Este trabalho investiga a termodifusão em coloides magnéticos através da técnica de varredura Z. O ponto de partida é a generalização do modelo de lente térmica, supondo o surgimento de um gradiente de concentração dos grãos magnéticos devido ao gradiente de temperatura causado pelo feixe de laser sobre a amostra. A partir do uso da técnica de varredura Z foi possível o estudo do coeficiente Soret (S IND.T) em ferrofluidos iônicos, surfactados e citrados, em amostras com baixa concentração de grãos (fração volumétrica de Fe, ø, menor que 1%). Na generalização do modelo de lente térmica que efetuamos, consideramos que a variação no índice de refração da amostra, em uma experiência de varredura Z, depende da variação da intensidade do feixe laser (I), da variação da temperatura (T) e da variação da concentração de grãos magnéticos (ø), onde C IND.N, C IND.T e C IND.S são seus respectivos parâmetros adimensionais no modelo. Uma vez que o tempo característico da termodifusão é da ordem de segundos, uma varredura Z com pulsos da ordem de 20ms é utilizada para a determinação de C IND.N. C IND.T é obtido independentemente por meio de métodos de óptica linear.Após a determinação de C IND.N e C IND.T, uma varredura Z com duração de pulso da ordem de 1 segundo é feita para determinar C IND.S e, posteriormente, o coeficiente Soret. A partir do comportamento da curva de evolução temporal da tranmitância com pulsos de 1 segundo pode-se determinar o sinal do coeficiente Soret. O sinal está relacionado com a tendência dos grãos de migrarem para a região mais fria (termofóbico, S IND.T>0) ou mais quente (termofílico, S IND.T<0) da amostra, dependendo de suas características físico-químicas. Mostramos que o módulo de S IND.T é proporcional a ø, em concordância com resultados obtidos para soluções mais concentradas (ø1) através da técnica de Espalhamento Rayleigh Forçado. Uma possível origem física para os comportamentos termofóbico e termofílico dos fluidos magnéticos poderia estar relacionada a mudanças na intensidade das forças que mantêm o equilíbrio coloidal, por ação da temperatura. / This work explores the thermodiffusion in magnetic colloids through the Z-Scan technique. The starting point is the generalization of the thermal lens model based on the assumption that the concentration gradient of the magnetic grains emerges due to the temperature gradient caused by the laser beam on the sample. By using the Z-Scan technique it was possible to study the Soret coefficient (ST) for ionic, surfacted and citrated ferrofluids in samples with low concentration of grains (Fe volumetric percentage, ø, less than 1%). In this thermal lens model generalization, we have considered that the refraction índex variation in a Z-Scan experiment depends on the laser beam intensity (I), the temperature variation (T) and the variation of the magnetic grains concentration (ø), where CN, CT and CS are their respective dimensionless parameters in the model. As characteristic time of thermodiffusion is of the order of seconds, a Z-Scan with pulses around 20 ms is used in order to determine CN. CT is obtained independently by using lenear optics methods. After the determination of CN and CT, a Z-Scan with pulses around 1 second is made in order to determine CS and, Consequently, the Soret coefficient. Through the behavior of the time dependent transmittance with 1-second pulses we were able to determine the sign of the Soret coefficient. The sign is related to the tendency of the grains to migrate to the colder region (thermophobic, ST>0) or to the warmer region (thermophilic, ST<0) of the sample, depending on its physical-chemical characteristics. We have showed that the ST module is proportional to ø, in agreement with the results for higher concentration solutions (ø1%) obtained through Forced Rayleigh Scattering. A possible physical originfor the thermophobic and thermophilic behavior of magnetic fluids could berelated to changes in the intensity of the forces that keep the colloidal balance, by means of temperature.

