Academic literature on the topic 'Multi Channel Analysis of Surface Wave (MASW)'

On May 27th 2006, Yogyakarta earthquake happened with 6.3 Mw. It was causing widespread destruction and loss of life and property. The average shear wave velocity to 30 m (Vs30) is useful parameter for classifying sites to predict their potential to amplify seismic shaking (Boore, 2004) [1]. Shear wave velocity is one of the most influential factors of the ground motion. The average shear wave velocity for the top 30 m of soil is referred to as Vs30. In this study, the Vs30 values were calculated by using multichannel analysis of surface waves (MASW) method. The Multichannel Analysis of Surface Waves (MASW) method was introduced by Park et al. (1999). Multi-channel Analysis of Surface Waves (MASW) is non-invasive method of estimating the shear-wave velocity profile. It utilizes the dispersive properties of Rayleigh waves for imaging the subsurface layers. MASW surveys can be divided into active and passive surveys. In active MASW method, surface waves can be easily generated by an impulsive source like a hammer, sledge hammer, weight drops, accelerated weight drops and explosive. Seismic measurements were carried out 44 locations in Yogyakarta province, in Indonesia. The dispersion data of the recorded Rayleigh waves were processed by using Seisimager software to obtain shear wave velocity profiles of the studied area. The average shear wave velocities of the soil obtained are ranging from 200 ms-1 to 988 ms-1, respectively.

The multi-channel analysis of surface waves (MASWs) method was used to obtain the shear wave velocity variations through near surface (depth < 30 m) and semi-deep (30 m < depth < 100 m) soil layers in the city of Ottawa, Canada. Sixteen sites were examined to evaluate the capability of the active and passive MASW methods for cases where the shear wave velocity(Vs)contrast between very loose soil (Vs< 200 m/s) and very firm bedrock (Vs> 2,300 m/s) is very large. The MASW velocity results compared with those of other geophysical approaches, such as seismic reflection/refraction methods and borehole data, where available, mostly confirming the capability of the MASW method to distinguish the high shear wave velocity contrast in the study area. We have found that, of the inversion procedures of MASW data, the random search inversion technique provides better results than the analytical generalized inversion method.

An acoustic soil profiler, using a so-called the high-frequency multi-channel analysis of surface waves (HF-MASW) method, has been developed, which uses surface (Rayleigh) waves to measure soil profile in terms of the shear (S) wave velocity as a function of depth, up to a 2.5 m deep below the surface. Several practical techniques have been developed to enhance the HF-MASW method, including (1) a variable sensor spacing configuration, (2) the self-adaptive method, and (3) the phase-only signal processing. Fundamentally, the S-wave velocity is related to soil mechanical and hydrological properties through the principle of effective stress. Therefore, the measured two-dimensional S-wave velocity images reflect the temporal and spatial variations of soils due to weather effects, geological anomalies, and anthropologic activities. Several HF-MASW applications will be reported, including (1) near surface soil profiling, (2) a long-term-survey for studying weather and seasonal effects, (3) short-term monitoring rain fall events, (4) detecting fraigpan layers, and (5) a farmland compaction study. This acoustic soil profiler can be used for agricultural, environmental, civil engineering, and military applications.

Surface-wave dispersion analysis is widely used in civil engineering to infer a shear wave velocity model of the subsoil for a wide variety of applications. Combining with a example, multi-channel analysis of surface waves method (MASW) was discussed in this paper. The entire MASW's procedure of three steps: acquiring ground roll data in the field, processing the data to determine dispersion curve, and back calculation of the geologic parameters for different depths. Based upon all the research results by far, MASW method is an efficient methods because of its high accuracy that is achieved by both special field technique and data processing technique.

