Journal of Advanced Materials in Engineering (Esteghlal)

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In this research, behaviour of clayey soils under triaxial loading is studied using Neural Network. The models have been prepared to predict the stress-strain behaviour of remolded clays under undrained condition. The advantage of the model developed is that simple parameters such as physical characteristics of soils like water content, fine content, Atterberg limits and so on, are used to model the stress-strain behaviour of clays under triaxial loading, without performing exact and time-consuming tests on samples. Results from the network show that neural network is a good tool for prediction of stress-strain behaviour of clayey soils using simple physical characteristics of such soils

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In this research, stiffness of polymer-clay nanocomposites was simulated by Mori-Tanaka and two and three dimensional finite element models. Nanoclays were dispersed into polymer matrix in two ways, namely parallel and random orientations toward loading direction. Effects of microstructural parameters including volume fraction of nanoclays, elastic modulus of nanoclays and interphase, thickness of interphase, aspect ratio of nanoclays and random orientation of nanoclays on elastic modulus of the nanocomposite were investigated by finite element model. Comparing the simulation with experimental results showed that the Mori-Tanak simulation results were closer to the experimental results. Analysis of results showed that the volume fraction of nanoclay, elastic modulus of nanoclay, deviation of nanoclay layers with respect to loading direction, nanoclays aspect ratio, thickness of interphase and the elastic modulus of interphase had respectively the most to the least effect on elastic modulus of nanocomposite.