Site characterization model using least‐square support vector machine and relevance vector machine based on corrected SPT data (Nc)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N_c), N values have been corrected (N_c) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three‐dimensional site characterization model, the function N_c=N_c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N_c value, is to be approximated in which N_c value at any half‐space point in Bangalore can be determined. The first algorithm uses least‐square support vector machine (LSSVM), which is related to a ridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel‐based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright © 2009 John Wiley & Sons, Ltd.     

Treatment of Loose to Medium Dense Sands by Granular Piles: Improved SPT ‘N<Subscript>1</Subscript>’ Values

The effect of granular pile installation on the modifications induced in loose to medium dense granular deposits is studied. SPT is the most often used to evaluate the in situ soil properties. Expressions for modified SPT N₁ values for different soils, i.e., for different initial SPT N₁ values, were determined as functions of replacement ratio from the available field data. Improvements in the ground are presented in the form of modified or improved SPT N₁ values versus replacement ratio charts, which can then be used to design the required degree of treatment for the expected improvement or to estimate the improved values of treated ground for different initial states of sands.     

Prediction of pressuremeter modulus and limit pressure of clayey soils by simple and non-linear multiple regression techniques: a case study from Mersin, Turkey

The Standard Penetration Test (SPT) is one of the most frequently applied tests during the geotechnical investigation of soils. Due to its usefulness, the development of empirical equations to predict mechanical and compressibility of soil parameters from the SPT blow count has been an attractive subject for geotechnical engineers and engineering geologists. The purpose of this study is to perform regression analyses between the SPT blow counts and the pressuremeter test parameters obtained from a geotechnical investigation performed in a Mersin (Turkey) city sewerage project. In accordance with this purpose, new empirical equations between pressuremeter modulus (E _M) and corrected SPT blow counts (N ₆₀) and between limit pressure (P _L) and corrected SPT blow counts (N ₆₀) are developed in the study. When developing the empirical equations, in addition to the SPT blow counts, the role of moisture content and the plasticity index of soils on the pressuremeter parameters are also assessed. A series of simple and nonlinear multiple regression analyses are performed. As a result of the analyses, several empirical equations are developed. It is shown that the empirical equations between N ₆₀ and E _M, and N ₆₀ and P _L developed in this study are statistically acceptable. An assessment of the prediction performances of some existing empirical equations, depending on the new data, is also performed in the study. However, the prediction equations proposed in this study and the previous studies are developed using a limited number of data. For this reason, a cross-check should be applied before using these empirical equations for design purposes.     

Predicting standard penetration test N-value from cone penetration test data using artificial neural networks

Standard Penetration Test(SPT) and Cone Penetration Test(CPT) are the most frequently used field tests to estimate soil parameters for geotechnical analysis and design.Numerous soil parameters are related to the SPT N-value.In contrast,CPT is becoming more popular for site investigation and geotechnical design.Correlation of CPT data with SPT N-value is very beneficial since most of the field parameters are related to SPT N-values.A back-propagation artificial neural network(ANN) model was developed to predict the N6o-value from CPT data.Data used in this study consisted of 109 CPT-SPT pairs for sand,sandy silt,and silty sand soils.The ANN model input variables are:CPT tip resistance(q_c),effective vertical stress(σ'_v),and CPT sleeve friction(f_s).A different set of SPT-CPT data was used to check the reliability of the developed ANN model.It was shown that ANN model either under-predicted the N_(60)-value by 7-16%or over-predicted it by 7-20%.It is concluded that back-propagation neural networks is a good tool to predict N_(60)-value from CPT data with acceptable accuracy.     