The study was to characterize the sub surface at Agere in Ekori, using seismic refraction method, multichannel analysis of surface waves technique and borehole intrusive technique. Data were collected using a 12channel seismograph and other accessories required for seismic refraction data collection. Software called seismicimager was used to examine the data. The primary wave velocity in the first layer varied from 690 m/s at 4.2 m to 96 m/s at 7.3 m. A Vp range of 315 m/s to 484 m/s at a depth of 2 m is present inside the layer and represents the organic soil constituents. A Vp range of 669 m/s to 1756 m/s represents loose sand (dry), loose made ground (rubble), landfill rubbish, disturbed soil, and clay landfill, all within a depth of 2.3 m to 12.1 m. In addition to the borehole intrusive method, multichannel analysis of surface wave (MASW) techniques was used to calculate the soil profile based on velocity. The source was a 7 kg sledge hammer, the detectors (receivers) were 24 units of 4.5 Hz geophones, and the recorder was a Terraloc Mark 8 ABEM. Seismicimager software was used for analysis. At Ajere 1 through 6, the MASW test configuration employed 5 m geophone spacing and a source offset distance of 5 m, while at Ajere 7, it used 1 m geophone spacing and a source offset distance of 2 m. Near the boreholes, all of the MASW test arrays were run. The trustworthy seismic data from Ajere 1 to 6 at depths of 0.7 m to 13.1 m and 4.7 m to 17 m. Based on SPT N values, the results showed that the shear wave velocities had been classified into three layers of soil: very soft, soft, and firm. The velocities below 164 m/s, between 164 and 190, and 190 m/s to 320 m/s were classified as these soil types. In the meantime, a drilling invasive technique based on SPT N value determines changes in the soil layer. Hard material shear wave velocity data was not provided. In conclusion, because of its non-destructive, non-invasive nature and relative speed of evaluation, the MASW technique has the potential to be adapted in soil study to complement intrusive technique.

Soil compaction plays an important role in every construction activities to reduce risks of any damage. Traditionally, methods of assessing compaction include field tests and invasive penetration tests for compacted areas have great limitations, which caused time-consuming in evaluating large areas. Thus, this study proposed the possibility of using non-invasive surface wave method like Multi-channel Analysis of Surface Wave (MASW) as a useful tool for assessing soil compaction. The aim of this study was to determine the shear wave velocity profiles and field density of compacted soils under varying compaction efforts by using MASW method. Pre and post compaction of MASW survey were conducted at Pauh Campus, UniMAP after applying rolling compaction with variation of passes (2, 6 and 10). Each seismic data was recorded by GEODE seismograph. Sand replacement test was conducted for each survey line to obtain the field density data. All seismic data were processed using SeisImager/SW software. The results show the shear wave velocity profiles increase with the number of passes from 0 to 6 passes, but decrease after 10 passes. This method could attract the interest of geotechnical community, as it can be an alternative tool to the standard test for assessing of soil compaction in the field operation.

Surface wave dispersion imaging approach is crucial for multi-channel analysis of surface wave (MASW). Because the resolution of inversed S-wave velocity and thickness of a layer are directly subjected to the resolution of imaged dispersion curve. The τ-p transform approach is an efficient and commonly used approach for Rayleigh wave dispersion curve imaging. However, the conventional τ-p transform approach was severely affected by waves amplitude. So, the energy peaks of f-v spectrum were mainly gathered in a narrow frequency range. In order to remedy this shortage, an improved τ-p transform approach was proposed by this paper. Comparison has been made between phase shift and improved τ-p transform approaches using both synthetic and in situ tested data. Result shows that the dispersion image transformed from proposed approach is superior to that either from conventionally τ-p transform or from phase shift approaches.

