shallow (e.g. 5 f,.et) or deep (te.g. 200 frct) situations may
be over- or unde-r-predicted by 50% or more. 0VI prediction of'normalizt'd
geotechnicai proper-les accounts for conlfirung stress influences on propefues.
TFhe process of using st~rcss normalization to predict geotechnical pro;)-rtik-s i*s
illustrate-d in Figure 1.3. CPT data arc initially nornialized to an cquival-it valuc: at
standard vertical effi-;tive stress (i c. a-imosphenc pressure) using stress exponeni
techniques. i normalized geotechnical plruper-ty is then predicted using the
normalizeaci PT values. Finally, the h.; situ property is determined using stress
exponent cconcepts. Tlhe stress normaiiization technique for CPT measurementqs arid
two geoicchnicall properties (i.e. SPT-N ,,alue and shiear wave velocity) are fufly
examined in this disser-tat)oni. NormJlized g-eotechnical properties Nwill be derived
lbaseci or, thc. CPT soil characterization chart.
8
CPT Boring
CPT Prediction ofgeotechnical properties
Normalized f /Ii Normalized \CPT' geotechnicaiparameters qc at O 1 atm e property /
Stress\ Normalization U t
\', Use stressnormalizationtechniques toinclude stresseffects
/- /
/ 7 L GeotechnicalU I t\ property 'I
¢ / /
CPT measurements
Figure 1.3 Using o' stress normalization for CPT prediction of geotechnicalproperties
9
Outline of Dissertation
High pressure triaxial testing of sands and the effect of confining stress level on
Mohr enveo, pe curvature are reviewed in Chapter 2, because for a given relative
density, the friction angle decreases with increasing confining stress. It will be
shown that this friction angle decrease continues until a specific confining stress is
achieved, namely the Stress Focus (corresponding to an approximate depth of a few
thousand feet). Specimens of all initial relative densities for a particular sand type
will have approximately the same strength (and density) at the Stress Focus, which
corresponds to a uncemented sedimentary rock strength. It will also be shown that
the decrease of friction angle with increasing vertical effective stress can be
explained in terms of dilation effects, grain crushing, and grain-to-grain rolling
influences.
The baw i stress exponent concept required for stress normalization and
determinati ( -f the Stress Focus is described in Chapter 3. Stress normalization is
achieved usi -j a stress exponent on the vertical effective stress.
CPT con resistance nornalization formulation for all soil types based on limit
equilibrium ai d cavity expansion theories is de-veloprd in Chapter 4. This
formulation al.,o accounts for the observed exponential relationship between cone
resistance and ,ertical effective stress.
CPT laboratory chamber test data are evaluated in Chapter 5. This evaluation
supports the contention that cone resistance can be represented by stress exponents
and the Stress Focus. Standard Penetration Test (SPT) chamber test data are also
used to show that the Stress Focus location is dependent on the sand classification.
10
CPT data from uniform in situ soil layers are used in Chapter 6 to establish a
technique for CPT prediction of tie stress exponent (required for normalizing CI"T
data). These data also show that the Stress Focus location depends on soil
classification.
New stress normalization techniques for SPT and the shear wave velocity are
given in Chapter 7. For the SPT, the constant drilling mud height used for
laboratory SPT chamber tests produces stress exponents that are too low. The
CPT-determined stress exponent (from Chapter 6) is thus recommended to be used
for SPT normalization. Shear wave velocity discussion will emphasize the need for a
soil type-dependent stress exponent that can be estimated using the cone resistance
stress exponent.
In Chapter 8, correlations are given for normalized CPT pararneters with the
fnolowing nnrmnalizetd oprtpehnirnal nron.-rtiP": SPT blow count, uMrdrnend c-hsiv
strength based on the unconsolidated undrained triaxial test (TxUU), undrained
cohesive strength based on the field vane shear (F Vane), and shear wave velocity.
These correlations are represented as contours on the CPT so] characterization chart.
Each contour was established using an Academic Quality Index (AQI) to subjectively
remove bias due to stratigraphic soil type changes between CPT soundings and
boreholes. Increasing the inclusionary AQI level increases the data group quality by
removing lower quality data.
The dissertation conclusions and recommendations for future research arc given
in Chapter 9.
11
Chapter 2
Mohr Envelope Curvature and
Development of the Stress Focus Concept
Introduction
Curvature of the Mohr failure envelope (i.e. a gradual decrease in failure
envelope slopc with increasing effecti ie stress) is well-known. It is incorporated in
many nonlinear behavior theQries but is rarely used in geotechnical engineering
practice. Mohr envelope curvature can be quantified analytically, but there are no
comprehensive means for predicting the actual curvature parameters based on soil
type and relative strength (e.g. friction angle for sands). At present, these Mohr
envelope curvature parameters can only be determined with a series of triaxiai tests
conducted using a wide range of confining stresses for a given sand type and a given
initial relative density. Mohr envelope curvature and the Stress Focus concepts
presented in this chapter arc the foundation for the CPT stress normalization
techniques in this dissertation.
Baligh Formulation of Curvature Envelope
Baligh (1976) imt-roved precedent cavity expansion theory by incorporating tlit
effects of Mohr failcre envclope curvatwi,.. Figure 2.1 summarizes the effects of
12
failure envelope curvature observed by Baligh (1976) in terms of friction angle for
several types of sanus and relative densities. Baligh (1976) quantified failure
envelope curvature and incorporated its effects into cavity expansion theory. He
proposed Equation (2.1) to express failure envelope curvature for laboratoiy triaxial
tests.
= + 1(2.1)
where
= Reference friction angle at o' = 1 ton/ft2 (tsf)
c = Balighs' Mohr failure envelope curvature parameter
The curvature parameter, ox, can be used to modify the reference friction angle, o,
at the reference stress level, u., as shown in Equation (2.2).
tan = tan4o - tanu aLog10o('l (2.2)
where
o = vertical effective stress (tsf)
= friction angle at ov
This curvature parameter (tan (x) is simply the semi-log slope for givcn relative
density trend in Figure 2.1. Baligh made no other inference concerning the trends
in Figure 2.1 concerning sand type or relative density toward the Mohr envelope
curvature parameter, a.
13
A?~ AO Do w(/~f
Rf/ovi 17 0 Ma"~%E~ i9V 4.0' OIUAwpr&/ (IIflde)
a ChwmeAr'm 00v 7I r~ 44"c do' 6,40 R'.W.,
ILus
Atrmv/ Jibra ten lAg /i/j P/vmat ef Athww, cr(Ay/avw.)
Figure 2.1 Failure envelope curvature effects for different relative densities andsand types (Baligh, 1976)
14
Yareshenko (1964) proposed an expression for the Mohr failure envelope
curvature of the form
"r = (ko)lln (2.3)
Baligh (1976) believed that Equation (2.3) was elegant and convenient for analytical
computations, but that it was inadequate for practical applications. He maintained
that there were many combinations of k and n that could fit experimental results
because they were obtained from log t versus log a plots.
New Strength Normalization Based on
Failure Envelope Curvature
A new exp~ession was developed by the author (Equation (2.4)) to describe
failure envelope curvature. This "stress normalization" technique will be fully
expllaned in Chapter 3. The normalized shear strength, cr1, in Equation (2.4) is the
shear strength at a vertical effective stress oi 1 atm. The proposed exponent-based
normalization formulation in Equation (2.4) is similar to that of Equation (2.3),
except that normalization concepts are used.
'Ut (2.4)
where
(o',) a, Vertical effective stress in units of atm pressure
(approximately tuns/ft2)
" = Shear strength at o,, in units of atm pressure
"• = Shear strength at ',= 1 atm (i.e. tan(%l))
t= shear strength stress exponent
15
This formulation overcomes the limitation stated by Baligh (1976) concerning the
Yareshenko (1964) equation, namely that several combinations of k and n can fit the
same set of data. For loose sands or clays which have little or no failure envelope
curvature, the JBaligh Mohr envelope curvature parameter, (x, is approximately zero
and the stress exponent is approximately 1 (or slightly less). For the dense Ottawa
sand in Figure 2.1, (4 is approximately 80 and the stress exponent (t) is 0.86. Each
of the constant relative density trends in Figure 2.1 can be expressed using
Equation (2.4) with a constant stress exponent.
The Stress Focus Concept
It would appear from Figure 2.1 that the only means to determine the stress
exponent (e.g. curvature parameter) is with a thorough laboratory strength testing
program. however, close examination indicates that all sands have approximately
the same friction angle at some high overburden stres:, between 70 and 300 atm
irrespective of the initial relative density. The overburden stress (of,) where
specimens of all initial relative densities have the same approximate friction angle
(ýf), is defined as the "Stress Focus". The Stress Focus is therefore a "hinge" to
which trends associated with a given soil type and all relative densities converge with
increased overburden stress as illustrated in Figure 2.2. This Stress Focus occurs at
a confining stress equival-nt to a depth of several thousand feet below gro. .i-d
surtace.
Data for the Chatahoochee 1,nd Sacramento sands in Figure 2.1 werc replotted as
shown in Figure 2.3 and Figure 2.4, respectively, to illustrate the effectv; of failure
envelope curvature and the resulting Stress Focus. These plots depict vertical
effective stress on the vertical axis as a log scale with the values increasing in the
downward direction. The dashed least square fit lin,:s are also shown for each initial
relative density group. These 30 year old data represent the best quality high stress
16
Sedimentary Rock Strength Behavior,
"�"--28 to 33 degrees-
Mohr Envelope C Aivature Stress
03-o1 - -
-/-
//
03
NOTE: Overburden Stress at the Stress Focus =expanded 70 to 300 atm (atmospheric pressute)simplified (e.g. 7 to 30 MPa or 70 to 300 tsf)
representation
Figure 2.2 Sinplified representation of tile Stress Focus using tlic Mohr envelopecurvature
17
tests available on sand. Other published data do not encompass the range of
confining stresses and the number of relative density groups represented in this data
set.
Figure 2.3 and Figure 2.4 indicate that at the Stress Focus the friction angle is
the same irrespective of the initial relative density from which the samples were
consolidated. Dense sands therefore have decreasing friction angle with increasing
confining stress until the Stress Focus is reached. At the Stress Focus, initially
dense and loose sands have the same friction angle. Loose sands have little Mohu
envelope curvature and therefore very little change of friction angle with depth.
When the figures are combined (Figure 2.5), the result suggests that the Stress Focus
location is dependent on sand type. Stress Focus location dependence on soil type
will be further demonstrated in Chapters 4 through 6.
Figure 2.3 and Figure 2.4 are plotted in terms of friction angle whereas
Equation (2.4) is expressed in terms of strength. If data for Sacramento sand (from
Figure 2.4) is replotted in terms of drained Mohr Coulomb strength (i.e. o'vtan(Q))
versus ao,, the result is shown in Figure 2.6. The effect of Mohr envelope
curvature in Figure 2.6 is not as obvious as in Figure 2.4, but the stress exponent (t)
(i.e. slope) and tj can be determined directly from this figure and used with
Equation (2.4).
Rock Mechanics and Friction Angle
at High Confining Stresses
The Stress Focus (for friction angle) appears to occur at a overburden stress
range between 70 and 300 atm. Barton (1976) sunimarized rock strengths at high
stresses (greater than 80 atm) for sedimentary rocks (e.g. sandstone, shale and
18
'r mctfoy angle
30 "10 4'
oi
I
"" 9 K/ 00
0 1 0
I . 0O0--n'% i u i ""I,,
7 A 0 -
o /- Stress 1ocu:, for
z -cuoj 0' " Chatdhooche'c sendq ...- •-..... "/ O,- 3
S ' " "-) .c/ * , * - 3 0 0 A tuu '
Cit-luo 0,' Sall)/ usig do I 3 ron lolil I
Figure 2.3 Strength Stress Focus described for Chatahoochee sand in terms of
friction angle and overburden stress (data from Baligh, 1976)
19
Friction ;Lnfl(b-
30 '15..)
-iU
stesY1U o
Muh 2~%6 j ~ILV- oS~s ,(
1)j 10-.
Fiur .4 Sregh tes --cs ccrbe orScrrmt an n eUsoficto [nl-nJ vrbre tes dt rmBai 17)
- I r20
Friction) angle
3035 40 .15
0 1
/ (Data front l3aligh 1976)1000 Morenecr curvatur sa o Stres locus
- arraincrto sn statistlcal trenld%
Chnatairomc-i sand 1)r r1'ChIitar,'jchv said, D, 3'
100 o ~ 04 0. 0______
Sli $slotus for -stress Focus lotSact arricylto Solid Chlrtuituoclr('c sariti
Figure 2.5 Effect of) sand type on Stress Focus location-
21
4
Strength (atn; units)
10 100 1000
4
-i - 1:1 Atiu-- 7
10Dr - 10(..
"--4 E 3
100
o •mZ
Sg' -220 Atm - ..
i 220
-1 /
- -'-tf cSS 1O0tlS for-ýacrCalflvrltC, S;ond
1000-
Mohr envelope Clirvaturc to Stress FouCs(data front Libligh 1976)
I D, 1 00%'
] Dr 3 8 %
Figure 2.6 Sacramento sand plotted in terms of strength versus confining strcss
22
siltsione) as shown in Table 2.1. This table indicates that the friction angle (at high
confining stress levels) increases from a range between 250 and 30' for clay based
sedimentary rock (e.g. chalk, shale, and slate) to a range between 30' and 340 for
quartz-based Sedimentary rock. The friction angles at the Stress Focus (ýf) for
Chatahoochee and Sacramento sands are approximately 320 and 310, respectively
(from Figure 2.3 and Figure 2.4). This is within the range of 30 to 340 for quartz
based sedimentary rock at high confining stress. It therefore appears that sand starts
to behave similarly to a sedimentary rock at the Stress Focus.
Table 2.1 High stress friction angle for sedimentary materials (Barton, 1976)
Material High pressure friction Referenceangle (not having
dilative behavior)
Sandstone 31-34 1 Coulson, 1972
River sand 30 Vesic & Barksdale,(normal stress of 196430 to 630 atm)
Siltstone 27-32 Coulson, 197231 Hobbs, 1970
Shale 27 Ripiey & Lee, 196232 Hobbs, 1970
Chalk 30 Hutchinson, 1972
Mudstone 27 Hobbs, 1970
Slate 25-30 Barton, 1971
Dilation effects in granilar materials can explain the friction angle versus
confining behavior at stresses less than that at the Stress Focus. Dilation is defined
as volume increase with shear. Figure 2.7 shows tla. the observed friction angle
during shear at typical geotechnical confining stress is caused by thc. accumulative
effect of: volume increase effects during shear (i.e., dilation), grain-to-grain
23
rearrangement and material frictional behavior (4)). All influences except the
material frictional angle (4)) vary with confining stress level (Mitchell, 1993). This
figure illustrates that dense sands have high measured friction angles due to the
dilation and frictional effects. On the other hand, very loose sands, at the critical
void ratio, exhibit a friction angle due only to grain-to-grain rearrangement and
material frictional effects. For dense sands at low confining stresses (e.g. 1 atm),
dilation behavior is a major conitributing factor toward the strength level. For
example, gravel ballast for railroads has a low overburden stress but very high
resistance to dilation. Dilation effects therefore increase the apparent friction angle
for dense sands.
Initially dense sand appears to have the same strength as initially loose sand at
the Stress Focus aý shown in Figure 2.5. Very loose sands do not dilate at any
confining stress and therefore exhibit no dilation effect at the Stress Focus. Dense
decrease with increased depth to a minimum (or near zero) level when the Stress
Focus is achieved as illustrated in Figure 2.8.
The density for different initial relative densities at the Stress Focus is an
important issue. Sand density will incitcase with increasing consolidation pressure.
Initially loose sands will consolidate (i.e. density increase with increasing confining
stress level) at a higher rate than initially dense sands. if initially loose sands and
initially dense sands have the same strengt") at the Stress Focus, then the densities
may also be equal at the Stress Focus. Moi, likely, the density difference between
initially loose and initially dense sands at the Stress Focus are probably evident but
minor.
The Stress •ocus represents the overburden stress where soil-like behavior
becomes (sedimentary) rock-like behavior. It also providcs a comprehensive means
of relating the initial relative density to confining stre:s level. The Stress Focus
24
46
42 - OM
42 Dilation
-cv
43
30 Rearrangement
S, ,,.-Crushing (estimated)
26 Z:=",- 'Densest i, True friction ,-- Critical Void
,-Packing To Zero Ratio
- I I I26 30 34 38 42
Porosity, n (%)
Figure 2.7 Components of shear strength in granular soils(After Mitchell, 1.93, and Rowe, 1962)
25
LOG strength (or CPT Cone Resistance)
4.)
>1
-1 , • "--.Dilation Effects
-Stresso ~Focus
Figure 2.8 Proposed interaction of iriction angle effects aiid thc Stress Focusconcept
26
therefore appears to be a fundamental geotechnical property which can be useful for
soil behavior evaluation at all overburden stress conditions.
For confining stresses greater than the Stress Focus, strength is achieved by
material friction, grain .rushing, and grain rearrangemeiit effects (which can be
considered as a minor dilative behavior (Bruce, et.al, 1966). Shear occurs through
the grains or at the grain-to-grain contacts because there is little potential for
granular rearrangement at high confining stress levels (Vesic and Clough, 1968).
27
Chapter 3
Stress Normalization
Introduction
Nonnalization as defined by the Webster's New Collegiate Dictionary (1975) is
"to reduce to a norm or standard". In geotechnical engineering, stress normalization
allows a variable geotechnical property to be reduced to an equivalent value at a
standarrd cnnfining qtre- The eaief-t nhtnined stanard rcnnfining streq fnr
geotechnical stress normalization is the vertical effective stress. It is the only
confining stress parameter that can be accurately calculated. The standard confining
stress unit should also be atmospheric pressure because English or metric units, are
arbitrary stress units.
Stress normalization enables an equation together with correlation curves to
cover a wide range of confining stress conditions (analogous to dimensionless
analytical solutions). Therefore, normalized CPT measurements can be used to
directly predict normalized geotechnical properties even though the confining stress
influences on tlhc CPT parameters and on the geotechnical properties may be
different.
'[his chapter will describe the basic stress normalization concept using stress
exponents. While the exponent is a basic mathematical concept, a full explanation
using geotechnical engineering terminology will simplify the discussion in this
28
dissertation. The Stress Focus, introduced in Chapter 2, will also be described in
terms of the stress exponent.
The Stress Exponent for Geotechnical Engineering
CPT measurements (in fact, all geotechnical properties) have some degree of
nionlinear dependence on increasing vertical effective stress. Curvature of the Mohr
envelope was quantified using a stress exponent in Chapter 2. When the behavior of
a geotechnical property is represented with an exponent of the vertical effective
stress, the representation is referred to as stiess exponent-based stress normalization.
Lineai and exponential behaviors shown at the top of Figure 3.1 become straight
lines on a log-log plot as shown at the bottom. Linear behaviors have slopes of one
to one and exponential behaviors have slopes which are not one to one. The
exponential slope is equal to the horizontal stress exponent (e) for a given log unit of
vertical overburden stress.
An exponentially curved line in Figure 3.1 becomes a straight line on a log-log
plot and can be expressed numerically with the following equation;
H = C V" (3.1)
where
II = horizontal ax*
V vertical axis
e = V exponent
C = Constant
29
Property Level (H)
r• Stress Level
LOG Property Level (H)
S o-Standardized"Tj Stress Level 1\Be.vio
Exponential LinearSBehavior (Equivalent
' linearfailureEnvelope) behavior)
Y
Figure 3.1 Representing geotechnical properties in terms of exponential behavior
30
This expression can be rewritten to represent the horizontal value when the vertical
axis is equal to 1:
H =H (3.2)ye
where
H1 IHorizontal axis value vwhen V= 1
The exponent in Equation (3.2) must be specified with a reference such as the
"V exponent" because the exponent is applied to V and the slope is equal to the
fraction (or multiple) of the log10 H for one loglo V cycle. This V exponent (e) is
the transformed slope on the log-log chart, namely the distance e for a given V as
shown in Figure 3. 1. Lines which are nearly vertical have very little V axis
dependence and therefore a V exponent of approximately zero. A linear relationship
with a 1:1 slope (i.e. 450 line) has a V exponent of 1.
In geotechnical enginecring the vertical axis is generally taken to represent
vertical effective stress (o',,) and the exponent is referred to as the stress exponent.
The stress exponent is thus equal to a fraction or multiple of the Alog10( property )
over one log,0 o', cycle. The normalized property value (e.g. H1 in Equation (3.2))
is simply the H data trend projected from a uniform depth zone to the - 1
31
horizontal line as shown in Figure 3.2. Stress exponent-based stress normalization
for geotechnical engineering is therefore defined as:
H - H (3.3)
where
G'•, = vertical effective stress (atmospheric pressure units)
H1 = The H property at oa'=l atm
H The H property at the oa', stress Ilvel
e - Stress exponent
32
Measurementor
H H Property Level
HI H
O 1 a t m --.-- ------------------------------....-'-
", Equivalent
\ LinearBehavior
VetialH , Failure
Effective IEvlp
Stress OR(atmn urfits)
Figure 3.2 Illustrating the parameters to describe the curvature of' the failureenvelope for geotechnical engineering
33
The Stress Focus and Stress Exponent Interrelationship
The Stress Focus, introduced in Chapter 2, represents the vertical effective stress
where all trends of relative density (i.e. curved Mohr envelopes) intersect.
Figure 3.3 is a generalization of the Stress Focus concept with one stress exponent
trend shown. Equation (3.4) is a simple representation, in terms of log scales, of the
stress exponent line in Figure 3.3 which can be simplified as shown in
Equation (3.5).
Log H1 + (log offf - log( 1 ))e = Log H. (3.4)
SHf -- /1 (o)fl,) (3.5)
Equation (3.5) shows that the H level at Stress Focus (H,) is equal to the
normalized value (i.e. H- at o = 1 atm) times the confining stress at the Stress
Focus (am) raised to the e power. Only three of the four parameters in
Equation (3.5) are required to define an expression. For example, if H, and e are
known and oaf- can be reasonably estimated, then the 1I level at the Stress Focus
(Hf) can be calculated.
Stress Type and Stress Normalization
Stress normalization using the vertical effective stress will be shown in this section
not to introduce error even when a particular geotechnical property is dependent on,
for example, lateral stress. CPT measurements and geotechtical properties are
controlled by either vertical, mean, octagonal, or lateral stress. This stress type
merely reflects a multiple or fraction of vertical effective stress. For example, mean
stress is equal to the average of body stresses on the three principle axes as shown ii,
34
LOG Measured Value (H)
1 10 100 1000 10000S0.1
,r-Normalized H
SHf! HI"1. a 1 Atm--2. a,' - 1 Aim
,.J A,,- Data trend forarticular
relative.e density
e toward the". 10.0
qtrt,--I ........
-"I. I
Different relative density \trends to the Stress FocHs ---
100.0(J
Stress Focus for H
1000.0
Figure 3.3 Stress Focus expressed using the stress exponent and normalized value
35
Equation (3.6);
ov + Ch 4 oh (3.6)Omean 3 -
All the terms in Equation (3.6) can be defined in terms of vertical effective stress
(',,) as shown by Equation (3.7) and finally by Equation (3.8).
,mean (1 +2K 13 (3.7)
3(3.8)Gm,W= = a, F- (3.8)
The mean stress in Equation (3.8) is a product of' a, and the stress factor, Fnxa,ý;
F I (3.9)mean 3
This stress factor can be generalized as F. with the * representing vertical, mean,
octagonal, or lateral stress. If K. does not change appreciably with -onfining stress
level then F. will remain consLant for all stress levels. The ao, F. expression can be
36
substituted into the basic normalized stress equation (Equation (3.3)) with the result
shown below;
HB ( H e (3.10)(a'v F.)°
which equals;
HH1 H (3.11)
where
H,= B, (F,)e (3.12)
•,,ivticn (q 1n1 i rtnw ennnm ti-) the h•.•ir- streS, nnrm-li7ation exnression (Euniiation
(3.3)) with I-1 in temis of F. (Equation (3.12)). If Ko (i.e. Fmean) does not change
with verticai efiective stress level, then H , is a constant (for a given soil type and
relative strength). Correlations by Kulhaway and Mayne (1990) have shown that K,
(y.g. Fmun ) changes very little with increasing ou'. Therefore, the stress type
(necan, lateral, etc.,) or K. are not required for stress normalization as long as the
overconsolidation level (or normally consolidation condition) remains constant for all
stress levels. As a result, oa can be used as the normalization stress type even if
the geotcchnical property is controlled by another confining stress factor (e.,;. mean
or lateral stress).
37
The Atmospheric Pressure Standard
Standard atmospheric pressure provides a convenient basis for expressing
geoteclmical properties. There is only one standard stress level and that is the
atmospheric stress-any other stress units such a KPa or psi (pounds/inch2 ) are based
on arbiLrary units. Atmospheric pressure (atm) is not a usual engineering pressure
level but is very close to the English ton/foot2 (tsf) or one kilogram force per
cm2 (Kgf/cm2 ) or bars units as shown below:1 am = 1.058 =1.033 Kg9f 1.013 bar = 101.32KPa (3.14)
ft 2 Cm 2
The conventional geotechnical engineering method for expressing normalized
parameters is shown in Equation (3.15) with Pa equal to the atmospheric pressure.
H HiPa (3.15)
Equation (3.15) adds an additional factor of complexity to a simple concept.
Moreover, if Equation (3.15) expressed in tenns of H1 the following is produced;
H
L(a¶ J(3.16)( 2p)1-eI
This final expression is more complicated than Equation (3.3) for stress
normalization because stress units are not atmospheric pressure units. Therefore,
atmospheric pressure (atm) is used for stress units throughout thUs dissertation to
keep the stress notation simple and because normalization concepts will become more
complex.
38
Chapter 4
Developing the Cone Resistance
Normalized Formulation
Introduction
A cone resistance normalization formulation allows the equivalent cone resistance
at o' = 1 atm to be determined. Cone resistance normalization is an integral part
of the process toward predicting gectechrdicai properties. It possible, it should have a
theoretical background rather than only match the trend of laboratory data. The
formuiation should be simple and not require elaborate laboratory test-based
properties as input to the fbrmulation. It should also account for exponential
behavior using the stress exponent concept from the previous chapters.
A CPT cone resistance norrnalization formubttion, based on gencralization of
bearing capacity formulations, iL develope:d in this chapter. The bearing capacity
formulation considers both limit equi!ibriuri techniques (for shallow bearing failures)
and cavity expansion theory (for deep bearing failw s). The observed non-linearity
of cone resistance with verical eficctivc strc.ss will also be introduced mid analyzed
further in Chapters 5 and 6.
"19_39
Comparison of
Limit Equilibrium and Cavity Expansion Theories
Most theories for the bearing capacity of both deep foundations (e.g. piles) and
penetroincters have severe shortcomings. During the initial half the 20'h century,
bearing failure were evaluated using limit equilibrium (i.e. surface expression)
theories. Th1ese classical limPi equilibrium the:ories assume soil movement upward to
the ground surface using resisting stresses on wedges (Vesic, 1972, Terzaghi, 1943)
as shown at the left of Figure 4.1. Limit equilibrium theories are based only on
Mohr envelope strength parameters (i.e. c and 4). In the 1960's aid 1970's, cavity
expansion *theories (Vesic, 1963, 1972) were shown to beter describe bearing failure
at great depth. Cavity expansion theory assumes a hypothetical spherical orcylindrical exp...i. C a.. ca...... ' during ;"t,"r,i•.i"of ar retrcvmeter ol ....... t f the
riomh! of Figure 4.1. Cavity expansion theories are based on non-linear strength
descriptors and volume change parameters. The --one resistance behavior in
laboratory chambers has also been computer modeled using cavity expansion theory
together with hyperbolic modeling of the elastic zone (Tseng, 1989).
Exponential Behavior of the Cone Resistance
Classical limit equilibrium (surface expression) theories esult in bearing stresses
which arc linearly proportional to vertical effective stress (Terzaghi and Peck, 1967,
Durgunoglu ana Mitchell, 1973, 1975). Cavity expansion theories, on the other
hand, produce a non-linear exponent-based relationship of cone resistance with
overburden stress (Vesic, 1972). Cavity expansion theories also show more
exponential curvature when soil compressibility and Mohr envelope curvature effects
are included (Baligh, 1975).
40
Limit Equilibriumfor Shallow depths
toward ground
surface)
The transitionbetween LimitEquilibrium andCavity Expansionis called the Cavity ExpansionCritical Depth at depth
Figure 4.1 Comparison of the Classical Limit Equilibrium based bearing tailur-e toCavity Expansion bearing failure
41
Combining a curved Mohr envelope effect with the simplistic limit equilibrium
bearing formulation, as illustrated in Figure 4.2, can also create a decreasing,
non linear exponential dependence of cone resistance on vertical effective stress.
