Abstract ▼ AI-Helper

A stochastic numerical model for predictions of differential settlement of foundation soils is developed in this thesis. The differential settlement is highly dependent on the spatial variability of elastic modulus of soil. The Kriging method is used to account for the spatial variability of the ela...

A stochastic numerical model for predictions of differential settlement of foundation soils is developed in this thesis. The differential settlement is highly dependent on the spatial variability of elastic modulus of soil. The Kriging method is used to account for the spatial variability of the elastic modulus. This technique provides the best linear unbiased estimator of a parameter and its minium variance from a limited number of measured data. The stochastic finite element method, employing the first-order second-moment analysis for computations of error propagation, is used to obtain the means, variances, and covarainces of nodal displacements. Finally, a reliability model of differential settlement is proposed by using the results of the stochastic FEM analysis. It is found that maximum differential settlement occurs when the distance between two foundations is approximately same with the scale of fluctuation in horizontal direction, and the probability that differential settlement exceeds the allowable value might be significant.

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