Combined analysis of the geomorphic evolution of Greymouth with Multi-channel Analysis of Surface Waves (MASW) provides new insight into the geotechnical implications of reclamation work. The MASW method utilises the frequency dependent velocity (dispersion) of planar Rayleigh waves created by a seismic source as a way of assessing the stiffness of the subsurface material. The surface wave is inverted to calculate a shear wave velocity (Park et al., 1999). Once corrected, these shear-wave (Vs) velocities can be used to obtain a factor of safety for liquefaction susceptibility based on a design earthquake. The primary study site was the township of Greymouth, on the West Coast of New Zealand’s South Island. Greymouth is built on geologically young (Holocene-age) deposits of beach and river sands and gravels, and estuarine and lagoonal silts (Dowrick et al., 2004). Greymouth is also in a tectonically active region, with the high seismic hazard imposed by the Alpine Fault and other nearby faults, along with the age and type of sediment, mean the probability of liquefaction occurring is high particularly for the low-lying areas around the estuary and coastline. Repeated mapping over 150 years shows that the geomorphology of the Greymouth Township has been heavily modified during that timeframe, with both anthropogenic and natural processes developing the land into its current form. Identification of changes in the landscape was based on historical maps for the area and interpreting them to be either anthropogenic or natural changes, such as reclamation work or removal of material through natural events. This study focuses on the effect that anthropogenic and natural geomorphic processes have on the stiffness of subsurface material and its liquefaction susceptibility for three different design earthquake events. Areas of natural ground and areas of reclaimed land, with differing ages, were investigated through the use of the MASW method, allowing an initial estimation of the relationship between landscape modification and liquefaction susceptibility. The susceptibility to liquefaction of these different materials is important to critical infrastructure, such as the St. John Ambulance Building and Greymouth Aerodrome, which must remain functional following an earthquake. Areas of early reclamation at the Greymouth Aerodrome site have factors of safety less than 1 and will liquefy in most plausible earthquake scenarios, although the majority of the runway has a high factor of safety and should resist liquefaction. The land west of the St. John’s building has slightly to moderately positive factors of safety. Other areas have factors of safety that reflect the different geology and reclamation history.

Master of Science<br>Department of Geology<br>Abdelmoneam Raef<br>Geotechnical site characteristics are a function of the subsurface elastic moduli and the geologic structures. This study integrates borehole, surface and laboratory measurements for a geotechnical investigation that is focused on investigating shear-wave velocity (Vs) variation and its implication to geotechnical aspects of the Ogden test site in eastern Kansas. The area has a potential of seismicity due to the seismic zone associated with the Nemaha formation where earthquakes pose a moderate hazard. This study is in response to recent design standards for bridge structures require integrating comprehensive geotechnical site characterization. Furthermore, evaluation of dynamic soil properties is important for proper seismic response analysis and soil modeling programs. In this study, near surface geophysical site characterization in the form of 2D shear-wave velocity (Vs) structure that is compared with laboratory measurements of elastic moduli and earth properties at simulated in situ overburden pressure conditions and synergy with downhole Acoustic Televiewer time and amplitude logs, proved very robust “validated” workflow in site characterization for geotechnical purposes. An important component of a geotechnical site characterization is the evaluation of in-situ shear modulus, Poisson’s ratio and reliable and accurate elastic modulus ([lambda]) and shear modulus ([mu]) estimates are important in a good geotechnical site characterization. The geophysical site characterization, undertaken in this study, will complement and help in extrapolating drilling and core-based properties deduced by the geotechnical engineers interested at the test site.