However, the magnitude of curvature is less than observed in laboratory chamber
tests. Therefore, the effects of Mohr envelope curvature provide only part of the
answer toward defining cone resistance to vertical effective stress behavior.
It will be shown that an exponent of the vertical effective stress (introduced in
Chapter 3) can chaxacterize the curved cone resistance behavior observed from
chamber tests (in Chapter 5) and from CPT tests in uniform soil layers
(in Chapter 6). Tl-:is stress exponent is based on observed data and accounts for
contributing factors such as Mohr envelope curvatuare, cavity expansion effects,
compressibility, grain crushing effects, and others. The cone res'swrce normalization
*.,C.IJ.I.•,.U q u ..JV.U 11 U11• i.41..jl'"J- a 1c is LeI ..uaz • 11 •,4.1WL'UJ tbk !.J. iJiL. lit e1LIo
data in later chapters.
Ix
!2
Non linear failure envelope-Non Linear failure envelope---
The linear andn on linear en velop es o; =. I tsf - _
equal at this point /
4
q -C
(Linear envelope)
qc
(Non linear envelope)
qc _VERTCAL
I Inferred
failureG,• -- p path
Figurt 4.2 Approximately combining the classical limit equilibrium bearingcapacity fonn-ulation with non linear Mohr envelope behavior
43
Development of the
Cone Resistance Normalization Formun ation
Limit equilibrium and cavity expansion bearing theories ac similar in that they
both have cohesive and frictional bcaring factor conoiv)eentst. The classic limit
equilibrium formulation for bearing failure stress is shovr- in Equation (4. i)
(Terzaghi, 1943):
go -- ck , + oN$9 + I ByN C, (4.1)_2 (4
where
qo= Bearing capacity
N1, NY, P1 = Bearing capacity factors as a function of
, , = Bearing capacity shape factors which depend on the soil
angle of internal 'friction (during shear) and shape of the
bearing surface
c = Cohesion ,or shear strength intercept)
G Confining stress
' = Soil unit weight
B = Strip footing width
44
The classic spherical cavity expansion formulation is shown in Equation (4.2)
(Vesic:, 1972).
P = cFC + oo (4.2)
where
PL = Cavity expansion pressure
F; and F = Dimensionless cavity expansion factors
(I I=- Effective mean normal stress
c = Soil cohesion4 sin2ý
Fq3 (I + sinf r) ý('3 -sinc) (I4)
FC (F )- i)cot4
Ir1In. •1 +- T A
Ir Rigidity Index = =ES 2 1v)
A = Average compressive volumetric strain in plastic zone
G = Shear modulus
E - Young's modulus
S = Soil shear strength (c 4 cr'tanm)
The cavity expansion pressure is the pressure required to expand a cavity in situ
(;.e. pressure required to expand a balloon at some depth). Cavity expansion
pressure is related to bearing pressure because a cavity must be opened for the
penetrometer to advance. While cavity expansion is simple in concept, converting it
to bearing pressure is not a trivial task. The cavity expansion pressure level V; still
related to the bearing pressure level, in general.
45
Both of these formulations can be summarized for penetrometers as shown in
Equaticn (4.3) using the Z, and Z, bearing factors.
qc = Zc C + Zo a (4.3)
where
qc bearing stress
ZC : cohesive bearing factor
Z- friclional bearing factor
c cohesion strength
C- overburden stress
The bearing stress (q,) or cavity pressure (p: was replaced by qc in Equation
(4.3) for the cone penetrometer representation. The ½2ByNY; component in
Equation (4.1) can be ignored because the penetrometer width (B) is very small
compared to the depth. At any depth the Zc mid Z4 can be determined (theory
dependent) and the bearing stress, q, may be calculated. The Z4 and Z. bearing
factors are dependent on friction angle and cohesive strength for limit equilibrium or
on several geotechnical parameters for the cavity expansion theory. The principal
difference between the limit equilibrium and cavity expansion theories lies in how
the Z bearing factors are determined. The Z0, for example, is as simple as the
equivalent Nq factor (Terzaghi, 1943) which is based only on the friction angle, or Z,
can be based on numerous geotechnical properties which are also influenced by
stress level (Vesic, 1972, Baligh, 1976).
"The following discussions separately derive a normalized cone resistance
expression for clay and sand. Nonlinear exponential effects , then bc includedusing the stress exponent concept. The final step is a normalized cone resistance
formulation for all soil types.
46
Development of the Bearing Capacity Formulation for Clay
The clay based normalized cone resistance can be derived from the generalized
bearing capacity formulation in Equation (4.3). Penetration of clay occurs as
undrained behavior. Therefore, the bearing stress for quickly loaded saturated clay is
not influenced by confining stress. As a result, the Z. frictional bearing factor is
equal to one (1) (Terzaghi and Peck, 1967)(Vesic, 1972) which reduces Equation
(4.3) to:
qc = Zo Su + awtal (4.4)
The cohesive strength (c) in Equation (4.3) was replaced with the conventional
notation Su for undrained shear strength. The next step is to define the net cone
resistance. If the clay deposit has zero strength (i.e. Su=O) then Equation (4.3)
implies that buoyant total force will act upward on the cone bearing surface:
qc = Owto (4.5)
The net cone resistance shown in Equation (4.6) is that remaining after removal of
buoyancy.
(qc),, = qc - °toter (4.6)
Equation (4.4) can now be rearranged as shown using the net cone resistance:
(q,),•, : qc - ootw : ZC S, (4.7)
The net cone resistance, (qc)nct, is now only dependent on the soil strength. The
next step requiies dividing both sides of Equation (4.7) by the nonnalizing vertical
effective stress, oL,, to produce the following:
47
Z - (4.8)0v 0 v
The normalized clay undrained strength, , in Equation (4.8) is often represented
by __£, which can also be expressed using normalization terminology as S.1:P
- - S (4 .9 )P O iV
Equation (4.8) an now be expressed as the normalized expression for clay as:
I = S (4.10)
Development of the Bearing Capacity Formulation for Sand
Bearing stress in sands is entirely a function of the effective stress, since sands
are frictional materials. Therefore, cohesive undrained strength, c, is zero andEquation (4.3) simplifies to:
qc = '• Zo(4.11)
V
If a sand has no shear strength (i.e. ý=O), then the frictional bearing factor (Z" ) is
equal to one (i.e. Nq=l) (Terzaghi and Peck, 1967)(Vesic, 1972). Therefore, q,,equals o,, according to Equation (4.11) because Nq= 1 . Hlowever, for a ¢=0
condition, a cotal =u (hydrostatic stress) which means (I v=O, which translates to q,=O
according to Equation (4.11) which is incorrect (it sitouia instead equal a buoyancy
48
stress). The q, in Equation (4.11) must therefore reflect a net cone resistance similar
to that shown in Equation (4.6) for bearing stress of clay. Equation (4.11) can now
be rewritten using the net cone resistance as shown below:
- a = ý a' (4.12)c - Wtal Ov a
with rearrangement, the normalized expression for sand is:
qe- °to _[ Z ] (4.13)
Modification to the Bearing Formulation for
Non-linear Exponential Behavior
-ihe vertical effective stress, av, in the denominator ol Equations (4.10)
and (4.13) is the normalizing stress. This oa' requires a stress exponent to reflect the
observed non-linear behavior of cone resistance with vertical effective stress (concept
introduced in Chapter 2 and to be illustrated in Chapter 5). The resulting normalized
cone resistance shown in Equation (4.14) is equal to the left side of either Equations
(4.10) or (4.13) with a stress exponent (c) included. The normalized cone resistance
(qce) subscripts have specific representations: "c" for cone resistance, "I" for
normalization to an equivalent value at a vertical effective stress of I atm, and "e" to
represent that normalization accounts for exponential curvature.
qc -0Ooaqc;e - C aoa (4.14)
where
c = Cone resistance stress exponent
49
Bearing Stress Formulation for All Soil Types
The normalized cone resistance expression for all soil types is the combined
effect of the cohesive bearing stress expression from Equation (4.10) and the
frictional sand bearing stress expression frcm Equation (4.13) as shown below:
-total = = S,,IZk + Zq (4.15)
(a) C
This new stress-normalized expression is remarkably similar in appearance to the
Terzaghi bearing formulation (expressed for deep penetrations) as shown below:
q = cN* + oN (4.16)
q
Equation (4.15) is expressed in terms of the normalized cone resistance, normalized
undrained cohesive strength, and bearing factors. It represents a new technique for
cone resistance normalization that will be validated using laboratory chamber data
in Chapter 5 and using uniform soil layer data in Chapter 6. It is also the basis for a
new technique for prediction of undrained strength of clays in Chapter 8.
It will, also be shown, in later chapters, that the bearing factors and the stress
exponent in Equation (4.15) are all related to the combination of void ratio anc soil
type at (i'=1 atm. The bearing factors (i.e. Zk and Zq) define the mechanical
(strength) behavior at a 0' =1 atm. And the stress exponent (c) defines the
exponential stress curvature of cone resistance to vertical effective stress. Therefore,
the bearing factors define mechanical strength behavior and the stiess exponent
defines the curvature of cone resistance to vertic;A effective stress. Chapters `a'id 6
will specifically show that increasing the initial relative density, of a given sand,
creates a higher strength (at o'3=l atm) and a lower stress exponent (c).
50
Chapter 5
Cone Resistance Stress Focus--
Confirmation Using
CPT Chamber Test Data
Introduction
The Sticss Focus concept. introduced in Chaptcer 2. c~ni also be. Used mo des-crjhc
the relationship of CPT cone resistance wvith overbuiden stress. A cone ':tsistance
Stress Focus concept cani be used to gerici-alize Dumex11ous effects .311h as cavity
expansion, Mohr envelope cur-vi ture, grain crushire, comprecssibility, and others.
Stress Focus will be confi~rned based On cone rcsistaiic%. Ymeasurements obtained fromn
CPT laborator-y la-gc diamycter chamnber tests. As additiOlr'! otir.1o. of the
.tress F-ocus for in sita pmviirometers, the StzidLX:-d Penictuxatio)) Test (SP') ) chamber
tresuits will ah--o be- cxaimined. It will LT shown inl this chapl'er that thle
ionship of cone x-sistancc to voirtical effective sitress obsctved in laborato v
CJZ.. rtests become, straight lincs when) plotted ILu-aritfiMiLcalN inidicating
(:or-staut ..ress expoy.ent. hi wAill ako be shown flhat the, trenos of all rchlaive dervothcs
on this logarithinic plot comverge to the. Stress l-ocus at great depth as iliu:,triiated in
Fig~ure 5. 1.
Net Cone Resistance (atm units)
1 1 0 100 1000 10,0000.01 'LL J 'LL L' ' - " '
0.1-
Q
) 1
10 C=1
100Stress Focusfor a given sand-
SBehavior at confiningstresses greater than the
1000 Suess Focus___
Figtzrc 5.1 Propuscd :claluonship of conc rcsistaucc versus vertical Qffective stresstrending fur a piven s,.A-id (or scil) type
5 2
It is proposed to show in this chapter that:
1) Cone resistance may be expressed as a function of vertical effihc'ive stress for
a given initial relative density using a constant si.ress ;exponent (indicating a
straight line or, a logarithmic plot)
2) The stress exponent decreases with inýrca.,,•.d isiltial relative density n sands
3) The relationships between cone resistance aInd ve'rtical ctlfective stress
(regardless of initial relative density) converge at great depth (winch i", de-Incd as
the cone resistance Stress Focus)
4) Overconsolidation causes a lower stress exponent
Interpretation of Large Diameter Test Chambt: Daa
The best means of introducing and defining the components of the cone
resistance Stress Focus is with a good example. Figure 5.2 (Baldi, et al., 1981)
surmuarizes relative density contours for Ticino sand derived from a large number of
chamber tests at various initial relative densities azad confining stress levels. These
contours were carefully established by the original researchers for each relative
density range. The same contours are replotted in terms of log10 net cone resistance
(e.g. (q,),1 ,) versus log,,, .' in Figure 5.3 (net cone resistance is the measured coneV
resistance minus the vertical total stress as described in Chapter 4). The relationships
shown for different initial relative densities in Figuro 5.- all converge to a common
Stress Focus for a given sand type. Relative density contours in Figure 5.3 are
remarkably straight in spite of the fact that the (q,),,, versus a,, relationship
(Figure 5.2) were produced by the original authors from scattered test data without
foreknowledge of the Stress Focus concept. These relationships have also becei
vcrified by replotting the original data as shown in a later section of this chapter.
The liles toi all relative densities converge to the Stress l'ocus because cavity
53
expansion, Mohr envelope curvatuie, grain crushing, and compressibility influences
are changing. A sand of initially high rebltive density (dense) will thus have the
same cone resistance (and density) as a initially low relative density (louse) sand at
the depth of the Stress Focas.
Explanation of the Cone Resistance Stress Focus
The cone resistanc.:, at the Stress Focus (qcf) in Figure 5.3 is at 2200 atm, and the
vertical effective stress at the Stress Focus (ofc) is 140 atm. The normalized cone
resistance a.t the Stress Focus (qcn) is 16 as shown in Equation (5.1) and illustrated
in Figure 5.4.
qfI2200 =6(5.1)140
The qcn represents the bearing factor Z, (i.e. Nq) for confining stresses greater than
the Stress Focus. This Z. represents an approximate friction angle between 28 and
3 V) using the simplistic bearing factors of Janbu and Senneset (1974) (see Figure 5.5)
or using cavity expansion techniqucs (u ;ing a low rigidity index) (Vesic, 1972).
This friction angle is also within vie range (i.e. 300 to 340) of most granular
sedimentary rocks tested at high stresses as was reported in Chapter 2.
Figure 5.4 is an an.otated version of Figure 5.3 intended to illustrate all aspects
of the stress exponent and Stress Focus concepts. As pieviously stated, a sand of a
given relative density will follow, with increased veitical effective stress, a straight
path on a logarithmic tplot to the Stress Focus. Dense sands have a low stress
exponent, whereas loose sauds have the highe:st stress Cxp(onent, the exponent may
approach I (one). Any point along a given path can be defined by the combination
of stress exponent (c) und the normalized cone resistance (cli). Alhernatively, an,,
point can be defined by the stress expoment (c) and the Strcss Focus point (tha.i is
54
CONE BEARING ,q ,bars
o 100 200 300 400 500
In0
_ _ I
V)
LiJ
F-
w
i-J
CE D 40%/ 50 60% 70%b 80%/ 90%>
5_L__II___________
Figure 5l Trends oi cone rcsistawl(c vc~rsu;' ver ticul Cff*CC~I;vc :illess I o'.I, 1':110sand (lBaldii, et.al.. 1981)
Net Cone Resistance (atrn units)10 100 1 0),( 1 1001,9
0 1
0 -- 't:0
Data lines replotted,--- honfiom Figure 5.2
Data trends to theStress Focus
S10 0 - ... ." . \\
0 -
0-. St'sS focus fo,
"2• , Of) 0 Ticino sand -\
~ig;ur' 5.3 Replotting of Jalcii, cr2.. 1981 daw curvcs from I igarc 5.2 in trn..
ofI Lou ilet cone se:ist.-cr e; '<u,..lUI vcLcg.l c.ficciivc stiCss,,
q5
defined by q,, and o •) as described in Chapter 3.
Shallow and Deep Bearing Stress in Terms of the Stress Focus
The bearing stress conditions for shallow -nd deep conditions may now be better
expiained as a result of the Stress Focus concept as illustrated in Figure 5.4.
Shallow conditions are controlled by vertical expansion based bearing capacity
failure (defined by limit equilibrium theories) and deep conditions are controlled by
lateral exansio�n based cavity expansioni cffkcts. Shallow bearing stress is associated
with a linear relationship between cone resistance and vertical effective stress as
reflected by limit equilibrium theories ('rerzaghi, 1943, Durgunoglu and Mitchell,
1975) antd shown by •he transforo 1ed linear behavior lines at the top of Figure 5.4.
Decp bearing stress conditions are controlled by cavity expansion (Vesic, 1972,
Balig-, 1975) and can be e-.pressed exponentiaily (i.e. transforml slope of c) as
shown at the bottom of this figure.
The transiticn between vertical (limit equilibrium) mid horizontal (cavity
expansion) bearing expansion is the "Critical depth" line. Historically, this tran;sition
Sas expressed as the D /B ratio (penetrom eter diam eter to depth ratio) and is typically
1(0 to 20. Increasing relative density causes a greater ciuical depth transition as
shown in Figure 5.4 (Ketisel, 1964, Olsen, 1992) for normal peuletroiae'er diameters.
.r~5
IV ~'
Net Cone Resistance (atm units)
1 10 100 1000 10,0000.01-- . --
"" "" 1 ,' i(surface),_ I
1 " "~ :1 •, Expansion , ,-
BGOAring0.1 1o,~ J Failure
-------Critical Depth LineAl IIO-- Stress Exponent
. 7 1 F'Si.0 Relative Dcxsity
A, , (k " I, ncreazing
. '\ \ . dilative behavior) ,S-~~~i w, , >," , .
g• - Ofc, • ,,7 ,,\\
A. 10" , ' 1,1, Horizontal
SET= 0, -,.,, (Cavity,C) Expansion)
SBearingio10 o i.• , Failureo;. . = 140 atm .... ..................................
Stress Focus ...for a given sand 4
1000 Aqcf m 2200 atn
Sedimentary Rock Behavior(with minimal dilative behavior)
Figu. e 5.4 Annotated description of the cone rcsistwutce Stress Focus together withbearml stcrss di:kdc, I into xvcrtical expression failure wad cavILycxpaol:;iOfl faii- 'rc
1000
800- LEGEND:600 -* CHAPMAN Ek DONALD (1981)
400 -+ BALDI et al. (961)
{ HOLDEN (1976)
200 - ESAI (1974)
0PARKIN et al. (1980)+Cr L VILLEY & MITCHE~.LL(1981)
0r 100/z 80 - Durgunoglu B MitChe 1 (1975)/
aý 60 -______._
Li,WB
40 -
Compreas~bilityZ 20 Proposed correla~tion
10C. 8
800 15-6V q
4/
< /,</V<- Joribu B Sernesoet(19*741
z~ 30932*34*31 0 3a20' 42" 440 46'48
00 0.2 0.4 0.6 0N8 1.0 1.2TANGENT 0,
Figure 5.5 Correlations bet-weei, cow.. resi-stwnce and fliction anglu based on liir-tequilibrium theonefs and laboratory chamber tests(Campanella and Robertson, 1983)
59
Using Chamber Data to Establish Trends of
Stress Exponent and the Stress Focus
Large diameter chamber tests provide the best experimental means for evaluating
stress effects on the cone resistance, because vertical and horizontal stresses can bc
controlled independently. Numerous researchers over the last 30 years have
performed CPT chamber tests using a variety of sands and confining stress
conditions. This section w.ill critically examine chamber data toward proving that the
cone resistance behavior indeed has a Stress Focus. Standard Penetration Test (SPT)
chamber tests results are also examined in a subsequent section because they incluu-
data for a large number of well documented sand types. SPT chamber rest results
verify that the Stress Focus location is sand type dependent.
A computerized database of chamber tests was created based on a data listing
provided to the author by Professor M. Jamiolkowski in 1989. This listing represents
4!0 cnle..n ':cts performed by ENEL, ISMES, and NGI over a period of 12 years
and represents two sand types, namely Hokksund sand and several variations of
Ticino sand.
Evaluation of the Chamber Data
The laboratory chamber data were initially divided according to sand types and
further divided into groups representative of normally consolidated and
overconsolidated conditions. Each sand type (oi batch of a sand) was then divided
into groups based on relative densit", each having an adequate number of points
(e.g. 6 minimum) for statistical e, iaation. For each relative density group (of a
60)
given sand type), the individual chamber test data points were plotted as log 10 (q,),, 1
versus logi, o, as shown in Figure 5.6 through Figure 5.9.
Using statistical least square fit correlations for each relative density group, for
the purpose of determining the Stress Focus, was not successful because one or two
poor data points will shift the best fit line; statistical correlations are easily biased b,,
poor data at or beyond the limits of data ranges (Taylor, 1990). Therefore a new
means was required to determine Stress Focus location. The Stress Focus location
can be iteratively varied (in the (q,)n~l and a', directions) until the optimum 1ocation
is found. For each Stress Focus location, lines are projected from the Stress Focus
through each relative density data group. The optimum Stress Focus location has the
best data fit for all of the relative density lines.
The Stress Focus locations from the preceding figures are summarized in
Figure 5.10. The main observation from these plots is that a cone resistance Stress
Focus car, be established using CPT chamber test data.
CF 7' Stress Exponent Evaluation
As shown in the preceding figures, cone resistance for each relative density range
i,. associated with a constant stress exponent relationship (e.g. straight line on a
logarithmic plot) to the Stress Focus. The relationship of cone resistance stress
exponent (c) to relative density for the various sands (i.e. Figure 5.6 to Figure 5.9) is
summarized in Figure 5.11. There is an apparent trend of decreasing stress cxponent
with increasing initial relative density.
Also shown in Figure 5.11 is the cone resistance stress exponent of c=0.61
suggested by the late 11. Bolton Seed (Seed, ct al., 1981) for relailve densities
61
1 0 100 11 DOOI(00
I- (
LV 1
-7i
Uf"142
C
WMi [0.1.14 jniiý ow0'ski. 117
()Jtu 9,),;
Figure 5.6 Net Conec rcsist=.cc versus vertical effective sticss for Ilokksand sand
62
Net (Com Resistance (&itnil nu1ts4)110 1 00 1000 1 000f)
0L 1
C: I
13x &
S10 0
U
- e(j* vcsi y(110 Ranoges C 0r)
100 0 TicirIn Sandl (1I"tri Jiiimbelb 1) 1 ie- ru-~ I (dote fr-om Jarniolkowsk,. 19813) I Cci Ticuicm suozd
I (batch nuhrter 1)
I K X - 71 t o 7 t, 7;ý
S 11 901 to 92- 7T
1000 0
Figure 5.7 Net cone: resistance: versus vertical effective stress for Ticino sand(batch III)
03
-2
Net Corw eitLI~ (aim unilsý)S0 1 0l) 1000 1000u
01 -0 -- -
30 o:
S--4 t ,I x I I
I o oa , )-
>f' Or 5 ý5-T, m(. Sand5
;'- - * "X
U).7
:" ; -X
,','.~9 t. , 9,lm!
C. _ _ _,,__ _ s__ _ _ _-_ ___
1, ]00 0 - I t' l~lb-J 2
C 00(dot,, iron, laim~ulk-owak-: 1 4(7) I..(a ci JIJJSJ 2 I .St re.s l-'or-u'. tot
*. *• Dr - .50 to 52'. TI(III sand
--I X D, -"75 to 78 3 ((Catch tijil,Cr• 2)
1(0 i-' A 1', - 'JO to 92
Figure 5.8 Net cone resistance versus vertical effective stress for Ticino sand(batch #2)
64
Net Cone RessLancc ( atmi u".tl)
10100 10100 10000
0 1I ), 34 ), 7
D,-] . ri - 927;
-• - 14 to O ".
-Aft
a; 100
-• q l<".R ýatlV ,, D ,:_ns aty ;i,nges MI r) . ' \\ -,
"• W~~aclqlu Sad/ \ ."(I" I[[ch nIum -iD( 4)
"LL. ((ota fr,)T) JJTrloIwows-:I 1987)
- I - 14 to I C. 1 ±00 0 Stress 'OLus tio
r2 to 235 Ticm sondc• --'• - r 32 ,., 5"•(latch nu~ml-tr 4)
0 to 950;
00.J0 0 -
Figure 5.9 Net cone resistance versus vertical effective stress for Ticino sand(batch #4)
65
NeO Comn: Resil-ýtirocc (Gt'. - lmlLt1 1 0 10) 1000 10000
01 _____ , - . ; - .--
All
S 1 0 ---q
U I
Hal.
(I.. -
-i-
SI lHokksund sand (3atch # 1)Stress Focus
1000 T 1cmo Sandg %.1 IC•,t .iI (}~3Litch) ,02) - ,r
L.ocus of stless I'o.-:for Tic"lino Sand
I 100.0
Figure 5.10 Stress Focus locations for Ilokksund and Ticino sands based onevaluation of laboratory chamber tests
66
betwe ,% and 80%. The stress exponent is calculated from CP using:.
CP 1 (5.2)
The Cp-based stress exponent was established by Seed, et al., (1981) based on
chamber tests performed at the University of Florida. These chamber tests were, at
the time, interpreted to have a constant stress exponent for all relative densities
(Schmertmann, 1978,). TLe Cp based stress expo-ent of c=0.61 in Figure 5.1i
envelops all of the chamber based relative densities from 4.0% to 80% and
specifically represents a relative density of approximately 60%. The overr;ding
conclusion from this figure is that the cone resistance stress exponent is inversely
proportional to relative density.
Overconsolidation Effects on the Stress Exponent
There is a consistent observation from chamber test results (and field uniform
layer trends discussed in Chapter 6) that overconsolidated soils have low stress
exponent values. Figure 5.12 is ar, example of overconsolidated chamber data having
a wide range of relative density levels and numerous overconsolidation levels. Tile
solid lines represent the normally consolidated trend (from Figure 5.9) while the data
points and dashed lines represent increasing overconsolidation level. The stress
exponents (c) for overconsolidatior range from 0.06 to 0.24, which also represents
the lower range for normally consolidated very dense sand. Overconsolidation at any
initial relative density therefore produces low stress exponents. A simple nmans of
explaining overconsolidation effects is to compare the conventional consolidation
relationship (e.g. odometer test results) to the cone resistance versus vertical effective
stress relationship in Figure 5.13-both have steep slopes associated with
overconsolidation. Interestingly, dense sands and overconsolidated conditions are
both locatcd in the upper right portion of the CPT soil characterization chart
67
(' 1, (Seed Ct a1.,1983)
(.=0.6 I for I(l,!-tive del-itiesut1tweefl-10 and 80u)1 0
,0 9
5069•0 7
0 7l-tK•
S0.4 -)
rA
SClr Co..e resisttance,r -chamber test iesilts
Cf-, ;Hukksund Sand
0.2 Tii nro (batch #1)
-• TTc~ino (batch #2)
--E3 Ticino (batch *4)
0 1 = epl8tted Ticino sand WomFg ure 3)
SData Frun) Al-A-katj 1975
0 1" T FI I I III
20 30 40 50 60 70 80 90 100
rillR elat~ive D rl-]Sit\; (%
Figure 5.11 CPT stress exponent range for several sands in terms of the Relativedensity and CPT cone resistance stress exponent
68
(Olsen, 1988)(Figure 1.2).
Chamber Boundary Effects for Dense Sands
Chamber size and chamber boundary conditions can affect CPT measurements.
Dense sands tested in laboratory (constant stress boundary) chambers produce
cone resistances that are lower than measured in situ (Bellotti et al., 1979; Keaveny,
1985). Typical laboratory chambers are too small to accommodate the full cone
resistance stress field produced in dense sand by a 3.6 cm diameter probe. Shear
stresses that would be generated beyond the radius of a typical chamber do not
develop because the pressurized confining water beyond the flexible boundary cannot
sustain shear stress or generate elevated lateral pressure. This results in lower
mea_.ured cone resistance in most chamber tests than are measured in situ for dense
%A L 'II•,w..u'i U%, ,UI..LUl IMAula )Ua.,%.;u U11 UIU bO.UU Lype, id o
diameter to probe diameter, and sand relative density are shown in Figure 5.14. This
figure implies that initially very loose, loose and medium dense sands are not
influenced by boundary effects with typical chamber diameters (i.e. diameter ratios
greater than 40).
The cone resistance Stress Focus concept developed using chamber data in this
chapter is valid for very loose to medium dense sands but questionable for dense
sands because of chamber boundary effects. Dense to very dense sand must exhibit
artificially low measured cone resistances because of chamber boundary effects.
