Application of the Static Cone Penetration Test

8/11/2019 Application of the Static Cone Penetration Test

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(a) Mechanical adhesion jacket cone (b) Electrical cone tip

Fig.1: Static cone penetrometer device

Interpretation of CPT Data

The development and wide application of the CPT method is mostly due to the fact that the testhas yielded a considerable amount of valuable information needed in the design of foundations.

The results of the CPT have been applied in various ways such as soil classification, thedetermination of physical and mechanical soil properties, the estimation of soil bearing capacity,prediction of soil settlements and the design of shallow and deep foundations. Numerous empiricalmethods and semi-empirical correlations have been developed to estimate geotechnicalparameters from the CPT data for wide ranges of soil types and conditions. The most important ofthese methods and correlations are briefly reviewed here.

Soil Classification and Profil ing

The major application of the CPT is for soil classification and description of soil strata penetratedi.e. soil profiling. Typically, the cone resistance qc is high in sandy soils and low in clayey soils andthe friction ratio Rf is low in sandy soils and high in clayey soils. It has been reported by manyauthors that the basic CPT parameters of cone resistance qc, skin friction fs and friction ratio, R fmay be used for soil classification. The most popular and commonly used soil classificationmethods based on CPT data are probably those proposed by Begemann (1969), Schmertmann(1977), Robertson (1990) and Fellenius and Eslami (2000). The CPT soil classification charts ormethods cannot be expected to provide accurate predictions of soil type based on grain sizedistribution but provide a guide to the mechanical characteristics of the soil, or the soil behavior.These CPT classification methods may prove to be quite useful when applied in some soilsdifferent from those for which they have been developed but differences may well be indicated inother locations because of their empirical nature. It is therefore recommended to examine the


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validity of any system before being used in countries where the experience on the interpretation ofCPT data is not adequate.

Prediction of Some Geotechnical Parameters of Soils

a) Undrained Shear Strength of Cohesive Soils

Various authors suggested formulae based on correlation studies between the cone resistance qcand the undrained shear strength of cohesive soils Sumostly based on the bearing capacity theoryusing the classical Terzaghis equation. All theories result in a relationship between Su and q c ofthe form:

Su = (qc- v)/Nc .. (1)

Nc is the bearing capacity factor, sometimes defined as the cone factor of clay and v is theeffective overburden pressure. Schmertmann (1977) showed that the Ncfactor cannot be imaginedas a simple constant but depends on several factors such as the shape and roughness of the coneand the physical and mechanical soil properties. Due to these factors, the N c values reported inliterature varied over a wide range of 5 to 70 and thus, the use of a certain value for all soils andpenetrometers leads to a serious error. Despite this variation in Nc values, equation (1) may beused by researchers and geotechnical engineers to make their own correlations for N c to matchtheir local clay soils.

b) Standard Penetration Test (SPT)or Relative Density of Cohesionless Soils

The standard penetration test (SPT) is used in many countries as a routine test for estimating therelative density (Dr) of cohesionless soils which measures the compactness of sands and has a

decisive effect on their angle of internal friction, bearing capacity and settlement.According to Robertson and Robertson (2006), despite continued efforts to standardize the SPTprocedure and equipment there are still problems associated with repeatability and reliability.Because of the widespread use of the SPT in the field of foundation engineering, many attemptshave been made to establish the relationship between the dynamic SPT N-value and the staticCPT qc. The first and most popular qc-N correlation was developed by Meyerhof (1956) for fine orsilty, loose to medium dense sand as follows:qc(kg/cm 2) = 4N (blows/30cm) .. (2)

Sanglerat (1972) received test data from various sources in different countries showing thatindiscriminative use of equation (2) without taking into consideration the types of penetrometer

used and soils tested might lead to a serious error. As a result, a more flexible relationship hasbeen proposed in which the Meyerhofs figure of 4 was replaced by a constant n varying widelyfrom 2 to 18 as reported in literature. The variation in n values was mainly attributed to variationsin soil type, equipment and method of testing. Schmertmann (1970) developed the followingcorrelation equation which gives N as a function of qc and the friction ratio R f that may beapplicable in any type of soil:

N (blows/30cm) = (A + B*Rf) qc (kg/cm2) .. (3)Where A and B are constants.