Side-by-Side Correlation of Texas Cone Penetration and Standard Penetration Test Blowcount Values

This paper presents side-by-side comparisons of blowcount values for the Texas cone penetration (TCP) test and the standard penetration test (SPT). The comparisons yielded statistically-significant regression models for both coarse-grained soils and fine-grained soils. Consistent with expected trends and published data, the TCP–SPT relationship is nonlinear, with weak to fair correlation strength (R² = 23–44%). For TCP blowcounts (N_{60, TCP}) varying from 25 to 200 blows/30 cm (1 ft), corresponding SPT blowcounts (N_{60, SPT}) are typically 30–60% lower than N_{60, TCP} in fine-grained soils. Likewise, corresponding N_{60, SPT} blowcounts are 10–70% lower than N_{60, TCP} in coarse-grained soils, all other things being equal. Comparative data were obtained from published sources and from project-specific field research sites used for full-scale deep foundation load tests. The final dataset consisted of 225 test pairs obtained in similar soils and geomaterials, at equivalent depths, with all blowcounts normalized to 30 cm (12 in.) penetration (i.e., blows/30 cm or blows/ft) within the bounds of typical test precision, and corrected to 60% hammer efficiency. The generally weak correlations do not support conversion of N_{60, TCP} to N_{60, SPT} (or vice versa) to compute foundation capacity for final design. But, engineers can certainly get an intuitive feel about site conditions and preliminary foundation capacity by using the correlation equations to translate their knowledge of one test to the other. This study extends previous work by formally comparing and contrasting the similar yet different SPT and TCP test methods in such a way as to make the results useful to users of both tests and to the broader geotechnical engineering community.     

Variations in shear wave velocity and soil site class in Kolkata city using regression and sensitivity analysis

The detrimental effects of an earthquake are strongly influenced by the response of soils subjected to dynamic loading. The behavior of soils under dynamic loading is governed by the dynamic soil properties such as shear wave velocity, damping characteristics and shear modulus. Worldwide, it is a common practice to obtain shear wave velocity (V _s in m/s) using the correlation with field standard penetration test (SPT) N values in the absence of sophisticated dynamic field test data. In this paper, a similar but modified advanced approach has been proposed for a major metro city of eastern India, i.e., Kolkata city (latitudes 22°20′N–23°00′N and longitudes 88°04′E–88°33′E), to obtain shear wave velocity profile and soil site classification using regression and sensitivity analyses. Extensive geotechnical borehole data from 434 boreholes located across 75 sites in the city area of 185 km² and laboratory test data providing information on the thickness of subsoil strata, SPT N values, consistency indices and percentage of fines are collected and analyzed thoroughly. A correlation between shear wave velocity (V _s) and SPT N value for various soil profiles of Kolkata city has been established by using power model of nonlinear regression analysis and compared with existing correlations for other Indian cities. The present correlations, having regression coefficients (R ²) in excess of 0.96, indicated good prediction capability. Sensitivity analysis predicts that significant influence of soil type exists in determining V _s values, for example, typical silty sand shows 30.4 % increase in magnitude of V _s as compared to silt of Kolkata city. Moreover, the soil site classification shows Class D and Class E category of soil that exists typically in Kolkata city as per NEHRP (Recommended provisions for seismic regulations for new buildings and other structures—Part 1: Provisions. Prepared by the Building Seismic Safety Council for the Federal Emergency Management Agency (Report FEMA 450), Washington, DC, 2003) guidelines and thereby highlighting the seismic vulnerability of the city. The results presented in this study can be utilized for seismic microzonation, ground response analysis and hazard assessment for Kolkata city.

     

Estimating Menard pressuremeter modulus and limit pressure from SPT in silty sand and silty clay soils. A case study in Mashhad,Iran

The Menard pressuremeter test is a relatively expensive in situ test, which generates useful information about the strength and deformation properties of any soil and weak rock, which is carried out in some projects. On the other hand, the SPT test is a rather inexpensive, simple and typical in situ test used to determine the engineering properties of silt, clay, sand, and fine gravel which is utilised in almost all projects.

In this study SPT blow counts (N₆₀) were correlated with pressuremeter modulus (E_PMT) and limit pressure (P_L) and empirical equations were proposed to estimate P_L and E_PMT from N₆₀ in silty sand and silty clay soils separately. These tests have been conducted during subway geotechnical investigation in Mashhad, Iran.