However, it appears that cone resistance behavior at all relative densities (for
chamber tests on a single sand type) converge to a common Stress Focus (Figure 5.7
to Figure 5.9). This convergence to a Stress Focus and the fact that dense sands
must have lower-than-expected cone resistance (e g. Figure 5.14) must be attributable
to chamber-tested dense sands having elevated stress exponents as shown in
Figure 5.15. Dense sand tested in chambers and in situ may therefore have the same
69
Net Cone Re.ý:isIancc (ohln mijl~ts)10 100 1000 1 0000
Df 73-
\ [)r - 92f"-I \' I Overerat-, .oh~daIor, for Di+34%
-- _,- Overconsohoetwon (,r Dr 9:-I %
\3K -oc -"z "1 0
-. "rendls for,,, . , '\
j rim•rmrmadyv (onsohdate. A Normally (orisolffhat md
'I,
10-
ii2 Effects o! Overconrsolhdation
of I Tclino Sadld
(d6t,, fron Jan,,o'kow.,ki. 1987) L E1 ND
-1 L" r 90 to 96 %
L),X Dr• -770 to 76 .cr n i Ljf•¢111lly " \J'U.rm con'rrllrf'.flOn
Y'\j 1
r 32 fo 35Cr ISOhdrted
1000 0 --
Figure 5.12 Relationship of the cone resistance stress exponent foroverconsolidated sands in chamber tests
70
Log cy, void ratio
cansolidaion
vid. Clay: Axis • xvoid Sand rotation andratio translation
consolidation "Sand4_ Clay.Log ....... •
Conventional o;consolidationrepresentation
Comparison
Log Cone resistance, qc
(e.g. 0.6) 1Normallyconsolidated
11 "\
c g, '• 1 '- (e.g. 0.1 to 0.3)Log II \\ •d•!; Over
Sand cor-olitdate
S-md
Clay,
Figure 5.13 Overconsolidation effccts illustrated by comparing the conventionalconsolidation representation to the obscrved relationship of concresistance versus vertical effective stress
71
50 -TNOTE;DIHORIZONTAL /
STRESS CONTROL /WH83:HORIZONTAL
STRAIN CONTROL 0C1 a
201- "t • 1 3, PIC
I• 0
20 k 83 BI NC
~DENSEor Dr 930%
U
U)
w 00 0 0
LOOSEz0LEGEND Ov U.O~30%
2 *1INC 02 B3 NC0
B83 OC
5 10 '20 sotoDIAMETER RATIO
(Chamber diometer/ Cone diameler )
Figure 5.14 Boundary effects on the measured cone resistance level in laboratorychamber test in sand (Parkin and Lunne, 1982)
72
Stress Focus but different stress exponents. Bulging at the chamber boundary limits
the size of the bearing pressure bulb in firont of the probe to that developed i.i a
lower relative density sand (i.e. having a higher stress exponent). A sand with an
elevated stress exponent is therefore equivalent vt a lowei relative density sand.
The elevated chamber stress exponent of dense sands in chamber tests can be
further illustrated by examining trends of stress exponent versus relative density.
Stress exponent versus relative density trends from Figure 5.11 having at least 3
relative density groups were replotted in Figure 5.16. The elevated chamber stress
exponents for dense sand are shown by the vertical arrows. This approximated
correlation of stress exponent to relative density is more linear than the relationship
derived from chamber results.
73
Net Cone Resistance (atm units)
1 10 100 1000 10,0000.01 J ____
(foi a very dense sand condition)
01 •/ -- Clamber relationship
•\-- In Situ relationship\ •• (estimated for illustration
purposes only)
"1.0-1 The chamberI boundary effects
-c -O4 (for a flexiablechamber boundary)
7cO. w~il decrease the"measured cone1 1 resistance level and
Itý 1 - increase the stressexponent (if the
1 Stress Focus is" "- constant)
10 0 - /
Stress Focus--- for a given sand
(assuming that the Stress Focusfor chamber and in situconditions are the same)
Figure 5.15 The reduced cone resistance for dense sands due to "chamber sizeeffects" can be represented with higher stress exponents because allrelative densities appear to have a common Stress Focus.
74
1.0 -
0.9 Chamber reflcctc-d relationmship%----
o- 0
S0.6o /
is /
S 05
C)
Z - E:Atirnated in situ rclotmn:Lipa------- ,/ I
!Elevated Stress ':xponentS 0 3-due the the hiinted diameter of -03 •laboratory chambers
0
CP'T' conmi resistancechamber teAt results
S 0. 1 - i Ticino, (batch #1)
-/- Ticimo (batch #4)
0 020 30 40 50 (30 70 80 90 10()
]-elo_-tive ).nst\ (L
Figure 5.16 Possible modification of the chamber based stress exponent for denseand very dense sands
75
SPT Chamber Evaluation
This section will evaluate SPT chamber test data on sand to show that the Stress
Focus location is soil type dependent. These SPT chamber data consisted of tests in
4 well documented sand types and were used to study sand type effects on location
of the Stress Focus. Data from SPT Chamber tests were therefore examined for two
purposes; 1) to show that SPT data can be expressed with stress exponents and the
Stress Focus, and 2) to show that sand composition affects the Stress Focus location.
If the Stress Focus is a genuine geotechnical property then SPT chamber tests results
should also reflect it.
The Standard Penetration Test (SPT) blow count is defined as the number of
blows required to advance a split-spoon SPT soil sampler one foot into the bottom of
a borehole using a standardized hanme._r The SPT zn-pler is resisted du,-ing
penetration by both static and dynamic end bearing and side forces on the sampier
(Schmertmann, 1979a, 1979b, Douglas, Olsen, and Martin, 1981, Olsen 1988).
A comprehensivc laboratory study of the SPT was performed using large
diameter chamber tests at the U.S. Army Waterways Experiment Station (WES) inthe mid 1970's by Bieganousky and Marcuson (1976, 1977). SPT chamber tests
were performed in a 4-foot diameter chamber very similar in concept to the large
diameter chambers used for CPT testing. For an SPT chamber test, a sand specimen
is prepared, confining stress applied, a borehole drilled into the sand using rotary
wash techniques (and drilling mud), and finally the SPT sampler is driven into the
sand beginning at the bottom of the mud-filled borehole. SI9' sampler blow counts
were obtained from different chamber depths, along the center of the chamber as
well as radially out from the chamber center. Only the center test values were used
for the currert evaluation.
76
SPT Chamber Data Plotting
The procedures for evaluating WES SPT chamber data are the same as used for
CPT cone resistance data in the last section. For Reid Bedford sand, trends related
to individual relative density groups are shown in Figure 5.17 to Figure 5.19; all
relative density data and trends are combined in Figure 5.20. For Standard Concrete
sand, all relative density group trends are shown in Figure 5.21, for Platte River
sand, all of the relative density groups trends are shown in Figure 5.22, and finally
for Ottawa sand, only ore relative density group is available as shown in Figure 5.23
(all data from Bieganousky and M, -.uson, 1976, 1977). The correlations by
Gibbs and Holtz (1957) are shown j Figilre 5.24 for comparison.
SPT Stress Focus and Sand Type
The SPT Stress Focus information from the preceding figureF are summarized in
Figure 5.25 together with trends of mean grain size and material composition in
terms of feldspar percentage. Quartz is the primary material type of these sands
with feldspar being the secondary material type--increasing feldspar content may
reflect a lower overall sand strength. Compared to quartz, feldspar is softcr, has
lower compressive strength, and has distinct cleavage. In Figure 5.25, as feldspar
content increases, the depth for the Stress Focus incrn 'ses. A deeper Stress Focus
(due to feldspar content increase) has a lower calculated normalized cone resistance
at the Stress Focus (q'f) (see page 54 for definition) which means that the friction
angle at high confining stress is also lower. Chapter 6 will also show th,'.t the ,.one
resistance Stress Focus is soil type dependent and exhibit the same general trend as
the sand mean grain size in Figure 5.25.
77
bWow coiiiit (N)
0 1 1 0 10(1 1000 lO00 0
0 .11 '
S, ~~Dr -3%\" -" {(rarige of 25 to 40% )
U.I
C• -- Best fit with the• • ~transformed Log axe:z for/ "
_ Reid Bedford sandi at Dr : 33ý
C, 100 0 -
1000.0 --
Figure 5.17 Cone resistance chamber data for a relative density7 of 33% for ReidBedford sand
78-
1~0 78
SPTblow count (N)
0 1 1.0 100 1000 100000. 1 i L-_L_. 2_l;I', W.~.L __J _ ___£ I [ I' l . n'.l
,.'-DI 4 457
10 ] ', (rar,ge of 42 to ,37)
100
SBest fit with the 1-1 trarisform ,_ed log 3xte:a foz
Reid Bedford sand at 1) - 45%
Uo I Oo} 0 -- '
100"3.0
Figure 5.18 Cone resistance chamber data for a relative density of 45% for ReidBcdford sand
79
Sill'
II I-Ioov," c'ouiit (N)" -
0 1 1 0 10 1 00 0 1000 0 J£
,1.
I \ r 671
\(rbrlg: of 60 tc 7.1")
100 -"
T.
Dest fit With1, transformed log axes for
, -1 Reid [edford Sand at D,. - G7%
.c 100 0
+-..2
LII
] oooo
Figure 5.19 Cone resistance chamber data for a relative density of 67% for Reid
Bedford sand
8(1
S1"I'blow Count (N)
0 1 1 0 10 1000 1000C0
0 \
,\ (range of ,12 to 53r)
1.0-rr"
"-- (range of 25 to 40%) (rarngc of 60 to 74%)
,[jest fits wit), the•.10 0 0
D to \) '_""•Stess locus elo ftcid lled'ft,, SthIid
-- ) 4--2 to 53n
D,( 2 5 to 40%~
1000 Q
Figure 5.20 Cone rsistance chambcr data for all relative densities for ReidBedford sand together with the Stress FocusSi "" i) • 0 to ",,t. xl
.SPI
bWOW counTt (N)
0 1 10 10C0 100 0 1000 C
0.1
0.1 -II" U I,.
Qjj
D~~4r = 50% vrg
.'-a ",. \\D 9J
5", ~ ~-1 J I '
-r I - avrg
I.,\, \H u\
wih t tespoding tre F
Log ransormed lg__82s/
h ~ 00 a -~ SfT chaniber test trends 's.-- 10 - for Standard Concrete sand Srs ou o
*•• Dr -25%, average Standard Concret, e sand
1r, Ilr = 50% average
-- ..... Dr - 9'5% average
eM1000.0 --
Figure 5.21 Cone resistance chamber data fbr Standard Concrete sand togetherwith the corresponding Stress Focus
82
SI'T1)1 o, count (N)
0 1 1 o 10 0 100 0 10()00
0 1_ ____ 1 L.J-L LLL -.
C.i
2• 10 x
- I) - 917
Srr
I r 20 to337
V.. 10 \0
transformed Log axes
. 1000 1 --• SPT Chamiber test evaluation forPlatte ihver sand
C) Dr- 20 to 33t'."e,- ocu
Dr - 55% veragcs- Poc-u
-Dr - 91,P average
10000 -- - --___
Figure 5.22 Cone resistance chamber data for Platte River sand together with thecorresponding Stress Focus
83
SIl'T)lo co C'OUflI (N)
0 1 1 0 10 0 100 0 1000 0
-I
S 1.0
r-Dr 591,
,,
• ---4
" 10 0 Uest fit with /
ti0r)sforIed log axes
. 1Range where the Stres Focus
100 0- could be located for 0 tawa sand. (because there is onlrdI on' relative de:nsity zone)
10000 -- q
Figure 5.23 Cone resistance chamber data for one relative density range of Ottawasand
84
SITI' blow couit. (N)
10 100 1000
0
J \\ \
,H\\
•-_\ \\ \ \
Y, 10.
C)
•- -O \ \\
reul su rnm re
C--
5 1000 0SPT 17,-- chn b ver tet
Figure~ ~~ (.4 Cn eitnecabrdt rnsfrGibbs & Holtz. data)
I 8
-. - I
E100.0 SPT cham er a Stecstertet
1 0 C 0X Dr=80E average tes ou
Fiue52 oerssanecabrdt rns for Gibbs < & Holtz dt
_- [ D'=Oav~ac PTch mb'r85si
SPT blow count. (N)01 10 100 100 0 1000 0
f0 1
Trending foi clays
"-• 1.0
- -\
10.0 -Ottawa Sand
Standard Concrete sand -, \
Reid Bedford sand
"Platte River sand -
S100 0 .0 lO 0 -,•O~i /• eldsp;l()i
02
0 25
1 o1o74
I44 1000 0
Figure 5.25 Comparisor of SPT Stress Focus locations for different sands to theresulting tiends of Feldspar percentage and D50
86
Chamber Test Stress Exponent Discussion
The SPT stress exponents calculated for data at each relative density (from the
proceeding figures on SPT chamber test evaluation) are summarized in Figure 5.26.
These SPT stress exponents confirm the general trends based on normalized SPT
stress expornent presented by Sd et al. (1981) that are also shown in this figure.
However, it is shown in Chapter 7 that the SPT stress exponent should be higher
because of mud pressure effects associated with SPT chamber testing.
The stress exponents developed from SPT and CPT chamber evaluations are
shown in Figure 5.27 and indicate a difference of approximately 0.18. This figure
will also be referenced in Chapter 6 during the introduction of the new SPT
normalization technique.
'it is U-aso iI1po1Uaant io nutr uatt uie diSrltudon of 01 S stress exponent for a
given relative density in Figure 5.26 may not be due entirely to data scatter. The
stress exponent can be related to sand type composition as shown in Figure 5.28 of
which is plotted in terms of feldspar content at a relative density of 36% (likely a
contractive condition). As previously stated on page 77 and shown in Figure 5.25,
increasing feldspar content increases the Stress Focus vertical effective stress.
Increasing feldspar content also appears decrease the stress exponent as shown in
Figure 5.28. Therefore, conceptually, the combined effects of increasing vertical
effective stress and decreasing stress exponent can be illustrated in Figure 5.29. The
Stress Focus location and stress exponents therefore appear to be interrelated.
87
11-,
S .P (l chamber stress exporciitts{diata ff on)
0.9 \wiegorlouski and Marcuson 19-I 1977)
\[3 Quartz Sand (one point only)
+ - Standard Concrete sand0- +
08 -- Platte River sand
--. \ + Reid Bedford SandS0.7 \ i~l" Gibbs & ]l°t s (1917O°)
O I _ _ _ _ _ _ _ _ _ _
S0.4 3404
/L / S
0- - ,/ =/ /,
02') Seed et.al.(19983)interpretataioi ofWES SPT chamber data
0 1 ii-0.45 for D,=60 to 8tý3- and
n=0.55 for D,=4() to 60',)
1 3 iI I I I III
20 30 40 50 60 70 00 90 100
R]°v Alvc\.( ])'i~sit v ("C")
Figure 5.26 Relationship between relative density and SPT stress exponent for
different sands from SPT chamber tests
88
1.1
,- Raiigc of1.0 2,' CPT stlress exponient.s (e).0-. / from1 c]Lorbe1 evaluationl
0.9 ' The average differencebetween the
PT and SPT chaniber
0 .8jI-ess exponents is0.8 approximatelv 0 1P3
2 0.61
U20
S0.5d
•"m 0.4.
0.3
Range of
0 1 SPT sLress exponents (n)froim chamntber r-aluati on
0 .0 11 I , - I I
20 30 40 50 60 70 80 90 100
Relative Densityv (2K)
Figure 5.27 Comparison of the ranges for CPT and SPT stress exponents fromevaluation of chamber data
89
(Lstimated)12•
S1.0 -_
CI) 09
0 -ew
CO 6
05
0 4
NJJ '0
um. 05-
0 4(I' i i ] i ii 0-1 1*1-i;l , i-, i i1 1I11 1 .0,-
0 10 2030
Feldspar (Percenlage)
Figure 5.28 Relationship between SPT stress exponent and Feldspar percentage ata relative density of 36% for chamber tests
90
Log net cone resistance (atm units)
Sqcf q cn q cflq~f q~l qfl ' =l1atm
C C
S.14oTrend., fo- ve low Stress-relative density Stress
(decreasing F/ocus• . stress. e.xPOnet with . rG.U.
increasing felspar " locatic iscontent)
Not to scale IcreasingfeldsparI content
Figure 5.29 interrelation of the Stress Focus and the stress exponent (for a v'pryloose sand condition) based on evaluation uf CPT cone resistancechamber data fc. increasing feldspar content
91
Conclusion
Tihe CPT cone resistance can be represented with the Stress Focus concept. The
cone resistance versus confining stress relationship for different relative densities will
converge with increasing vertical effective stress to a Stress Focus that is dependent
on sand type. This sand type dependent Stress Focus location appears to be based on
gradation effects and material composition. The Stress Focus location appears to
occur at a overburden stress ranging from 70 to 300 Atm. Dense sands have the
lowest stress exponent and loose sands have a stress exponent of approximately one.
92
Chapter 6
CPT Prediction of
CPT Normalization Parameters-
Developed using
Uniform Soil Layer Data
Introduction
Stress normalization provides the means to account for confining stress influence
on in situ measurements and geotechnical properties. However, to be useful the
stress normalization parameters must be predictable using the field CPT
measurements without auxiliary information. Data from CPT tests in uniform soil
layers can be used to establish correlations for prediction of the CPT cone resistance
stress exponent. Specifically, field CPT data from tests in uniform soil layers can be
used for several purposes: to show that the Stress Focus exists, the Stress Focus
location (i.e. equivalent overburden stress and cone resistance) is dependent on soil
type, the cone resistance stress exponent can be estimated using field CPT data, and
to prove that the Ct . soil characterization chart concepts are valid.
93
Limitations and Merits of Using
In Situ Data for Stress Normalization
Evaluation of unitbrm soil layers is more difficult than evaluation of chamber test
data. The main difference between in situ uniform layer CPT data and chamber test
data is that in situ data can represent all soil types, whereas, to date chamber data
can only represent clean sands (and in some cases sand with fines) of low to medium
relative density. On the other hand, the initial relative density and confining stress
levels can accurately be varied in chamber test programs. The principal merit of
in situ uniform soil layer data is that it can represent the full spectrum of soil types
and thus that it can be used to determine the Stress Foci for all soil types. However,
when a very uniform soil layer is found, it represents only one relative strength level;
e.g. a sand with a 70% relative density or a clay with an undrained normally
consolidated strength ratio (c/p) of 0.32.
A single uniform soil layer has a constant trend of log net cone resistance versus
log o' that can be represented with a constant exponent slope. To establish the
Stress Focus for a single soil type requires numerous uniform layers of varying
relative strength consistency levels. A database representing uniform soil layers must
therefore be large enough for the purpose of establishing the Stress Focus for
numerous soil types.
94
1W•
Establishing In Situ Uniform Layer Trends
A uniform soil layer is defined as a constant soil type at a constant initial relative
strength (e.g. friction angle for sand or _C for clay). A plot of Log (q,)net versusP
Log (a') (and Log (,f) versus Log (o°') ) will follow a straight path over the uniform
soil layer interval as illustrated in Figure 6.1. These net cone resistance relationships
can be projected to the normalizing stress of (,'=1 atm to determine the normalized
cone resistance, qcl,. The log-log slope is the cone resistance stress exponent (c).
Soil samples are not required for this technique, although proper soil classification is
useful for indexing purposes.
Logarithmic plotting emphasizes the lower stresses, therefore special care was
exercised while identifying uniform soil layers-For example, a depth interval of
3 to 8 ft has approximately the same log (a') differential (i.e. 0.3) as the depth range
from 30 to 60 ft. Shallow uniform soil depth zones are artificially emphasized. It
would be easy to use a simple Alogl0 (,a') criterion such as 0.2 to represent a
minimum uniform depth zone. However, it was important to examine deep layers
for small ALogl 0 (o,'), such as 0.08, that could represent a uniform 12 foot layer at
= 2 atm.
Approximately 600 field CPT soundings were examined fbr depth zones having a
constant relative strcngth. This was accomplished by plotting all C1P1 soundings
using the Logl( (net qc) versus Log,0 (,',) and then examining the traces for any
95
SoilColumn Log Cove Resistance
UniformLayerq l
•""-I.~~ " cle /•\ •
UniformLayer
L"- Log
VerticalEffectiveStress, oY'
V
Figure 6.1 Determining the cone resistance normalization value (q,,,) andcorresponding stress exponent (,c) using uniform soil layers
96
depth zone having constant slope (indicating a uniform relative strength level).
Identifying uniform soil layers using CPT data was a developed skill that improved
as more data was evaluated. Only 78 uniform soil layers were extractable from the
600 CPT soundings. An example of a uniform soil layer is shown in Figure 6.2 with
the soil layer limits and normalized parameters shown by computer-plotted lines
based on the data from the database. For each uniform soil layer, the following
information was extracted:
1) normalized cone resistance, qcle (e.g. equivalent (qc)net at o&'= I atm)
2) qc log-log stress exponent (c)
3) Normalized sleeve friction resistance, fsle
(e.g. the equivalent f, at G'= I atm)
4) f, log-log stress exponent (s)
5) Calculated normalized friction ratio, R rlc, based on fse and qc1e
6) Soil tvne if there ik nenrhv hboring nr the depmnoit tvnp ift knon
7) The Academic Quality Index (AQI) which is based on soil layer uniformity
potential and quality of the cone and sleeve fiction resistance measurements-(see
Chapter 8 for description). The AQI is a subjective quality index based on the
academic grading scale; 75% is average, 85% is good and 95% is excellent.
8) Top arid bottom o' limits of the soil layer.
Establishing Cone Resistance Stress Exponents
using the CPT Soil Characterization Chart
The CPT soil characterization chart was used to develop predictive contours for
the cone resistance stress exponents using data from uniform soil layers. As
illustrated in Figure 6.3, uniform soil layers are identified (Step #11), normalized CPT
parameters are calculated (Step #2 & #3), the results are assigned to a point on the
97
Cone Resistance - Total Stress
(atm units)
10 1004 6 6S 2 4 6
0.01 I , ,
LO4j 2..rI
C
E A
-.ro
U)
V)
W A-
-_ -c ~ - -1 - - -- -m 6- Exonntc . .6
'4-J
U.-
>ion2-
L Ci
(D ~ Exponent c= .6> O0servational AOI = 2
10 1 1 1\ I
Figure 6.2 Example of in situ cone resistance data having a uniform soil layerwith the stress exponent, c, and normalized cone resistance, qcjc,defined
98
CPT soil characterization chart (Step #4), and the point is assigned the cone
resistance stress exponent (c) (Step #5). This point represents one uniform soil layer.
Figure 6.4 to Figure 6.13 represent a few interpreted uniform soil layers for different
soii types and relative strengths. Also shown at the bottom left corner of each figure
is a representation of the CPT soil classification chart (logarithmic 3 cycles by 2
cycles) and the normalized point that represents the uniform soil layer. All available
data from uniform soil layers are plotted in Figure 6.14 using the techniques
illustrated in Figure 6.3. The estimated contours of cone resistance stress exponent
based on the trends of plotted data points are also shown in Figure 6.14.
Discussion of Cone Resistance Stress Exponent on the CPT Soil
Characterization Chart
Figure 6.15 is a replot of Figure 6.14 with the soil type of each unitbrm soil
layer data point indicated. Also slhown in this figure are CPT soil classification lines
from Olsen (1988). The soil classifications of the uniform soil layers approximately
match the CPT soil classifications. Figure 6.16 is an annotated version of
Figure 6.14 that also describe various soil characterization zones. Note the lack of
uniform soil dats for soil mixtures and silt in the middle of Figure 6.14; Thick
layers of a soil mixture or silt are seldom found in nature because the requircd
deposition dynamics are difficult to maintain over large soil depths.
The contours of cone resistance stress exponent in Figure 6.16 reveal important
inoxrmation about the estimated cone resistance contours. Loose sands typically have
low friction ratios (Masood, 1990) because the Nq bearing factor is low. Loose
sands should also exhibit little Mohr envelope curvature and, therefore have a stress
exponent very close to one as described in Chapter 2. The stress exponent contour
of one approaches the annotated loose sand zone on the CPT soil charazterization
chart, as expected. Also, normally consolidated clays should have stress exponents
99
Net Cone Resistance (Log scale) Sleeve Friction Resistance (Log scale)
I-q•.l o (Step 2) 4"i, (Step 2).
I -Atin I-o.-At.
S(St p 1) (Step 1)
(Ste [) (Step 2)
Step 3
\f
R.fic e q o c fle
\)Step 4 1 <Step 5/
ep---------------0/ cornt .• /!d) U-Cnours of
•o • •' •--.CPT Soilz• JJ Characterization
Chart (Olsen, 1988)
IT0 Normalized Friction RatioR fle
Figure 6.3 Using uniform soil layer data to establish cone resistance stressexponent data points on the CPT soil characterization chart
100
Cone Resistance - Total Stress
(atm units)
110 1002 8 2 A 6 8
0.01- . . I •. ,
41~ 2-
Cc
E
W 28W
Ci
L 2-
U 8
c-0.92
Lu
_ ac~e =28a 6 Exponent c= .92> Observational AOI 8010- •' i ' ' '
2~e
28FRI0.42
Figure 6.4 Uniform sand layer at the Holmen, Norway(NGI research site)
101
Cone Resistance - Total Stress(atm units)
10 100
0 .0 1 - . . . . . . . . . . . .
2.
E
q .
U, r. iq = 2.3I cle
L 2
U)
II
•X =I 5-
U4.J
L_ - leL 6 Exponent c- 1 .5 "> Observational AGI - 75 N\
FRI
5.65
Figure 6.5 Uniform unstable silty clay layers for a Hlong Kong Bay deposit(airport replacement project)
102
N,
Cone Resistance -Total Stress
(atm units)
1 610 61000. 01
4J2-
-r|--
E
tn0.1:
V 4) Ci
LI
4HE-
L0 C=0 . 1
4J 2- le 230
"L
01 6Exponent C- .15
C...7Q> 8, Ot-_rati naAO
S20 FRI
20 .. .B...
2.69
Figure 6.6 Uniform sandy silt layer in the core of Ririe dam (Corps of Engineers)
103
2-_-
C
ILCone ResistanCeat u ts- Total StressI
1 0 100
0 .01 . ,-
V, 4-
E4-I-4 .J
M
0.1-
0J QcrleL 2U)
N% 4'>,
L 2
4 Qce 39o. _a)_ 6 Exponent c- .655 ./.m -
AA8 Observational ,%01 90
ce 64
390FRI0.53
:"Figure 6.7 Uniform sand layer for project code DE-S-R
1104
W 2?
' .'T--,I I1I
Cone Resistance - Tota) Stress
(atm units)S10 100
/ 2 4 6 8 4 6 a
0.01 4
0.1
4J
4-
>
L.. c, 160m e Exponent c= .E
B O10servataon•1 AGI 79
10 -- -- - - - -- - -
160m
0.81
Figure 6i.8 Uniform silty sand layer in th,• Aflchafalaya River (dredging. svudy)
105
Cone Resistance - Total Stress
(atm units)
1i0 100
C
E4J
to
U1 0.1U) 16
Q.) L:le
4-'V)
4 -)
U I-
14-) c e1L.L
'-
\
u\
t c. = 16\
W Exponent c= .6> Observation18 AGI , 82
10- y -- -
16FRI:3.25
Figure 6,9 Ucik._•n .;ilty clay ivycr in th• A1t-1'ifaiaya Rivcr (DricdgMiu study)
106
Cone Resistance - Total Stress
(atm units)
10 1000 . 1 4- . .. i , ,--4-•---4-
4 2-
C
B...
0 . -
U) :QC 13W.6I2-
4-J
U 0.1U) - 13
" Q (lee
I .e 3 9d
FRI3.23
Figure 6.10 Uniifolm silty clay layers of thc founidatioUfor Lucky Pecak Darn (Corp• of Engineers)
104
Cone Resistance - Total Stress(atm units)
10 1002 4 6 8 2 A 68
0.01- I
2-
c:
AE
~cleL
4j
-4 - - - - - - -
c: 07
U
L QcIe It11
a) Exponent c- .75> 005er'vational A01 75
u• O. i
Ito
FRI0.3
Figure 6.11 Uniform sand iaycr segment at the McDondalds IFarm, Sea Island,Canada
108
Cone Resistance - Total Stress
(atm units)
o0 100
tn2
C
U 0.1-
(1) : cle
L 2-
4-.J
(D Exponent c- .75
> Obser'vational AGI 90
Cie
45-
FR,
BI
.44
Figure G-.12 lUrafonn siity sand layer at Sa1inas (Old Ifilitown), California~•US(3S c-,i ar4 c project)
1099
Cone Resistance - Total Stress
(atm units)
1 10 1002 d 68? 2
0.01 -
CD
-J4
E
m 6
n 0.1 =M iqCIE! = 5.5
L2-
wL c-0. 75
U \
SOcea, 5.5\L \i• D Exponent c- .75 \> 0- O0servational AGI
4-- •
qcle M71
5.5FRI•5.27
Figure 6.13 Unifbrn foundation clay layer (Levee failure investigation)
110
- Cont. resistantc! stress cxponient (c) contoirsu sing dato frcrn uniforn soil laycr,
, C c-gý
, c - 0 5
I -* c o
1000 --- 1 \
-~ 5C 5
70+'5 '70 079
1~ 0 _7C075
( 70 qj Ij""100 80 0CD 0 " T5'•
-080 0. ' 0 1
(-, A
A 0. 5
C -1 0 --. -0"--3 . 0 1
0.75 eC:
7 U 0 0
o -I
S I A
-1 j• 10
11 0
5)1 1 0 1{)0
No]-111011zeO V"I~ ~l l 10-,0,1 HM ( .)