Este trabalho investiga a termodifusão em coloides magnéticos através da técnica de varredura Z. O ponto de partida é a generalização do modelo de lente térmica, supondo o surgimento de um gradiente de concentração dos grãos magnéticos devido ao gradiente de temperatura causado pelo feixe de laser sobre a amostra. A partir do uso da técnica de varredura Z foi possível o estudo do coeficiente Soret (S IND.T) em ferrofluidos iônicos, surfactados e citrados, em amostras com baixa concentração de grãos (fração volumétrica de Fe, ø, menor que 1%). Na generalização do modelo de lente térmica que efetuamos, consideramos que a variação no índice de refração da amostra, em uma experiência de varredura Z, depende da variação da intensidade do feixe laser (I), da variação da temperatura (T) e da variação da concentração de grãos magnéticos (ø), onde C IND.N, C IND.T e C IND.S são seus respectivos parâmetros adimensionais no modelo. Uma vez que o tempo característico da termodifusão é da ordem de segundos, uma varredura Z com pulsos da ordem de 20ms é utilizada para a determinação de C IND.N. C IND.T é obtido independentemente por meio de métodos de óptica linear.Após a determinação de C IND.N e C IND.T, uma varredura Z com duração de pulso da ordem de 1 segundo é feita para determinar C IND.S e, posteriormente, o coeficiente Soret. A partir do comportamento da curva de evolução temporal da tranmitância com pulsos de 1 segundo pode-se determinar o sinal do coeficiente Soret. O sinal está relacionado com a tendência dos grãos de migrarem para a região mais fria (termofóbico, S IND.T>0) ou mais quente (termofílico, S IND.T<0) da amostra, dependendo de suas características físico-químicas. Mostramos que o módulo de S IND.T é proporcional a ø, em concordância com resultados obtidos para soluções mais concentradas (ø1) através da técnica de Espalhamento Rayleigh Forçado. Uma possível origem física para os comportamentos termofóbico e termofílico dos fluidos magnéticos poderia estar relacionada a mudanças na intensidade das forças que mantêm o equilíbrio coloidal, por ação da temperatura. / This work explores the thermodiffusion in magnetic colloids through the Z-Scan technique. The starting point is the generalization of the thermal lens model based on the assumption that the concentration gradient of the magnetic grains emerges due to the temperature gradient caused by the laser beam on the sample. By using the Z-Scan technique it was possible to study the Soret coefficient (ST) for ionic, surfacted and citrated ferrofluids in samples with low concentration of grains (Fe volumetric percentage, ø, less than 1%). In this thermal lens model generalization, we have considered that the refraction índex variation in a Z-Scan experiment depends on the laser beam intensity (I), the temperature variation (T) and the variation of the magnetic grains concentration (ø), where CN, CT and CS are their respective dimensionless parameters in the model. As characteristic time of thermodiffusion is of the order of seconds, a Z-Scan with pulses around 20 ms is used in order to determine CN. CT is obtained independently by using lenear optics methods. After the determination of CN and CT, a Z-Scan with pulses around 1 second is made in order to determine CS and, Consequently, the Soret coefficient. Through the behavior of the time dependent transmittance with 1-second pulses we were able to determine the sign of the Soret coefficient. The sign is related to the tendency of the grains to migrate to the colder region (thermophobic, ST>0) or to the warmer region (thermophilic, ST<0) of the sample, depending on its physical-chemical characteristics. We have showed that the ST module is proportional to ø, in agreement with the results for higher concentration solutions (ø1%) obtained through Forced Rayleigh Scattering. A possible physical originfor the thermophobic and thermophilic behavior of magnetic fluids could berelated to changes in the intensity of the forces that keep the colloidal balance, by means of temperature.

In this thesis, theoretical and computer simulation studies of vibrational phase relaxation in various molecular liquids are presented. That includes liquid nitrogen, both along the coexistence line and the critical isochore, binary liquid mixture and liquid water. The focus of the thesis is to understand the dependence of the vibrational relaxation on the density, temperature, composition and the role of different interactions among the molecules. The density fluctuation of the solute particles in a solvent is studied systematically, where the computer simulation results are compared with the mode coupling theory (MCT). The classical density functional theory (DFT) is used to study the vibrational relaxation dynamics in molecular liquids with an aim to understand the heterogeneous nature of the dynamics commonly observed in experiments. Chapter 1 contains a brief overview of the earlier relevant theories, their successes and shortcomings in the light of the problems discussed in this thesis. This chapter discusses mainly the basic features of the vibrational dynamics of molecular liquids and portrays some of the theoretical frameworks and formalisms which are widely recognized to have contributed to our present understanding. Vibrational dephasing of nitrogen molecules is known to show highly interesting anomalies near its gas–liquid critical point. In Chapter 2, we present the results of extensive computer simulation studies and theoretical analysis of the vibrational phase relaxation of nitrogen molecules both along the critical isochore and the gas–liquid coexistence line. The simulation includes the different contributions (density (ρ), vibration–rotation (VR), and resonant transfer (Rs)) and their cross–correlations. Following Everitt and Skinner, we have included the vibrational coordinate (q) dependence of the inter–atomic potential, which is found to have an important contribution. The simulated results are in good agreement with the experiments. The linewidth (directly proportional to the rate