Probabilistic analysis of strip footings resting on spatially varying soils using kriging metamodeling and importance sampling

Abstract

Abstract This paper aims at computing the probability of failure of strip footings resting on a spatially varying soil and subjected to a vertical load. The active learning reliability method (called AK-IS) which is a combination of kriging metamodeling and importance sampling (IS) is used. The AK-IS technique significantly reduces the computation time with respect to the classical active learning reliability technique (called AK-MCS) combining kriging with Monte Carlo Simulations (MCS) by sampling around the design point. It was shown that the critical realization corresponding to the design point exhibits a perfect symmetry about the central vertical axis of the foundation.