Figure 6.14 Establishing contours of cone resistance stress exponent using CPTdata from in situ uniform soil layers with constant relative strength
1ll
General sod type from uniform soil layers
*& fdands
"�* Sand. (ovurconsolidated)
j E) Clayc'
*] Clays (overconsolidated)
1000 • o unknowi, soil typ.I
S100C
o //
S . / A.,
-ID
I v / o*, ,,
,V/
AfA
h1mx /1 988) -
1 j o L /I
1121
Hc2i ,- -- t2 •Co > I&•,> U,1(\ I -- /• '<"" "/ - I
,_ IKI
// •--C I G ] ::oiI cha .jo tr~rlz~dioni[ -
•, ilis- Ois ll. l~l0 )El
01 10 100
iolr~lallzced tll<..tloll l•,tlo .;
Figure 6.15 Comparing soil types from uniform soil layers to the cPr soil •_classification line (from Olsen, 1988)I,
112 •
1000 --
0.55'--)O / \ -
0.0 0G. 00 \ .-
I '~~~ IK i LId
S0o. 0 overlt"•~-1 i " Oe
70 0779 / coIisolidated
2"• Loose•
-- o0 -H /070680
10 0 A 1 D,,/803
0.8o 0r-4l0
0~~~ 80 ) 0
I~oh~nallzcd V cto 1tt1 (
F r 1 vs h ce r% sisn sp et c lhrtsuhow\/ 0 61 40 1 (
character.Cizationalin
liles (Ol n. ] 9J81 ) I3llix lrui'L'
0 1 i 0.. . -- l ) (
Noi-nialized 1`,1-1 (A lm h-'(,t Io (,
]Figure 6.16 Annotated version of the cone resistance stress exponent chart showing,soil zones (and strength character) together with CPT soilcharacterization line
113
of one or slightly less; the stress exponent contour for normally consolidated clay is
between 0.8 and 1, as expected. Dense and overconsolidated sands have stress
exponents contours between 0.15 and 0.55, as expected. Overconsolidated clays are
shown to have stress exponent contours between 0.55 and 0.75, also as expected.
Unstable silty clay (i.e. silt structure with underconsolidated clay matrix) have stress
exponents of about 1.1 to 1.5 and are located at the bottom right of the CPT soil
characterization chart, which is a new finding.
The cone resistance stress exponent contours displayed in Figure 6.16 are
approximately perpendicular to the CPT soil characterization (classification) lines.
For a given soil type, increasing the relative strength (e.g. relative density for sand)
should move the CPT-based soil characterization (i.e. qcle and FRIe point on the
chart) along a contour of constant soil type to the upper right (Olsen, 1988, 1984). It
was shown in Chapter 2 that as relative strength increases, the stress exponent
decreases. Soil type and relative steAn•g•h shoulId Vc i-d.c..nd..t of .a.h ot.lh...
because they define different aspects of a soil; i.e. what it is and the state that it's in.
For a given soil type, a relative strength increase can be represented on the CPT soil
characterization chart as a decreasing stress exponent contour level (i.e. increasing
relative strength) along a given soil type contour as shown in Figure 6.16. The CPT
soil characterization chart is therefore, verified in part, therefore, because the soil
classification contours are approximately perpendicular to the stress exponent
contours.
114
Establishment of the
Sleeve Friction Resistance Stress Exponent
.The CPT sleeve friction resistance is obtained through a high-strain strength
measurement where the confining stress on the sleeve is equal to the cylindrical
cavity expansion pressure (Masood, 1990). Sleeve friction resistance is also
influenced by many of the same geotechnical properties as the cone resistance.
However, the sleeve friction is a high strain strength measurement; whereas the cone
resistance is a bearing stress (many times higher than confining stress) that is
dependent on both small and large strains. Therefore, the sleeve friction stress
exponent should not be equal to the cone resistance stress exponent.
Direct Correlation of Sleeve and Cone Stress Exponents
The first attempt toward developing a correlation between sleeve friction stress
exponent and cone resistance stress exponent using uniform soil layer data was
simply a scatter plot of sleeve resistance stress exponent (s) versus cone resistance
stress exponent (c) as shown in Figure 6.17. Tids figure shows a large data scatter
but suggests that both stress exponents are approximately equal without considering
soil type or relative strength consistency contributions. The large scatter does
indicate that other factors are influencing the relationship between the two exponents.
The sleeve friction is more difficult to measure accurately than the cone
resistance because of mechanical constraints such as strain-gauge accuracy, thermal
effects, and dirt clogging the joints (Olsen, 1994). As a result, it was not possible to
establish contours of the sleeve friction stress exponent (s) or the ratio of s/c on the
CPT soil characterization chart. A reliable s/c ratio would allow the less accurate
115
Correlation of thesleeve friction resistance stress exponent (s)
to thecone resistance stress exponent (cM
S AQI greater than 88- (high quality doto)
[3 Q en 73% and 88%
W AQ! les than 73% (lower quality daLta)
1310 -1
oC [] /•-/ U
I /
Q,2
13 C;-J[
'6I I
0 1 2
Sleevce frictliol resistaIlce strcss exp)oletil (O<)
Figui'e 6.17 Relationship of sleeve friction resistance stress exponent (s) to thecone resistance stress exponent (c) using uniform soil layer data
116
sleeve resistance stress exponent (s) to be indexed to the more accurately determined
cone resistance exponent (c). The only correlation that proved satisfactory was that
between the s/c ratio and normalized sleeve friction resistance, as shown in
Figure 6.18. The s/c ratio is interesting because it is analogous to the ratio of
cylindrical expansion pressure (on the sleeve) to the spherical plus cylindrical
expansion pressure (for the cone) as illustrated by Equation (6.1). The s/c appears
to correlate to the normalized sleeve friction resistance quite well probably because
the sleeve measurement is primarily influenced by cylindrical cavity effects.
sleeve stress exponent (s) cylindrical pressure (6.1)cone resistance exponent (c) cylindrical pressure effects + spherical pressure
117
J
10.0 S ,sc Relationship
-1/ (AQI are quality indices)
AQls from 90% to 100'. (Exce llent daIta)
S AQIý; h-oie 86% to 1007 (Good date)
S•) AQis from 0% to 100%o (All data)
0
' 1
- 1.0 _ _ - - 2-
f/Ac0 I . 0
0o
0o
031
0) 1 - , -,--y --iq YlTl , -.VT-im TT ,T Fr1 TI~
0.01 0.10 1 00 10.00Normalized sleeve resistance (atll u Ls)
Figure 6.18 Correlation of the s/c ratio (sleeve to conc stress exponents) to thenomalized sleeve friction resistance (f,,,)
118
Determining the Soil Type Dependent Stress Focus
using Uniform Soil Layer Data
CPT data from tests in uniobrm soil layers was used to show that the Stress
Focus iocation is soil type dependent. The first step in this process involved dividing
the in situ uniform soil layer database into 3 soil classification groups: clays, soil
Lmixtures, and sands. This grouping of data was accomplished based primarily oni
soil type observed in nearby borings and secondarily on the information about the
site geology. Only a smail portion of the database was composed of uniform soil
mixtures due to the geologic scarcity of such deposits. These soil classification
groups were also further distinguished as either normally consolidated or
overconsolidated soils. Overconsolidated soils have very low stress exponents
(0.1I to 0.3J) andW dAV L 1114ý "~e OWA ljy ) cý
cf +he moderately overconsolidated sands probably were classified as normally
consolidated dense sairds be3cause their behavior is similar to that of a dense sand.
Developing the Stress Focus Relationship for Different Soil Types
All uniform clay layer data collected in this research program are shown in
Figure 6.19. The projections for normally consolidated uniform clay layers (using
different clay types) produces a Stress Focus at an overburden stress of
approximately 9 atm.
A clay Stress Focus can also be observed using Figure 6.20 by plotting the clay
and silty clay trends using the stress normalization format from Chapter 3 with the
resultant shown in Figure 6.21. Ihe clay trends in Figure 6.21 appear to converge to
a Stress Focus at an overburden stress of apprcximately 5 to 10 atm, that is
119
Nect Cone, Roscs v&]ce( (LAtin- u iit _110 100 1000
I ,-- Norinaiv eonsohzdoteu trend
x O-(-ver (ccsolidatedW-, ste--1pýwf(
cz :
C.,
Stes oSt o
-3:) Trend trnd for
10.0-11 11f lM (:ý1j',?2-
coli rei sac vru lo vetclfet stress Pou fr
0 -- ci2 \,
approximately the same as 9 atm from Figurc 6.19.
The data in Figure 6.19 indicate that normally consolidated clays have a stress
exponent (c) of about 0.8 to 1.0 and a normalized cone resistance (qc,,) of about
3.5 atm. A cone resistance stress exponent of 0.8 (also shown in Figure 6.16) is
significant because prior geotechnical property formulations (e.g. prediction of S" for
clay) have historically implied a stress exponent of one. The stress exponent of 0.8
to 1 results because net cone resistance rather then the raw cone resistance was used
to establish the trend-soil strength level is more proportional to the
net zone resistance than the raw cone resistance (Chapter 4).
The Stress Focus for clay occurs at a vertical effective stress of approximately
9 atm. The undrained strength at the clay Stress Focus, assuming a c/p of 0.3 1, is
approximately 5600 psf (280 KPa). A clay strength of 4000 psf (200 KPa) has a
strength discriptor of hard (Peck, el al., 1974) and is at the lower boundary for
classification as a compaction sha.c. It is therefore reasonable to assume that a shale
like behavior starts at the Stress Focus for clay deposition.
Overconsolidated clays were observed to have a higher q,,, and lower stress
exponents than for a normally consolidation condition. The overconsolidated stress
exponents typically ranged from 0.4 to 0.6, whereas normally consoli&ted clay stress
exponents range from 0.8 to 1. The clay stress exponent due to overconsolidation is
therefore approximately 50% to 60% of that associated with the normally
consolidated condition.
All uniform sand layer projections are shown in Figure 6.22. The unitorm sand
layer trends are shown to project to a general Stress Focus because dift'Crent sand
types can not be distinguished. Overconsolidated sands have low observed stress
exponents, as expected.
121
4.5-1
\ \e,' , . I I
Seae\ \.: 1 .... t3.0 -.- t
I t' FieldtestsI de
C coidoaOl ,! 1 i i ii I' -. sg
SI' IRK'" ,br
I I ' Tl~ry . ! I lSI I ~ \ "l I" I -- 1.
. o,, -... , I°g, •"w 1.9
3.01
• , , Ch•Ago-T -- Lond-• g • 2.0
0 : "' "- Venezlt elans1 . - rod T '-Ih-".•_ t' 2 .3"
0 22.> .001 01 01 1 10 100 1000
Effective Vertical Stress (atm units)
Lff JfI I I L] L J1 3 10 30 100 300 1000 3000 10,000
Approximate depth (Ut)
Figure 6.20 Compression curves for several dlays and silty clays(from Mitchell, 1993; L~ambc & Whituian, 1969)
122
Void Ratio
10 ! 0.1- 0.1 KopingŽ
-;ATjiuur~y IClaysGosport
- HoeenS(silty clay )
Silts
C1 10 typebase..dStressFocus
.• 100 locationsC.)
1000
Figure 6.21 Replot of selected soil types from Figure 6.20 in using stressnormalization format to show that clays have an approximate StressFocus
123
Net Conc Resistancc (.tAr ult )
1 10 1100 1000 10000
0 ! t ! I : : il1 l I ...........i J.LI1,.. , __________ ,__ ,__,
ct, //. ho~rially Cojisohidred Treutjl
- 1 9 ---0-1
c/, •ron~ulldaled
10.0- xx----t
I t'ars eonxplonnshdtrnt),.a
C-- tr CI~ d 3 to -ard Itt , Stress Fo u / -' •
S100.0 7Approxlnintc{ Stru' i Focus, Iolo sand • .A
,-24
- -I1 ,liournia tly ronsofrdatcH . -eid tll oward h S tress laocui
E2 100}.0} -- __
igure 6.22 Projrctins ntf Strend foru unform sond layer intrso lgntc
r(itncvcs- o eria feciesrs
C-' 12I
All uniform soil mixture layer projections are shown in Figure 6.23. Soil
mixtures are more complex and cover a wider range of conditions than do clays or
sands. As a result, the soil mixture layers projections are more complicated than for
clay or sand. For example, dense silty sand can be stronger than a den..-c clean sand
and a honeycombed silty clay may have a moderately high sensitivity much like
salt-leached clay. The locus of Stress Focus trends in Figure 6.23 represents the
zone projection for all soil mixture classifications. Clayey soil mixtures project to
the upper left of the elliptical locus and stronger sandy silts with higher qcle are
project to the lower fight of the elliptical locus. Unstable soil mixtures are also
depicted and project into the soil mixture Stress Focus to the upper left of the
elliptical locus.
Soil Type Dependent Trend of the Stress Focus
There is enough information at this point to support establishment of a
soil type-dependent Stress Focus that will be called the "Stress Focus boundary".
Shown in Figure 6.24 are the Stress Foci for clay (from Figure 6.19), soi, mixtures
(from Figure 6.23), and sands (from Figure 6.22). Also shown are the Stress focus
locations for Hokksund and Ticino sands from laboratory chamber test evaluations
(from Chapter 5). The soil type dependent Stress Focus boundaiy is shown as a
thick dashed line that passes through all of the Siress Foci. This boundary is curved
and represents an increasino normalized Stress Focus (qn) (see Chapter 5 for
definitioin) as the soil classification changes fiour. clay to sand. Conceptually, the
Stress Focus boundary represents the boundary between a 3oil-like afd (sedimentaiy)
rock-like mechanical behavior.
"The soil type dependent Stress I'ocus boundary is depictd al,arn in Figure 6.25
to show behavior at confining stresses inwcr and highcr than th" Stres.s Focus. Fo,
confining stress less than thi" Stress Focus, a fcw example soil typ,'s arc Jepictcd
125
A ~Net. cone Betsstance (ciliA1 Units)
1 10 100 1000 10000
j ~uniform soil mjotort layers
- ~~Sir!3 . oc. l',slon
[2 100.0lO-
Ct - Zonic of onsfof,!c or weak ooi; rniotujrcz.(V I g tlayc oIl's ýLlly daOys) on') uidcrcojisolidoted (lay-,
h1 i ýsit u da ao trendUs fur un formj sc)il I iwxt uru2'ý0, g C~ I lyev sIlIt, M41 ,sIlt v cI ia v sl I Nv san Id, ct i
1000 0-n - _ _ _ _ - I
Figure~ 6.23 1'io-jections of trend, fur nilfoirm soili mixture layers in jerms of Logcone resistanice versus Log'- vncalQH effective, st"ciss
I 26
together with different relative strength trends. Also shown is the probable behavior
for all soil types at ccnfining stresses beyond the Stress Focus; this behavior is likely
at a stress exponent of one and in a domain where strength behavior is
(sedimentary) rock-like.
Conclusions
The main requirement for normalizing the CPT measurements is the stress
exponent. Figure 6.16 can be used to determine the cone resistance stress exponent
using field CPT data. The sleeve fiiction resistance stress exponent is estimated
using Figure 6.18 in conjunction with Figure 6.16. Cone resistance stress exponent
contours are approximately perpvndicular to soil classification lines in the CPT soil
characterization cuart; representing indirect support for the validity of the chart.
Finally, in situ uniform soil layer data and chamber test data were used to establish
the soil type dependen't Stress Focus boundary.
0
127
Net. Cone Resistance (atri units)
110 100 1000 100007-- I
"--; J , • tress Focus from
0ý1J uniforn, Lla')' layers
! / -- In SituI data trend ., from un ufnruiiI i-/soi I ' Lure 1'rs
55
•":/ I 0 • rt SituJ dot. tlrfnd,10 0 f ro, i, u iformQ., -snd layers
100.0 *
Cý -Sodl type( deperldelitI Stess F Scu s bou Fuda sr.based o no tyrends from sr
•. - lin si~Lu Ujilfollll soil layers & sr• • f- ...... at .... ofIl •. b o r a t o ly (2h a l n ib e - t e s t s ) DI n r, , . Hl Id ,,, 1 9- 1 . )
1000 0-
Fi.gure 6.24 The soil type dependency trcnd for the Stress Focus based OD uniformsoil layer and laboratory chamber test evaluationl
120
Net Cone Resistaiicc (brm uiit.s)
1) 100 1000 10000
lncreasirignormalizedstrength
S \ \ Particular Increasilig3 It 0 ife e t , '\ a tiu\, sil mi re Rl V
S- 10- ford
different\ \rclays a SOL , psarid type
cfJ -'•mixture
H \ \ ,V'\\
" a swid (
o 4% \.
1 . - Soil tyl)p dependent. /- . ".-. Stre~ss Focus boundarv -J
/D > 3 2>• Incieasing frictiloji ang)t
for high con'fining stress uoriditi •i t; ,.:
1 000.0 -1_ "
Figure 6.25 Inferences concerning the soil type dependent Stress Focus
129
Chapter 7
Normalization of
Selected Geotechnical Properties
Introduction
Geotechnical property normalization is vital toward development of CPT-based
prediction correlations and prediction of in situ geotechnical properties. CPT
predictori of gcotu-chinica properties requires accurate stress normaiiiLUMi;
otherwise, for very shallow or very deep conditions, the stress normalization will
itself induce errors into the predictive process. This chapter will describe new
normalization techniques for the Standard Penetration Test (SPT) blow count and the
shear wave velocity.
Standard Penetration Test (SPT) Normalization
Normalization is required to convert the measured SPT blow count, N, to a
representative value that would be measured when vertical effective stress
equals 1 tsf (e.g. approximately 1 atm). This normalized SPT blow count can then
be used to predict a variety of normalized geotechnical properties, such as
liquefaction resistance and friction angle. A new observation will be introduced that
results from the fact that SPT laboratory chamber tests arc subject to a stress relief
130
associated with the constant mud pressure in the chamber borehole. During a SPT
laboratory chamber test, the borehole mud height is always the same (approximately
6 feet), regardless of the chamber confining stress level. Quantifying this pressure
relief will show that the SPT chamber-derived stress exponents are too low. It will
also be shown that the correct SPT-based stress exponent for field applications is
equal to the CPT-based stress exponent.
Historical SPT Blow Count Normalization
The state-of-the-practice for Standard Penetration Test (SPT) blowcount
normalization for the last 12 years was developed by Seed et al. (1983) and later
confirmed by Skempton (1986). This SPT normalization technique uses an exponent
of the vertical effective stress for two relative density ranges. Seed et al. (1983)
used data from the Bieganousky and Marcuson (1976, 1977) study to develop the
SPT CN normalization parameter shown in Figure 7.1. The SPT blow count, N60,
(i.e., measured using equipment that delivers 60% of theoretical maximum free-fall
hammer impact energy or adjusted to simulate same) is converted to a
stress-normalized value, (N1)60, at an equivalent vertical effective stress of I ton/fl2
131
using the following equation:
(Nl)6 =6N CN= 1 (7.1)(Go')"
where
(N1 )60 Normalized SPT blow count, equivalent SPT at a vertical
effective stress of I ton/ft2 (approximate atmospheric pressure)
N 6 0 SPT measured blow count at 60% of theoretical maximum free-
fall energy which is the US approximate average achieved in
practice
(I Vertical effective stress in tons/ft2 (e.g. approximately
I atm, 100 KPa, 0.1 MPa, etc.,)
n = SPT overburden stress exponent
nr0.45 for relative densities from 60 to 80%)
CN SPT normalization factor (See Figure 7.1)
A range of CN values back-calculated from field and laboratory chamber test
results is shown in Figure 7.2 (Skempton, 1986) in terms of overburden stress.
Overburden stress is always represented in terms of tons/ft2 (approximately 1 atmn)
and CN is equal to I when the vertical effective stress is I tsf (i.e. approximately I
atm). For the last 12 years, equivalent SPT stress exponents of 0.45 for relative
densities from 60 to 80% and 0.55 for relative densities between 40 to 60% as shown
Figure 7.1 have been widely used. The CPT chamber-based stress exponents are
typically 0.6 to 0.7 (Schmertmann, 1979a), with 0.61 commonly used for relative
densities between 40 and 80% (Seed, et al., 1983). Therefore different stress
exponents for CPT and SPT normalization have been inferred fTom chamber test.
132
There appear to have been no theories developed to explain why the stress exponents
for Equation (7.1) decrease with increased relative density or why there is a
difference between CPT and SPT chamber derived stress exponents.
SPT Blow Count Normalization
As background, SPT chamber data were evaluated in Chapter 5 and show that the
SPY Stress Focus location is sand type dependent. Also showýn were correlations of
SPT chamber derived stress exponent versus relative density. The SPT chamber
testing procedures used by Waterways Experiment Station (WES) were also
described in that chapter.
S&fesses at the SPT Sampler
Distinguishing ".le stress states developed during penetration at and nearby the
SPT smnpler is important for the discussions to follow. These stresses are illustrated
* in Figure 7.3. The SPT blow count reflects a complex combination of static and
dytnamic forces acting at the end and along the side of an SPT sampler. The
combination of all these forces on the SPT sampler determines the SPT blow count.
The SPY blow couni is also dependent on confining stress as reflected in the Cn
normalization technique. Therefore, because the SPT blow count is proportional to
the confining stress, the stresses influencing the SPT sampler (csw) are dependent on
th,. confining stress (a,,) adjacent to the SPT sampler. If the mud pressure
influences the confining stress neI.f to the SPIT sampler (asY) then the stresses tha!
iniuence the SI'T blow count (asi) will be affected.
133
CN
0- 0.2 0.4 0.6 0.8 1.0 1.2 1.4 .6u
7-1
N,-2 q -VALUES BY CPT
(D =40 TO 80%)Q r3
S4-
w D = 40 TO 60%> r0 7
{-. Note:
U 8 C,, is the SPT normalization parameterwa'• 8- Dr is relative density -
LL qc is measured cone resistance
N-VALUES BY SPT
101 1 -1 - I 1 -1 1 1
Figure 7.1 C.. versus vertical cfl'ective stress ,(Ki ps/ft2 ) relationship developed bySeed et al. 1983 (Note: 2 Kips/ft' = I atm)
134
C0 1.0 2.0
00
100--
N =CN N
E~ N
FIELD TEST DATA0 Fill0 NC Ifine sands~
m NC Coarse sandh
PA LABORATORY TESTS
[ jMarcusonb:--JBieganouskyV (1977)
Gibbs & Hottz(1957)
300 _ _ ~ __ _ _ _ _
Figurc 7.2 IBack-cal,.ulatedl SPi C1 pararn -t(.TS from field and laboratory charnbctest (Skerupton, 1936)
135
Mud Stress Influence at the SPT Sampler
In the field, the borehole mud pressure is approximately equal to the soil vertical
effective stress. If the borehole mud pressure is low (which is true in chamber
testing) in comparison to the soil vertical effective stress, then ihe confining stress
(@Yc) next to the SPT sampler will be reduced. It is outside the scope of this
dissertation to determine analytically the exact reduced stress level at the sampler due
to reduced mud pressure effects; however, an approximation will be examined. At
the bottom of the chamber borehole, the reduced mud pressure decreases the effects
of the in situ vertical effective stress around the SPT sampler. The typical 5-inch
diameter borehole bottom can be thought of as an equivalent "reversed" circular
footing exerting an upward stress equal to the difference between the in situ vertical
effective stress and the mud pressure as shown in Figure 7.3. At a SPT sampler
penetration of 18 inches (11/2 feet), the ratio of equivalent footing diameter to depth
icfZ. ilec riACiil1C ;?I q1 "tpie1rcipri f (.tin,"opcc tl1rnn(:mif nf RnTlfltOiM~qtf1V So/,,
based on the simplistic Boussinesq stress distribution theory (Lambe and Whitman,
"1969). Howeýver, the SPT blow count is determined by advancing the SPT sampler
from 6 to 18 inches below the bottom of the borehole. At a depth of 6 inches, the
ratio of equivalent footing diameter to the depth is 1.1 which corresponds to a
"revei'se footing" stress t.~ansn.isswin of a orcximn,.ieiy 30%. 77hereforc, the mud
pressure cffe;t, on the SPT sainpler, end bearing forces during penetration starts at a
transmission of 30% and redulces to 5% at the end of penetration.
The side frictionar forces generated duning 18 inches of SPT sampler penetration
are also affected by the mud pics:rc efffcts. The SPI samplci side friction
developed from 0 to 6 in,:h,:: below the bottom of the boreholu dominates thesampler side frictional force dilirig, sampler pcncti-ation from 6 to 18 inches
(Sclmcrtmnanii, 1979a). Moreover, the side friction at 18 inches below the bottom of
the borehole will only influcnce thf.e final blow couni. Side fri'don contributions
from the first 6 inches arc scvcjal tiwes wore influential thai fliom the last 6 inches
136
of penetration. Sampler side friction influence therefore decceases vith depth below
th? bottom of the borehole. As a result, the mud pressure transmission from the
cquivalent mud pressure "reverse footing" on the SPT side friction is probably
greatel than 60% because the first 6 inches of side friction is so dominant.
The SPT sampler is resisted during penetration by a combination of end bearing
and side frictional forces (Schmertmann, 1979a, and Douglas, et.al, 1981). Reduced
mud pressure influences will affect both of these SPT sampler forces. The stresses
surrounding the sampler (c;,) should therefore be reduced by an amount equa! to 10
to 50% of the difference between the in situ vertical effective stress and the mud
stress at the bottom of the bore hole (i.e. mud p.essure "reverse footing" effect).
This 10 to 50% range is based or, the 60% value given for side frictional force
in: -ience and the 5 to 30% range for end bearing forces. For the inmmediate
discussion to follow, an arbitrary 30% reduction will be a&ssumed. However, other
mud pressure reduction factors will also be evaluated at tht.; end of the SPT'
no~rmalization section.
Stresses at the SPT Sampler for Field In Situ conditions
For a field condition, the. irud pressure, at the bottom of a bore bole shown as
line B in Figure 7.4. The vertical efthctivc stress is shown as line V. Thle calculated
confining stress at the SPT sampler for the field condition, (cyt)f, is shown uts line F
using the 30% mud pressure influence. The rcsulting confiuting: stress on the SPI
sampler (oS,) 1 is linear and very cl,:se to the vertial eilcct'le :,tress. 'I hereiore, mud
pressure does not significantly influence the SPT sampler 1: Iheld condition:;.
137
footingSiress
(mud pre-ssureminus
vertical effective stress) Gmud
- F I, nn PeT~KfF Chamber100% I'!Field 7
20% / IfLii&11: - Influencing Stresssampler
Swe-s,, Urmnsmissionmaaor(preentofthe equivalent q S'CS
rý,vci,,cd looting siress.Using tnef Bowssim~sq ela-stic Comliftation of titatic and dyanai;mstress &iLibutiun thii,'iy. forcfn cn the saiupler side and end
atrcIas
Fiigure 7.3 Mud pre~ssw-e effects on thc STT sampler
13S'*
0 1~
Vertical,,. Effective
Stress
2 -- ----- --- - -------- - -- -.- ---------------
. I 'Field in situ
F 31 ,, _ : at the sampler I3 1 (-- -- --- )-- - -- --- ------ -- --- --I( )
-4 . . . . ... . - - . . .
-------------- . . . . . . . . . ."......... - - - ---------- --- ------ -.. 3 0 % th e.-j I V(difference
£1 (between thei l . ...... ------ ...... i.... 4" , -i •.- ! .
B.. .. . . B - in situ and10 ............ ............ ......... 1\ , I.: !
- ---------------------------------- m ud stresses
30%
*_ /\
n 6 ," 070W 7//I o20
Stze.ss (atm units)
NOT1E: 11wtho Fard i ISitu tes
V,•• ,ua •~ v -I .. . o /C 0. , MGJ U• [hl
o •r• L v C-,,:O• .
"w I nplcr 1 - (oa) t
Figure 7.4 Drilling mud pressure effects for the SJ'1 sampler in field bozeholes
139
Stresses at the SPT Sampler for Chamber Testing (onditions
SPT laboratory chamber tests have a constant borehole mud heligt. for all
chamber overburden stresses. This mud pressure is always equal to a 4 to 6 feet
column of mud having an approximate pressure of 0.16 tsf as show-I as Line M in
Figure 7.5. The calculated confining stress at the SPT ,:an:pier for the chamber
condition, (crsc),, is shown as line C using the 30% mud pres:.we influence
assumption previously discussed. Thc slope of Line C on the log log plo. in zerns
of vertical effective stress is 0.70. Line C represents the relati ils'hip between
confining stress surrounding the sampler (for chamnber tests) (o o and 1>V
SPT Chamber tests yield blow count versus ,j', relationstips that are analogous
to the stress influencing the SPT sampler (ao,.) versus a' From historic SPT
chamber tests, this relationsbip between (a,-), and o',, has a SPT stress -exponent of
approximately 0.50, The 0.50 stress exponent is the average of 0.45 to 0.55 by Seed
et al. (1983) or is the average of the range at a relative density of 60% from
Chapter 5. A stress exponent is simply the log log slope as; shown as Line L. in
Figure 7.5 for the (Xi), to
All the stress relationships that influence t : SPT sampler have been cescribe.dt
and are in terms of q' . Line C (mud pressure influence) describes the reduced
confining stress next to the SPT sampler (aoL.) C, and line L (from interprctation of
chamber tests) describes the stresses on the SPT sampler that influence the blow
140
--- Vertical effective stress
.. .. •-- --- --- at the samnpler in the ctamber1 '
30% the differettce00tween the cbambei-
.and drilling mdst
---- --- - (if cn Wi st e s1-- -- -------
201lm mud (a----n------ - -
I ov))i)i / \
--I -- ----.-- --.-.........
