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| Probabilistic Collocation Method for geotechnical stochastic field and response analysis |
| Received:November 27, 2013 Revised:January 22, 2014 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx201501011 |
| KeyWord:Probabilistic Collocation Method Mento Carlo geotechnical parameter stochastic field |
| Author | Institution |
| 申林方 |
昆明理工大学 建筑工程学院, 昆明 ;北京大学 工学院, 北京 |
| 王志良 |
昆明理工大学 建筑工程学院, 昆明 |
| 常海滨 |
北京大学 工学院, 北京 |
| 李邵军 |
中国科学院 武汉岩土力学研究所, 武汉 |
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| Abstract: |
| Probabilistic Collocation Method (PCM) is an effective way for uncertainty analysis.The input stochastic field is represented by Karhunen-Loeve expansion in terms of a set of independent standard random variables.The output field is approximated using polynomial chaos expansion with the same sets of standard random variables.The value of the sets of standard random variables known as collocation points are determined through certain algorithm.Then let the residual be zero at these given collocation points,therefore the stochastic problem can be simplified to a deterministic problem.And the software for solving deterministic equation could be employed directly.Polynomial expansion coefficients which stand for the statistical property of output can be obtained by solving a set of linear equations.This paper introduces PCM into geotechnical parameter field analysis.The bulk modulus is the input random field,and the displacement is the output random field.Elastic and plastic deformations are investigated under these stochastic field.Results indicate that the PCM greatly reduces the difficulty for solving random problems.Meanwhile,compared with Mento Carlo,PCM is less time-consuming with higher efficiency which exhibits obvious superiority. |