Many aspects of the behavior of sands are affected by the content of non-plastic fine particles and these various aspects should be included in a constitutive model for the soil behavior. The fines content affects maximum and minimum void ratios, compressibility, shear strength, and static liquefaction under undrained conditions. Twenty-eight undrained triaxial compression tests were performed on mixtures of sand and fine particles with fines contents of 0, 10, 20, 30, 50, 75, and 100% to study the effects of fines on void ratio, compressibility, and the occurrence of static liquefaction. The experiments were performed at low consolidation pressures at which liquefaction may occur in near-surface, natural deposits. The presence of fines creates a particle structure in the soil that is highly compressible, enhancing the potential for liquefaction, and the fines also alter the basic stress-strain and volume change behavior, which should be modeled to predict the occurrence of static liquefaction in the field. The void ratio at which liquefaction occurs for each sand/fines mixture was determined, and the variation of compressibility with void ratio was determined for each mixture. This allowed a relation to be determined between fines content, void ratio, compressibility, and the occurrence of static liquefaction. Such relations may vary from sand to sand, but the present results are believed to indicate the trend in such relations.

There has been growing agreement that geotechnical reliability-based design (RBD) is necessary for establishing more advanced and integrated design system. In this study, resistance factors for LRFD pile design using CPT results were investigated for axially loaded driven piles. In order to address variability in design methodology, different CPT-based methods and load-settlement criteria, popular in practice, were selected and used for evaluation of resistance factors. A total of 32 data sets from 13 test sites were collected from the literature. In order to maintain the statistical consistency of the data sets, the characteristic pile load capacity was introduced in reliability analysis and evaluation of resistance factors. It was found that values of resistance factors considerably differ for different design methods, load-settlement criteria, and load capacity components. For the total resistance, resistance factors for LCPC method were higher than others, while those for Aoki-Velloso's and Philipponnat's methods were in similar ranges. In respect to load-settlement criteria, 0.1B and Chin's criteria produced higher resistance factors than DeBeer's and Davisson's criteria. Resistance factors for the base and shaft resistances were also presented and analyzed.

A significantly thick zone of steep slopes is commonly encountered above groundwater table and the soils within this zone are unsaturated with negative pore-water pressures (i.e., matric suction). Matric suction contributes significantly to the shear strength of soil and to the factor of safety of unsaturated slopes. However, infiltration during rainfall increases the pore-water pressure in soil resulting in a decrease in the matric suction and the shear strength of the soil. As a result, rainfall infiltration may eventually trigger a slope failure. Therefore, understanding of shear strength characteristics of saturated and unsaturated soils under shearing-infiltration (SI) conditions have direct implications in assessment of slope stability under rainfall conditions. This paper presents results from a series of consolidated drained (CD) and shearing-infiltration (SI) tests. Results show that the failure envelope obtained from the shearing-infiltration tests is independent of the infiltration rate. Failure envelopes obtained from CD and SI tests appear to be similar. For practical purposes the shear strength parameters from the CD tests can be used in stability analyses of slopes under rainfall conditions. The SI tests might be performed to obtain more conservative shear strength parameters and to study the pore-water pressure changes during infiltration.

In recent years, several computer-aided pattern recognition and data mining techniques have been developed for modeling of soil behavior. The main idea behind a pattern recognition system is that it learns adaptively from experience and is able to provide predictions for new cases. Artificial neural networks are the most widely used pattern recognition methods that have been utilized to model soil behavior. Recently, the authors have pioneered the application of genetic programming (GP) and evolutionary polynomial regression (EPR) techniques for modeling of soils and a number of other geotechnical applications. The paper reviews applications of pattern recognition and data mining systems in geotechnical engineering with particular reference to constitutive modeling of soils. It covers applications of artificial neural network, genetic programming and evolutionary programming approaches for soil modeling. It is suggested that these systems could be developed as efficient tools for modeling of soils and analysis of geotechnical engineering problems, especially for cases where the behavior is too complex and conventional models are unable to effectively describe various aspects of the behavior. It is also recognized that these techniques are complementary to conventional soil models rather than a substitute to them.

Artificial neural networks (ANNs) are a new type of information processing system based on modeling the neural system of human brain. The prediction of swell pressures from easily determined soil properties, namely, initial dry density, initial water content, and plasticity index, have been investigated by using artificial neural networks. The results of the constant volume swell tests in oedometers, performed on statically compacted specimens of Bentonite-Kaolinite clay mixtures with varying soil properties, were trained in an ANNs program and the results were compared with the experimental values. It is observed that the experimental results coincided with ANNs results.

The radius and coordinate of sliding circle are taken as searching variables in slope stability analysis. Genetic algorithm is applied for searching for critical factor of safety. In order to search for critical factor of safety in slope stability analysis efficiently and in a robust manner, some improvements for simple genetic algorithm are proposed. Taking the advantages of efficiency of neighbor-search of the simulated annealing and the robustness of genetic algorithm, a hybrid optimization method is presented. The numerical computation shows that the procedure can determine the minimal factor of safety and be applied to slopes with any geometry, layering, pore pressure and external load distribution. The comparisons demonstrate that the genetic algorithm provides a same solution when compared with elasto-plastic finite element program.

The interactions between a granular pile and raft placed on top are investigated using the continuum approach. The compatibility of vertical and radial displacements along the pile - soil interface and of the vertical displacements along the raft - top of ground interfaces are satisfied. Results show that consideration of radial displacement compatibility does not influence the settlement response of or sharing of the applied load between the granular pile and the raft. The percentage load carried by the granular pile (GP) increases with the increase of its stiffness and decreases with the increase of the relative size of raft. The normal stresses at the raft - soil interface decrease with the increase of stiffness of GP and/or relative length of GP. The influences of GP stiffness and relative length of GP are found to be more for relatively large size of raft. The percentage of load transferred to the base of GP increases with the increase of relative size of raft.