Moreover, in order to verify these empirical equations, they were compared with similar equations that have been proposed by other researchers. These comparisons display that in all equations a linear relationship exists between N₆₀ - E_PMT and N₆₀ - P_L. However, the line slopes are different so it can be concluded the line slopes are related to soil type and geological condition of an area. Thus, for each area a separate empirical equation must be presented.     

Simplified DMT-based methods for evaluating liquefaction resistance of soils

This paper presents simplified dilatometer test (DMT)-based methods for evaluation of liquefaction resistance of soils, which is expressed in terms of cyclic resistance ratio (CRR). Two DMT parameters, horizontal stress index (K_D) and dilatometer modulus (E_D), are used as an index for assessing liquefaction resistance of soils. Specifically, CRR–K_D and CRR–E_D boundary curves are established based on the existing boundary curves that have already been developed based on standard penetration test (SPT) and cone penetration test (CPT). One key element in the development of CRR–K_D and CRR–E_D boundary curves is the correlations between K_D (or E_D) and the blow count (N) in the SPT or cone tip resistance (q_c) from the CPT. In this study, these correlations are established through regression analysis of the test results of SPT, CPT, and DMT conducted side-by-side at each of five sites selected. The validity of the developed CRR–K_D and CRR–E_D curves for evaluating liquefaction resistance is examined with published liquefaction case histories. The results of the study show that the developed DMT-based models are quite promising as a tool for evaluating liquefaction resistance of soils.     

Probabilistic evaluation of seismic soil liquefaction potential based on SPT data

The performance-based liquefaction potential analysis was carried out in the present study to estimate the liquefaction return period for Bangalore, India, through a probabilistic approach. In this approach, the entire range of peak ground acceleration (PGA) and earthquake magnitudes was used in the evaluation of liquefaction return period. The seismic hazard analysis for the study area was done using probabilistic approach to evaluate the peak horizontal acceleration at bed rock level. Based on the results of the multichannel analysis of surface wave, it was found that the study area belonged to site class D. The PGA values for the study area were evaluated for site class D by considering the local site effects. The soil resistance for the study area was characterized using the standard penetration test (SPT) values obtained from 450 boreholes. These SPT data along with the PGA values obtained from the probabilistic seismic hazard analysis were used to evaluate the liquefaction return period for the study area. The contour plot showing the spatial variation of factor of safety against liquefaction and the corrected SPT values required for preventing liquefaction for a return period of 475 years at depths of 3 and 6 m are presented in this paper. The entire process of liquefaction potential evaluation, starting from collection of earthquake data, identifying the seismic sources, evaluation of seismic hazard and the assessment of liquefaction return period were carried out, and the entire analysis was done based on the probabilistic approach.     

Determination of undrained strength of fine-grained soils by means of SPT and its application in Turkey

The Standard Penetration Test (SPT) is one of the oldest and the most common in situ test used in soil explorations. In the recent years with the advent of new technology and techniques in determining the drawbacks in SPT, several researchers have attempted to correlate corrected field measured values with several soil properties. In this context, corrections applied to field values have become critical. In this study a questionnaire including the performance of the standard penetration test and equipment used in practice in Turkey is circulated in order to determine the relevant correction factors. Thus the appropriate corrections are used in acquiring corrected SPT-N values. The relationships between SPT-N and the undrained shear strength (S_u) are examined from the statistical point of view by taking the test types and SPT corrections into consideration, and comparison is made with previous studies. It is observed that SPT corrections play an important role on the obtained correlation equations. In addition, the importance of the effects of test types on the correlations is also emphasized. The Standard Penetration Test is found to be sufficient for reliable assessment of S_u.     

