Efficient Reliability Evaluation of Axially Loaded Piles in Spatially Varying Soils Using Importance Sampling: Fid-Bau Portal

Efficient Reliability Evaluation of Axially Loaded Piles in Spatially Varying Soils Using Importance Sampling

Fan, Haijian / Liang, Robert

In reliability analysis, the crude Monte Carlo method is known to be computationally demanding. To improve computational efficiency, this paper presents an importance sampling-based algorithm that can be applied to conduct efficient reliability evaluation for axially loaded piles. The spatial variability of soil properties along the pile length is considered by random field modeling, in which a mean, a variance, and a correlation length are used to statistically characterize a random field. In each realization, the random fields are used as inputs to the well-established load transfer method to evaluate the load-displacement behavior of an axially loaded pile. Failure is defined as the event where the vertical movement at the pile top exceeds the allowable displacement. By sampling more heavily from the region of interest and then scaling the indicator function back by a ratio of probability densities, a faster rate of convergence can be achieved in the proposed algorithm. An example is given to demonstrate the accuracy and the efficiency of the proposed method. It is shown that the estimate based on the proposed method is unbiased. Furthermore, the size of samples can be greatly reduced in the developed method.