scholarly journals Multiresolution Analysis for Stochastic Finite Element Problems with Wavelet-Based Karhunen-Loève Expansion

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Carsten Proppe
Keyword(s):  
Finite Element ◽  
Random Field ◽  
Spatial Resolution ◽  
Multiresolution Analysis ◽  
Random Parameter ◽  
Wavelet Expansion ◽  
Projection Operators ◽  
Stochastic Finite Element ◽  
Truncation Level

Multiresolution analysis for problems involving random parameter fields is considered. The random field is discretized by a Karhunen-Loève expansion. The eigenfunctions involved in this representation are computed by a wavelet expansion. The wavelet expansion allows to control the spatial resolution of the problem. Fine and coarse scales are defined, and the fine scales are taken into account by projection operators. The influence of the truncation level for the wavelet expansion on the computed reliability is documented.

Stochastic finite element analysis of rockfill dam considering spatial variability of dam material porosity

2019 ◽  
Vol 36 (9) ◽  
pp. 2929-2959
Author(s):  
Hui Chen ◽  
Donghai Liu
Keyword(s):  
Finite Element ◽  
Constitutive Model ◽  
Spatial Variability ◽  
Random Field ◽  
Model Parameters ◽  
Mechanical Parameters ◽  
Stochastic Finite Element ◽  
Content Type ◽  
Rockfill Dam ◽  
Stochastic Fem

Purpose The purpose of this study is to develop a stochastic finite element method (FEM) to solve the calculation precision deficiency caused by spatial variability of dam compaction quality. Design/methodology/approach The Choleski decomposition method was applied to generate constraint random field of porosity. Large-scale laboratory triaxial tests were conducted to determine the quantitative relationship between the dam compaction quality and Duncan–Chang constitutive model parameters. Based on this developed relationship, the constraint random fields of the mechanical parameters were generated. The stochastic FEM could be conducted. Findings When the fully random field was simulated without the restriction effect of experimental data on test pits, the spatial variabilities of both displacement and stress results were all overestimated; however, when the stochastic FEM was performed disregarding the correlation between mechanical parameters, the variabilities of vertical displacement and stress results were underestimated and variation pattern for horizontal displacement also changed. In addition, the method could produce results that are closer to the actual situation. Practical implications Although only concrete-faced rockfill dam was tested in the numerical examples, the proposed method is applicable for arbitrary types of rockfill dams. Originality/value The value of this study is that the proposed method allowed for the spatial variability of constitutive model parameters and that the applicability was confirmed by the actual project.

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