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c) Soil Compressibility Characteristics

The first correlation between soil compressibility and CPT data using the Dutch cone penetrometerwas probably the one proposed by Buisman (1940) for loose sands. Subsequent research workshave indicated that the constant value of 1.5 in his equation must be modified by using a variabledenoted as which depends on the nature of soil tested to be as follows:

C = (q c/ o) .. (4)Where C is a constant of compressibility of the layer being compressed and o is the effectiveoverburden pressure. The constant C is also related to the soil constrained modulus (E s) and theoedometric coefficient of volume change (mv) as follows:C o= E = 1/m v .. (5)

From equations 4 and 5, E and mvmay be related to q cby the equation:

mv = 1/E = 1/ *qc .. (6)

The Buismans method originally developed for cohesionless soils has been extended for cohesivesoils by applying equation (4) and using the relationship between C, void ratio e and thecompression index Cc(C c= 2.3[(1+e)/C] determined by laboratory consolidation testing. Therefore,the compression index Ccmay be related to the cone resistance q cusing the relationships given byequations 3 and 5 as given below:

Cc = [2.3(1+e o) o]/( q c) . (7)

Equation 7 is only valid for normally and underconslidated clays i.e. with ovalues within the linear

portion of the consolidation curve. For over-consolidated clay soils, the equation was modified bysome authors by replacing the initial values of oand e oby the over-consolidation pressure candthe corresponding void ratio ec.Equations 4 through 7 furnish simple mathematical forms that can be verified experimentally bycomparison of the qc measured by the CPT method and C c (or C) and m v determined fromlaboratory compressibility tests. Following this approach, investigations were carried out in differentcountries and several correlation relationships have been developed between soil compressibilityparameters and CPT data for various soil types. However, the results of previous studies indicatethat it is not possible to establish a simple and reliable relationship between CPT data and soilcompressibility. This suggests that the applicability of any of the methods developed in a specificarea to soils from other regions would be questionable.

Applications of CPT Results In addition to using CPT results to estimate geotechnical parameters needed as input in analysis,they may be directly applied to an engineering problem without the need for soil parameters.Typical examples of this approach are the CPT application in predicting bearing capacity andsettlements of shallow and deep foundations and evaluation of compaction control and liquefactionbehavior of soils. Some of these aspects are briefly presented here.

Bearing Capacity and Settlement of Shallow Foundations


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For shallow footings of commonly used dimensions, the net allowable bearing capacity (qa) may beestimated from the following empirical equation based on CPT data (Meyerhof, 1956) for width offooting B>1.22m and settlement of 25.4mm:qa = (qc/25)[(3.28B+1)/(3.28B)] 2 . (8)T he qavalue given by equation (8) may be doubled for raft foundations.

The elastic settlement of granular soils can be estimated by the use of the semi-empirical straininfluence factor proposed by Schmertmann et al (1978). According to this method, the immediateor elastic settlement Scis given by the equation:

Sc=C1C2(q- qo)(Izz/Es) (9)

Where Iz is the strain influence factor, E s is the Youngs modulus of elasticity, z is soil layerthickness, C1is a correction factor for foundation depth, C 2is a correction factor for soil creep, q is

the stress at foundation level and qois the overburden pressure.Several authors (e.g. Schmertmann, 1970) have correlated Es needed for computing the elasticsettlement from equation 8 to the CPT cone penetration resistance qcas follows:

Es= 2q c (10)

Estimation of settlements for shallow foundations resting on clayey soils from CPT results hasbeen studied by some researchers (Sanglerat, 1972). However, the general trend for such cases isto depend mainly on the results of laboratory tests and the conventional settlement computationmethods.

Bearing Capacity of Piled Foundations

The development of the static CPT is strongly connected with its application to the pile foundationdesign for buildings and other structures and several Dutch and Belgian authors have suggestedmethods to estimate pile capacity and embedment as early as 1950. According to the Dutchmethods, the ultimate pile bearing capacity (Qu) is the summation of the base resistance (Qb) andthe pile shaft resistance (Qs) and is given by:

Qu= Q b+Q s = q cA b+f sA s . (11)Where qcis the average cone resistance measured in the CPT and is calculated from the followingequation:

qc = 1/2 (q c1+qc2) .. (12)

qc1 is the average of the envelope of minimum cone resistance above the pile toe over a hight of8D (D= pile diameter) above the largest section of the pile base and qc2is the mean of the averageof the cone resistance below the pile toe over a depth range 0.7D to 4D below toe level and theminimum cone resistance value recorded within this depth range. Ab and A sare the pile base andperipheral areas and fs' is the peripheral shear or skin friction of the pile. According to Sanglerat(1972), the fs'value may be estimated from the CPT cone resistance qc (f s' = qc/200) or from skinfriction fs (f s'= 2fs) measured by the adhesion jacket cone.The application o the Dutch bearing capacity calculation method is restricted to driven piles only.De Beer (1964) concluded that some reduction factor has to be applied to those of driven piles in


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order to determine their ultimate bearing capacity of bored and cast-in-situ piles. He proposed areduction factor frthat may be estimated from the two shear strength parameters c (cohsion) and (angle of internal friction) of mixed soils which is given by the following expression in cohesinlesssoils: fr =qc'/qc= 1 /tan(45+ 2)2 .. (13)

The factor qc' being the cone resistance value to be used for the bearing capacity calculations ofbored piles instead of qcof driven piles.Besides the Dutch and Belgian experience, an important experience has been gained elsewhereand several authors from various countries have reported the value of the CPT method in theprediction of pile bearing capacity for driven and bored reinforced concrete piles. However, fieldtrials to correlate the CPT cone resistance with pile bearing capacity estimated from loading testresults are necessary in any locality where there is no previous experience to establish therelationship between the soil parameters.