Two surface wave testing methods, namely, (i) the spectral analysis of surface waves (SASW), and (ii) the multi-channel analysis of surface waves (MASW), form non-destructive and non-intrusive techniques for predicting the shear wave velocity profile of different layers of ground and pavement. These field testing tools are based on the dispersive characteristics of Rayleigh waves, that is, different frequency components of the surface wave travel at different velocities in layered media. The SASW and MASW testing procedure basically comprises of three different components: (i) field measurements by employing geophones/accelerometers, (ii) generating dispersion plots, and (iii) predicting the shear wave velocity profile based on an inversion analysis. For generating the field dispersion plot, the complexities involved while doing the phase unwrapping calculations for the SASW technique, while performing the spectral calculations on the basis of two receivers’ data, makes it difficult to automate since it requires frequent manual judgment. In the present thesis, a new method, based on the sliding Fourier transform, has been introduced. The proposed method has been noted to be quite accurate, computationally economical and it generally overcomes the difficulties associated with the unwrapping of the phase difference between the two sensors’ data. In this approach, the unwrapping of the phase can be carried out without any manual intervention. As a result, an automation of the entire computational process to generate the dispersion plot becomes feasible. The method has been thoroughly validated by including a number of examples on the basis of surface wave field tests as well as synthetic test data. While obtaining the dispersion image by using the MASW method, three different transformation techniques, namely, (i) the Park’s wavefield transform, (ii) the frequency (f) -wavenumber ( ) transform and (iii) the time intercept ( -phase slowness (p) transform have been utilized for generating the multimodal dispersion plots. The performance of these three different methods has been assessed by using synthetic as well as field data records obtained from a ground site by means of 48 geophones. Two-dimensional as well as three-dimensional dispersion plots were generated. The Park’s wavefield transformation method has been found to be especially advantageous since it neither requires a very high sampling rate nor an inclusion of the zero padding of the data in a wavenumber (distance) domain. In the case of an irregular dispersive media, a proper analysis of the higher modes existing in the dispersion plots becomes essential for predicting the shear wave velocity profile of ground on the basis of surface wave tests. In such cases, the establishment of the predominant mode becomes quite significant. In the current investigation for Rayleigh wave propagation, the predominant mode has been computed by maximizing the normalized vertical displacements along the free surface. Eigenvectors computed from the thin layer approach (TLM) approach are analyzed to predict the corresponding predominant mode. It is noted that the establishment of the predominant mode becomes quite important where only two to six sensors are employed and the governing (predominant) modal dispersion curve is usually observed rather than several multiple modes which can otherwise be identified by using around 24 to 48 multiple sensors. By using the TLM, it is, however, not possible to account for the exact contribution of the elastic half space in the dynamic stiffness matrix (DSM) approach. A method is suggested to incorporate the exact contribution of the elastic half space in the TLM. The numerical formulation is finally framed as a quadratic eigenvalue problem which can be easily solved by using the subroutine polyeig in MATLAB. The dispersion plots were generated for several chosen different ground profiles. The numerical results were found to match quite well with the data available from literature. In order to address all the three different aspects of SASW and MASW techniques, a series of field tests were performed on five different ground sites. The ground vibrations were induced by means of (i) a 65 kg mass dropped freely from a height of 5 m, and (ii) by using a 20 pound sledge hammer. It was found that by using a 65 kg mass dropped from a height of 5 m, for stiffer sites, ground exploration becomes feasible even up to a depth of 50-80 m whereas for the softer sites the exploration depth is reduced to about 30 m. By using a 20 lb sledge hammer, the exploration depth is restricted to only 8-10 m due to its low impact energy. Overall, it is expected that the work reported in the thesis will furnish useful guidelines for (i) performing the SASW and MASW field tests, (ii) generating dispersion plots/images, and (iii) predicting the shear wave velocity profile of the site based on an inversion analysis.