Use of Surface Waves in Statistical Correlations of Shear Wave Velocity and Penetration Resistance of Chennai Soils

Shear wave velocity (V _s) is one of the most important input parameter to represent the stiffness of the soil layers. It is preferable to measure V _s by in situ wave propagation tests, however it is often not economically feasible to perform the tests at all locations. Hence, a reliable correlation between V _s and standard penetration test blow counts (SPT-N) would be a considerable advantage. This paper presents the development of empirical correlations between V _s and SPT-N value for different categories of soil in Chennai city characterized by complex variation of soil conditions. The extensive shear wave velocity measurement was carried out using Multichannel Analysis of Surface Waves (MASW) technique at the sites where the SPT-N values are available. The bender element test is performed to compare the field MASW test results for clayey soils. The correlations between shear wave velocity and SPT-N with and without energy corrections were developed for three categories of soil: all soils, sand and clay. The proposed correlations between uncorrected and energy corrected SPT-N were compared with regression equations proposed by various other investigators and found that the developed correlations exhibit good prediction performance. The proposed uncorrected and energy corrected SPT-N relationships show a slight variation in the statistical analysis indicating that both the uncorrected and energy corrected correlations can predict shear wave velocity with equal accuracy. It is also found that the soil type has a little effect on these correlations below SPT-N value of about 10.     

Estimating the number of casualties in earthquakes from early field reports and improving the estimate with time

We investigate the time dependence of the number of deaths reported through Internet after earthquakes and/or earthquake-generated tsunami. An approximate relation N(t) = N ₀ [1 − exp(−αt)] is used to describe such temporal variation, in which N(t) is the number of deaths reported at time t, N ₀ is the final number of deaths, and α is the coefficient reflecting the rescue process. We considered 12 earthquake cases since 2001 using the information from the web, which shows that the N-t relation approximates the data, and the logarithm of α is reversely proportional to the magnitude of earthquake, albeit with significant uncertainties. Quick and rough estimate of the final death toll can be made using this simple and approximate relation, with the empirical α-M relation as a reference. For the 12 cases under consideration, quick and rough estimate of fatalities can be obtained 2 days after the earthquake, fitting the real situation in the order of magnitudes. Although being very rough, this estimate can assist the emergency decision-making and can be revised as time lapses. When more and more data becomes available, curve fitting can provide both N ₀ and α at the same time. The method is tested against the data of the recent Yushu earthquake on April 14, 2010.     

Seismic reliability-based analysis and GIS mapping of cyclic mobility of clayey soils of Mumbai city,India

Cyclic mobility is a mechanism of ground failure due to lateral spreading of soils during an earthquake that usually occurs in soft or medium stiff saturated soils. The simplified procedures developed by the researchers give a factor of safety for judging the cyclic mobility potential. However, the simplified procedures do not take into account the uncertainty in the parameters required to estimate the cyclic stresses in the soil. In this study, a reliability framework based on the simplified procedure, considering the parameter uncertainty, has been proposed for computing the probability of cyclic mobility of clay deposits for a metro city of India, i.e., Mumbai city (latitudes 18°53′N–19°19′N and longitudes 72°47′E–72°58′E). Extensive geotechnical borehole data from 1028 boreholes across 50 locations in the city area of 390 km² and laboratory test data are collected and analyzed thoroughly. A correlation between undrained shear strength (Su) and other parameters such as natural water content (w), SPT N value, liquid limit (LL) and plasticity index (PI) has been established for Mumbai city and has been used in the proposed approach. The sensitivity analysis of the proposed approach predicts that Su has significant influence in the evaluation of the cyclic mobility. Cyclic mobility hazard maps are prepared using the geo-statistical analysis tool in GIS, and it shows that the clayey soils at few locations have a 60–90 % probability of cyclic mobility for a moment magnitude (M _w) of an earthquake of 7.5. These hazard maps can be used by the geotechnical engineers for the cyclic mobility hazard assessment of Mumbai city.     

