Σκοπός της παρούσας Διατριβής Ειδίκευσης είναι η ανάλυση, η παρουσίαση και η αξιολόγηση των γεωτεχνικών συνθηκών της πόλης των Πατρών, σε σχέση με την εκδήλωση του φαινόμενου της ρευστοποίησης και τις συνθήκες γεωλογικής καταλληλότητας για τις προς δόμηση περιοχές. Στα πλαίσια της διατριβής πραγματοποιήθηκαν γεωτεχνικές έρευνες για είκοσι πέντε (25) γεωτρήσεις που έχουν διανοιχθεί κατά μήκος της πόλης των Πατρών, και αξιολογήθηκαν τα αποτελέσματα των επί τόπου και των εργαστηριακών δοκιμών. Με τη βοήθεια του λογισμικού Petal υπολογίστηκε ο συντελεστής ασφάλειας για ρευστοποίηση σε κάθε γεώτρηση και συντάχθηκαν χάρτες ζωνών επικινδυνότητας για την πόλη των Πατρών. Η έρευνα αυτή πραγματοποιήθηκε για δύο σεισμικά γεγονότα. Για το σεισμό των Πατρών το 1993 με μέγεθος 5.4 Richter και το σεισμό του Αιγίου το 1995 με μέγεθος 6.2 Richter. / The aim of this MSc Project is the presentation, the analysis and the assessment of the geotechnical conditions in city of Patras, Western Greece, for liquefaction phenomenon and geological suitability for construction purposes. In this project were done geotechnical surveys for twenty-five (25) boreholes in area of Patras, and assessment insitu and laboratory tests. Using Petal program we can estimate the factor of safety against liquefaction. The data used to perform mapping, in some zones of liquefaction risk. The survey based on seismic facts. The first one was the earthquake in 1993 in city of Patras with magnitude 5.4 Richter and the second one was the earthquake in city of Aigio in 1995 with magnitude 6.2 Richter.

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.

Mankind is facing the problem due to earthquake hazard since prehistoric times. Many of the developed and developing countries are under constant threats from earthquakes hazards. Theories of plate tectonics and engineering seismology have helped to understand earthquakes and also to predicate earthquake hazards on a regional scale. However, the regional scale hazard mapping in terms of seismic zonation has been not fully implemented in many of the developing countries like India. Agglomerations of large population in the Indian cities and poor constructions have raised the risk due to various possible seismic hazards. First and foremost step towards hazard reduction is estimation of the seismic hazards in regional scale. Objective of this study is to estimate the seismic hazard parameters for Lucknow, a part of Indo-Gangetic Basin (IGB) and develop regional scale microzonation map. Lucknow is a highly populated city which is located close to the active seismic belt of Himalaya. This belt came into existence during the Cenozoic era (40-50 million years ago) and is a constant source of seismic threats. Many of the devastating earthquakes which have happened since prehistoric times such as 1255 Nepal, 1555 Srinagar, 1737 Kolkata, 1803 Nepal, 1833 Kathmandu, 1897 Shillong, 1905 Kangra, 1934 Bihar-Nepal, 1950 Assam and 2005 Kashmir. Historic evidences show that many of these earthquakes had caused fatalities even up to 0.1 million. At present, in the light of building up strains and non-occurrence of a great event in between 1905 Kangra earthquake and 1934 Bihar-Nepal earthquake regions the stretch has been highlighted as central seismic gap. This location may have high potential of great earthquakes in the near future. Geodetic studies in these locations indicate a possible slip of 9.5 m which may cause an event of magnitude 8.7 on Richter scale in the central seismic gap. Lucknow, the capital of Uttar Pradesh has a population of 2.8 million as per Census 2011. It lies in ZONE III as per IS1893: 2002 and can be called as moderate seismic region. However, the city falls within 350 km radial distance from Main Boundary Thrust (MBT) and active regional seismic source of the Lucknow-Faizabad fault. Considering the ongoing seismicity of Himalayan region and the Lucknow-Faizabad fault, this city is under high seismic threat. Hence a comprehensive study of understanding the earthquake hazards on a regional scale for the Lucknow is needed. In this work the seismic microzonation of Lucknow has been attempted. The whole thesis is divided into 11 chapters. A detailed discussion on the importance of this study, seismicity of Lucknow, and methodology adopted for detailed seismic hazard assessment and microzonation are presented in first three chapters. Development of region specific Ground Motion Prediction Equation (GMPE) and seismic hazard estimation at bedrock level using highly ranked GMPEs are presented in Chapters 4 and 5 respectively. Subsurface lithology, measurement of dynamic soil properties and correlations are essential to assess region specific site effects and liquefaction potential. Discussion on the experimental studies, subsurface profiling using geotechnical and geophysical tests results and correlation between shear wave velocity (SWV) and standard penetration test (SPT) N values are presented in Chapter 6. Detailed shear wave velocity profiling with seismic site classification and ground response parameters considering multiple ground motion data are discussed in Chapters 7 and 8. Chapters 9 and 10 present the assessment of liquefaction potential and determination of hazard index with microzonation maps respectively. Conclusions derived from each chapter are presented in Chapter 11. A brief summary of the work is presented below: Attenuation relations or GMPEs are important component of any seismic hazard analysis which controls accurate prediction of the hazard values. Even though the Himalayas have experienced great earthquakes since ancient times, suitable GMPEs which are applicable for a wide range of distance and magnitude are limited. Most of the available regional GMPEs were developed considering limited recorded data