S-1 0.-- ---5g - - - - -
-!Stesc infu ! g h
r S .1 1
mStreos o(are uhrts)
((oeret
°I I 1- ' l 0,
spm:tr ý'.o__ 01.5+ (oi). •]Stresse influemncing the\
$PT &.unpler blow count level, (ore)c(Fo Seedl, etal., 1981 orftaerrctation of SPT chambcr test)
(00 0.43 Lo 0.53 (using 0.5 for itLunvtion)
Figure 7.5 Stress effects on the SPT sampler for historical laboratory chambertests due to a constant drilling mud stress at differing confining stresslevels
141
count, (oysi) .C Both are in terms of vertical effective stress. Line C can be
represented as;
C, - (7.2)0.70
where
(UsCc) &PT sampler confining stress level
for the chamber condition
C, normalized parameter (equivalent value at I Atm)
Likewise, Line L can be represented as:
L, )° (7.3)
where
(GSi) = SPT sampler influencing stresses
for the chamber condition
LI normalized parameter (equivalent value at i Atm)
142
Equations (7.2) and (7.3) can be combined to determine the ratio of stresses
influencing SPT sampler (i.e. blow count) to the confining stress next to the SPT
sampler:
C1 0.70 (74)
with further reduction and condensing:
X, = ((7.5)0.71
where
X, combined normalized effect
This formulation relates the stresses influencing the SPT blow count, ; ., to
the confining stress next the SPT sampler in the chamber, (a tc) c with a stress
exponent of 0.71. Equation (7.5) therefore relates the SPT blow count (as reflected
by (aj )c) to the actual confining stresses at the SPT sampler ( (aJ)c ). For the
field SPT condition, the confining stress next to the device is approximately equal to
a',. In both cases, SPT blow count is related to the confining stresses surrounding
the SPT sampler as shown in Figure 7.6. For the fie!,' ,'.PT condition, the confining
stress is equal to the vertical effective stress (ao,). However, for chamber SPT tests,
the confining stress is equal to the mud pressure reduced confiring pressure ( (sc)).
The ultimate goal for field SPT normalizat;on is a relationship of SPT blow count
(N) to al,. Equation (7.5) reflect this N to n', relationship because the chamber
reduced confining stress (a..). influences the SPT sampler just like the field o'
influ,.-n es the SPT sampler. Therefore, the stress exponent of 0.71 in Equztion (7.5)
143
(rather than 0.5 for Line L in Figure 7.5) is the correct stress exponent for field SPT
situations. The next few paragraphs will show that the SPT field condition (i.e. SPT
stress exponent) is equal to the CPT chamber conditions (i.e. CPT stress exponent).
A simple means of determining the stress exponent for (0,C) C based on the mudtm
pressure reduction value and the chamber test stress exponent can be developed
based on logarithmic construction with the result shown below:
HoHJb - n •
100) _
for
X-- (7.7)
where
b = Stress exponent for confmini, stress adjacent to SPT sampler
n Stress exponent determined from SPT chamber tests
(from historic SPT chamber test,)
R, Percent reduction of confining stress on the SPT sampler due to
the mud pressure
Using the initial example of n=0.5 and Rk=30%, the result is b=0.71 using
Equation (7.6). For a loose sand, the mud pressure reduction (P() at the SPT
sampler could be 20% (low end of the range of 5 to 50% on page 137), the chamber
stress exponent could be n-0.6 (see Chapter 5), and the result is calculated to be
b=0.75. For a dense sand, the reduction factor could be R.=45% (high end of the
range of 5 to 50%), the chamber stress exponent could be n=0.22 (see Chapter 5),
and the result is calculated to be b=0.40. The average stress exponent (n) for the
144
Equvalent Field FieldChamber SPT CPT
SPT
Equ i--aku i
6 foot mudicolumnheight
•"• •~ (\ =vOReduced a'(aconfining stress at I C I 2]the SPT sampler SLi E edue to mud /samplerpressure effects SPT
sampler
Figure 7.6 Comparison of confining stress surrounding the SPT sampler (or CPTprobe) for chamber and field conditions
145
SPT chamber stresses influencing the sampler ((oa,) .) to o' for these three
examples is approximately 0.44; which is at the lower range of the
Seed, et al. (1983) range of 0.45 to 0.55. The stress exponent (b) for the SPT feld
stresses influencing the sampler ((o;) j) to a'v for these examples is approximately
0.62; which is within the range of 0.6 to 0.7 from CPT cone resistance chambei
tests. For these examples, the difference between stress exponents (n) and (b) are
specifically 0.21, 0.15, and 0.18, with an average of 0.18.
The difference between the CPT chamber stress exponents (c) and SPT chamber
derived stress exponent (n) are shown in Figure 7.7 (taken from Chapter 6). This
stress exponent difference (i.e. c-n) in Figure 7.7 is about 0.18, which is also the
approximate difference between the SPT stress exponent (n) and (b) from the
previous paragraph. If c-n approximately equals b-n then c=b. Therefore, the cone
resistance stress exponent (c) equals the field based SPT stress exponent (b). This is
additional evidence that the CPT cone resistance stress exponent (c) is the correct
SPT stress exponent for field SPT data normalization.
Conclusion
The Seed SPT stress exponents of 0.45 to 0.55 are in error because of mud
pressure influences for chamber tests at high confining stresses. Drilling mud
pressures at the SPT sample in chamber tests are too low compared to those that
exist in the field. The best stress exponent for SPT nomialization is the CPT cone
resistance stress exponent. The CPT cone resistance stress exponent also falls within
the range of back-calculated CN in Figure 7.2. Chapter 6 introduced a technique aid
chart for determining the CPT cone stress exponents using field CPT data from
which the SPT normalization stress exponents can be taken as weii. To determine
the best stress exponer• for SPT stress normalization therefore requires a nearby CFT
sounding where CPT stress exponent can be estimated.
146
Rbnge of'
~~~~P st2 ~css, expoiierits()I from chamiber evablut~it~ioii
The averagc diffc-rence0.9 -ibetween the
CPT and SPT chambu2r
0.8 stress exponents isCL) I ap})roxiinatcJy 0. 18
> 07-
0).6
Q.,
0.1 - f ioI.l chamaber evC luaiop01
,)0 30 4(0 50 60 U U 8 9
F; vvi c 7.7 Ccmipa~ison oftiv.iiv.-t.ngec3 for CPT 'zdSPT str-ess ce;,ponciits frOhnt
evaluationm of chluuib data
147
Normalization of the Shear Wave Velocity
Introduction
CPT prediction of shear wave velocity requires a good technique for
normalization of the shear wave velocity--and the shear wave velocity normalization
requires a technique for estimating the slieav wave velocity stress exponent.
Correlations for CPT prediction of shear wavw velocity will be developed in
Chapter 8. A shear wave velocity normalization formulation must be simple
(following the stress normalization concepts from Chapter 3) and be relatable to
previously proposed formulations. A variable shear wave velocity stress exponent
will be introduced and shown to be dependent on soil type, and predictable using the
CPT cone resistance stress exoonent.
This shear wave velocity normalization formulation should also be based on the
maximnur, shear modulus formulation because the two arc theoretc ally related. The
fimst stel:r will be to introduce the maximum shear modulus formulation and then
shoow that the historical formulations can be related to it. The next step is converting
the norrmalized maximum shear modulus formulation to the normalized shear wave
velocity formulation. Thc final step is to correlate historical stress exponents for the
wave velocit5; to the stress exponent for the CPT cone resistance.
148
Definiticri of Normalized Maxinunm Shear Modulus
Using the stress normalization concepts in Chapter 3, the normalized maximum
shear r.ioduluz, can be defirned as (Olsen, 1988):
G = (Gm)j (7.8)
wherie
GmhX shear modulu.i (in Atin units)
(Gj,)WI Nonnalized shear modulus at an equivalent vertical effective
stess of I atmospheric pressure
m = Shear modulus exponent value
This equation requires verification that it does represent a generalized maximum
shear modulus formulatiou. Verification is showT hi Table 7.1; (Gma,,) are shown
that are derived from historic maximum shear modulus formulations. The next step is
converting (Gm.), to a normalized shear wave velocity (VW1) using theoretica!
relationstips.
Relating Maximum Shear Modulus to Shear Wave Velocity
For linear elastic behavior, the maximum slheaj modulus is theoretically related to
shear wave velocity, V,, (Telford, et.al., 1976) as shown beilw:
G,= V• (7.9)
where
Vs = Shear wave velocity (in units consistent with GM( and p)
p = Mass density
149
SI H
0 Ell
02oo
~~0 0
co 65.
o. II-
0 --
U~rD i *n , .:
"" h u I ,- -")
-u .- 0,
SII EI I Ii l h 15
150~~ '
This equation can be combined with the normalized shear modulus relationship
(Equation (7.8)) to produce the following:
(Gm,) (&)r = p V2 (7.11)
where
(o',) a Vcrtical effective stress in teims of Atmospheric pressure
(mean stress (omean) is historically used in thir place however
amcan is simply equal to Finean (a ,) (Sec Chapter 2) )
m = Stress exponent for GmX
With simple rearragngement, shear wave velocity, VS, is equal to:
This is the basis for the normalized shear wave velocity formulation. The
normalized shear wave velocity, V51, from Equation (7.12) is defined as:
I =(7.13)
N P
with the shear wave velocity stress exponent (v) equal to rn/2. The normalized shear
wave velocity fomulation is therefore defined as the following, based on Equation
151
(7.12) and using Equation (7.13) with v-rn/2;
where;
v Shear wave velocity exponent =--
2
(VsI)4,s Normalized shear w~.ve velocity in xemis of feet/seco.nd
(V5 l can be defined ii; any velocity units)
Relationships of Shear Wave Velccity Stress E-poie.-t to Soil Type
Lee and Campbell (1985) presented generalized relationships of ";hear wavc
velocity versus depth based on 15 years of project work. This summary o" shear
wave data obtained for differing site conditions are in terms of log shea, \\c'.'.
velocity versus log dept,. The publication does not present the actial datw; howeve:,
it presents the general trends and range based on the data. An exawnplc fto firn
natural soils is shown in Figuie 7.8. These shear wave velocity verses depth 'nd:
were also represented as showni below;
V (d c)' (7.15)
where
V5 Sihcar wave velocity, in nizts 3of ft~second
d = depth, units of feet
c = depth, accounts for tbe non-linear intei-section of shear wave velocity
a' the growtd surface
n = depth exponent
K constant in terms of ips/hi'
152
The depth exponent (n) can be related '.o the shear wave velocity stress
exponent (v), because depth is used to calculate t[c vertical effective stress from the
effective unit weight t(') as sbown below;
(os' (y ' ~ (y')V (h )Y (7.16)
The :erti..al effective stress and depth paramnetrs in Equation (7.16) both have the
s-irne exponent. Therefore the depth exponent (n) in Equation (7.15) is
approximately eqaa! to the shear wave velocity stress exponent (v), at least fbr
normalization purposes. Lee and Cami,pbell's (1985) data were summarized for soft
natural soils, intern-ediate firmn natural soils, and firm soils as shown in Table 7.2.
Tne depth expanent (i.e. stre:s expouzil.) from this table will be related to soil type
and the CPT cone resistance stress exponeni at the- end of this discussion.
Tahie 7.2 Shear wave Nelocit; parameteis dcternince from dauw presented byLee and Campbell (1985) for differing soil conditions
I Soi _V,"(ftsec) a! a depth o Dcpd3 exponent (n)200 for sarwave velolty
Soft n'•ural soils 780 0.46
Intermediate f'rm 950 0.43natuxal soils
Firm soils 1300 (. 1
Probab)y den'e sands
Approximately V SIal a', ='- I AlA' ***Approximately %.qual to the s',:ear wave velocity stieos exponinl (v)
Shear Wave Veiocity Stress Exponent trculd from a tStlnd SitRc
13;.J.i, Pc,:v~i, Superbo, 13Btaglio and R,:,mio'IPewski (1988) s.'udýe, die th'ered
sbeac wave v:Vcities for Po River sand:. 'l he -r -und, have a fines conten1 (Ii terns,
1 35.
1,000---7I rrrr-rr1 T-7T7
FIRM NATURAL. SOILS
100 /ULJLU /LL /
z
0 10I
I00 1!0010w
~15
of the percent passing the #200 sieve) ranging from 3 to 9%. They related
overburden stress and maximum shear modulus in a form indexable to Equation (7.8)
but also related fines content to the stress exponent (m) for the maximum shear
modulus as shown below:
20 (7.17)m = 0.43 + 0.39 (7.17
where
m = Stress exponent for the maximum shear modulus
P200 percent passing the #200 sieve as a percent
This equation can be expressed for the shear wave velocity stress exponent (v) as
shown below, because (v) is theoretically equal to half of (m).
0.215 + 0.195(7.18)
Fo, a clean sand (i.e. P2 00=0%) the shear wave velocity stress exponent (v) is 0.21
and for a sand with 10% fines content (P2o=10%) the stress exponent (v) is 0.24.
Therefore for the transition from clean sand to dirty sand, the shear wave velocity
stress exponent chaznges from 0.21 to 0.24.
Relating Stress Exponents for Shear Wave Velocity & Cone Resistance
"Table 7.3 presents additional data relating the soil type to the shear wave velocity
stress exponent from published sources and this research. The table indicates that the
shear wave velocity stress exponent for clay !anges between 0.42 to 0.50 and for
sands ranges between 0.18 and 0.28. Tiese ranges from Table 7.3 together with the
Baldi et al.(1988) and Lee and Campbell (1985) data are summarized in Figure 7.9
155
in terms of soil type. Also shown in this figure are typical cone resistance stress
exponents from Chapter 6 based on soil type. The trends from Figure 7.9 indicate
that the shear wave velocity stress exponent (v) is approximately 45% of the
estimated cone resistance stress rxponent (c). While this stress exponent prediction
technique can only be considered an estimate, it represent the best method when
there are no uniform layers to support establishment of a stress trend.
Table 7.3 Published stress exponent for shear wave velocity
Basic Specific SS
soil type Soil type (ft'sec) exponent, Reference
Review of 07.i8to-0.25 Stokoe, LeeW& Knox, 1985publishedcd•y sandsOttawa s P2 eq,•,_n 0.3 - c_--
t.'Nva sand equation 0.25 Hardin & ichat (1963) TIiTh~e quoartz -- 782 0.8 amillton (197 1)"
Sand ' -ine quartz 0.31 n (1971)uobrse 410.26 Hmlo(1971)
quartz rClay 0. Hardin and Drmevich
Clays (1972)(Normally Aaskan 375 OT Singh & Gardner (1979)'
Consolidated) clays
over 1400 -0.-13 S g & Gardner (1979)consolidated
Clays Alaskan clay(Over compacted 420 0.09 Harding Lawson Assoc
Consolidated) sandy clay 1978)fill
156
1.0•---V Normally consolidated clay
0.9ý0.8 "Medium
SU ýsCi•- ,'U dense0.7 tCO t., 1 sand
0.6- shear SWa veS'velocity
o.5 t05'al0.4, lO •k I t /-
0.3
0.2'' Thc shear wave volot"y suess �.xpoaet (v)0. 1' is aptproximttely equal to 45 % of the"
cone resistance stress exponent (c).
Clay Soil Mixtures Sand
Soil Classification
LegendCane rcsistaace Stress exponent trends from Chapter 5
Stokoc, L.e, and Knox, 1985, and Table 11
SIce and Campbell (1985)
i Baldi, et-al., (1988)
Figuk'e 7.9 Comparing the stress exponcnt ranges for shear wave velocity and
cone resistance
157
Conclusions
The shear wave velocity stress exponent for normalization is related to soil type
and can be estimated based on the CPT cone resistance stress exponent. The shear
wave veiocity (V,) stress exponent (v) is approximately 45% of estimated cone
resistance stress exponent (c) (fiom Chapter 6). This procedure represents a new
approach for n'"-malizing shear wave velocity and seems to give good results. To
successfiilly normalize the shear wave velocity, therefore, recuires a nearby CPT
sounding where the CPT stress exponent can be estimated and then converted to the
shear wave velocity stress exponent (v).
158
Chapter 8
Development of Correlations for
CPT Prediction of Geotechnical Properties
Introduction
One of the ultimate goals of using the CPT as a geotechnical investigation tool is
direct prediction of geotechnical properties. Prediction of geotechnical properties
using, CT data is iflustrated in Figure 8.1; CPT data is normalized, the normalized
geotechnical property is predicted, and finally the geotechnical property is calculated
for the in situ stress condition.
Historicaly, research has concentrated on developing relationships between cone
resistancc and various geotechnical properties. In this chapter, CPT correlations
using CPT cone resistance and sleeve friction resistance are developed for prediction
of SPT blow count, clay undrained strength, and shea wave velocity. Several
important ingredients were required for developing these correlations, namely 1)
stress normalization techniques for the CPT (and geotechnical properties), 2) a large
database of CPT and soil sample data, and finally, 3) accounting for bias data caused
by soil profile differences between CPT soundings and boreholes.
159
CPT Boring
CPT Prediction ofgeotechnical properties
Normalized fsle I Normalized\CPT ) a1geotechnicalparameters qC at o= atm property /'
SNormalization Use stress
normalizationtechniques toinclude stresseffects/
-~/
IfS Geotechnical/ �j prope, ty
CPT measurements
Figure 8.1 Using CPT r measuremnci.,s io predict gcotcchnical propcrties
160
The CPT and soil sample database
A large database of CPT and soil sample infotmation that represents soils from
around the world is described in the Appendix. This database contains data from
approximately 90 projects, 670 CPT soundings, 580 borings, and approximately 8100
laboratory and field test values. The soils include weak clays in San Francisco,
Sweden, Hong Kong, (and sensitive d.;ays in Norway), liquefiable soil mixtures from
China, stiff clays from South Carolina, and sands from Po River and desert alluvial
sands from Nevada (this is only a partial list of the total database).
I Ising the CPT Soil Characterization Chart
to Predict Properties
Two measurements are always better than one when establishing a correlation.
Moreover, the CPT provides two measurements which are unique, repeatable, and
accurate. The CPT soil characterization chart shown in Figure 8.2 (Olsen, '.988) is
based on normalized CPT measurements. This chart provides the means of'
characterizing soil behavior in terms of soil type and relative strength--the relative
strength is in terms of increasing overconsolidation at one extreme and increasing
clay sensitivity or a metastable condition in sand at the other extreme. While the
underlying normalization techiique for this chart was substantially improved as a
result of the current research effort, the fundamental aspects of this chart arc still
valid. This chart therefore provides the two soil behavior indexes based on the
normalized CPT measurements. namely soil type and relative strength consistency.
The cone resistance stress exponent (c) was shown in Chapters 5 and 6 to be
inversely related to the relative strength (e.g. relative density for sands). In
161
Chapter 6, the stress exponent (c) contours on the CPT soil characterization chart
was demonstrated to be perpendicular to soil classification contours. Soil type and
relative strength are independent of each other and this perp.-ndicularity of soil type
to stress expoient signifies independence. Consequently, any soil type and relative
strength level combination will correspond to a unique point on this chart.
Therefore, contours of geotechnical property levels can be established on the CPT
soil characterization chart because the chart characterizes soil type and relative
strength.
Statistics and CPT Correlations
Statistical errors can be divided into three categories; systematic (bias) errors,
random (variance) errors, and mistakes (Taylor, 1990). Random errors are
fluctuation errors about the mean and are statistically characterized by the standard
deviation. Bias errors are offset errors from the mean. For CPT data evaluation,
bias errors are caused by stratigraphic soil type differences between CPT soundings
and nearby boreholes. This type of bias error will be shown to account for most of
the statistical error during CPT correlations. However, there is little written about
bias errors (Taylor, 1990, Mosteller & Tukey, 1977, Huaslin, Mosteller, and Tukey,
1983). Tlherefore a subjective quality index and evaluation technique were developed
to account for data having bias error. Reducing bias error effects represented the
primary statistical evaluation effort used in establishing CPT correlations in this
chapter.
162
1000-800- OPT Soil Charactcurizaton Number
600 GP (SON) for the displayed co~ntou~r-GM
400-
GRAVELAND
0 200 SANDS
4- -- 'ANDSc 100 CLF..-,N sANDl
60-
Ii II 40 SM0~ SP
I SAND MIXTURES C\1f201 \ SILTY SAND
LAE SANDI
10- ~ SILT MIXTURES C8 ML CLAYEY S.ILT
0 6-SLYCA
4- ConeCLAYSexpponent CAvalue CLY(SLT CLY
-'A~
A, PEATS*1Equivalent OH
usosrange
T - -I- - - -
0.1 0.2 0.4 0.6 0.8 1 2 4 6 8 10
Corrected Friction Ratio (%) in terms of tsl
FJ f-i10 fs,/dv f _
FR ,100100 =
Figure 8.2 CPT Soil Characterization chart in terms of the normalized coneresistance and normalized friction ratio (Olsen 1 988)
163
Bias Error Results from Stratigraphy
There is always some geological difference between field CPT soundings and
nearby boreholes at the same elevation. At a given elevation and for short lateral
distances between a CPT sounding and a borehole (such as 10 to 25 feet) the
following can be generally assumed; 1) the soil types may be different, 2) the
formational environment is generally the same, 3) the vertical effective stress is
constant, and 4) the vertical stress history (i.e. overconsolidation level) is generally
the same. Soil type changes between CPT soundings and boreholes is therefore
more likely the cause of bias error than differences in overburden stress,
overconsolidation, oi lateral stress. The potential for soil type change for a given
elevation interval is dependent on the depositional environment; e.g. a lake or tailings
deposit generally has uniform layers and lenses whilc a rapidly flowing, meandering
river produces the most non-uniform deposit.
Stratigraphic soil type change (i.e. geologic change) is a bias error because it
shifts the average and increases the variance-other types of random statistical errors
only increase the statistical variance level without aftecting the average. For
example, clay lenses within a sand deposit w-ill move the average downward to the
clay trend and away from a sand trend as shown in Figure 8.3. Likewise, silt or
sand seams within a clay deposit will create a higher average as also shown in
Figure 8.3. Bias error direction is therefore different for clay and sand correlations
(or dense/stiff and loose/soft correlations).
The Academic Quality Index (AQI)
The Academic Quality Index (AQI) was developed during this research program
as tool for accounting for bias error. It also provides a basis tbr weighting data from
164
0S
Clay LensesS// / influence
G~ Sand lenses influence0
Standard deviationwith lense influence
Staind.ia I deviation for uniform sails
CPT measurement
CPT measurement CPT measurement
Sn lnClaylens
t Soil Soilsample sample
Cinterval terva
Clay Layer Sand Layer
Figure 8.3 Hypothetical example showing that soil lenses of differing soil type(or strength) can bias correlations
165
the different sites in the development of CPT to property correlations. This ranking
scale is almost a universal scale because it's based on the student academic grading
scale understood by all ages and professions. For example, data with average quality
has ai AQI of 76%, good data has an AQI of 80 to 85% and excellent data has a
AQI of 90 to 95%. This index, while subjective, does allow excellent quality data to
be isolated from good or poor quality data.
An Academic Quality Index (AQI) can be individually assigned for stratigraphic
change potential, CPT work quality, and boring/laboratory quality. The overall CPT
AQI is equal to the stratigraphic change potential together with any decreasing
influence of measurement quality. The overall CPT AQI therefore reflects the
potential for lateral matching of the soil type (and relative strength) between a
exceliLnt quality CPT sounding ano adjacent quality borehole. Some of the
commercial CPT data in the database has poor quality, for example, a high capacity
COe - u,- ,o ;...-/sft,&1 iuher- a luwn, rcna itv, hiah .acrcurasy cone would have
been more appropriate. If the CPT or laboratory testing data quality is not excellent,
the overall AQI is less than the stratigraphic AQI. For example, if the stratigraphic
continuity is excellent (i.e. AQI of 95%) but the CPT measurements are near the
equipment noise level, the overall AQ, might only be 80%. If there is little
information about ;ite geology or testing quality, then an overall AQ1 of 76% is
assigned. While these are obviously arbitrary distinctions they arc easily
remembered and useable.
The stratigraphic AQI is based on a simple arbitrary system equal to the
estimated percent of soil depth which are continuous between a CPT sounding and
nearby borehole. For example, if 76% of the soil layers are continuous between a
C 'T sounding and borehole then the stratigraphic AQI is 76% as shown in
Figure 8.4. This stiatigraphic AQI must also account for the CPT-to-boreholc
distance because AQI will increase 4s the lateral distance decreases. For example, if
the AQI is equal to 76% for a lateral distance of 20 feet, then the AQI might
166
CPT measurements(with AQI)
Laboratory testing CPTCi (with AQI)
_Boring
I M Potentially good correato
4Figure 8.4 Definition of a stratigraphic AQI of'76% (i.e. 76% of the soil layersare continuous between the boring and CPT sounding)
167
increase to 85% for a distance of 10 feet. Research sites with thick uniform
horizontal deposits can have a stratigraphic AQI of 95% for CPT-to-borehole
spacings of 20 feet.
Overall AQI values were assigned for each geotechnical project in database based
on the concepts just described. The overall AQI values are shown in the fourth
column of table A-i in the Appendix.
Developing CPT Predictive Contours
Consider the ncn-lineat response surface based on two dependent parameters as
shown in Figure 8.5. The two dependent parameters are the X and Y axis with theLiicontoured (predictive) response surface (or blanket or contours) in the Z direction.
This response surface is always non-linear in geotechnical engineering and can be
determined by fitting the data points in the 3 dimensional space using gridding
techniques (Box and Draper, 1987) if the data noise (i.e. error distribution) is
random. Contouring techniques do not account for bias error. The next section willdescribe a technique using the AQI quality index for establishing the best fit
correlation for each contour by excluding biased data. The response surffice (i.e. set
of contours) is established by separately generating each individual contour and then
combining all the contours. Each contour was developed using 2D data scatter
plotting software program while also accounting for the shapes of the other contour
levels,
168
Predictiveproperty(e.g. N)
_ _.,----Predictive contours/
/ -
Response surface/ /\./ *__/ -
--e//.
/ .. /
/ i> : '/-/• t~• ", • I-•//; / Dependent,.../
I ,parameterSI . / (e. g. q¢1
Cle
SA- //r
Dependentparameter Projected contour onto(e.g. FR1 ) the 2D space
Figuire 8.5 Description of a response surface
169
Process for developing CPT Predictive Contours
Developing contours of geotechnical properties on the CPT soil characterization
diagram required numerous steps that are described in this section. All data fbr a
given geotechnical property are extracted from the database and placed into a single
sequential computer file list (composed of normalized CPT measurements and
corresponding normalized geotechnical properties). Also included in each list are the
AQIs for each CPT to geotechnical property comparison. The list is then imported
into a spreadsheet for the goal of creating scientific graphics. This spreadsheet data
list is initially sorted by the data column having the geotechnical property. The
spreadsheet data list is then divided into 6 to 7 geotechnical property level groups
(i.e. 100 to 200, 200 to 400, 400 to 800, etc.,) for the purpose of establishing CPT
based correlations based on data groups. Each of these geotechnical property level
grO.....pS A. -11h i;n.i.vidll sorted based n- he, ACQ rnhimn ThjQ flnal nort
differentiates potentially biased data from good data for each geotechnical property
level group. To establish a trend for a given geotechnical property level data, all or
part of the data within each data group can be plotted. The best correlations (i.e.
contours) are established by using the highest quality data which means using the
highest AQi level for each data group.
Use of the AQifor Developing Predictive Contours
A low stratigraphic AQI implies a higher likelihood for soil type change between
a CPT sounding and borehole. When a group of data having a minimum AQI of, for
example, 80% is used for a correlation then this is defined as the "minimum
inclusionary AQI" of 80%. If all data is included for a correlation then the minimum
inclusionary AQI is zero. By increasing this minimum inclusionary AQI, low quality
biased data is excluded and the predictive correlation will shift away from the biased
170
data. If the minimum AQI is raised too high, there will be insufficient quantity of
data to develop a trend. For a particular data set, the optimum AQI might be 85%
but if this minimum AQI is increased to 95%, there might only be 2 points which
may not be enough data to establish a trend. For a given predictive property the
mirnimum inclusionary AQI must therefore be carefully increased until the optimum
trend is estý,' "ished.