Two surface wave testing methods, namely, (i) the spectral analysis of surface waves (SASW), and (ii) the multi-channel analysis of surface waves (MASW), form non-destructive and non-intrusive techniques for predicting the shear wave velocity profile of different layers of ground and pavement. These field testing tools are based on the dispersive characteristics of Rayleigh waves, that is, different frequency components of the surface wave travel at different velocities in layered media. The SASW and MASW testing procedure basically comprises of three different components: (i) field measurements by employing geophones/accelerometers, (ii) generating dispersion plots, and (iii) predicting the shear wave velocity profile based on an inversion analysis. For generating the field dispersion plot, the complexities involved while doing the phase unwrapping calculations for the SASW technique, while performing the spectral calculations on the basis of two receivers’ data, makes it difficult to automate since it requires frequent manual judgment. In the present thesis, a new method, based on the sliding Fourier transform, has been introduced. The proposed method has been noted to be quite accurate, computationally economical and it generally overcomes the difficulties associated with the unwrapping of the phase difference between the two sensors’ data. In this approach, the unwrapping of the phase can be carried out without any manual intervention. As a result, an automation of the entire computational process to generate the dispersion plot becomes feasible. The method has been thoroughly validated by including a number of examples on the basis of surface wave field tests as well as synthetic test data. While obtaining the dispersion image by using the MASW method, three different transformation techniques, namely, (i) the Park’s wavefield transform, (ii) the frequency (f) -wavenumber ( ) transform and (iii) the time intercept ( -phase slowness (p) transform have been utilized for generating the multimodal dispersion plots. The performance of these three different methods has been assessed by using synthetic as well as field data records obtained from a ground site by means of 48 geophones. Two-dimensional as well as three-dimensional dispersion plots were generated. The Park’s wavefield transformation method has been found to be especially advantageous since it neither requires a very high sampling rate nor an inclusion of the zero padding of the data in a wavenumber (distance) domain. In the case of an irregular dispersive media, a proper analysis of the higher modes existing in the dispersion plots becomes essential for predicting the shear wave velocity profile of ground on the basis of surface wave tests. In such cases, the establishment of the predominant mode becomes quite significant. In the current investigation for Rayleigh wave propagation, the predominant mode has been computed by maximizing the normalized vertical displacements along the free surface. Eigenvectors computed from the thin layer approach (TLM) approach are analyzed to predict the corresponding predominant mode. It is noted that the establishment of the predominant mode becomes quite important where only two to six sensors are employed and the governing (predominant) modal dispersion curve is usually observed rather than several multiple modes which can otherwise be identified by using around 24 to 48 multiple sensors. By using the TLM, it is, however, not possible to account for the exact contribution of the elastic half space in the dynamic stiffness matrix (DSM) approach. A method is suggested to incorporate the exact contribution of the elastic half space in the TLM. The numerical formulation is finally framed as a quadratic eigenvalue problem which can be easily solved by using the subroutine polyeig in MATLAB. The dispersion plots were generated for several chosen different ground profiles. The numerical results were found to match quite well with the data available from literature. In order to address all the three different aspects of SASW and MASW techniques, a series of field tests were performed on five different ground sites. The ground vibrations were induced by means of (i) a 65 kg mass dropped freely from a height of 5 m, and (ii) by using a 20 pound sledge hammer. It was found that by using a 65 kg mass dropped from a height of 5 m, for stiffer sites, ground exploration becomes feasible even up to a depth of 50-80 m whereas for the softer sites the exploration depth is reduced to about 30 m. By using a 20 lb sledge hammer, the exploration depth is restricted to only 8-10 m due to its low impact energy. Overall, it is expected that the work reported in the thesis will furnish useful guidelines for (i) performing the SASW and MASW field tests, (ii) generating dispersion plots/images, and (iii) predicting the shear wave velocity profile of the site based on an inversion analysis.

Thesis (M. Sc.)--University of Canterbury, 2008.<br>Typescript (photocopy). Three folded leaves of ill. in pocket. Includes bibliographical references (leaves 175-185). Also available via the World Wide Web.

碩士<br>朝陽科技大學<br>營建工程系碩士班<br>101<br>The objective of this thesis is to develope a Non-destructive Testing (NDT) system for Multi-channel Analysis of a Surface Wave (MASW). The system uses geophone as the receiver and an analog-to-digital (A/D) converter to convert the analog signal into digital form. In order to verify the feasibility of the software developed in this study, the surface wave propagation signal were simulated with FLAC finited difference software, then the phase velocity analysis scheme of Park (2004) was used obtain a multi-channel spectrum, and compared with a theoretical dispersion curve using the thin layer stiffness method proposed by Chai et. al. (2011). Finally the shear wave velocity stiffness profile was then obtained. The software utilizes a graphical user interface thus making data retrieval, data analysis and data presentation in a single step. From the results of this study, it can be seen that the simulated dispersion curve match with the theoretical dispersion curve, so this research method is feasible. Using the LabVIEW platform can save development time and money. Furthermore the resulting interface is much more user friendly.

碩士<br>國立中興大學<br>水土保持學系所<br>102<br>This test method applied geophysical exploration, active multi-channel seismic wave, passive multi-channel seismic wave and resistivity image profiling method to passive SAW as the main research method, the control variable is the source and the array shape. Array shape into a cross array linear array, the source into high iron source, messy source, quiet source, self-driving source. And to take the initiative with a multi-channel surface wave and resistivity image profiling method to release the results of exploration contractors assisted.Before testing the bottom of the high-speed railway, the first country in the Yongding small Erlun Township, Yunlin County, Wells PS Log facilities to do multi-channel wave shock test experience, will take the initiative to SAW, SAW passive, active passive merger results are presented. Trend shear wave velocity of the test is intended to measure the shear wave velocity proofreading wells and non-destructive testing of the resulting wave is the same.The main purpose of this study was to explore the impact factor of the source array factor and provide work site investigations and tests on an array of factors and source selection factor, this factor discuss the results of the two auxiliary tools for proactive dimensional seismic wave the results and the results of resistivity image profiling method.