CPT METHOD USED AND FIELDS OF APPLICATIONS FOR SOME SUDANESE SOILS

As stated in the previous section, the importance of establishing relationships between the soiltypes and characteristics determined from the conventional testing methods and the static CPT forlocal soils is that some theoretical and empirical solutions of foundation engineering problems arebased on the CPT. This test has proved its reliability in solving quickly and successfully some ofthese foundation problems in the regions where a sufficient experience has been gained in theinterpretation of the CPT results.The static cone penetrometer types used in all studies were mechanically operated deep sounding

machines with rated capacities of 100 and 200 kN. The type of cone regularly used throughout thetesting programs in all studies was the adhesion jacket cone known as Begemans tip shown inFig. 1(a).For the purpose of making good and sound comparisons for the various soil parameters studied,the CPT soundings were made at test points very close to the locations of the conventionalboreholes drilled to obtain soil samples required for testing and the locations of the pile load testsin the studies on the bearing capacity of bored piles. A typical graph showing the variations of CPTresults with depth measured at one site in Khartoum State is shown in Fig. 2. The boreholes weredrilled by a truck mounted Acker rotary rig in all investigated sites using continuous augers foradvancement of borings. Most of the sites investigated in the various previous works are mainlylocated within Khartoum State territory but some areas in other parts of the country were

considered in few studies.


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Fig. 2: Typical chart showing variations of CPT data (qc, fsand R f) with depth

The main research topics covered in the studies undertaken at the BRRI since the time ofimporting the first CPT machine to Sudan in 1977 include the following:

Soil classification and profilingEvaluation of the undrained shear strength of cohesive soilsCorrelation with the Standard penetration test (SPT)Estimation of the compressibility characteristics of fine grained soils, andPrediction of the bearing capacity of bored piles

The main results findings of the research works accomplished so far on the use and application ofthe CPT for prediction and evaluation of the engineering behavior of local soils are presented in thefollowing sections.

USE AND APPLICATION OF CPT METHOD TO CLASSIFY AND EVALUATE THE BEHAVIOROF LOCAL SOILS

Soil Classification and Profiling

On the basis of a comprehensive study, a soil classification method was developed at BRRI byZein (1980) for local soils from analysis of CPT and standard laboratory test results for various soilsamples from Khartoum State and other sites in Jonglei and Upper Nile States in southern Sudan.A detailed description of the developed CPT soil classification method is given elsewhere ( Zeinand Ismail, 1981) but a brief account on the same is outlined here. Zein (1980) analysed a largesize of CPT data points pertaining to soil types that had been tested in the laboratory to determine


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their grain size distribution and consistency characteristics. All the soil samples tested wereclassified using laboratory test results according to the USCS(Unified System for Classifying Soils)scheme and divided into four main groups namely; clays, silty and sandy clays, clayey sands andsilt-sand mixtures, and sands.The cone resistance (qc) and friction ratio (Rf) were obtained by the two mechanical CPT machinesequipped with adhesion jacket cones at the corresponding depths of the soil samples considered inthe analysis. It was noted from plotting of the soil types on a combined qcversus R fgraph that eachsoil group tends to occupy a certain region in the plot, though overlap between the groups canhowever be observed. To enable classification of a soil sample according to the CPT only, thespecific zone occupied by each soil group should be defined.A statistical approach of data analysis known as the discriminant method was used todifferentiate in mathematical terms between the zones corresponding to the four soil groups in theqc-Rfplot. In this method, the term soil population which in this case has the same meaning ofsoil group is used to describe one set of data having similar characteristics. Each soil group has a

certain function known as decriminant function, Xl of which parameters have to be derived fromstatistical analysis of the CPT data that is known for certain to come from that group as describedby Zein (1980).The following descriminant functions were developed for the four soil groups considered in thestudy:

X1= 0.041*q c+ 4.04*R f - 12.6 for clays (n = 82) .. (14a)X2= 0.044*q c+ 3.18*R f - 8.3 for silty and sandy clays (n = 81) .. (14b)X3= 0.070*q c+ 2.50*R f - 7.4 for clayey sands and silt-sand mixtures (n = 93) ... (14c)X4= 0.10*q c+ 1.40*R f - 7.9 for sands (n = 62) .. (14d)

In the above functions the value of qc is in (kg/cm 2) units and Rf in (%) whereas n denotes thesample size used for analysis in each soil group. According to the developed classification method,a soil sample of known cone resistance qcand friction ratio R fbut of uncertain type is allocated tothe nearest population where nearness here is a measure of probability. The nearest populationis that from which a greater likelihood of the sample is coming and therefore the sample should beallocated to whichever population gives the greatest value of X lin equations 14a to 14e.