and/or pure synthetic ground motion data. This chapter presents development of a regional GMPE considering both the recorded as well as synthetic ground motions. In total 14 earthquakes consisting of 10 events with recorded data and 4 historic events with Isoseismal maps are used for the same. Synthetic ground motions based on finite fault model have been generated at unavailable locations for recorded events and complete range distances for historic earthquakes. Model parameters for synthetic ground motion were arrived by detailed parametric study and from literatures. A concept of Apparent Stations (AS) has been used to generate synthetic ground motion in a wide range of distance as well as direction around the epicenter. Synthetic ground motion data is validated by comparing with available recorded data and peak ground acceleration (PGA) from Isoseismal maps. A new GMPE has been developed based on two step stratified regression procedure considering the combined dataset of recorded and synthetic ground motions. The new GMPE is validated by comparing with three recently recorded earthquakes events. GMPE proposed in this study is capable of predicting PGA values close to recorded data and spectral acceleration up to period of 2 seconds. Comparison of new GMPE with the recorded data of recent earthquakes shows a good matching of ground motion as well as response spectra. The new GMPE is applicable for wide range of earthquake magnitudes from 5 to 9 on Mw scale. Reduction of future earthquake hazard is possible if hazard values are predicted precisely. A detailed seismic hazard analysis is carried out in this study considering deterministic and probabilistic approaches. New seismotectonic map has been generated for Lucknow considering a radial distance of 350 km around the city centre, which also covers active Himalayan plate boundaries. Past earthquakes within the seismotectonic region have been collected from United State Geological Survey (USGS), Northern California Earthquake Data Centre (NCEDC), Indian Meteorological Department (IMD), Seismic Atlas of India and its Environs (SEISAT) etc. A total of 1831 events with all the magnitude range were obtained. Collected events were homogenized, declustered and filtered for Mw ≥ 4 events. A total of 496 events were found within the seismic study region. Well delineated seismic sources are compiled from SEISAT. Superimposing the earthquake catalogue on the source map, a seismotectonic map of Lucknow was generated. A total of 47 faults which have experienced earthquake magnitude of 4 and above are found which are used for seismic hazard analysis. Based on the distribution of earthquake events on the seismotectonic map, two regions have been identified. Region I which shows high density of seismic events in the area in and around of Main Boundary Thrust (MBT) and Region II which consists of area surrounding Lucknow with sparse distribution of earthquake events. Data completeness analysis and estimation of seismic parameter “a” and “b” are carried out separately for both the regions. Based on the analysis, available earthquake data is complete for a period of 80 years in both the regions. Using the complete data set, the regional recurrence relations have been developed. It shows a “b” value of 0.86 for region I and 0.9 for Region II which are found comparable with earlier studies. Maximum possible earthquake magnitude in each source has been estimated using observed magnitude and doubly truncated Gutenberg-Richter relation. The study area of Lucknow is divided into 0.015o x 0.015o grid size and PGA at each grid has been estimated by considering all sources and the three GMPEs. A Matlab code was generated for seismic hazard analysis and maximum PGA value at each grid point was determined and mapped. Deterministic seismic hazard analysis (DSHA) shows that maximum expected PGA values at bedrock level varies from 0.05g in the eastern part to 0.13g in the northern region. Response spectrum at city centre is also developed up to a period of 2 seconds. Further, Probabilistic seismic hazard analysis (PSHA) has been carried out and PGA values for 10 % and 2 % probability of exceedence in 50 years have been estimated and mapped. PSHA for 10 % probability shows PGA variation from 0.035g in the eastern parts to 0.07g in the western and northern parts of Lucknow. Similarly PSHA for 2 % probability of exceedence indicates PGA variation from 0.07g in the eastern parts while the northern parts are expecting PGA of 0.13g. Uniform hazard spectra are also developed for 2 % and 10 % probability for a period of up to 2 seconds. The seismic hazard analyses in this study show that the northern and western parts of Lucknow are more vulnerable when compared to other part. Bedrock hazard values completely change due to subsoil properties when it reaches the surface. A detailed geophysical and geotechnical investigation has been carried out for subsoil profiling and seismic site classification. The study area has been divided into grids of 2 km x 2 km and roughly one geophysical test using MASW (Multichannel Analysis Surface Wave) has been carried out in each grid and the shear wave velocity (SWV) profiles of subsoil layers are obtained. A total of 47 MASW tests have been carried out and which are uniformly distributed in Lucknow. In addition, 12 boreholes have also been drilled with necessary sampling and measurement of N-SPT values at 1.5 m interval till a depth of 30 m. Further, 11 more borelog reports are collected from the same agency hired for drilling the boreholes. Necessary laboratory tests are conducted on disturbed and undisturbed soil samples for soil classification and density measurement. Based on the subsoil informations obtained from these boreholes, two cross-sections up to a depth of 30 m have been