An illustrated example will show how the inclusionary AQI concept is used to
determine : best fit contour. Consider a hypothetical data range for a normalized
shear wave velocity (V,1) of 300 to 500 feet/second (fps) (with an average of 400
fps) shown in Figure 8.6-a. The displayed data points represent data having a V.,
between 300 and 500 fps and are plotted in terms of ql, versus FRIe, A V,, of 400
fps can be considered at the low range typically considered in geotechnical
engineering (i.e, 300 to 2000 fps). Therefore, biased data for 400 fps data will tend
to skew the average to higher q,,, and f, levels. The total data in Figure 8.6-a can
be divided into two inclusionary AQI ranges (as shown in Figure 8.6-b) in terms cf
the data range and average for each inclusionary AQI range. With increasing
inclusionary AQI ranges, the lower quality data is excluded ai.d the average moves
away from the skewed group average. Figure 8.6-c is probability distribution along a
cut through the data set in Figure 8.6-b to show how increasing the inclusionary
AQI moves the data average by excluding biased data.
The next example is taken from the next section on CPT prediction of the
nor-malized SPT NI. All data from the ditabase for SPT N1 ranging from 1 to 3
(average of 2) are shown in Figure 8.7. For sands, a SPT N, of 2 is considered a
loose sand and therefore car be biased by dense and medium dense sand layers.
When the minimum inclusionary AQI is raised to 89% (shown with solid circles in
Figure 8.7), only the best data are included a&d clearly show a correlation at the
lower boundary of the total data scatter.
171
(a) (b)
Limits of the dataAverge trend of data-7
,/,
0 0 0 o0 0'
S0
0 t 0•goo\o 0All data fo-Qr ) /
Z VslI- 300 to 500 Z
NormalizedNormalized Friction Ratio Friction
Ratio
//-Good data (AQI-78 to 100%)/"/" /-- Excellent data (AQI-95 to 100%)
/
Probablitydishtrbutionacross the k//cross section - All data (AQI,,O to 100%)in (b) . \ Good data (AQI-76 to 100%)
S I N- , Excellent data (AQI= 95 to 100%)
(C)
/ "
- Average moves as bias data is removedl
(c)Figure 8.6 An i)'ustration of the iterative technique for removing bias data using
the AQI index
172
3000 . i
VG - "1Biased dat i
4 J
B c3st Lrezd 1)asCed2 on daLa wiLfL AQI
LgreaLer than 897
100 --1 /.-
I %/ 2• &2 ..' "
CL 4 /~
o 2-1 VI • E / ",
n\ -. , . . .
0 2 / ,, /.
i ", y~otIM_, of ,Ire K
t'- ý' - ý"*"
CF'T /
ISlPI t| 2 •ortour '' •'
(at diff.renti AQI statisticOI covek) /. •" --•_SAql horn 66 ro 1iO (.l~de'ien 8.1a) . "\ - /
[] Ai•I from 60 L• iO0-'"\
/. •qi Ironr, 0 ho (0O% (.ll 8.1.)
..___________________A
1jr , BI6 I' .I
01 10 1uJb
Figure 8.7 Example using the Academic Quality Indcx (AQI) toward establishingthe best correlation line by excluding biased data
173
CPT Prediction of the SPT blow count
Introduction
Prediction of the Standard Penetration Test (SPT) blow count using CPT data is a
complex task because the SPT sampler resistance during penetration is dependent on
the combination of end bearing and side friction forces which are dependent on soil
type and soil strength (Douglas, et.al., 1981). The SPT sampler is resisted by the
same types of forces that are measured by the CPT, therefore using both CPT
measurements to predict the SPT blow count (Schmrertmann, 1979a) is a better
approach than using only the ratio of cone resistance to SPT blow count (e.g. q,/N).
The forces acting on the SPT sampler are reflected in the final CPT-to-SPT
correlation if both CPT measurements are used for the evaluation.
It was shown in Chapter 7 that the historic SPT stress exponents (i.e. 0.45 to
0.55) for normalization are incorrect and the actual values are equal to the CPT cone
resistance stress exponents. This also implies that the SPT normalization is
dependent on soil type and relative strength consistency as is the CPT normalization
(Chapter 6).
Historically, there have been two general techniques for CPT prediction of the
SPT blow count; 1) the qJN ratio to predict the SPT N (Rodin, et.al., 1974,
Robertson, et.al., 1983, Seed and De Alba, 1986, Kuihawy and Mayne, 1990), and
2) using both CPT measurements to predict the normalized SPT N, (Olsen, 1984,
1986, 1988). What dif-erentiates these two techniques that the first technique is
based on an empirical correlation and the second technique indirectly accounts foi
the end bearing and side friction forces that act on the SPT sampler.
174
SPT Prediction using Both CPT Measurements
Research indicates that the resisting stresses on the SPT sampler are analogous to
the CPT stresses as shown in Figure 8.8 (Schmertmann, 1979a). McLean, Franklin,
and DahIstrand (1975) developed a computer model of the dynamic forces
influencing SPT sampler based on work by Schmertmann (1971). Douglas, Olsen
and Martin (1981) also developed a computer model to prediit SPT using the CPT
measurements based on work by Schmertmann (1979a, 1979b) in terms of the static
and dynamic forces on the SPT sampler. This work evolved to a technique of
predicting the SPT blow count which uses both CPT measurements (Olsen, 1984)
with the most recent published version shown in Figure 8.9 (Olsen, 1988). However,
in 1987, there was no realistic means of showing the data that was used to develop
the contours of SPT N1 on the CPT soil characterization chart. Also, the database
for this research program is approximately 7 times larger than existed in 1987 for
developing SPT N1 contours.
175
''F
a local0 ldc*a3SC~ f rictgionýth liners jacket
n liner .EO.
(•;chmrtmann 19 7Ca) m
II
176
1000 - . ,I ..... . . .800-
600-GRAVEL
S~AND.• 40O SANDS
S 200.
100-
S 80 .S N S5
~60.4
40- 40
SAND MIXTURES~20 Predicted
Q• )'Ri o N ,
10-8- SILT MIXTURES .
N 6-"Soil Characterizaton 2(Classitic CLAYS
0 SPT:2 Rotary Wash Boring
Safety hammerTwo turns of an old rope
1 - , , '3 ' • ' I " , , ' 3
0.1 0.2 0.4 0.60.8 1 2 4 6 810
Normalized Friction Ratio (%)
Figure 8.9 Prediction of the SPT blow count, N, using both CP'l' measurements
(Olscn, 1988)
177
CPT Prediction of N, using the CPT Soil Characterization Chart
Establishing correlations of normalized CPT parameters to SPT N, was found to
be very dependent on the AQI statistical technique. AQI was used to remove biased
data effects thereby allowing the best correlation of CPT to SPT. All SPT data
from the database, for all projects, were divided into seven N , ranges for the purpose
of establishing individual correlation contours on the CP'T soil characterizatio 1i chart.
The results of the SPT N 1 correlations are shown in Figure 8.10 to Figure 8.16 for
average N1 levels of 2, 4, 7, 15, 25, 35, and 50. The best fit correlation contour in
each figure was based primarily on highest inclusi-'nary AQI but also accounted for
the lower quality data together with the shape of the other SPT N1 contour groups.
Figure 8.17 shows all the SPT N, predictive contours together with soil classificationI:--_ -. ____ f'l|%00/ 1 %O'
1111UN• JLUIII IJI",U;I k1700).
Discussion of CPT Prediction of the SPT Blow Count
The new contours for predicting normalized SPT blow count (Figure 8.17) in
general have more curvature compared to the 1988 version (Figuie 8.9); however, for
fiiction ratios less than 0.5%, the contours are parallel to cone resistance, which was
not expected. The contour shapes and intervals for the 1988 version are symmetric
due to the lack of data; newer version contour shapes and intervals are not in general
synmmetric. The shape of the contours for the newer version reflect soil type and
relative strength contribution. Within the sands area of the chart for friction ratios
less than 0.5%, the contour shapes and intervals are symmetric. Within the clay area
of the chart (from normally consolidated to overconsolidated), the contour shapes and
intervals are also symmetric. However, the contour shapes are changing in the
middle of th. chart withi- the soil mixture area (transition between clays and sands).
178
1000 -I . . ._
"• CPT eorrel~hori of
SPT N 1 - 1 o 3
(at differe t AQ1 stati qtJcal hI - ls)- I
- AQIs 1,85 % 1c 100"
1-/ AQIs from 0 to 100-' (ahi data)
fBest fit contour for NI-2
I - Other N, contours
I {iL
100 -- ,
Un-.
o ')5 y AL , -
qz
C.) ,.. .,,.-.A \. :
o75
S/' •A L2, Y-'L•L"ZLQ A ~,\
011 10 / Z.Zýa
Z • LL Z, Z
6
4 •- L • )4 (
0.1~~ 7.ol(
Normalized Flriction Ratio (2L)
Figure 8.10 Prediction of the N,=2 contour on the CPT Soil Characterization Chart
179
4j -
-Z- - -
C") 4-
-- ,0 0 • -- - -
V;A Z
4Z 8 a \Z3 O
610Z
o CM," correlation of A,SSFT Nl- 3 to 5 Z-\
(ftt different AQI statisticnf level9)A Ql, Ir-on) 89.% to ,oor/ 7- 1
Q AQls fromu 86.% to 100!72 Z • ~ AQ1 fro ml O-r to 100 r. (all dat 3)- '
- the NI contour5
"2 4 6 41
01 10 100
Norm alized l:'rictioil .LI.io ()
Figure 8.11 Prediction of the N 1-4 contour on the CPT soil characterization chart
180
1000 --1
61
4 - - -
V
- 2 L /., r.-- • ~L '- ".
" • • • , Z•
6 - Z -5 ,
r-Z-
- • O4 <- A" a IO 9 Z., Lz
2 -1
(at Zd A QIZ-
0 CPT a tio.-l" stio of/
* AQls from 0N , 5 to 100. 5 \
~J AQls [rmci W. to 100-
[] AQIs from o6 to 1007 (all data)\
S[lest fit contour loi l7-7 t.oitOurL \ -/
tOilier N1 contour. ' ,
.1-F I I i1T7t I
I 2 41 b 2 4 6 .Z I.
0.1 1.0 10 0
No'l-rai.,zed Fr'iction 1,utio (Put)
Figure 8.12 Prediction of the N1=7 contour on the CPT Soil Characterization Chart
181
i --
LLA -- =
Z-11
2 , ,wý -Z
8 Z,
- - Ll-
Z A
-4!! orelhn of A u•
- -L QI fro 0%to 00 all d~t} L N_ g;."
*4 ( ( 2 L {-)t
ZZ,
-~ A
Car
1821
C) CPT correlation of
z ~ 1 at SP 1 ' 10 to 20 AS(tdifferent AQI statistical leve~s f'
-~ * AQis from 90% to 1007'
S AQls from 87% to 100r
/ ~ AQ13 fromn 0% to 100% (.1l dcita) Y
IIilest fit contour for N1 -15 A AI - Other N, cvritours -f
No m hz) 1rcil 10 100
Figure 8.13 Prediction of thu N= 1oy5 contour on the CPT Soil CharacterizationChart
182
100o0
6-
I *I
.~ 100 jZ
6
El ~ ~ ~ ~ ) AZ3fo 6%t 10
-~~ ~Z - terN onor
A &
10 1 t .010
C CT o rrelationd of 'cio ~A~o (k
Figue 8. 4 Prdi tio oifftern N=2 saitconou on~s th P olCaatrzatoChart
AQs ro 87'to 183%
2-
610
""10. ^ -4 "SU) A •
A ̂ t, n \
, .• C 0 C P T c o r re la tio n o f \bSPT N 30 to 40
?-=, 4(at different AQI staltistical levels)"\
:•i ] • A Q ls fro in 7 5 ,% to 10 0 ,% V - •
"'I [ ' z• •
0 2Ql•" from 60% to 10r
•'• " Z• Aqls from 0 to 100-% (all date) '
:'i'A
Bes 10t cotu fu N\35
0.1 A.0 10.0
NorCrralized o riction Ritio
Figure 8.15 Prediction of the Nf=35 contour on the CPT Soil Characterization
Chart
184
1000 ...-- --I
--4£
Q4 4
U)p
NI 10 L r
66 Z,,•\ e l10 CT corrlation of"
""-- NI 4/t 6
IAl from 85% to 100r t
C AQis from 717 to 1007,
L\A AQ-s fron 0 to 100% (all data)
ficst fit contour for N1.50
(- - OIIC" N, conltoui\
I T I I I1
0 1 .0 10 0-
bNoi-rirnlizcei Fr~ictioni Nuot (7
Figure 8.16 Prediction of the N1=50 contour on the CPT Soil CharacterizationChart
185
1000 1-° - .. . ..--- ,-_--____-t _
a Conltours of StRY N1-1
IN 25
1 0 0 -,•
/ -•
o 4
"F Cr']' soil characteriization linesfrom Olsen (1 91-3)
4 G 8 8
0 1 1 0 10 0-
Nor mialized Frictioni tx i a (7',s)
Figure 8.17 Final plot of the best fit SPT N1 contours on the CPT SoilCharactenzation Chart
186
When the CPT friction ratio is low, such as 0.6%, the contours of predicted SPT
N, are almost parallel to the nomialized cone resistance (qcl,) which indicates that
the SPT sampler end bearing force dominates the SPT resistance. Therefore, for
loose to medium dense sands (which produce low friction ratios, less than 0.6%)
(Douglas, 1982) the SPI sampler is resisted primarily by end bearing forces.
For CPT friction ratios greater than 3% in Figure 8.17, the predicted normalized
SPT N1 contours are approximately parallel to the normalized CPT sleeve friction
resistance, f,,, (contours of constant normalized sleeve friction resistance are shown
in Figure 8.18). This indicates that the SPT sampler resistance is primarily
dependent on the side friction resistance for dense and overconsolidated sands
together with all clays. Dense sands and overconsolidated soils also have high lateral
stress ratios (K,,). For sands, a high lateral stress produces a higher CPT sleeve
resistance (Masood, 1990) and therefore would also produce a higher S" I sampier
resistance. The relative contribution of SPT side friction forces to SPT end bearing
forces can be calculated from the product of factors: the area ratio (i.e. SPI sampler
side area to SPT end bearing area) and stress ratio (i.e. the CPT friction ratio). 'In.area ratio is the SPT side friction area to the SPT end bearing area which is equal to
28 at 1 ' foot penetration. For clays and overconsolidated sand, the CPT friction
ratio is approximately 5% (i.e. stress ratio of 0.05), therefore the SPT side force to
end bearing ratic is calculated to be 1.4 (i.e. 28 times 0.05). The SPT side friction
force is 1.4 times higher than the end bearing force. However, if side friction forces
inside the sampler are included, then the area ratio increases to 44 and the SPT side
foice to end bearing ratio increases to 2.2.
An example of CPT predicted (using Figure 8.17) versus field measured SPT
blow counts is shown in Figure 8.19 together with annotations. Numerous other
exam.ples of CPT predicted versus field measured SFT blow counts are shown iri
Figure 8.20 to Figure 8.27. Prediction of ,he SPT blow count is difficult as
187
I000B-e.I
4-
cd 100-
0
.4)Pr-4
10
0.1 1.0 10.0
Normalized Friction Ratio (%)
Figure 8.18 Contours of constant normalized sleeve friction resistance on the CPTsoil characterization chart
188
illustrated by large variance for each predictive SPT blow count contour (for example
Figure 8.14). However, as seen from these prediuted versus measured examples, the
match of predicted versus measure does support this technique of using both CPT
measurements to predict the SPT blow count. These figures also show how much
detail is missed by having only discontinuous SPT measurement records.
189
CPT based SOILCLASSIFICATION
L L IVD D L
4J 4-1 0D>X X.. .
SPT (N1 ) -(Normalizeo Blows per Foot) o> ro C C -
W -~ . -ofuo0 IC 20 30 40 50 o. 0 U I uO 2 5
I0-----------
10-A CL
CLAY. SILTY
CL -_-- L20 E .CL
< CL (CLAY)
CL) M L 1 •
CL
iField measr .LCL (CLAY. SANDUY].4-j - -ied-e• €• CL i --
C. 40 OPT predicted CLA- SM
ML-SM
SMS'-CL SILTY)
70 - -M . .
i-p
CPT predict'.• SC'j12 Soil classification(Soil Classification Number) from SPT soil(Olsen, 1988) sampler
Figure 8.19 Examnple of CPT Prediction of SPT blow count with comparison data(Barklcy darn scismnic evaluation study, data from Olsen, et al, 1989)
190
CPT based SOILCLASSIFICATION
xf 'x LA
N o r m a l iz e a S P T Ln v) Ln tn •m
(N) 60 (Blows per foot) C C c €rn4 to
50 x0 1 2 30 50 n
0 . . . I . . . . I . . .. . ... ,.... i.. . i . . . . . ,
300
.. 0 1_2 d
30 10 20 0 0 5 aOm
40
20
~~4d
PTt050
Fiur 8.20 C 7Tpeitdvru esrdSTN o h ake a esi
70
730
evaluation study (data from Olsen et al., 1989)
191
CPT based SOILCLAMSIFICATION
.X L a0>
Normalized SPT n o U
"4 > -W t) '(N5 ) 0 (Blows per foot) t M, c c a0 10 20 30 40 5 0 C 0 En 2• U ) 3 En 4 n10 20 30 40 0 012 3A45
10
C-6 Ac•'t '-- inves t igati•onrCAT rv tl tOACPT
CPT-6 PT-6Investigati~on Inv@ txflat
20 • sn-sM2O-
a) IAJ
J30-
19-2) II
C-
U
40-
60-CPT Pr'edicted S'T N, - CPT Predicted Classification,
----- S11il Samole Eujuvalent Zones
S Measured SPr N, e.g. SM Soil Somole Cla5sifiration
Figure 8.21 C11T predicted versus measured N, for sites on the East coast of theUS (data fr-om project code LE-JN)
192
CPT based SOILCLASSIFICATION
a]) )
L L (D~n >
Normalized SPT N (fl
(N1 )8 0 (Blows eier foot) M M - c c c
0 10 20 30 40 50 o. 2 Ln 3 In )
10
20 t00:
30
40
50 50
60 - .
I- 7Q B0-ar, 7
80 T
80T-20 ~-- PT -20sit gat ior 1In tag t an
1000
Ito
120 . ,.
CPT Predicted SPT N, CPT Predicteo Cls851fIcetlor
{ MteOured SPT N,
Figure 8.22 CPT predicted versus measured N, for a CPT sounding through thehydraulic core of Sardis dun
193
CPT based SOILCLASSIFICATION
a1) -uL LZ D
x L
Normalized SPT x x
(N1) 6 0 (Blows per foot) C -• c c
0 10 20 30 40 50 O. U , ,n4 OI0 . . . . .... .... ........
20-
30 .
40 "D'1)RING -SM
6 CP•T5 8I , -I st! gation Inveltiga•ion Iv M
E;0
60 1
- 700)
80
go
CLS100 .
(L
120
130
SC140-M
150- ______________ SM
160 E=____________
17 0 ---
170
CPT Predlcted SPT N, CPY Predicted Cia•sificotionSoil Sumple Equvalent Zoneu
4 Measured SPT N, e.g9 sM Soil Sample Clessiflc•tion
Figure 8.23 CPT predicted versus measured SPT N1 for a stift/dense dirty sand site(project code DE-S-R)
194
CPT based SOILCLASSIFICATION
WO V)
L LD D>
Normalized SPT in v t "U,
(N 1 ) 6 0 (Blows per foot) M M C c C0a O 0 A0 50 . u L m U) U0 i 2 30 40 50 0 1 2 3 4• 5
CL (Clay.silty)
CTPIR20 PT
10fVestigatiofl T-, CL (Clay. sanay)
(CL (Clay. San4dy)
20 SC (Sariu. ClOyey)
4J
,wL -- 4 4cu 30 L
a.z- r -SC (Osno clayey)CL
40-
UCL (ClOy. Silty)
"CL (CIly. Silty)
70
cPT Predlcte' SPT N, CPT Pr'edlcted Cla5•1(lcatlon
- -ll Sample Equvalent Zones
Nmusired SPT N, e.g. SN SeIl Saersle ClaJsSflcaLtio
Figure 8.24 CPT predicted versus measured SPT N, for a site composed of soilmixtures in Tracy California (project code WC-TSS)
195
CPT based SOILCLASSIFICATION
LL a,4J
4J M
x L
Normalized SPT inm on m
(N1 ) 0 (81OW5 per foot) m so c c CsW - -MM
0 10 20 30 40 50 0u 2 3 • A0 -
CWT WRING
ON ~MCDON CI Gatigetson Investlgetlcn Inv* US O n
1 0 . . .... ..... ...
20-3 0 ., l .... .... .. ...... .4011
Z 50 .... .. . .
50-O. 60 ... .U
7 0 . . . . . .... .: . ... ... . ....... .70 -
pso80
CPT Predicted SPT NH CPT PrediCted C16$3SOIctiOn
I 14Masured SPT N1
Figure 8.25 CPT predicted versus measured SPT NI tbr McDonalds Farm, Sea
Island, Richmond, British Columbia, Canada (University of British
Columbia research site)(data from Campanella, et al, 1982)
196
CPT based SOILCLASSIFICATION
in w/ W
ww J
x x L
Normalized SPT Ln U) Yn inAj >,,,,-j,,"0 "o 1U(N )60 (Blows per foot) m M- c C C
0 10 20 30 40 50 ao- 2ui 3 En4n
FP52 I I F1i0 -oB-122
Inveat igat ion
20-
30_
4-J4
0j
Q.-
U
U5 0
60
70
80 n'',
CP' tjr~eaicted SPT N, CPT Prealcted ClasaifictitionSall Samole Equv:17ntZones
Measuped SPT N, e.g. SM Soil Semple Clas i 1C io~n
Figure 8.26 CPT predicted versus measured SPT N, for the Arcadia Darn seismicevaluation study
197
CPT baseo SOIL
CLASSIFICATION
L L
Normalized SPT t m M4J >, AJ ' ' '(N1 ) SO (Blows per foot) M M - C C C
0 10 20 30 40 50 ' M'0 10 0 30 0 5o CL 0 I U 2 En3 En4 i5
WL
10
20 P SMI etigatie ooN mI • B~~-CM-S - s
lnvestigat(o)n SM
ci U51
S300.
4O
55P
U
40-
50-
60-......... ....... . . .
- CPT Predictted SPT N, CPT PredlCted Classificatlon
S- Soil Somple Equva]ent Zones
Measured SPT N, E.g SM Soil S mpe ClossIfrcatlen
Figure 8.27 CPT predicted versus measured SPT N, at the Coyote North site (nearSan Jose) California (data from Marin & Douglas, 1980)
198
CPT Prediction of Clay Undrained Strength, Su
Introduction
The undrained strength, Su, of clay is one of the classic geotechnical properties
and is critical for many design applications. In the U.S., the standard practice for
obtaining clay undrained strength requires retrieval of relatively undisturbed soil
samples, typically with a 3 inch shelby tube, for unconsolidated undrained (UU)
triaxial testing. However, only a few laboratory strength tests are typically
performed for most geotechnical projects and it is assumed that they represent the
character of the total site.
In Europe, the standard practice for obtaining the undrained strength of soft clays
is the field vane shear test. However, the vane shear strength is always too high
because of silt . .tent, overconsolidation effects, the high vane rotation rate, and/or
vane geometrk. effects. A correction fator (p) is required to reduce the field vane
shear strength to the field strength level (typically the equivalent unconsoli.ated
undrained triaxial test level). This correction factor (jt) is dependent on many
foctors, but generally established based on site specific correlationis.
CPT Prediction of S,
Clay undrained strength was the first geotechnical property predicted using CPT
data in the 1930's (reported by Broms and Flodin, 1988). For the last six decades,
the literature has been filled with theoretical and case studies on the topic of
199
undrained strength prediction. It was difficult task then and is still a challenge today.
Historically, the problem has been to select the correct bearing Nk factor in order to
calculate the undrained strength from the CPT cone resistance measurement. This Nk
factor, which ranges from 8 to 25 (Aas, Lacas.3e, Lunne, and Hoeg, 1986, Lunne
and Kleven, 1981), depends on overconsolidation, clay type, sensitivity, silt content,
reference testing device, and to a lesser degree on overburden stress. A new
technique is developed in this chapter that uses both CPT measurements to directly
predict the undrained strength without the need to estimate the Nk factor.
Historical Means of Estimating Nk for CPT Prediction of S,
The classical means of predicting undrained strength using the CPT uses the N,
factor which can be estimated using Table 8.1 (Olsen, 1994). However, this
pr ..oed,.re re•uires pnrin know!,•AgeP of the in situ state of the soil. The best
procedure for calculating Su is to estimate Nk assuming a medium stiff normn..2y
consolidated condition (i.e. Nk = 13) then calculate S. 1.t'Aug Equation (8.1) and then
sucalculate the S- ratio.
ov
S = qC - atOl (8.1)NAt
Equation (8.1) was introducted in Chapter 4 during the development of the
normalized cone resistance formulation. If the calculated -u-7 is 0.29 to 0.33 and SuOv
is 250 to 500 psf (medium stiff condition) then the soil is probably normally
consolidated with Nk equal to approximately 13 (within the range of 10 to 16). If
200
S•
the calculated -- is high, than the clay is probably overconsolidated or a stifferav
condition prevails which requires a higher Nk. Iterations might be required until the
conditions regarding Nk in Table 8.1 are matched. A few reference laboratory
strength tests for each project should still be required. This discussion has shown the
importance of the toward estimating the Nk.av
Determining Si, using CPT Soil Characterization Chart
C SThe normalized undrained strength Su1 (i.e. _ or -- 7) can be correlated to CPT
measurements using the CPT soil charactefization chart. This section will introduce
the concept of predicting Sul based on beating capacity fornoulation and t',e next
section wili describe the process of establishing Su1 contours on the CPT soil
characterization chart.
The cone resistance bearing formulation (Equation (8.2)) was developed in
Chapter 5 and is in terms of the normalized undrained strength (Sul), cohesive
bearing factor (NO) and the normalized cone resistance (q,,,):
S - q (8.2)
Nk
This equation can be rearranged as shown below:
q =l- Sul Nk (83)
Equation (8.3) can also be represented in a graphic forrmi ba:ied on the CPT soil
201
Table 8.1 Typical Nk values for estimating the unconsolidated undrained strengthof clays using the CPT cone resistance (Olsen, 1994)
Unconsolidated Undrained (UU)Triaxial Test
as thereference strength standard
Clay condition -__Nk Nk
range average(typical)
normal se i itivity,soft to mc . urn stiff
Normally c., isolidated, 9 to 13 11moderatel3 ,nsitive,soft to ver oft
Moderately *ver 15 to 20 17consolidate.non-fissured
Highly over 17 to 23 19consolidated.
fissured
202
characterization chart as shown in Figure 8.28. The q,1 e in Equation (8.3) is equal to
the combined effect of Sul contouis and Nk contours in Figure 8.28. For a given Sl,
contour, increasing qce (vertical axes) will correspond to an increasing contour
of Nk. Increasing the overconsolidation or sit content will also increase the Sul
contour level as also shown with arrows and annotations. Therefore, any point on
the CPT Soil Characterization Chart (for example point "A") has a Nk contour value,
a Sul contour value, and a qcle value from the vertical axis. Contours of Sul can be
established directly on the CPT Soil Characterization Chart using laboratory
unconsolidated undrained triaxial strength data ((Sul)TxUU) or field vane shear
strength data ((Sul)FV) together with the normalized CPT data. There is no need to
determine the Nk contour because Sul is the ultimate goal.
Establishment of S,,1 contours on the CP7 soil characterization 'chart
The procedure used for establishing contours of normalized undrained strength
(Sul) for clays on the CPT soil characteriza.tion chart was the same as was used in
the last section for prediction of the SPT blow count. Two sets of Sul contours were
established using measured undrained strength data from the database developed for
this research program (and described in the Appendix). The first set of Sul contours
were Lised on data from laboratory unconsolidated undrained triaxial (TxUU) tests
and the second set were based on data from field vane (FVane) shear tests. The Sul
contours were also established based on the knowledge (from the last section) that
the contours should increýase in value with increased qcle and fsic levels.