Zein (2003) introduced major modifications to the formerly developed CPT classification method tomeet the current requirements of research workers and practicing engineers by satisfying thefollowing objectives:

To improve the degree of classification accuracy by including in the analysis the soil test data

from research works and site investigation reports for various engineering projects made availablebetween the years 1980 and 2003.

To consider new grouping of soil types by splitting and rearranging so as to be more specific inthe soil classification.

To develop computer software that simplifies and speeds up the computations involved in theapplication of the analytical procedure; and

To incorporate in the classification method some important information on the degree ofcompactness (relative density) in cohesionless soils and the degree of consistency in cohesivesoils.


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Five main soil groups based on the same terminology of the USCS scheme were considered in the2003 study for the purpose of statistical analysis using the descriminant method for the subsequentclassification of soils using the CPT data only. These were:

a) Clays of high plasticity (CH)b) Clays of low plasticity (CL)c) Silty soils of low to high compressibility (ML and MH)d) Clayey and silty sands (SC and S M), ande) Poorly and well graded clean sands (SP and SW)

The measured CPT data pertaining to these five soil groups were used for the calculations of thestatistical parameters as shown in Table 1.

Table1: Summary of CPT statistical data used as input for analysis

Soil group

Statisticaldata

Clays of

highplasticity(CH)

Clays of

lowplasticity(CL)

Silty soils

(ML or MH)

Clayey or

silty sands

(SC or SM)

Clean Sands

(SP orSW)

Data size 201 152 184 257 134Mean qc( 11) (MN/m2) 4.49 6.10 6.60 10.54 13.69

Variance of qc 1094.48 2639.05 6045.44 6377.16 3596.24Mean R ( 12) (%) 6.10 4.48 4.07 3.50 2.09

The data in Table 1 were subsequently used input for the derivation of the five differentdiscriminant functions corresponding to the different soil groups as follows:

X1= 0.35*q c+ 2.40*R f + 8.31 for CH clays (n = 201) .. (15a)X2= 0.39*q c+ 1.87*R f + 5.39 for CL clays (n = 152) .. (15b)X3= 0.41*q c+ 1.73*R f + 4.86 for ML and MH silts (n = 184) .. (15c)X4= 0.58*q c+ 1.59*R f + 5.87 for SC and SM sands (n = 257) .. (15d)X5= 0.70*q c+ 1.12*R f + 5.99 for SP and SW sands (n = 134) .. (15e)

The units of qcand R fin equations (15a) to (15e) are MN/m 2and % respectively.To classify a soil sample of known qc and R f it should be allocated to the soil group thedescriminant function of which gives the highest numerical value when substituted in equations(14a) through (14e). Important and useful information have been incorporated in the revised and

updated CPT soil classification method to roughly evaluate the degree of consistency and relativedensity in cohesive and cohesionless soils respectively using only the CPT data ( q cand R f). Thewidely accepted correlations developed by Terzaghi and Peck (1948) between the standardpenetration test (SPT) N-value on one hand and the relative density of sandy soils and consistencyof cohesive soils on the other were adopted as basis of comparison along with using an empiricalcorrelation developed for local soils between the SPTs N value and the CPT parameters qcand R f(see Section 3.2.3).Table 2 gives the proposed ranges of qccorresponding to the various degrees of consistency andrelative density developed for local clayey and sandy soils respectively. With this added feature,


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the developed CPT soil classification method may be used not to predict the soil type of local soilsonly but moreover to roughly evaluate some of its physical and engineering properties.

Table 2: Estimation of soil consistency and relative density from CPT data

Clay SoilsEquivalent qcvalues in MN/m2

Sandy and

silty soilsEquivalent qc values inMN/m2

Consistency

N value CH CL Relativedensity

N valueML/MH

SC/SM

SP/ SW

V. Soft < 2 < 1.3 < 1.4 V. Loose < 4 < 1.8 < 1.9 < 2.5

Soft 2 - 4 1.3 - 1.6 1.4- 1.7 Loose 4 to 101.8-2.9

1.9 -3.2

2.5 - 4.6

Medium 4 - 8 1.6- 2.1 1.7- 2.4 Medium 10- 302.9-6.4

3.2 -7.2

4.6 -10.6

Stiff 8 - 15 2.1- 2.9 2.4- 3.6 Dense 30- 506.4-9.4

7.2-10.5

10.6-14.8

V. Stiff 15- 30 2.9 - 4.7 3.6- 6.0 V. Dense > 50 > 9.4 > 10.5 > 14.8

Hard >30 > 4.7 > 6.0

To facilitate a continuous profiling of the soil strata at any CPT point in investigated site, aninteractive computer software was developed by a research student to enable computations of thediscriminant values according to equations (14a) to (14e) for every penetration depth at which theqcand R fvalues are measured (normally every 200mm intervals). The application of this computerprogram enables fast classification of the penetrated soil layers and provides rough evaluation of

their degrees of consistency of clay soils or the relative density of sandy soils based ranges of theqcvalues listed in Table 2.

