Small-Strain Shear Modulus of Calcareous Sand under Anisotropic Consolidation

In this study, the small strain shear modulus of a calcareous sand was investigated by conducting bender element tests on both horizontal and vertical planes. The effects of sample preparation method, stress path and stress history on the developing of void ratio, the parameters in the modified Hardin equation and the stiffness anisotropy were examined. The test results show that the moist tamping samples have the least void ratio variation among the five samples. The void ratio recovery in σ'h = 100 kPa tests is higher than that in the σ'v = 100 kPa tests. The samples prepared in dry state have lower stiffness than those prepared in moisture state, which is not influenced by the anisotropic stress state. The stiffness anisotropy induced by the sample preparation method is significant under anisotropic consolidation. In σ'h = 100 kPa tests, the stiffness ratios at the end of the unloading stage are lower than the initial values at the loading stage, which is not found in the σ'v = 100 kPa tests, meaning that the stress history and stress path could affect the stiffness anisotropy and cover the impact of fabric anisotropy.

A Deviatoric Softening Model to Simulate Compressibility Properties of Soft Clays

Soft clays are often associated with high compressibility due to their high void ratio, low shear strength, and creep behavior. Structures built on top of it can experience excessive settlement issues over a long period of time. The prediction of these settlements has attracted attentions from many researchers for over a century, but accurately predicting them still remains a difficult issue due to complex properties of soft clays, including plasticity, viscosity, anisotropy, soil structure and so forth. Therefore, studying the compressibility of soft clay is of significant importance. This dissertation aims to investigate the influence of plastic deviatoric strains on the compressibility of soft clays. First of all, the dissertation reviews a number of published incremental anisotropic consolidation tests on Finnish clays. The results demonstrate the dependence of soil compressibility on stress ratios. Based on the result, a modified yield surface size deviatoric softening law has been introduced. This softening law describes yield surface softening to be related to plastic deviatoric strain increments. Secondly, a new model named MEVP-DS, has been incorporated into the framework of Yin’s elaso-viscoplastic model to consider deviatoric softening, destructuration, and yield surface anisotropy of soft clay. Furthermore, the verification of MEVP-DS has been done through three phases. Phase one is the simulation of published incremental anisotropic consolidation tests on intact Finnish clay samples. The model results demonstrate MEVP-DS successfully captures the soil compressibility in response to different stress ratios. Phase two is the application of MEVP-DS in modeling 1-D consolidation tests on sensitive Champlain Sea clay. Model results highlight that using MEVP-DS is beneficial for predicting the compressibility and excess pore pressure response of the clay subject to constant rate of strain loading. Phase three is the application of MEVP-DS in simulating a real embankment dam on Champlain Sea clay. MEVP-DS not only simulates 40-year settlement measurements of the dam reasonably well, but also improves the prediction of lateral spreading of the dam. In summary, the MEVP-DS model proposed in this dissertation has shown to improve the simulation of soil compressibility of soft clays subject to 1-D, anisotropic and more complicated loading conditions.

A Deviatoric Softening Model to Simulate Compressibility Properties of Soft Clays

Soft clays are often associated with high compressibility due to their high void ratio, low shear strength, and creep behavior. Structures built on top of it can experience excessive settlement issues over a long period of time. The prediction of these settlements has attracted attentions from many researchers for over a century, but accurately predicting them still remains a difficult issue due to complex properties of soft clays, including plasticity, viscosity, anisotropy, soil structure and so forth. Therefore, studying the compressibility of soft clay is of significant importance. This dissertation aims to investigate the influence of plastic deviatoric strains on the compressibility of soft clays. First of all, the dissertation reviews a number of published incremental anisotropic consolidation tests on Finnish clays. The results demonstrate the dependence of soil compressibility on stress ratios. Based on the result, a modified yield surface size deviatoric softening law has been introduced. This softening law describes yield surface softening to be related to plastic deviatoric strain increments. Secondly, a new model named MEVP-DS, has been incorporated into the framework of Yin’s elaso-viscoplastic model to consider deviatoric softening, destructuration, and yield surface anisotropy of soft clay. Furthermore, the verification of MEVP-DS has been done through three phases. Phase one is the simulation of published incremental anisotropic consolidation tests on intact Finnish clay samples. The model results demonstrate MEVP-DS successfully captures the soil compressibility in response to different stress ratios. Phase two is the application of MEVP-DS in modeling 1-D consolidation tests on sensitive Champlain Sea clay. Model results highlight that using MEVP-DS is beneficial for predicting the compressibility and excess pore pressure response of the clay subject to constant rate of strain loading. Phase three is the application of MEVP-DS in simulating a real embankment dam on Champlain Sea clay. MEVP-DS not only simulates 40-year settlement measurements of the dam reasonably well, but also improves the prediction of lateral spreading of the dam. In summary, the MEVP-DS model proposed in this dissertation has shown to improve the simulation of soil compressibility of soft clays subject to 1-D, anisotropic and more complicated loading conditions.

Modelling the monotonic and cyclic behaviour of sands using Artificial Neural Networks

In this study artificial neural networks (ANN) are used to simulate the monotonic and cyclic behaviour of sands observed in laboratory tests on Karlsruhe sand under drained and undrained conditions. A genetic algorithm (GA) is used to obtain an optimal framework for the ANN. The results show that the proposed genetic adaptive neural network (GANN) can effectively simulate drained and undrained monotonic triaxial behaviour of saturated sand under isotropic or anisotropic consolidation. The GANN is also able to predict satisfactorily the cyclic behaviour of sands under undrained triaxial test with strain and stress cycles. In addition, GANN is able to distinguish between monotonic drained and undrained conditions by delivering a good prediction when trained with the combined database.