All roeasuredt strerngth data from the database, for all projects, were divided into
unconsolidated undrained triaxial and field vane shear tests and then further dividedinto 6 strength ranges for the purpose of establishing individual correlation contours
on the CPT soii characterization chart. Bcst fit corntours of nornmalized
uncor.nsolidated undrained triaxial strengths are shown in Figure 8.29 to Figure 8.35
203
SA IncreasingSleeve
Incresing Frictionqc 2:= Nk u r Resistance"le k/u silt content
// /I
/ -
SIncreasingS, .... overconscidation
Nk"-
Log Friction Ratio (%)
".1
Figure 8.28 Establishing Sul (i.e. c/p) contours on the CPT soil characterizationchart based on bcaring theory for clay penetration
204
based on the minimum inclusionary AQI levels for average (SUI)-xUUj levels of 0.15,
0.25, 0.31, 0.39, 0.54, and 2.0. The final plot having all the best fit (S,,1).1,uu
contours is shown in Figure 8.36. The best fit contours of normalized field vane
strength are shown in Figure 8.37 to Figure 8.41 for average (Sui)rv levels of 0.25,
0.31, 0.54, 0.80, and 2.0. The final plot having all (S, 1)FVan, contours is shown in
Figure 8.42.
Sev,'ral exampli-s of CPT predicted versus measured triaxial unconsolidated
undrwarcd (L"U) t,;st results ((Su)Txtdr) are shown in Figure 8.43 to Figure 8.49..c aese exarripit. re scpsent. sites composed of soft to stiff clay including several sites
comnp,3sed of sandy to silhy c!ay. There are also several examples of desiccated
layers vith prol:erly predicted (SU) 1.uu ievels.
Sevw',a! examples o.C CPT p7'edicted versus measured field vane shear test results
soft to mcdium.x stiff clay sites and contain a few cxamples of desiccated strength.
"Ihere is nnoie field vane strength data compare-! -to lboratory triaxial strength data,
probably bcause the fic'1d. v test is easier to perforn and less expensive.
"llvz. contours of (S',,I)1xUU and (S.•)fa, have (he some general contouring,.-haracteristi,.-:, -namely increasin..-, S with irnci,:asinng qc and f,,,. The differences
between these comanurs is impcwtant. The ia-io oK (Sul]) T x UU to (Sul)|:Vanc is the
historic Bjen-urn ',ane she,,r corrction rZj. r, p. (Bjerrum, 1972) as shown:
(SSu"e (. _ _ (8.4)
205
10 0 0 4 A. . . . ... . -2 -- _ _-_-_-
81 CP- cur-IM-r, of
1 -"I I {SuIT.UL'dj 01 to6 fi m,, d,.f-,-n' AQI s+tau tIC,,I ",',-Is) •-
- AQ15 96 . to 100%
E3 A(41,79-. c 100%
AQIs 0 to 10057 (.11 dL,)
•contour fu- S0 - I t
S10 0_
Qýo; -I N
(34I N]
C.4
0 oI
- ~ jo-- - -- -".+N -- N , x . - ,
Z1 -.
Q)Q
I -Yctt
4';4
"" 4 (3 '.2 4I t4 (
01 10 100
Noi-rmalizc(A ]"' i Rl [•tl(
Figure 8.29 Predition of the (Su1)YIuu= 0 .1 contour on the CPT SoilCharacterization Chart
206
1 000i_____________
CP'T corrplatioon of
-lo ISU)TXUL - 0 2 to 02
* AQ!ý fromj 98% to 0-
I C AQIF from, 9G- to 100..
V/ / AQls from, 0 to IM" (a[- data)
BeC Nj [3s 1contour for (SITIL .0 24
- tther (su 1TXUU cuiou~r%
-ý N
2. 100
0zN
0207
1000 . . .
8-SCT- rorrIlaotoj of
C (.Sul}T, 'U • 0 2.8 t U 03 1
(a differr nt AQI statistn•al 1ev- ,)
4 0 AQkl from 91% to 100%
EJ] AQI from 33% to 300%
Gr,,, ,' AQIs from 0% to 100 (ai: d,.ta)
| PBest fit contour for (S. Txt -031
2] - Othr (Su)TXU: contouri
S100 "-,-1_.8
CL
C)
1 r' A41 6 6
0.1 1. " 0CL 81" -. ,. ..'
o 1
1-i-ii I I II I t I I i 1
,.2 4 ctl 2 ,t U 8
0.1 1 0 10 0
Figure 8.31 Prediction of the (Su ).Ix-UU=0. 3 1 contour on thi CPT SoilCharacterization Chart
208
1000. I
CPT correlation of(Sut I) ' 0 34 to 0 44G " ( ulTxUl' II -- (at different AQI statiStIc8l l-el'!
"" AQIs from 967; tI, 100%1
4 I-Q AQIf fronu 90% to 100%
4/ A• AQIs from 0 to 100r) (lII data)
Dest fit contour for 1 uIf xU. 0 :39
C-U
100
84
GN
Q1NI N.
) 10\L
240
o 'I
.- 10 .
Q•r i A. " L \ .
:-1 -- r
- IA
- 14-
o. ) 17 1 Nlzc' .'i tl l t•a i v;
Chr ctizaioChrt~lzdIiton IfI)(
209
1 0 0 0.. .. . " .. . . ._
""I-CPT correlation or
(5il)TxUt; 044 to 06,
S(at different AQI st.atistivc levcls)
"" * AQIs from 95% to 100
1 F] AQIs fromi 83% to 107.
1 A AQIs froni 0 to 100% (all data)
IBest fit contour for (u TxUti -054
-- - Othey ('ul)TxUU contoursi
8-"-• 6
0 2n 10
0 2
<_) I. '
"-- - AC) --. ,N I0~-- A
o L
4 6 13 4\
z -L- N_ . . .
N"
I I
I I I I I I iI****j I I I I lI II
0.1 1.0 10.0
No-rni•ized tF1Ictioon t a (Rato )
Figure 8.33 Prediction of the (Su 1 x),UU=0.54 contour on the CPT SoilCharacterization Chart
210
1000 _ _,_,-_ _ _ _
1 - CII correlationl of(3 I I
5O)TULU - 065) t" 09'(itt different AQi statst•ac I level)
"* AQI' frormn 9.! to 1007,4 1
El AQls from 7I% to 1007%
Z/. AQIs from 0 to 100% (all dataý
- Best ft contour for (Su 1 ).xUL "
S- - - - Other (S l )TxtI contours I
NI
60
N 100-1
Ct 8-] 0.
E -"o 2 4 El -.- A-
r I -'. .
0;
10 1 1 0 1 0
Nor1alz('d Friction \at 109 N
Figure 8.34 Prediction of the (Sul.rxuu 0. 8 0 contour on the CPT SoilCharacterization Chart
211
-ooo- I ---
1 -1 0-
C9
44
N
2]
0N \..
S100 - V
coIx -. ,
be CPT correl t fo r of \ !u- -( S u I ) T x U U -0.9 5 t o 3 0. • " "
r 4 (et differ 4nt AQI st (ti jtre l levels) "Z } •) AQIs from 64%. to 200% "j ' . " -
[] AQIs froml YO%. t' 100%
Z• AQIs from, U to 100,% (elI data) \ [2 (est 1,1 contol-|ur -o S ITu 2
- - Other (SuI•:LL conltours5I ' ' " -tiJ .''.
12 4i C£,1 6
0.1 1.0 10 U
Noo:'malizcd PriciOl N• t .io (';)
Figure 8.35 Prediction of the (SuI)TxUU= 2 contour on the CPT Soil CharacterizationChart
212
1 0 0 0 -' -. . . . . . •----------- -- -
CCUT soil clia racteA'i zatj on ulies //
6] froni Olsen (1988) ->
4-.A
Contours of ". -- Normalized\
SUndrained /StIength / '
based As /
2. on the ½ /
100 + 'xUU test ! .81 FU
61
(S .)
1 8 (s I),r uV%,/
k.,4 (ulTxUU =0 139 , , Q
Lb (I -
(S I, 7C-3 106 (SUlI)TxU 0.24
4 (Su 4 (5 II 0. 1 f
4 6 8
0.1 1 0 10 0
Normalized Friction PtO io (Cc)
Figure 8.36 Contours of normalized (S0 l)TUU (i.e. (S)rxuu/1 'v) on the CPT soilcharacterization chart for the unconsolidated undrained triaxial strengthtest
213
10004K CPT correlation r IL,
1 1ul)Fvanp 0 Zto 9 ?H
3 1(at different AQ] z st ilal levels),} I
* AQ]i fromn 9- to 1o00%4] AQIs from 9(;- to 100%
, j AQ•s from 0 to :0M% (all dt•)
/ Best fit contour for (Su 1)FV -i024
S- Other tSu)),FX. contours
10
(Zip
7
o 10 -- 010
o 24
.N 10 - "N -- 1 - .- \
-. - -• . N•
A .. . . .. I ~ . . . i. .. 1
2 4 6(3 , 4 eI l
01 10 100
Figure 8.37/ Prediction of the (SU1)FV•• 0.25 contou.- on the CPT soilcharacterization chart
214
1 0(00)____C).ai .I~i.4.
CPT correlation of
"G (SuI)F.V ae , - 023 to 034
(at different AQI taLtstic~l irverlf)
I& AQis from 987 to 1007.
l AQ•s from 9,% to 100-%
X0AQ0s f-ro 0 to O00% (all d1ta)
SBest fi, c~ntour for (S,,)FVý -(031
SOt~her colt ou r'
Cj
.o 10
- 7
I 7
4
N
4
S1 1.0
0 10 F H M
Figure 8.38 Prediction of dhe (Sui)j:v,,,, 0.3 i coniour on the CPT soilcharacterization chart
215
10 00 ,--
......4
CPI corre'etir-i c[fI J(:•tLl)c~, 0 *;4 I" 0 51
( at d iffere nlt AQi stak ititcal level , I I
,AQI h-'.-. 977: to 1007
C AQI! from 96 to 1007%
oy:.-
[, A QI', fto~ 0 to 100%• ( .111 d p',d
'"-"1, tises' fit contour 1- Of I
"2 " Other (.UoI}F., ontourl
10 0 - I 1_
_ _ ,,_ _ _ _
i
2 -
oZ- %
4 6
1 0 1
CI I
Nigure 8.39 I'redhicion oi'the (Su1 )1 :v811,, = 0.54 contour on the CPT soilchaacte, lzatiof Otart
216
-1 (a ~,ffr*,tAQ! situcti: 1 , vI I
4 * AQIý f-om 9? to 100Q.
C3 AQI.s fromibr ~sti c fý
AQ]S f, onj 0 to t 00- (Ail dal a)
Ifest fit contour for (5.01-v ( (3
2~~ Lh- -Othvr ( . Contours
S 100-
-44
C-1
0) 21
0 E3
C 8
d 4 6 6 4 C
0 1 110 0
Figure 8.40 Prediction of the (SuI)I-vazic 0.80 contour on the C11T soilcharacterization chart
217
] 000 -' - ...
CPT correlatlon of6 - ( sui)•vf3e • 95~ 1, °3I(a, different A4 slatntC, . 've s)'
ACIk froni 130 , to,, i00';
AQ]1 Iron, 76r to 10•'3
. A qR from 0 to !0 "l (Al! data)I [Ilest fi1 cont0 lt l for ( u% )F . 2
t •] - - O t t er ( ; c orýo u r s
c 100--
"1J
Q.) 4 -
Q.).
7 1 0 -- - - -. _
lo-,-
0
T I0101 1 0 1(00
Norm ul ,'/'d 1"vie! iom ] H ,io (>1)
Figure 8.41 Prediction of te (Sj)Iv.,C 2 contour on the CPI soilcharacterization chart
218
-IS
-1
1Q'
i /. /
I I!
E-I.
Ii ( oEItou1S 0.
I N
-0 1 1 ofl0iz'2U /
" NoI bia'sed cai the / /S. 42 Co toeldi o ante /, / tc. r Ehea v test.
te 7 •- C. /
L ( -c 21
0 1 1.0 1o0-_
Fgr .42c Cotorso I ("tii'iv ° (i@e " S -- \ • , &~ for th ildvn ro
theCP oil chaa" t iatin ca
r- 219
CPT based SOILCLASSIFICATION
4J4-I. I0•
NormalizeO Undrainea 0 ) V)
Strength. (Su) TXUU s* , ,' C
S 00.5 1.5 auin u 3 nw0 -. . . . .. I.... | _1..
c•T eOrZN@ .i
KONRAD kO LADO V UIAD10 Invsutiga. ton Inv t-gatnn In :. tipat on
20 .
4050-,
IU
70-'80 I.I
*1. -QrIi
90
o II.--o
CF:T P•rel•cted S,,u -- CPT Prodictud ClassificationMeas@ureld S.,
U!
-vigure 8.43 C1PI predicted versus measured for,,. caysroi FrseRiver o~dsite,c Vancouvera.19) Intemationtal Air-port. Canada (data from
220
CPT based SOILCLASS I FIC ATION
L L W)
AIJ .J 10XX L
0
Normalized !Jndr'ained 0d In )4) I 4 )' D 'D
toI.C C CStrengtrm. (13,1) TXUU EW EU EUID
0 0.5 1 1 .5 LLuU`2V)3(f) A M I01 ýLJL.ALILLAL ILLA
10
,,5
(4 0 4AOS
CPT Predicted S ~ CPT Pr-edicted classificationM eawtured S, - - S.jII GemL-le Eau',8]eft Zones
e~.SM Soil Sample Lla~siflcatiOn
IFigure 8.44 CPT predicti-d versus rn.masured for silty clay fiomn LinimaMe'ilosa, Sweden (40 kin north of Stockholm) (d-ata trom Larsson &Mulabdic, i ýY)1)
221
CPT based SOILCLASSIFICATION
1303 -
41 4.) IQx x C.
Normalized Undrained x
Strength, (s ) TD C C C:S)
0 0.5 1 1.5 UI2En 3 A5
10 . . . . . ... ... .
:-to - CA ls . .. . .:'
JI'wostigation NO Ginve! tIgot lary
e - I20 Investigation .... ........
40.. . lA7 0 ..."•. •• .. . ... ... .....50~
60-
"70 "
0 .. . ... •...... .. .....S90 .. ..
cL120
130
I170
180
190
200 "'I " '---
- -PT PrtdlCted Sý, CPT tPpdicted Clasellcatior'
I "evoursd S., 5011! SBmple EnuvOeCrt Zonese.. 5w 50il Saample Clasalflc tlorn
Figure 8.45 CPT predicted versus measured (S.1 )1 xutj for San Francisco Bay mudat thi Muni Metro turnaround facility (the measured strcngth data arelocated at 10 different elevations) (data from Dames & Moore, 1992)
222
CPT based SOILCLASSIFICATION
c{ .. (,
x x I~
Normalized Undrained i 0M13. 14' V V
Strength. (S01 ) TXUU 0 a M
0 t 0 . 5 1 1 . 5 co u (nv (n En
O10NS0C(1%" -ONSOY !BX7. L- ....
10
20-
30 7
0.
050.
I-
60
I L70-
go
CPT Predicted S., CPT Predicted asisuificatton
I Meured S., Soil Sample EQuvyelent Zones
e.g. Sm Soil Sample Classiflccation
Figure 8.46 CPT predicted versus measured ýSul)-xtU for the Onsoy site ": Norway
(NGI research site) (the measured strength data arc at four difierent
depths) (data from Rad, et al, 1985, Gillespie, ct al., 1985)
223
CPT based SOILCLASSIFICATION
an m M
L L £1x_ r,_ • -
4J 4-1 IDNormalized Undrained ..m m --_
aJ s"4J •3I
Strength, "SU1) TXUU m - C C3 ,- -~i a, n a} n
0 0.5 1 1.5 o. Utw2n3fU)0-*
CIST NG CT _CPT-- -CC PT-g
InvesItigation estigAtion In tigat on
1 0 - . ..... ......... ..... .
20.
•30 ........ ... ...... .. ......
QI
00..
40. . . .-
50-
410
- i I I
60--
CPT P"-edlcted Su CPT PradlCtqd Classification
M4ea•ured S,,- SOil Sample EPuvalent ZOnes
e.g. S4 Soil Ssmple Ciassification
Figure 8.47 CPT predicted versus measured (Su)rxuu for San Francisco Bay mudat Hamilton AFB (University of California at Berkeley research site)(data from project code ET-SE)
224
CPT based SOILCLASSIFICATION
61 1 q in4) 4) V-L L 4,
xX L-- C3
Normalized unaraineaA-i sSJ V
Strength, _(Sul) TX(5 0 0- C C C0 0.5 1 1. 5 Q.o0U: I 2t3 U) 4En5
lnes avti l Invelstlgation lInve got on
10 ............
20
I 304. 3 0
.. [ ..... ......
00
40 -.. .. ..... .. .........
50--
CPT Predicted S., CPT Predicted Classlfication
I Measured S., Soil SamDle Equvalfnt Zones
etg. SM Soil Sample Classificatlon
Figure 8.48 CPT predicted versus measured (SUI)1,,Uu from Norrkoping, Sweden(with measurements at 11 different depths) (a Swcdish GeotechnicalInstitute research site) (data from Larsson and Mu abdic, 1991)
22i
CPT based SOILCLASSIFICATION
CL L 0)
X • L
Normalized Undrained N 0 M )Strengt h., (S- ) TXUU O a C a
0 0.5 1 1.5 n0 L I 23u0-,
CPT BROPING COTKONRAD KONRAD X NPAD
I ,lOstlastiOlon InvgStlgatltion In . i tIG t UO1 0 ... ..... ......
20 .
3 0 .. . ... ..
., 5 0 ... .. .. ..
0
0.. 50-
7 0 . . ... . .. .
80 ... . ..
90 ' . .. .
-PT Predicted S., CPT PrediCted C18*91fication
M deasured S.,
Figure 8.49 CPT predicted versus measured (Su1)iTUU from the Hibernia offshoreinvestigation (data from Konrad, et al., 1991)
226
CPT based SOILCLASSIFICATION
in M• In
L L 4)
L f L
Normalized UndrainedStrength. (Su 1) FVlne M M . C C C
S 00. 51 .M Un 2 U 3U.. ... ... . ......
t0 C-3 C3lnvelt lgat lon In eitgation.
: FV-•[flvitlg tlt Of
2 0 ".. " " " ..... ... ..... .. .
3 0 -...... ...
4 .o .. i - - -. .... . . . .. .30
so
UIEO I
s o - 1 . . . . . . .. ............
100:
110 "
120
14 0 . . • • - " ,-"-........... .......
CPT Preldicted S., CPT Predicted Clansi~ficaton
I eeasur-ed' ----........ Soil Samp:le Eauvalent. Zone$
e.g. SW Soil Sample Cleasification
Figure 8.50 CPT predicted versus measured (SuI).r',uu for San Francisco bay mudat the muni rnetro turnaround facility, (with measurements from 17different depths) (data from Dames & Moore, 1985)
227
CPT based SOILCLASSIFICATIONSin cn
41 a, aI L L3 3
Normalize:) Uno,'ained ,,,4j >-Stuentti, Sj C C C
0 0.5 1 1.5 CLU 1 U2C3 50 1 3 5
0 - L• . . . . . ._.-.. .... . ... ...
C-1 SOFING C;Invevifttgaet n B-VANE Invel
Invest Igat ion
20 .........
30 .. .
•J
I-U 5 0
x 1CSO
70
xt
G o - . . . . . I " ' .. . ." " . ... . .... . .
CPT Predicted S-3 CPT Predicted Classificatton
I Measured S.ý
Figure 8.51 CPT predicted versus measured (Sul),v.ne for a conference pile loadtest at Northwestern University in 1988 (with measurements from 12different depths) (data from Stratigraphics, Inc, 1988)
228
CPT based SOILCLASSIFICATION
L L LX
Normalizea Undr'ained inn nStrengtri, (Sul)Fvane CC
0 0.5 . 1.5 D-U0(00
CPT V~'r-PEFAIL. CPT
Investicat~on -"P I W. tILe
10 _7"NE Rkt
20 .L
40
50
60-
I-
Figure 8.2 CPT predicted vursus measw~cd (S~ for a foundation clax'Ly.for the Nerlerk Hecin liq~uefaction Alide study,
229
CPT based SOILCLASSIFICATION
LL'Z3 >
4 J .J 0
Normalized Unldrzned 1" U x x
Strength, (S51 ) FVer~ e M C C C
0 0.5 1.5 0 oU2W3U1 50-
C I BORINGTnvestjqat•'or, GFONO "nv at "I
lnvaat)qaticn
10-
20-
ZZ3050
E L.
70
60- -
go . .9..0-...................
CPT Predicted S., CPT Predicted Closo'flcotlon
Measured S.
Figure 8.53 CPT predicted versus measured (S. at the Fraser River Delta
Bridge, 25 km SW of Vancouver, Canada (with measuremcnts from I Idifferent depths) (Data from Crawford & Campanclla, 1991)
230
CPT baseod SOILCLASSIFICATION
M M•
AJ4J toC. .. 6)
~x x L
flormalized Urndrainecd x x N
Strengnth. (S..1) FVanc M M C C C
0 0.5 1 1.5 oa 7 tn ( (1)0 0 1 45
.0 . . . .. f....
Al ZNGM~29
Invdaigstig~or
20 F.nvLJgi I~
3J . .
0.4 0'
I.)
U-)
50 - ___. ....
6 0 . . .. ..
CrPl Predicted 5 CPT Prwd fetedj Claasl f cat ion
I Measured S,- Soil 5SamPle Equvalent Zonese.g. SM Sol] seMole Classf1ication
Figurc 8.54 CPT predic-,.ed veisus measured (Sul) nc for bay sediments at theltong Kong Airport repl.ccnment at Chek Lap Kok (data from Daines& Moore, 1982)
231
CPT based SOILCLASSIFICATION
S W "-LL ri• >
NormaliZeO Undrained i o ) M
Strength, (5.1) Fvane 0 u C. C C0 0.5 1 1.5 n 1a tflU)
0--E32N 2ND!
ln I 'g lo20 L...10-
4 0 . .....
050-
--
70-
SCPT V'r@Clrted S., -CPT Predicted Clasolf1cotaor
K heegUrgd
Figure 8.55 CPT predicted versus measured (Su1).a at Lower 232 Street,Langley, British Columbia, Canada(data from Campanella, et al., 1991)
232)
CPT based SOILCLASSIFICATION
0 41
XX ..
Normalized UndraineO d i i c
Strength, (S 1) M
0 0.5 1 1.5 n. U)VnU•0 1 2 3 5. . .. .. . ....
BEG-BUInves t iositon
2 0 - . .. ..... . .....
CPT"J z1• t of,30
cl-
20
cibFCF
4 0 ; ... ....
0 . ... .... .. .. . .
6 0
CPT Preoicted S., CPT Predictea Classlificrntil,,
I Measure tI " 1•d 5ý,
Figure 8.56 C PT] predicted w.vr:sas w ,,-ais wlcd (Su~ l,101 % "'n 'itl larklcv dan, -w itthiI clay
lenlses ((Ji.lu fionli Ol.sen, et al.. 1989)
233
This ý,L fiactor is used to reduce. t~he nmeasui--d field vane shear strength to an
equivalent undrained triaxial test strength icvel (i.e. field. strength value for siope
stability evaluation). The ui is thereibre the- ratio Of (SL.1)TXUIJ contours in Figure 8.36
to the. (S, 1l)F\. contours in Figure 8.42 as illustrated in Figure 8.57, xvith the results
shoAn in Figure 8.5-11 Thf; ýt contours in Figure 8.58 (i.e. 0.5 to 1.0) have the same
general range as from historic observations in Figine 8.59 (i.e. 0.4 to 1 .0). The
Bjerrurn ý.; factor was hi~torically indexed to Plasticity Ind,.x (P1) as shown in
Figure 8.59 (Bjerrum, 1972). PI is now used only to index ox'erconsolidation
character as showii at the top of Figure 8.60 (Aas, Lacasse, Lunne, and Hoeg, 1985).
After the overconsolidation character~ is estimated, the Bjeiruni [.i factor is then
estirriated using the chart ui the bottom of Figure 8.60. This figure shows that the
U facWTo is approximately 0.6 to 1 .0 for viorrmally consolidate-d clay and 0.35) to 1 .0
for overconsoli date (I clay. The contours in Figure 8.58 showv a calculated Pi factor of
abi-ut 0.9 to 1 .0 for normnally consolidated clays deýreasing to 0.5 w-ith increasing
ovcerconsolidation or increasing silt conten~t.. The lack olffteld vane shear dato for
hiighly overconsolidated clays prevents esuiblishing jk contours &-chae lower Lhari
0.50.
Conc/us ions
Thiis section introduced a new tectniquc for estimating undralined strength of'clay
which is appears to bu as accurate as rnetloods which r-equirc estimraiing the cohiesIVe
Nk bearing factor. These correlations were shown to give good agrecx~1eni b,,iwlce-n
measured anid predicted values for clays around the wvorld.
234
100 - 101
0.1 1 10 IC
//rciaRatio M% J'ctiCmcr Ratio()
"(S \U FV
0.1 1 10
Plricio Pjiio (9;)
Fit!,ure 8.57 ifiustration on how to calcuflate the B1jerrurn ýi correctionl factor usingthe predicied Sul contours
235
100()0 0. .
Contours of tihe
Vane Shear testcorrection
vi.factor, /
.. 7
1 0 -- C ' -
'~~~ z .
/y
-Jc
cr by t
236
4] -7, / ] I
Figure 8.58 Calculated contours of (SuI).xUJ/(Su),SV on" thea CIT soil chawactcnization
chart by taking a ratio of contours on !"iguc ...36 to F~igure 8.42:
236
1.4 .
su (Field)=p-. (Vane)
1.2 - ' _ _ _ _ -
- 1.0 '",,4- IU ___ _ 7 Bjirrums (1972)
___ ,_AD Recommended Curve
ru Q0
S0.6 -___
0.4
0 20 40 60 80 100 120Plasticity index, IP (%)
Figure 8.59 Correlation oi P1 to the Bjt-rrum Ii correction factor for determiningthe ulidiained snerigih from field vane shear results (Bjerrum, 1972)
237
100
80NC0
20 40 v i
20 el '-.
0'0
1.4 A Embankments
-,L ' .. L~dVdl IUI3•
1.0 -X,, -S-u corr. "- Lt u (Fv)
0.8 - i. -
0.4 -"- - --- - -- o_
o.4 0C~0.2
0 0.2 0.4 0.6 0.8 1.0
S U (FV]/rVO
Figure 8.60 Correlation of (Sujl)Iv to PI to establish the overconsolidationcharacter and then to get the Bjerrum p correction factut
(Aas, Lacasse, Lunne, and Hoeg, 1985)
238
CPT Prediction of Shear Wave Velocity (VS)
Introduction
As noted earlier, accurate prediction of the shear wave velocity, V, , using the
CPT results may not be possible because Vs is a low strain measurement while the
CPT is a high strain measurement. Nonetheless, there have been several attempts to
establish useful correlations. Typically, Vs has been predicted using the CPT cone
resistance (Baldi, et.al., 1988) or more recently by using both CPT measurements
(Olsen, 1988). The Olsen (1988) publication developed a technique for CPT
prediction of the maximum shear modulus (Gm,) (Gm. and V, are theoretically
related). This section will extend the Olsen (1988) technique for CPT prediction of
V. based on improved stress normalization techniques (Chapters 6 & 7) and use of
the new larger database (Appendix A). Vs, Gm,,, (Gm•,)i, 8 and V51 were fully
described in Chapter 7 during the development of the shear wave velocity
normalization stress exponent (v).
Minimal Stratigraphic Error when V, Measured by CPT sounding
There are two general means of measuring shear wave' velocity in the field: with
borehole(s), or with the CP[ probe. Borehole based shear wa,,e measurements are
performed cither using crosshole (i.e. borehole-to-borehole) or downhole (surface
energy source and geophones in the borehole) teclhiques. The Ci1T based shear
wave velocity measurements use downhole measurement with the geophones inside
the CPT probe (about 1 meter up from the cone tip) (FUGRO, 1980; Campanella and
Robertson. 1984). During a shear wavL test with a seismic CPT probe, thb shear
wave tra, tls dowi. "Arough the soil directly adjacent to the probe. The soil tz-sted by
239
the CPT probe is the same soil traversed by the shear waves, therefore, there should
be little if any stratigraphic bias when establishing correlations. However,
developing a correlation is still difficult because shear wave velocity is a low strain
measurement and the CPT measurements are high strain measurements.
i-vstorical use of both CPT Measurements to Predict V/ or Gmax
The first technique for estimating V, (i.e. Gn,,) using the normalized cone and
sleeve resistances is shlown in Figure 8.61 (Olsen, 1988). The contours of (Gm•)i in
this figure are parallel to normalized sleeve resistance. Gmax appears to be
proportional to the sleeve friction resistance, more so than to the cone resistance.