Undrained Shear Strength of Cohesive Soils

The first study to estimate the undrained shear strength (Su) of Sudanese cohesive soils directlyfrom CPT data was reported by Zein (1980) who tested alluvial silty clay and clayey silt depositslocated near the Blue Nile left bank (Khartoum city side) in Khartoum State. Fifty undisturbed soilsamples mostly representing the CH and MH soil groups were taken at different depths fromboreholes drilled near the CPT soundings where conditions of full and partial saturation existed.Being the most commonly used type of shear strength tests, the undrained unconsolidated (UU)

was adopted in this study to determine the soil shear strength parameters; cohesion cuand angleof internal friction uThe undraind shear strength (S u) was determined from measured cu and uvalues using the following expression:

Su = c u + tan u2[R(1-sin u) +(1+sinu)] (16)R is the ratio of normal failure stress fand the minor principal stress 3.

A statistical regression analysis was carried out to correlate the Su determined according toequation 16 and the average CPT cone resistance qc measured at the corresponding sampledepths to determine the cone factor Nc defined in equation 1.The analysis yielded the following


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relationship between qc and S u, both expressed in kg/cm2, for all soil samples tested with a highcorrelation coefficient (R2= 0.81):

qc = 34.9 S u+ 0.16 . (17)

For practical purposes, the constant of 0.16 can be ignored and Nc is assumed to be 35. Hassan(2004) carried out a research for a larger sample size (187 samples) including those reported inZeins study to investigate the effects of soil type and stress history evaluated in terms of the soilover-consolidation ratio (OCR) factors on the qc-Su relationship. To study the effects of thesefactors on undrained shear strength, the soils tested were divided into two main groups; clay soils(subdivided into CL and CH types) and silty soils (subdivided into ML and MH types). Each soiltype was further divided into three categories; normally or slightly consolidated (OCR


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N of the SPT to enable estimating either soil parameter from available data of the other. In Sudan,the first comparison study was undertaken at BRRI by Zein (1980) and has been updated (Zein,2003) to examine the validity of some published qc-N relationships and to search into thepossibility of developing a sound correlation for Sudanese soils. The CPT soundings wereperformed with the adhesion jacket cone and the SPT was done following the ASTM standardprocedure. The qc and R fwere determined at approximately the same borehole depths were theSPT had been made. The soils in the different sites investigated in 1980 which are located inKhartoum and Jonglei States covered a variety of types including silty, clayey and sandy soildeposits.Since widely different soil types and conditions were considered in the two studies it was deemedimportant to introduce a parameter or index to account for soil variability in order to establish areliable correlation between qc and N. In a previous study on local soils, Zein and Ismail (1981)found that the qc/N ratio is dependent on the soil type indicated by the average Rfvalues of the fourmain soil groups as given in Table 4.

Table 4: Relationship between qc/N ratio and friction ratio R ffor local soils.

Soil type Clays Silty clays andsandy clays

Clayey sands andsand-silt mixtures

Sands

Average R (%) 5.8 4.5 3.5 1.7qc/N ratio > 2.0 2.0-3.0 3.5-4.5 > 5.0

Therefore, the friction ratio Rf of the CPT was chosen as it has been shown in many previousinvestigations to be a good soil type indicator. To study the qc-N relationship more closely, theywere plotted against each other for the soil types of approximately constant Rf values and a linearrelationship was found to exist between the two parameters (Ismail and Zein, 1987). The observed

qc-N relationship trends and the data given in Table 4 indicate that higher q c/N ratio values andlower Rf values correspond to cohesionless soils where their opposites correspond to cohesivesoils.In a more recent study (Zein, 2002), a statistical analysis was carried out on 138 CPT and SPTdata points assuming many mathematical forms to establish the best qc-Rf-N correlationrelationship for local soils and the following empirical polynomial equation was obtained betweenqc and N/Rfratio :qc = 10.3 + 1.6(N/R f) 0.0038(N/Rf)2 with R 2= 0.64 . (18)In this equation, qcis expressed in kg/cm 2units, N in blows/30cm and R fin percent.The suitability of the qc-Rf-N correlation given by equation (18) was examined using data publishedin literature for American soils (Bennet et al, 1979) in which the same CPT and SPT methods were

followed and as a result the following correlation was obtained:qc = -1.23 + 11.56(N/R f) 0.0865(N/Rf)2 with R 2= 0.76 . (19)

