A Prediction Method Based on Monte Carlo Simulations for Finite Element Analysis of Soil Medium considering Spatial Variability in Soil Parameters

• Published in: Advances in materials science and engineering Vol. 2020; no. 2020; pp. 1 - 10
• Main Authors: Tang, Kedong, Li, Lielie, Wang, Jialiang
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 2020; Hindawi; Hindawi Limited; Wiley
• Subjects: Computer simulation; Computing costs; Convergence; Fields (mathematics); Finite element analysis; Finite element method; Interpolation; Investigations; Mathematical analysis; Measurement techniques; Methods; Monte Carlo simulation; Normal distribution; Parameters; Random variables; Safety margins; Soil analysis; Soil properties; Soils; Standard deviation; Stochastic processes
• ISSN: 1687-8434; 1687-8442
• DOI: 10.1155/2020/7064640

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.