The proportionality of Vsj (i.e. (Gmax)I ) to f,,, was believed in 1987 because both
paramieters are influenced by horizontal stress. It will be shown in a later section
that this proportionality is more likely because bodi paua:,--.tu7, ýoe dependent on
'void -atio and soil type.
CPT Prediction of Vz using Both CPT Measuremems
The procedures for establishing contours of riorrnahied shear wave velocity (V,,)
on the CPT soil characterization chart using the miniml inclusionary AQI tectmique
is the same as used for establishing the N, and S,,, ccntours in previous secOi,.': ofthis chapter. All shear wave velo-:ity data from the database, for all projcts, 'erc
divided into five V51 ranges for the purpose of establishing individual conrelations
contours on the CPT soil characterization, chart. The best-fir contours of uoirnalized
shear wave vetucity using the highest inclu:;ionary AQI a show)i in l-gure 8.62 tv,
Figure 8.6o for average V~1 levels of 150, 400, 650, 900, and 1200 tIcv'second. The
final best fit V., contours ar-. show•• in Fi-ure 9 A7
240
1000 -
800- CPT technique for estimating the
600 maximum shear modulus
400- //
GRAVELS K2! AND AN4
SANDS r0 200- 1/ 0 OR
10 0 .01 /01 (GM 8Xjj (tsf)C s 100- <0 /
Cr 60- 01
40--oS SANDS
a• 8
CTp
201 0lop,0
SAND MIXTURESio
10 .-
" 6- SILl MIXTURES CLAYS
Q 4-00.
Gmax (G All parameters in terms of Ist-aa. , 1 0.77
2 Grria= 1000 K 2 (&m) 05 All parameters in terms of psi
While the average of each range is the best estimate.the range is required because the CPT measurements areonly influenced, not controlled by shear modulus
1---------------, TI I I
0. 0.2 0.4 0.60.8 2 4 6 8 10
Corrected Friction Ratio (%) in terms of tsf
FRI •= 100= i00 = q 100
Figure 8.61 CPT prediction of the maximum shear modulus using both of the CPTmeasurements (Olsen, 1988)
241
I )((J00il
CPT c~rrelation oftat - 10 -t 30U ft/s,con't
(td.fft-rent AQi slat,.,tica) levels)
4II* AQ' r' -it 80-. tu 100!; (best dat,)
L. [] A., roi.. '71"'. to 1 1
/' AQls G~t to 100': .2.; data)1 ltest fit CDo-.,Tu Ijil V, 1 -200 fi ,sCond
E £ - Other VCento,,,s
(-U-
0.' 4-1 L-
I U
6
- 1 101
o242
1000- ________________- -
8 C('fT (Orrch-tuoo Of
6 v~s I- 300 to 500 L t setond*' ,, d,ffcrmnt 1,(4 St.,ttIbci IcCITI)
*1- AQ~s frr 8 . 10
- ,fitist wi co t i -ft % 1' 4 0 f cor
0- thwr V co'ili.,uU,
- Z-
CL L.
Q,
-o-
ý7-i
8AA
oi -i
L I C
Non)hzc Frictim) Put;()
i'iguvv 8.63 P~redictionL of tiic Vj ý-- 4(03ji t1Js¶.c ,oi~ttox on Lin, CTI' 1soilcliaractefizat~on cflart 2,1I
1000 -,1-_ - __½ 1W ½
NB
-~Z 'A42D
0 I C
AZ
I -- [
o~ / )J o80 tscn(at /jfrn A -! .tttiall~ h
N4 [2 t ,
4ikr /,4 Pei.to fl 5 thýccnoro h lsi
2 2 4
i On
2 -L "A[
cc 0
100- ¼
E- -
2orlto of
0 1 W 0 /A0f0No iiI.,', 12rc I cl a,-h
Fliur 365 Prditin f heV~ =90 fl'eccotor n heCJT 'l
chr(tr.)tm chart -
24U
1000 ~- __
-i-
10 -.
8 -4
In dik r tA ISal /IR eC5
C] AQC frm8- tCD
I-' tsCCý0
100-4
0 j1, T1 A c rNt
ClFiue86 rdcino h 0 20 tsucnoro h PIsi
chrccnzjio hr
-246
6 Goult ill's of N0Vflija~lz(.d
4 \.,((et Sc( 01)(1)
120
1000
4 A.
_cf
C;10N
0 1 -
N cl -I II I d ))II
oiuc86 o tuso*nr aiait lcrw v ýlct Vl oltl ATSlchlatrzto cha - (Y
*1 247
Several examples of ClPT predicted versus rricaured normalized' she'ar wave
vt"iocity (Vs') are shown in Figure 8.68 to Figune 8.76. Ti-hese plots represent all s•Ail
type ard all relative strength levels. The important observation from these figures is
that the CPT predicted V,1 agrees well with both the inmasured values and ,heir
variation with depth. It is also importamt to note that a-,'n 80% of the shear wave
velocity data was measured usiog the seismic. CPT probe so there is very little
stratigraphic bias error.
Discussion of CPT prediction of V•I
For clays and silts, the nercrialized shear wave velocity (V,,) contours in
Figure 8.67 are parallel to normalized sleeve friction, f , (j) contours are shown in
Figure 8.18). This indicates that overburden stress similarly intluences V,, and is>..
However, sleeve friction resis-ance refiects a high-strain surengLh (Douglas wi, d
Olsen, 1981) w•ile the shear wave velocity represents a modulus at extremely small
stlains (10-5 percent). Shear wa,,e velocily is indexable tu; void tio, confining stress
and soil type (Richa-t, Hall, and Woods, 1970., Seed a-nd idJiss, 1970). Sleeve
friction resistance appwaches steady state strength (if thre is no volwnetric shear)
(Wahl, et.al-, 1991, Castro, ct.al., 1989). Sleeve friciion resistance should bc
indcxablk to tfh-e Sa.e properxie., as steady state strength, namely; void ratio,
confining stress wid t;oil type (Castro, 1969, Schofleld and Wrotli, 1968). Because,
the V. and 1•1, cotours are parallel (for clayey soils), it suggests that they ire also
depewkd ct to dhe ,.ame combination of gcotcchrtdcal propei-Cs.
The \V, conitours bend withun the sand zones of the CPT soil characterization
chart (Figure 8.67) hiz loosc. aid reiodium dense sands. CPT probing, of these sands
causes volame cieauge dac to• the hbigh bearing t esses which result!, in a denser soil.
For loose clraz• sa3ds, the measured cone resistance tt;ereltuc reflec. a denser state
than tc' in situr conditio because of grain rvirrazgemeudt, grain erw.;hir{., and
248
CPT ba~va SOTLCL AS SI FI CAT ION
L L wJ
SL
Aj >1 4j lf Vin ternEý of feet/second 10' C C c
0 500 1000 1500 2000 C-UE2n3nAI
"HOL*4tV r.VXnVE stigntion
S HOLI4EN- M MN-
In Ir 6tjqat n 1"91 t2put
30
C01
601
-v .P, erltted1 V 1 CPT Pred~iiAtn ci~aa~fcnt~un
e1hAsoil 56mole1 CLasv1lcnt Zone
Filglure 3.L6O CPT predicted versus measured V,,1 for flc H-olnien site, LDiarrnmcn,Norway (N(1 research sitec'} (daiia frOlit Christ-oficisen and Luurie,1982; (JiliesTi.', Iunnc. an~d Lidsmoeri, 1985)
249
CPT ased SOILCLASSIFICATION
LL a)
x- x
10 N0
in terms of feet/second c -" c c ci ,1 - IQ to to
500 1000 1500 2000 u (n V) m) (n00 2 3 A" L ~~~0 . .. . .. .' .' ............ .- ..-.....
20
30-
40-
Cnrt i CPTOI RpycSI50 Invsstl~etlo, lnvmstlgstion In'. tf oan
50o
l-- 7
so
720 .- ..
1V3,
a•4
•0~0010
I180 • I •-•
130- -.
o1401
1701%8
ieo l..rar~rr..rY-.V.,-~~rr.r CPT Prodlictgd dlJasva'lfC-qtfa'
I tbsastrd v.
¼ Fiurt8.69 CIV[ predicted ver-sus measured V,, for a stifl/dense dirty sand site inthe U.S (project cod(, DL-Y-R)
:ý50
CPT based SOILCLASSIFICATION
(~n V) (LL 4):3 >
xx L
Val U) W1 fD4., >.. fl C) 10in terms of feet/second 0 M- C r -
0 500 1000 1500 2000 C 1 4 M 5
OR 1kG103PTv-26
10 ... ...
20 - .=. W . .
CPT7-T-2
ln'~.Itlg t n I gto
t o 0 ... .... '!....
.4 .
70
90 ...
CPT Predicted V., C1T Pprdicted C]gssifir tio,'
Measured V.,
Figure 8.70 CPT predicted versus measured V,, fbr the Barkley darn seismicevaluation study (data from Olsen, el al., 1989)
251
CPT baesed SOILCLASSIFICATION
L L IU
XX L
4J >1 4J'0 'D '
in terms of feet/second 0 - C C C
0 500 1000 1500 2000 1L U E2)(11 (f tf01 34
)4AASOn MIn 1 . 1Irvutlatitl n tion lnweztiqat
5-
10 I
15 .
Z'20I
r-25
El301
50 4I
CPT Predirted V,1 CPT PragdlctL Classification
I IMeasureS V,, S011 SamflUl Eauvalent Zonuis
2-9 Sb' Soil SaM0I. Cleoulfiestlor.
Figure 8.71 CPT predictedi versus measured VS1 tbi a site at Tuktoyaktule,Bugmallit bay, Beautbrn Sea, Canacia(data frk,m (Lamptanella. et a]., 1 987)
2 52
C•T based SOILCLASSIFICATION
un (n Qn
L L 4)M
.. J 4.J .-
4J>.-I 3 V
2n terms of feet/second 0 M - c c cIi - -' MU 10
0 500 1000 1500 2000 O UL 1 ) L(n4 J
10
.4
-IU>
~25
30-
IT
25
30
- CPT Predicted V., CPT PredlCted Classification
I Measured V., Soil Sapole EauvOlent Zones
e.g. SM Soil Samols Classification
Figure 8.72 CPT predicted versus measured V., for a uniformly compacted sand(data from project code DN-HJ2)
253
CPT based SOILCLASSIFICAI ION
Li . (_LL L >MJ M4 U)
LX L71 :3 >-
Va.G V)iV
in terms of feet/second u, © - C C G
0 500 1000 15Oo O000 0- 0 U (n M U0~~0 PW1- '0 .. ,,,. ,oL,.L
CPN\ SOMINGON50YY52 5%-1;
jny.' got n Invautigeti C.' in . 9 t.ka ft
10
o .60 . .. .
750 . ...ci
607
70 .. I...
CP_ Preditor_ V., _ CPT Prielctdd Clatilficet:.1n
I ebsurid V., ........... Sol] S#l r ZQuv~lert Zonese.g..SM Sol) 58W',10 Clavislifcatior,
Figitre 8.73 CPT predicted versus measured Vsj for a site at Onsoy, Norway(NGI research site)
254
CPT based SOILCLASSIFICATION
LL aJ:1 : >
S L
4 >. 4j ao a 'ain, terms; uf feet/second M M - C C
0 500 1000 '1500 2000 nLUV)( 3 ) 4 Ln 5
I~~ ~ ~ I 3UM T I5U31-
so 4 - 'I " . ... ........ ..-
.----. ___
20 - - .m.,
IT,
(UU
0*'o
II M V -
z ~C -----.
2 5
LPT Pf'edicted Vm, CPT PredlCtert1 C]asnitlcat~on i
I eaouuf'd V*, ...... 5l] SOiole Eouveltnt Zon~ls • -.e.gJ. SM Sal] Snmple ClnnsLelfcaL1on
Figure 8.74 CPT predicted versus meaisured g• at Treasure Island, San Francisco, •-_Calitbirija (data irorn Hryciv,,, 1990)
255 -
CPT based SOILCLASSIFICATION
IIC
in terms of feet/second- c c C
0 5 0 0 1O0 0 0 i5 0 0 2 0 0 0 0 -0 " 1 ' 2 ' 3 ' 4 ' 5. . . .~.. .............. .0
ZX Z
f 05 'r0 ;-01310- 'JKnrh Y> 01 7V-.
81 50
E fl
70 1 . . .. .... ....20 . " -
I0 ........ .. .......
C 1• "
a- 4 kr
60 .. A. . ...
70 ... I " .
I I.
____-CPT FR-wdlctef Vm• CPT PrgdI~tgd Clau~lflcat Ion
Measured V.,
Figure 8.75 CPT predicted versus measured V s at the parameter levee area ofSanta Cruz, California (data' ' im tIryciw, 1990)
256
CPT based SOIL
CLASSIFICATION
:) 3 >6j 4J a,
in terms of feet/second r V c c c
0 500 1000 1500 2000 n0)M20 En A En 5
0"
50- .... m
0o . . . . . . . . . ..- .. ..
00
50-- ...
; 0.0.. . ...-
U C•T l=War--•20)
300
CPT-03 P-i t V
F00Icrlv@St lgr ted v s CVa Veon Irls silt on
CP P|eI tod V51 C Pvf~ .~tdCasfct
Peak dam, Idaho
257
densification. However, for dense sand, the Vs1 contours appear to be parallel to tl.
Dense sands do not densify during shear. Therefore, for dense sands, the in situ void
ratio is approximately equal to (or even greater than) the void ratio surrounding the
sleeve and cone units during penetration The resultant is a Vs, contour which is
approximately parallel to a fsic contour from clay to dense sand as shown in
Figure 8.67 for Vs51 =1200 ft/second.
The V51 contours in Figure 8.67 can also be generalized as shown in Figure 8.77
as a means to explain densification effects for loose to medium dense sand during
penetration. A line of constant normalized sleeve friction resistance is shown as Line
CF in Figure 8.77. Line CF would be parallel to the Vs! contour if there was no
volume change in the clean sands. However, line VF is a typical Vs1 contour. The
differenet between Lines CF and VF could be the effecL of sand volume change
during probing resulting in a denser soil for loose to medium dense sands. Point N
is along a constant fse contour (Line CF) representing no volume change for clean
loose sand. Point S represents a denser sand condition due to probing and a higher
rmeasured fsle (and ql,) because the sand surrounding the sleeve unit is denser.
Therefore, CPT probing of clean loose to medium dense sand produces a denser
condition than exists in situ which results in an explainable bending of the V51
contours.
.25
258
Constant Vs1 contours10001-- If no de-sification had occured
, i In sire condition (densified) Dense sands do-- not densify
Dense duing shear/ Nsands / x• (therefore the
dense sand MWcontour doesnot bend)
N K Constant soil
SM ' type contourS• ~~Loose ...
sands
Dirty sands 0, <
Mixtures00z C
Clays
1 -
0.1 1 10
Normalized Friction Ratio, 1j
Figure 8.77 Illustration why the predicted shear wave velocity contours on the CPTSoil Characterization chart are curved
259
Chapter 9
Conclusions
The primary objective of this research was to develop techniques and correlations
for predicting geotechnical properties using CPT cone resistance and sleeve friction
resistance measurements. Stress normalization provided the means for taking
confining stress dependence into account when predicting geotechnical properties
using CPT measurements.
A new concept, the Stress Focus, was discovered and confirmed which provides
a basis for understanding strength behavior (e.g. friction angle, cone resistance, etc.,)
as a function of confining stress. This stady demonstrated that the relationships of
sand friction angle to conf'inng stress for different initial densities converge to a
Stress Focus at high pressure, where the strength behavior is similar to that of a
sedimentary rock. This convergence to a Stress Focus was also confirmed using the
CPT cone resistance measurement. The paths of convergence to the Stress Focus are
exponentially related to overburden stress and can be represented as straight lines on
a log-log plot of strength versus vertical effective stress. A sand at a given relative
density can be represented by a straight line on this log-log plot with all relativw
density lines converging to the Stress Focus. The slope of this line, termed the stress
exponent, is inversely proportional to sand initial relative density.
"The strength of dense sand is strongly influenced by dilation effects. Dilation
effects for a dense sand will decrease with increascd vertical effective stress until the
Stress Focus is reached where its behavior is similar to that of a sedimentary rock.
260
The convergence of relative density lines to the Stress Focus for sand is caused by
coinsolidation (i.e. decreasing void ratio) which is reflected in numerous geotechnical
properties such as Mohr envelope curvature, gr-.in crushing, compressibility, etc.,
Sands of all relative densities will have approximately the same bulk deilsity
(i.e. void ratio) at the Stress Focus and, as a result, approximately the same strength
behavior. The Stress Focus should therefore be considered a fundamental
geotechnical property. The Stress Focus concept replaces the variable soil type
dependent stress exponent technique for normalizing cone resistance previously
developed by the author (Olsen, 1984, 1988).
The Stress Focus concept was confirmed using historic high pressure triaxial test
data in Chapter 2 (collectively shown by Figure 2.5). Sand strengths are shown to
converge to a Stress Focus at a vertical cffective stress of approximately 100
atmospheres. A simple yet uniquc CPT cone resistance normalization formula,
which accounts for exponential stress dependence of the tip stress, has been derived
in Chapter 4. The Stress Focus for CPT cone resistance is demonstrated using CPT
laboratory chamber data in Chapter 5.
The Stress Focus location (i.e. vertical effective stess and strength level) was
shown to be soil type dependent using field CPT data from uniform soil layers
(Figure 6.24). For clay, the Stress Focus occurs at a vertical effective stress of
approximately 9 atm. For sands the Stress Focus occurs at a vertical effective stress
of approximately 70 to 200 atm.
A technique to estimate the stress exponent required for cone resistance
normalization was also developed using CPT data from uniform soil layers.
Contours of cone resistance stress exponent were established on the CPT soil
characterization chart (Figure 6.16). These stress exponent 'contours also support the
validity of the CPI soil cha-acterization chart (Olsen, 1988) to characterize soil in
terms of soil type and state.
261
The constant drilling mud height (i.e. constant pressure) used in SPT cl-amber
tests, for all confining stress levels, reduces the confining stress-es next to the SPT
sampler (Chanter 7). All SPT chamber tests in the pas' have had this problem. This
reduced confining stress results in a SPT based stress exponent which is too low if
derived from the results of chamber tests. The SPT-N to N, normalization concept,
developed over 10-years ago, is based on SPT chamber test results and therefore uses
stress exponents that are too low. The stress exponent for SPT borehole applications
were shown to be equal to the CPT cone resistance stress exponents. Therefore, the
CPT determined cone resistance stress exponent should be used for SPT
normalization. To achieve the best SPT normalization, therefore, requires a nearby
CPT sounding where the cone resistance stress exponent can be estimated.
The stress exponent for shear wave velocity is shown to be soil type dependent,
and it can be approximated as 45% of the CPT cone resistance stress exponent as
shown in Chapter 7.
Developing CPT correlations to geotechnical properties required a large database
of CPT and tested soil sample data (described in the Appendix). The !argest error
during correlating of CPT measurements to nearby borehole soil samples is
geological change of soil type. A change of soil type is corsidered a bias condi-.ion
because it will skew the data trend. Bias data must therefore be discounted when
developing correlations. A quality index was developed in an attempt to account for
possible soil type difference between CPT soundings and boreholes-namely the
Academic Quality Index (AQI). The overall AQI accounts for possible stratigraphic
change and CPT measurement quality. Establishing predictive contour trends on the
CPT soil characterization chart was accomplished with a new technique that uses the
AQI quality index to account for bias error. Correlations were established for the
following normalized geotechnical properties; SPT blow count, undrained cohesive
strength from the upconsolidated undrained triaxial test, undrained cohesive strength
from the field vane shear test, and the shear wave velocity.
262
The contours of normalized SPT blow count on the CPT soil characterization
chart have a predictable trend (Figure 8.17). In loose to medium dense sands, the
SPT sampler is primarily resisted by end bearing force (while the sampler side
friction force is minor). Cn the other hand, for dense (and overconsolidated) sands
and clays, SPT sampler side fri'ction force dominates. This relative contribution of
SPT sample; end bearing to side friction forces for different relative densities is
confirmation of work by Schmertmanr (I )79a). The technique for predicting the
SPT-N values based on the CPT cone resistance and sleeve friction resistance models
the forces on the SPT sampler and demonstrates the potential for reliable prediction
of SPT N values from knowledge of CPT cone and sleeve friction resistances.
Contours of normalized undrained cohesive strength (i.e. u, or Sul forP o,
unconsolidated undrained triaxial tests (Figure 8.36) and field vane shear tests
kll-u16" o.42') were estabiosned on the CPT_'I soil characterization chart. Historncally,
the Nk (i.e. ratio of net cone resistance to measure undrained strength) must be either
be estimated or deveioped as a site specific value. An estimation of the N, bearing
factor is not required with this new technique for CPT prediction of clay undrained
strength. The ratio of the (S,)TXtU versus (S,)3:v is the historic Bjerrunm [t 'orrection
factor used for reducing the field vane shear test results to unconsolidatwd undrained
triaxial (TxUU) strength levels. The calculated p (Figure 8.58), based on these new
correlations, has the same range published by NGI, namely 0.9 to I for normally
consolidated clays and decreases to 0.5 for overconsolidation (or increased
silt content).
Contours of normalized shear wave velocity were also established on the CPT
soil characterization chart. These contours are parallel to the normalized sleeve
friction resistance contours when there is no volume change during shear (e.g. clays,
clayey silts, clayey sands, dense sands, etc.,). It appears that the friction sleeve
resistance and shear wave velocity are influenced by the same geoteclnical properties
263
and in the same proportion. The normalized shear wave velocity contours were also
observed to bend within the loose to medium dense clean sand area of the CPT soil
charactedization chart because volume change during shear causes a denser state.
The predicted shear wave velocity agreed well with the measured values.
Future Research
* Integration of the Stress Focus concept int- critical state soil mechanics.
• Continue to evaluate chamber test results toward better understanding and
definition of the Stress Focus.
* Evaluate man-compacted soils (e.g. earth dams, fills, etc.,) toward establishing
better techniques for stress normalization and prediction of geotechnical properties.
• Investigate the soil property and bulk density at the Stress Focus.
• Seek more verification of the CPT predicted geotechnical properties.
• Continue to develop the AQI as a subjective index for excluding bias error.
• Develop a computer technique for locating the Stress Focus using several relative
density groups (this is an iterative procedure which searches for the optimumlocation for the Stress Focus by minimizing the relative density trend variances).
* Deve!op improved techniques for calculating the CPT stress exponents using field
data.
264
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281
Appendix
The Database Contentshi
Introduction
Collecting the CPT and boring data represented the single largest effort (and
longest time effort) for the purpose of developing CPT correlations of geotechnical
properties. There were three major sources for this data, namely, 1) the author's
project files, 2) requests for data by letter, and 3) requests for data after a lecture was
presented. Overall, the best CPT and boring data originated from the author's project
files. This data base represents the largest coherent accumulation of CPT cone and
sleeve with boring/laboratory project/research data in the world (1994). This
collection of data also contains two types of data: field CPT/boring data and
laboratory large diameter chamber test data. Most of the collection emphasis was
directed toward field CPT/boring data.
Requesting Data by Letter
From 1986 to 1988, about 120 letters were sent to government, utility and
coinsulting firms requesting CPT and boring data. Only 15% of the requests for data
7. resulted in data aid only 5% of the total database came from these blind requests for
data. Oldy 60% of the data received during this research program was uscable. Less
* than 15% of the geotechnical engineering publications which describe projects having
CPT data actually show a CPT sounding log. When a CPT sounding log was
282
presented in a publication, less than 10% of the total also show sleeve friction
measurements. Therefore, only a small fraction of this database originated from
publications.
Requesting Data by Presenting Lectures
Approximately half of the geotechnical data came from professional contacts and
as a result of presentation lectures on CPT technology. A total of 23 lectures were
presentations by the author to consulting engineering companies and state/federal
organizations from 1988 to 1992. Engineers typically felt obligated after a lecture
was presented to search for and copy at least one geotechnical project for this
research program.
The Data in the Database
This database contains approximately 670 CPT records and 580 borings from 90
projects. The CPT records represent approximately 51,000 ft of data and t -re are at
least 1,200 boring soil samples with a total of approximately 8,100 laboratory and
field test values. The following is a partial list of the types of data in the database:
CPT measurements (cone resistance, sleeve friction resistance, and dynamic pore
pressure), SPT blow count, measured shear wave velocity, water content, plastic
limit, liquid limit, total density, percent passing #200 sieve, D50, field vane shear
strength, laboratory triaxial strength test results (and testing method). Unifield Soil
Classification System designation, word descriptor based soil classification,
consolidation parameters (e.g. C,, C,, OCR, P,.,,, etc.,), void ratio, etc.,
283
Test Chamber Data
Data from several large diameter test chambers are also included in the database
for establishing new CPT and SPT normalization techniques. The CPT chamber data
was provided by Jamiolkowski (1988). SPT chamber data by Bieganousky and
Marcuson (1976, 1977) and Gibbs and Holtz (1952) were also included in this data
base collection. A complete listing and description of the CPT and boring data base
are shown in Table A-I. The soil conditions column provides a general descriptor
only for comparison between sites.
Data Sensitivity
Most of the data used in this research program originateu from military,
sensitive security, or sensitive private projects where the data source rrust be kept
confidential. Much of the private project data (classified as sensitive private sites)
were provided by geotechnical engineering consulting firms with the understading
that the data and source would be kept confidential. In all cases, the data could be
used to establish data correlations and the data points on the correlation plots could
be published; however, the provider would not allow the site. name to be published.
284
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Form ApprovedREPORT DOCUMENTATION PAGE MNo07418
pubfik teponig Lvrcefi for this c lectioEn of inforaton M n.t~ imettfted to average I hour per I Joorse. Including thetiefrevwngntucs Seahng xsigdtaore.rid ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~~~~~crnft titiigtedtneddAM oirftnanreiwnth oetiiofifrainSnfc regarding this burden ustimate of any other' aspec of this
colcto f tn~formatlefi. .ncui% g rv getlorn for reducing this bufden. to Washington meadQuarter Service$. Directorate for In'ruMatIOf OPIPIatforfl1 and AePOi'ts. 1215 Jetfer'ionowlis 14.hway. suite 11204. Arunt= i VA2202 4302. and to the Off ice of Manageernet and budget. fPaperwohl i Reduction Protect (0704-0168). WashunqtO'i. DC 20S03.
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4. TITLE AND SUBTITLE 5.U~ 194FUNdreot DING NUJMBERSNormalization and Prediction of Geotechnical Properties Using theCone Penetrometer Test (CPT)
6. AUTHOR(S)
Richard S. Olsen
7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) B. PERFORMING ORGAN4ZATION
U.S. Army Engineer Waterways Experimnent Station REPORT NUMBER
3909 Halls Ferry Road Technical ReportVicksburg, MS 39180-6199 GL-94-29
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U.S. Army Corps of Engineers AGENCY REPORT NUMBER
Washington, DC 20314-1000
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13. ABSTRACT (M-aximum 200 words)
This research was to develop techniques for (1) stress normalization of CPT measurements (andgeotechnical properties) and (2) CPT' prediction of geotechnical properties using cone and sleeve frictionresistance values. Stress normalization allows a variable geotechnical property to be reduced to' an equivalentvalue at a standard confining stress.
A new concept, the Stress Focus, was identified which provides a basis for understanding soil strength asa function of Confining stress. This study demonstrated that sand friction angles for different initial relativedensities converge to a Stress Focus at high confining stress (approximately 100 atm), where the strengthbehavior is similar to that of a sedimentary rock. Dilation of dense sands decreases with increased confiningstress until the Stress Focus is reached, as confirmed using historic high pressure tj xa test data as well withCIPT mneasurement~s from laboratory chamber tests and uniform soil layers. The paths of convergence to theStress Focus are exponentially related to confining stress and are the basis for development of CPT cone andsleeve friction resistance normalization techniques. The overburden stress at the Stress F~ocus is soil typedependent.
(Continued).
14. UBJCT TRMS15. NUMBER Of PAGESSee reverse. - 322
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UNCLASSIFIE.D UNCLASSIFIED I___I__L___NSN 7540-01-280-5500 Standard Form 298 (Rev 2-89)
P,eMrdi,ed by ANSI %Io 139-18
13. (Concluded).
The stress exponent for SPT normalization was shown to be equal to the CPT derived stress exponent.CPT correlations to geotechnical properties were established using both CPT cone resistance and
friction ratio. These correlations were based on a large database which was developed for this researcheffort. Statistical evaluation during the development of these correlations concentrated on excluding biaseddata. CPT based correlations were established for the following geotechnical properties: SPT blow count,unconsolidated undrained triaxial test strength, field vane shear test strength, and shear wave velocity.
14. (Concluded).
Geotechnical properties Stress exponentSand friction angles Stress normalizationSoil strength