This implies the suitability of the mathematical form and soil variables used in equations (18) and(19) for describing the qc-N relationship for soils of different origins.A graphical solution of equation (18) was made as shown in Fig. 3 to enable estimating N directlyfrom known qcvalues or vice versa for soils from known or arbitrarily assumed R fvalues. The R fvalue needed to be substituted in equation (18) is directly taken from CPT data for estimating the Nfrom a known qc value or assumed using the data in Table 4 for the appropriate soil type if q c is tobe estimated from known N value. For using the data in Table 4, one needs either to test or uses


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his judgment and experience to identify the type of soil from the visual inspection of the soil samplerecovered inside the SPT sampler tube.

Fig. 3: Combined qc-Rf-N correlation chart for local soils (Zein, 2002)

Therefore, either the data presented in Table 4, the charts shown in Fig. 3 or the correlationrelationship given by equation (18) can be used to estimate either qcor N if information is available

on the other for local soil types. In this manner, it would be possible to apply the theoretical andempirical solutions of the foundation engineering problems which have been based on the resultsof the CPT and SPT methods.

Soil Compressibility Characteristics

A research study was undertaken by Eltahir (1994) under the supervision of the author on localsoils aiming at investigating the possibility of developing useful correlation between CPT and soilcompressibility characteristics. An experimental testing program was performed on 76 undisturbedsoil samples representing clayey soils (CL and CH types), silty soils (ML and MH types) and sandysoils (SC and SM types) obtained from different sites located in four different Sudanese states;

Khartoum, Northern and southern Kurdofan and White Nile. The CPT was made at points locatedadjacent to the boreholes from which the soil samples had been taken. Consolidation tests wereperformed in the laboratory following the BS1377(1990) procedure on soil samples soaked tosaturate and the compression index Cc and coefficient of volume compressibility m v weredetermined from the results of these tests for each sample. The CPT data (q c and R f) were alsodetermined at the borehole depths corresponding to those from which the soil samples werecollected. Further details on this study were published by Zein and El Tahir (2002) but the mainfindings and conclusions of the study are presented here.Because no particular trend was observed in the relationship between q c and C c when all thesamples were considered in analysis, it was decided to divide the samples of soil types tested into


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plastic and nonplastic soil groups. The plastic group included the clay soils where the non-plasticgroup included the silty and sandy soils. The least square regression method was used to establishthe relationship between Cc and qcfor each soil group and the highest correlation coefficients (R 2=0.52 to 0.53) were given by the following two equations for clays and silty and sandy soil typesrespectively:

Cc= 0.001q c2 0.03q c+ 0.38 . (20a)Cc = 0.002q c2 0.05q c+ 0.47 .. (20b)

It was noticed that the degree of data scatter was significant in the qc-C crelationships representedby the above two equations and therefore a new parameter was introduced to reflect the effect ofsoil type in an attempt to improve the correlation and thus the accuracy of the Cc-qcrelationships.After several trials of data analysis, it was found that the best correlations would be obtained byusing the plasticity index, PI, and the fines content FC (soil fraction passing No. 200 test sieve), asindicative indices for the clay and silty-sandy soil samples respectively. The following correlation

equations were derived upon introducing the PI and FC indices, to describe the Cc versus q crelationships for the clays and the silty and sandy soils respectively:

Cc = 1/PI [0.007 q c2+ 0.28 qc+2.19] . (21a)Cc = 1/FC [0.25 q c2- 6.67 qc+48.2] . (21b)

The qc values in equations (20) and (21) are expressed in MN/m2 and the PI and FC are inpercent.The coefficient of volume compressibility mv (m 2/MN) and constrained modulus Es (MN/m 2) werealso related to qc for an assumed consolidation pressure increment from 100 to 200kN throughevaluation of the coefficient (defined in equation 6) to the soil friction ratio R f (%) as given below:

= 0.032R f1.74 for clay soils (R2= 0.61) (22a) = 0.032R f2- 5.8 R f + 2.77 for silty and sandy soils (R 2= 0.56) .. (22b)

Thus in order to estimate Es or m vfrom known q cand R f, the coefficient is firstly obtained fromequations (22a) or (22b) and then the values of and q care substituted in equation 6 for the soiltype under consideration.