Site characterization is an important task in Geotechnical Engineering. In situ tests based on standard penetration test (SPT), cone penetration test (CPT) and shear wave velocity survey are popular among geotechnical engineers. Site characterization using any of these properties based on finite number of in-situ test data is an imperative task in probabilistic site characterization. These methods have been used to design future soil sampling programs for the site and to specify the soil stratification. It is never possible to know the geotechnical properties at every location beneath an actual site because, in order to do so, one would need to sample and/or test the entire subsurface profile. Therefore, the main objective of site characterization models is to predict the subsurface soil properties with minimum in-situ test data. The prediction of soil property is a difficult task due to the uncertainities. Spatial variability, measurement ‘noise’, measurement and model bias, and statistical error due to limited measurements are the sources of uncertainities. Liquefaction in soil is one of the other major problems in geotechnical earthquake engineering. It is defined as the transformation of a granular material from a solid to a liquefied state as a consequence of increased pore-water pressure and reduced effective stress. The generation of excess pore pressure under undrained loading conditions is a hallmark of all liquefaction phenomena. This phenomena was brought to the attention of engineers more so after Niigata(1964) and Alaska(1964) earthquakes. Liquefaction will cause building settlement or tipping, sand boils, ground cracks, landslides, dam instability, highway embankment failures, or other hazards. Such damages are generally of great concern to public safety and are of economic significance. Site-spefific evaluation of liquefaction susceptibility of sandy and silty soils is a first step in liquefaction hazard assessment. Many methods (intelligent models and simple methods as suggested by Seed and Idriss, 1971) have been suggested to evaluate liquefaction susceptibility based on the large data from the sites where soil has been liquefied / not liquefied. The rapid advance in information processing systems in recent decades directed engineering research towards the development of intelligent models that can model natural phenomena automatically. In intelligent model, a process of training is used to build up a model of the particular system, from which it is hoped to deduce responses of the system for situations that have yet to be observed. Intelligent models learn the input output relationship from the data itself. The quantity and quality of the data govern the performance of intelligent model. The objective of this study is to develop intelligent models [geostatistic, artificial neural network(ANN) and support vector machine(SVM)] to estimate corrected standard penetration test (SPT) value, Nc, in the three dimensional (3D) subsurface of Bangalore. The database consists of 766 boreholes spread over a 220 sq km area, with several SPT N values (uncorrected blow counts) in each of them. There are total 3015 N values in the 3D subsurface of Bangalore. To get the corrected blow counts, Nc, various corrections such as for overburden stress, size of borehole, type of sampler, hammer energy and length of connecting rod have been applied on the raw N values. Using a large database of Nc values in the 3D subsurface of Bangalore, three geostatistical models (simple kriging, ordinary kriging and disjunctive kriging) have been developed. Simple and ordinary kriging produces linear estimator whereas, disjunctive kriging produces nonlinear estimator. The knowledge of the semivariogram of the Nc data is used in the kriging theory to estimate the values at points in the subsurface of Bangalore where field measurements are not available. The capability of disjunctive kriging to be a nonlinear estimator and an estimator of the conditional probability is explored. A cross validation (Q1 and Q2) analysis is also done for the developed simple, ordinary and disjunctive kriging model. The result indicates that the performance of the disjunctive kriging model is better than simple as well as ordinary kriging model. This study also describes two ANN modelling techniques applied to predict Nc data at any point in the 3D subsurface of Bangalore. The first technique uses four layered feed-forward backpropagation (BP) model to approximate the function, Nc=f(x, y, z) where x, y, z are the coordinates of the 3D subsurface of Bangalore. The second technique uses generalized regression neural network (GRNN) that