Applications of a GIS-based geotechnical tool to assess spatial earthquake hazards in an urban area

A geotechnical information system (GTIS) was constructed within a spatial geographic information system (GIS) framework to reliably predict geotechnical information and accurately estimate site effects at Gyeongju, an urban area in South Korea. The system was built based on both collected and performed site investigation data in addition to acquired geo-knowledge data. Seismic zoning maps were constructed using the site period (T _G) and mean shear wave velocity to a depth of 30 m (V _S30), and these maps were presented as a regional strategy to mitigate earthquake-induced risks in the study area. In particular, the T _G distribution map indicated the susceptibility to ground motion resonance in periods ranging from 0.2 to 0.5 s and the corresponding seismic vulnerability of buildings with two to five stories. Seismic zonation of site classification according to V _S30 values was also performed to determine the site amplification coefficients for seismic design and seismic performance evaluation at any site and administrative subunit in the study area. In addition, we investigated the site effects according to subsurface and surface ground irregularities at Gyeongju by seismic response analyses in time domains based on both two- and three-dimensional spatial finite element models, which were generated using spatial interface coordinates between geotechnical subsurface layers predicted by the GTIS. This practical study verified that spatial GIS-based geotechnical information can be a very useful resource in determining how to best mitigate seismic hazards, particularly in urban areas.     

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.     

Property Correlations and Statistical Variations in the Geotechnical Properties of (CH) Clay Soils

This study was focused on the correlations between the physical and mechanical properties and geostatistical analysis of the clay of high plasticity (CH) soil based on the experimental data and the data collected from various research studies. Four types of CH soil with liquid limit (LL) of 50, 62, 76 and 88% were collected from the field, tested, compared with the data from literature and qualified using hyperbolic model. X-ray diffraction analyses showed the major constituents of the CH soil with LL of 50% were calcium silicate (Ca₂SiO₄), aluminum silicate (Al₂SiO₅) and quartz (SiO₂) and the major constituents of the CH soil with LL of 88% were montmorillonite (Na, Ca) _0.33(Al, Mg) ₂(Si₄O₁₀) (OH)₂·nH₂O, kaolinite (Al₂Si₂O₅(OH)₄) and quartz (SiO₂). The index properties, compacted properties, free swelling and compressive strength of the CH soils were investigated and quantified with over 1000 data collected from the literature. Using the mean (μ), standard deviation (σ), variation (σ²) and coefficient of variation parameters of CH soils properties such as density (γ), index properties (LL and PL), compaction properties (OMC and γ_dmax), swelling index (FS), initial void ratio (e_o), compression index (Cc) and undrained shear strength (S_u) properties were also studied. Liquid limit of CH soils varied between 50 and 110% and plasticity index varied between 26 and 72%. The wet unit weight (γ_wet) for the CH soils varied from 1.30 to 2.19 g/cm³. Undrained shear strength (S_u) of CH soils were varied from 10 to 184 kPa and quantified very well as a function of liquid limit, plasticity index, moisture content and dry density using the experimental data and data collected from the literature.     

Geospatial contour mapping of shear wave velocity for Mumbai city

Shear wave velocity is one of the most important input parameter in the analysis of geotechnical earthquake engineering problems, particularly to estimate site-specific amplification factor and ground response study. Dynamic in situ tests such as spectral analysis of surface waves (SASW) or multichannel analysis of surface waves (MASW) are very expensive. Also due to lack of specialized personnel, these tests are generally avoided in many soil investigation programs. Worldwide, several researchers have developed correlations between the SPT ‘N’ value and shear wave velocity ‘V _s’, which are useful for determining the dynamic soil properties. In the present study, more than 400 numbers of soil borehole data were collected from various geotechnical investigation agencies, government engineering institutes and geotechnical laboratories from different parts of Mumbai city, which is financial capital of India with highest population density. In this paper, an attempt has been made to develop the correlation between the SPT ‘N’ value and shear wave velocity ‘V _s’ for various soil profile of Mumbai city and compared with other existing correlations for different cities in India. Using Geographical Information System (GIS), a geospatial contour map of shear wave velocity profile for Mumbai city is prepared with contour intervals of 25 and 50 m/s. The scarcity of database or maps of shear wave velocity profile for Mumbai city will make the present geospatial contour maps extremely useful and beneficial to the designer, practitioners for seismic hazard study involved in geotechnical earthquake engineering.     