Prediction of Bearing Capacity of Bored Piles

The application of the CPT to predict the bearing capacity of piles in Sudan was limited to the caseof bored or drilled shaft piles, being the foundation system that has received wide acceptance by

local foundation design and contracting engineers and executed during the construction of severalengineering projects. Two different research studies have been carried out at BRRI to assess thereliability of some published CPT based methods proposed for predicting the bearing capacity ofbored piles developed in other countries for local soils.The first study was made at the site of Gerief-Manshia bridge on the Blue Nile in Khartoum State inwhich a 1.50m diameter and 21.5m long bored pile was constructed and tested by a slowmaintained load method. One deep borehole and one CPT were made close to pile test location todetermine the types and characteristics of soil strata and CPT data. The soil profile waspredominantly comprised of alluvial silt and sand deposits resting on highly to moderatelyweathered Nubian sandstone or mudstone formations. A comparison was made between the pilesbearing capacity estimated from the pile load test results as well as the results of testing soil


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samples using two empirical methods and that predicted according to three methods based on theCPT data, namely the methods developed by Schmertmann (1977), the Dutch Engineers(Sanglerat, 1972) and Meyerhof (1956) and one empirical method by Touma and Reese (1974).The Chins method (1970) was adopted to evaluate the bearing capacity from the pile load testdata. A summary of the results of comparison of the pile bearing capacity end bearing and skinfriction predicted according to the different methods considered in this study is given inTable 5. Asmay be noted in Table 5, there is a good comparison of the total bearing capacity of the bored pileestimated according to the five different methods. Taking Chins method as a basis for comparisonthe discrepancy in the predicted total bearing capacity was -15.7 to 23.6%. However, somedifferences were noted in comparing the pile end bearing and pile skin friction components of thepile capacity calculated according to the five different methods. An exception is the methodproposed by Touma and Reese which compared favorably with Chins method for both pile bearingcapacity components while the method by Schmertmann gave a good comparison with Chinsmethod for estimating the pile skin friction only.

Table 5: Comparison of bearing capacity values predicted according to CPT and other methods fora bored pile foundation.

Pile capacitypredictionmethod

Ultimate pileskin friction

Ultimate pileend bearing

Allowable pilebearing capacity

Discrepancy (%)based on Chinsmethod Qallvalue

Qs(tons) Qb(tons) Qall(tons)

Meyerhof 149.3 133.5 494.6 -6.9

Touma and Reese 777.9 565.5 447.8 -15.7

Schmertmann 816.2 1153.6 656.6 23.6

Dutch 230.6 1159.2 463.3 -12.8Chin 929.9 664.1 531.3 -

In a recent study (Babikir, 2006), a research work which involved drilling borehole, performing CPTsoundings and carrying out pile load tests was undertaken under the authors supervision tocompare the bearing capacity values estimated according to different approaches for eight boredpiles of variable lengths and diameters at five different sites located in Khartoum State. Thebearing capacity results were obtained for the tested piles according to five different predictionmethods including two based on CPT data (Bustamante and Gianeselli, 1982 and Aoki and DeAlencer, 1975), two based on interpretation of pile load test results (De Beer, 1964 ,Chin 1970)and Meyerhofs method. However, the results obtained from this study indicated that the bearing

capacity values predicted according to the five different methods considered were inconsistent andsignificantly different for practically all the piles tested. Based on the findings of this study, none ofthe two methods based on the CPT was reliable in estimating the bearing capacity of bored pilesconstructed in local soils. The differences in pile bearing capacity prediction may be attributed toseveral factors, the most important of which is the scale effects, the characteristics of the soils atthe investigated site and the procedure used to determine the pile load capacity from the load test.Despite these differences, the CPT is still believed to give the closest simulation to a pilefoundation system. Superiority of the CPT methods over non CPT methods has been confirmed bysome authors (as cited by Robertson and Robertson, 2006).In this respect, a study has recently been started at BRRI to search into developing a sound CPTbased method that can be used for estimating the bearing capacity of bored piles with acceptable


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iii. Successful applications of the CPT method has been considered in some geotechnicaldesign and research oriented works on local soils for the provision of information and parametersrequired for the foundation design to:

a) Facilitate a continuous profiling of the soil strata at any CPT point in any investigatedsite, using an interactive computer software based on the developed soil classificationmethod described in section 3.2.1 for every penetration depth at which the qc and R fvalues are measured. The application of this computer program enables fastclassification of the penetrated soil layers and provides rough evaluation of their degreesof consistency and relative density of clayey and sandy soils respectively.b) Predict the bearing capacity of bored piles drilled at various lengths through thedepths of local soil strata. This foundation system has received wide acceptance byfoundation designers and has been used for the construction of the superstructures forseveral large engineering projects in Sudan.

ACKNOWLEDGEMENT

The author acknowledges with gratitude the assistance offered to him by the former and presentM.Sc. students at BRRI Asher Rifaat,Mostafa Hasan, Haitham A. Babikir and Samah B.Mohammed for collection some of the data used for analysis in this study and Hisham Osman, forthe preparation of computer program.