generated. These cross-sections show the presence of silty sand in the top 10 m at most of the locations followed by clayey sand of low to medium compressibility till a depth of 30 m. In between the sand and clay traces of silt were also been found in many locations. In addition to these boreholes, 20 deeper boreholes (depth ≥150 m) are collected from Jal Nigam (Water Corporation) Lucknow, Government of Uttar Pradesh. Typical cross-section along the alignment of these deeper boreholes has been generated up to 150 m depth. This cross-section shows the presence of fine sand near Gomati while other locations are occupied by surface clayey sand. Also, the medium sand has been found in the western part of the city at a depth of 110 m which continues till 150 m depth. On careful examination of MASW and boreholes with N-SPT, 17 locations are found very close and SWV and N-SPT values are available up to 30 m depth. These SWV and N-SPT values are complied and used to develop correlations between SWV and N-SPT for sandy soil, clayey soil and all soil types. This correlation is the first correlation for IGB soil deposits considered measured data up to 30 m. The new correlation is verified graphically using normal consistency ratio and standard percentage error with respect to measured N-SPT and SWV. Further, SWV and N-SPT profiles are used Another important earthquake induced hazard is liquefaction. Even though many historic earthquakes caused liquefaction in India, very limited attempt has been made to map liquefaction potential in IGB. In this study, a detailed liquefaction analysis has been carried out for Lucknow a part of Ganga Basin to map liquefaction potential. Initially susceptibility of liquefaction for soil deposits has been assessed by comparing the grain size distribution curve obtained from laboratory tests with the range of grain size distribution for potentially liquefiable soils. Most of surface soil deposits in the study area are susceptible to liquefaction. At all the 23 borehole locations, measured N-SPT values are corrected for (a) Overburden Pressure (CN), (b) Hammer energy (CE), (c) Borehole diameter (CB), (d) presence or absence of liner (CS), (e) Rod length (CR) and (f) fines content (Cfines). Surface PGA values at each borehole locations are used to estimate Cyclic Stress Ratio (CSR). Corrected N-SPT values [(N1)60CS] are used to estimate Cyclic Resistance Ratio (CRR) at each layer. CSR and CRR values are used to estimate Factor of Safety (FOS) against liquefaction in each layer. Least factor safety values are indentified from each location and presented liquefaction factor of safety map for average and maximum amplified PGA values. These maps highlight that northern, western and central parts of Lucknow are very critical to critical against liquefaction while southern parts shows moderate to low critical area. The entire alignment of river Gomati falls in very critical to critical regions for liquefaction. Least FOS shows worst scenario and does not account thickness of liquefiable soil layers. Further, these FOS values are used to determine Liquefaction Potential Index (LPI) of each site and developed LPI map. Based on LPI map, the Gomati is found as high to very high liquefaction potential region. Southern and the central parts of Lucknow show low to moderate liquefaction potential while the northern and western Lucknow has moderate to high liquefaction potential. All possible seismic hazards maps for Lucknow have been combined to develop final microzonation map in terms of hazard index values. Hazard index maps are prepared by combining rock PGA map, site classification map in terms of shear wave velocity, amplification factor map, and FOS map and predominant period map by adopting Analytical Hierarchy Process (AHP). All these parameters have been given here in the order starting with maximum weight of 6 for PGA to lower weight of 1 for predominant frequency. Normalized weights of each parameter have been estimated. Depending upon the variation of each hazard parameter values, three to five ranks are assigned and the normalized ranks are calculated. Final hazard index values have been estimated by multiplying normalized ranks of each parameter with the normalized weights. Microzonation map has been generated by mapping hazard index values. Three maps were generated based on DSHA, PSHA for 2% and 10 % probability of exceedence in 50 years. Hazard index maps from DSHA and PSHA for 2 % probability show similar pattern. Higher hazard index were obtained in northern and western parts of Lucknow and lower values in others. The new microzonation maps can help in dividing the Lucknow into three parts as high area i.e. North western part, moderate hazard area i.e. central part and low hazard area which covers southern and eastern parts of Lucknow. This microzonation is different from the current seismic code where all area is lumped in one zone without detailed assessment of different earthquake hazard parameters. Finally this study brings out first region specific GMPE considering recorded and synthetic ground monitions for wide range of magnitudes and distances. Proposed GMPE can also be used in other part of the Himalayan region as it matches well with the highly ranked GMPEs. Detailed rock level PGA map has been generated for Lucknow considering DSHA and PSHA. A detailed geotechnical and geophysical experiments are carried out in Lucknow. These results are used to develop correction between SWV and N-SPT values for soil deposit in IGB and site classification maps for the study area. Amplification and liquefaction potential of Lucknow are estimated by considering multiple ground motions data to account different earthquake ground motion amplitude, duration and frequency, which is unique in the seismic microzonation study.