of the vibrational phase relaxation) is found to have a lambda shaped temperature dependence near the critical point. As observed in the experimental studies, the calculated lineshape becomes Gaussian–like as the critical temperature (Tc) is approached while being Lorentzian–like at the temperatures away from Tc. Both the present simulation and a mode coupling theory (MCT) analysis show that the slow decay of the enhanced density fluctuations near the critical point (CP), probed at the sub–picosecond timescales by the vibrational frequency modulation, and an enhanced vibration–rotation coupling, are the main causes of the observed anomalies. Dephasing time (тv) and the root mean square frequency fluctuation (Δ) in the supercritical region are calculated. The principal results are: 1. a crossover from a Lorentzian–like to a Gaussian–like lineshape is observed as the critical point is approached along the critical isochore, 2. the root mean square frequency fluctuation shows a non–monotonic dependence on the temperature along the critical isochore, 3. the temperature dependent linewidth shows a divergence–like (λ–shaped) behavior along the coexistence line and the critical isochore. It is found that the linewidth calculated from the time integral of the normal coordinate time correlation function (CQ(t)) is in good agreement with the known experimental results. The origin of the anomalous temperature dependence of linewidth can be traced to simultaneous effects of several factors, (i) the enhancement of the negative cross–correlations of ρ with VR and Rs and (ii) the large density fluctuations as the critical point (CP) is approached. Due to the negative cross–correlations of ρ with VR and Rs the total decay becomes faster (correlation times are in the femtosecond scale). The reason for the negative cross–correlation between ρ and VR is explored in detail. A mode coupling theory (MCT) analysis shows a slow decay of the enhanced density fluctuations near the critical point. The MCT analysis demonstrates that the large enhancement of VR–coupling near CP may arise from a non–Gaussian behavior of the equilibrium density fluctuations. This enters through a non–zero value of the triplet direct correlation function. Many of the complex systems found in nature and used routinely in industry are multi–component systems. In particular, binary mixtures are highly non–ideal and play an important role in the industry. The dynamic properties are strongly influenced by composition fluctuations which are absent in the one component liquids. In Chapter 3, isothermal–isobaric (NPT) ensemble molecular dynamics simulation studies of vibrational phase relaxation (VPR) in a model system are presented. The model considers strong attractive interaction between the dissimilar species to prevent phase separation. The model reproduces the experimentally observed non–monotonic, nearly symmetric, composition dependence of the dephasing rate. In addition, several other experimentally observed features, such as the maximum of the frequency modulation correlation time (т c) at a mole fraction near 0.5 and the maximum rate enhancement by a factor of about 3 above the pure component value, are also reproduced. The product of the mean square frequency modulation ((Δω2(0))) with тc indicates that the present model is in the intermediate regime of the inhomogeneous broadening. The non–monotonic composition (χ) dependence of тv is found to be primarily due to the non–monotonic χ dependence of тc, rather than due to a similar dependence in the amplitude of (Δω2(0)). The probability distribution of Δω shows a markedly non–Gaussian behavior at intermediate composition (χ - 0.5). We have also calculated the composition dependence of the viscosity (η∗) in order to explore the correlation between the viscosity with that of тv and тc. It is found that both the correlation times essentially follow the nature of the composition dependence of the viscosity. A mode coupling theory (MCT) analysis is presented to include the effects of the composition fluctuations in binary mixture. Water is an interesting and attractive object for research, not only because of its great importance in life processes but also due to its unusual and intriguing properties. Most of the anomalous properties of water are related to the presence of a three–dimensional network of hydrogen bonds, which is constantly changing at ultrafast, sub–picosecond timescales. Vibrational spectroscopy provides the means to study the dynamics of processes involving only certain chemical bonds. The dynamics of hydrogen bonding can be probed via its reflection on molecular vibrations, e.g., the stretching vibrational mode of the O–H bond. Recently developed femtosecond infrared vibrational spectroscopy has proved to be valuable to study water dynamics because of its unique temporal resolution. Recent studies have shown that the vibrational relaxation of the O–H stretch of HDO occurs at an extremely fast timescale with time constant being less than 100 femtosecond. Here, in Chapter 4, we investigate the origin of this ultrafast vibrational dephasing using computer simulation and appropriate theoretical analysis. In addition to the usual fast vibrational dynamics due to the hydrogen bonding excitations, we find two additional reasons: (a) the large amplitude of angular jumps of the water molecules (with 30–40 fs time intervals) provide large contribution to the mean square vibrational frequency and (b) the projected force along the O–H bond due to the solvent molecules, on the oxygen (FO(t)) and hydrogen (FH (t)) atoms of the O–H bond exhibit a large negative cross–correlation (NCC) between FO(t) and FH (t). This NCC is shown to be partly responsible for a weak, non–Arrhenius temperature dependence of the relaxation rate. In the concluding note, Chapter 5 starts with a brief summary of the outcome of this thesis and ends up with suggestions of a few relevant problems that may prove worthwhile to be addressed in the future.

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.