REFERENCES

Aoki, N. and De Alencer, D. (1975). An approximate method to estimate the bearing capacity ofpiles. Proc. 5thPan-American Conf. on SMFE, Buenos Aires, Vol. 1, pp. 367-376.

Babikir H.A. (2006). Unpublished M.Sc. Thesis, BRRI.Begemann H.K.S. (1969). The Dutch static penetration test with the adhesion jacket cone.Lab. Groundmech., Delft, Netherlands, 13(10): 1-86.Bennet M.J., Youd T.L., Harp E.L. and Wieczorek G.F. (1979). Subsurface investigation forliquefaction, Imperial Valley Earthquake. Calif. US Geological Survey Report 81-502.BuismanA.S.K. (1940). Gronndmechanica, Waltman, Delft.Bustamante, M. and Gianeselli, L. (1982). Pile bearing capacity prediction by means of static conepenetrometer CPT. Proc. 2nd European Symposium on Penetration Testing, ESOPT-II,Amsterdam, Vol. 2: 493-500.Chin, F.K. (1970). Estimation of the ultimate load of piles not carried to failure. Proc. 2 ndSoutheastAsian Conf. on Soil Engineering, Singapore, : 81-90.

De Beer, E.E. (1964). Some considerations concerning the point bearing capacity of bored piles.Proc. Symp. On Bearing Capacity, Roorkee, India, Vol. 1, p.178.El Tahir M.M. (1994). Use of the static cone penetration data for the prediction of compressibilitycharacteristics for some local soils. Unpublished M.Sc. Thesis, BRRI, Univ. of Khartoum.Fellenius, B. H. and Eslami, A. (2000). Soil Profile interpreted from CPTu data. Proc. Year 2000Geotechnics Geotchnical Engineering Conference, Asian Institute of Technology, Bangkok, 18p.Hassan M.A. (2004). Evaluation of undrained shear strength from CPT data for local fine grainedsoils. Unpublished M.Sc.Thesis, BRRI, Univ. of KhartoumHolden, J. (1974). Penetration testing in Australia. Proc. European Symp. On Penetration Testing,Stockholm, Vol. 1: 155-162.


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Ismail H.A.E. and Zein A.K.M (1987). Prediction of the undrained shear strength and standardpenetration test using the static cone penetration test data. Proc. 9 th Africa Regional Conf. onSMFE, Lagos: 185-192.Meyerhof G.G. (1956). Penetration tests and bearing capacity of cohesionless soils. ASCE, J.SMFE Division, Vol. 82, SM1: 1-12.Mohammed S.B. (2009) Personal contact.Robertson P.K. and Robertson K.L. (2006). Guide to cone penetration testing and its application togeotechnical engineering. Gregg Drilling and Testing Incl. Report, July 2006.Robertson, P.K. (1990). Soil classification using the cone penetration test. CanadianGeotechnical Journal, Vol. 3, No. 1: 151-158.Sanglerat G.G.J. (1972). The penetrometer and soil exploration. Development in GeotechnicalEngineering. Elsevier Publishing Co., Amsterdam.Schmertmann J.H., Hartman J.P. and Brown, P.R. (1978). Improved strain influence factordiagrams. Proc. ASCE, J. GE Division, Vol. 104, GT8: 1131-1135.

Schmertmann, J.H. (1970). The importance of side friction and lateral stresses to the SPT N value.Proc. 4thPan-American Conf. on SMFE, Puerto Rico.Schmertmann, J.H. (1977). Guidelines for CPT performance and design. Report prepared forFedral Highway Administration, Washington D.C.Terzaghi K. and Peck R.B. (1948). Soil Mechanics in Engineering Practice. J. Wiley and Sons,Inc., NY.Touma, F.T. and Reese L.C. (1974). Behavior of bored piles in sand. Proc. ASCE, J. GE Division,Vol. 100, GT7:749-761.Zein A.K.M. (2002). Development and evaluation of some empirical methods of correlationbetween CPT and SPT. BRR Journal, Vol. 4: 16-28Zein A.K.M. and El Tahir M.M. (2002). Prediction of compressibility of some Sudanese soils using

cone penetration test method. Proc. Geotechnical and Geo-environmental Engineering in AridLands. Alawaji(ed): 121-126.Zein, A. K. M. (1980). Correlation between static cone penetration and recognized standardtest results for some local soils. M.Sc. Thesis, Civil Eng. Dept., U. of K.Zein, A. K. M. (2002). Development and evaluation of some empirical methods of correlationbetween CPT and SPT. BRR Journal, Vol. 4: 16-28.Zein, A.K.M. (2003). Use of cone penetration test for classification of local soils. BRR Journal, Vol.5: 23-29.Zein, A.K.M., and Ismail, H.A.E. (1981). Use of static cone penetration test for soilclassification. BRRI Current Paper Publication CP1/81.

Documents

Application of the Static Cone Penetration Test