is trained with suitable spread(s) to approximate the function, Nc=f(x, y, z). In this BP model, the transfer function used in first and second hidden layer is tansig and logsig respectively. The logsig transfer function is used in the output layer. The maximum epoch has been set to 30000. A Levenberg-Marquardt algorithm has been used for BP model. The performance of the models obtained using both techniques is assessed in terms of prediction accuracy. BP ANN model outperforms GRNN model and all kriging models. SVM model, which is firmly based on the theory of statistical learning theory, uses regression technique by introducing -insensitive loss function has been also adopted to predict Nc data at any point in 3D subsurface of Bangalore. The SVM implements the structural risk minimization principle (SRMP), which has been shown to be superior to the more traditional empirical risk minimization principle (ERMP) employed by many of the other modelling techniques. The present study also highlights the capability of SVM over the developed geostatistic models (simple kriging, ordinary kriging and disjunctive kriging) and ANN models. Further in this thesis, Liquefaction susceptibility is evaluated from SPT, CPT and Vs data using BP-ANN and SVM. Intelligent models (based on ANN and SVM) are developed for prediction of liquefaction susceptibility using SPT data from the 1999 Chi-Chi earthquake, Taiwan. Two models (MODEL I and MODEL II) are developed. The SPT data from the work of Hwang and Yang (2001) has been used for this purpose. In MODEL I, cyclic stress ratio (CSR) and corrected SPT values (N1)60 have been used for prediction of liquefaction susceptibility. In MODEL II, only peak ground acceleration (PGA) and (N1)60 have been used for prediction of liquefaction susceptibility. Further, the generalization capability of the MODEL II has been examined using different case histories available globally (global SPT data) from the work of Goh (1994). This study also examines the capabilities of ANN and SVM to predict the liquefaction susceptibility of soils from CPT data obtained from the 1999 Chi-Chi earthquake, Taiwan. For determination of liquefaction susceptibility, both ANN and SVM use the classification technique. The CPT data has been taken from the work of Ku et al.(2004). In MODEL I, cone tip resistance (qc) and CSR values have been used for prediction of liquefaction susceptibility (using both ANN and SVM). In MODEL II, only PGA and qc have been used for prediction of liquefaction susceptibility. Further, developed MODEL II has been also applied to different case histories available globally (global CPT data) from the work of Goh (1996). Intelligent models (ANN and SVM) have been also adopted for liquefaction susceptibility prediction based on shear wave velocity (Vs). The Vs data has been collected from the work of Andrus and Stokoe (1997). The same procedures (as in SPT and CPT) have been applied for Vs also. SVM outperforms ANN model for all three models based on SPT, CPT and Vs data. CPT method gives better result than SPT and Vs for both ANN and SVM models. For CPT and SPT, two input parameters {PGA and qc or (N1)60} are sufficient input parameters to determine the liquefaction susceptibility using SVM model. In this study, an attempt has also been made to evaluate geotechnical site characterization by carrying out in situ tests using different in situ techniques such as CPT, SPT and multi channel analysis of surface wave (MASW) techniques. For this purpose a typical site was selected wherein a man made homogeneous embankment and as well natural ground has been met. For this typical site, in situ tests (SPT, CPT and MASW) have been carried out in different ground conditions and the obtained test results are compared. Three CPT continuous test profiles, fifty-four SPT tests and nine MASW test profiles with depth have been carried out for the selected site covering both homogeneous embankment and natural ground. Relationships have been developed between Vs, (N1)60 and qc values for this specific site. From the limited test results, it was found that there is a good correlation between qc and Vs. Liquefaction susceptibility is evaluated using the in situ test data from (N1)60, qc and Vs using ANN and SVM models. It has been shown to compare well with “Idriss and Boulanger, 2004” approach based on SPT test data. SVM model has been also adopted to determine over consolidation ratio (OCR) based on piezocone data. Sensitivity analysis has been performed to investigate the relative importance of each of the input parameters. SVM model outperforms all the available methods for OCR prediction.