Open AccessA Prediction Method Based on Monte Carlo Simulations for Finite Element Analysis of Soil Medium considering Spatial Variability in Soil Parameters
Author(s) -
Kedong Tang,
Jialiang Wang,
Lielie Li
Publication year - 2020
Publication title -
advances in materials science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 42
eISSN - 1687-8442
pISSN - 1687-8434
DOI - 10.1155/2020/7064640
Subject(s) - monte carlo method , finite element method , interpolation (computer graphics) , convergence (economics) , multivariate interpolation , mathematical optimization , computer science , mathematics , algorithm , structural engineering , engineering , statistics , animation , computer graphics (images) , computer vision , economics , bilinear interpolation , economic growth
With the Stochastic Finite Element Method (SFEM), the spatial variability of soil properties can be incorporated into the analysis of geotechnical structures. Although this method is significantly superior in principle to the homogeneous analysis of soil parameters, generalizing the method in engineering practice is difficult due to its computational inefficiency. In this paper, we propose a new method for the fast calculation of convergence results. The proposed method introduces a distance space to the Monte Carlo Method (MCM) random field instances and, considering the importance of a safety margin in structures, uses selected spatial interpolation to predict the MCM instances to be solved. Two case study simulations are presented. The results show that compared to the full Monte Carlo Simulation, the fast calculation method proposed in this paper can achieve very accurate convergence results while substantially reducing the computational cost, and the simulation errors for the structure are on the safer side.