Liquefaction Hazard Assessment of Earth Quake Prone Area: a Study Based on Shear Wave Velocity by Multichannel Analysis of Surface Waves (MASW)

The shear wave velocity (V_S) profile based on the dispersive characteristics of fundamental mode of Rayleigh type surface waves indicate underground stiffness change with depth as well as near surface stiffness. The most important utility of shear wave velocity (V_S) is to estimate the liquefaction hazard potential of an area particularly in seismically active region. Rayleigh type surface waves were utilized to estimate the velocity (V_S) of shallow subsurface covering a depth range of 30–50 m employing multichannel analysis of surface waves. The liquefaction hazard map predicts an approximate percentage of an area that will have surface manifestation of liquefaction during an earth quake. The surface wave data acquired in an earth quake prone region of Jabalpur (Seismic zone III), India, yields a velocity (V_S) range of 200–750 m/s corresponding to the subsurface depth of 30–35 m. The results were analyzed for possible liquefaction hazard in the study area and presented here besides the N values.     

Bearing capacity of strip foundations reinforced with geogrid sheets by using upper bound finite‐element limit analysis

By using the upper bound finite‐elements limit analysis, with an inclusion of single and two horizontal layers of reinforcements, the ultimate bearing capacity has been computed for a rigid strip footing placed over (i) fully granular, (ii) cohesive‐frictional, and (iii) fully cohesive soils. It is assumed that (i) the reinforcements are structurally strong so that no axial tension failure can occur, (ii) the reinforcement sheets have negligible resistance to bending, and (iii) the shear failure can take place between the reinforcement and soil mass. It is expected that the different approximations on which the analysis has been based would generally remain applicable for reinforcements in the form of geogrid sheets. A method has been proposed to incorporate the effect of the reinforcement in the analysis. The efficiency factors, η_c and η_γ, to be multiplied with N_c and N_γ , for finding the bearing capacity of reinforced foundations, have been established. The results have been obtained (i) for different values of ? in case of fully granular and cohesive‐frictional soils, and (ii) for different rates at which the cohesion increases with depth for a fully cohesive soil. The optimum positions of the reinforcements' layers have also been determined. The effect of the reinforcements' length on the results has also been analyzed. As compared to cohesive soils, the granular soils, especially with higher values of ?, cause a much greater increase in the bearing capacity. The results compare reasonably well with the available theoretical and experimental data from literature. Copyright © 2013 John Wiley & Sons, Ltd.     

A performance-based framework for assessing liquefaction potential based on CPT data

This article describes a new performance-based approach for evaluating the return period of seismic soil liquefaction based on standard penetration test (SPT) and cone penetration test (CPT) data. The conventional liquefaction evaluation methods consider a single acceleration level and magnitude and these approaches fail to take into account the uncertainty in earthquake loading. The seismic hazard analysis based on the probabilistic method clearly shows that a particular acceleration value is being contributed by different magnitudes with varying probability. In the new method presented in this article, the entire range of ground shaking and the entire range of earthquake magnitude are considered and the liquefaction return period is evaluated based on the SPT and CPT data. This article explains the performance-based methodology for the liquefaction analysis – starting from probabilistic seismic hazard analysis (PSHA) for the evaluation of seismic hazard and the performance-based method to evaluate the liquefaction return period. A case study has been done for Bangalore, India, based on SPT data and converted CPT values. The comparison of results obtained from both the methods have been presented. In an area of 220 km² in Bangalore city, the site class was assessed based on large number of borehole data and 58 Multi-channel analysis of surface wave survey. Using the site class and peak acceleration at rock depth from PSHA, the peak ground acceleration at the ground surface was estimated using probabilistic approach. The liquefaction analysis was done based on 450 borehole data obtained in the study area. The results of CPT match well with the results obtained from similar analysis with SPT data.