The study mainly deals with the stochastic variability of soil properties, but also addresses other uncertainties affecting geotechnical design. Methods for (1) field data analysis for estimating the probabilistic characteristics of spatial variability, and (2) digital simulation of non-Gaussian random fields representing the stochastic distribution of various soil properties are proposed. Monte Carlo simulations of soil liquefaction are performed for a saturated soil deposit subjected to seismic excitation, and the predicted excess pore pressures are compared with similar results obtained from deterministic analyses. It is concluded that a more realistic pattern of soil liquefaction occurrence, and higher pore water pressure build-up are predicted if the stochastic variability of soil properties is accounted for.
|Geotechnical Special Publication
|Published - Dec 1 1996
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Building and Construction
- Geotechnical Engineering and Engineering Geology