Effect of spatial variability of cross-correlated soil properties on bearing capacity of strip footing

Geotechnical engineering problems are characterized by many Sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for it probabilistic analysis that considers the spatial variability of cross-correlated soil properties is presented and applied to Study the bearing capacity of spatially random soil with different autocorrelation distances in the vertical and horizontal directions. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two-dimensional cross-correlated non-Gaussian random fields are generated based on a Karhunen-Loeve expansion in a manner consistent with a specified marginal distribution function, an autocorrelation function, and cross-correlation coefficients. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses was performed to study the effects Of uncertainty due to the spatial heterogeneity on the bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to geotechnical problems and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment. Copyright (C) 2009 John Wiley & Sons, Ltd.