scholarly journals Fuzzy-stochastic FEM-based homogenization framework for materials with polymorphic uncertainties in the microstructure

2018 ◽  
Vol 116 (9) ◽  
pp. 633-660 ◽  
Author(s):  
Dmytro Pivovarov ◽  
Thomas Oberleiter ◽  
Kai Willner ◽  
Paul Steinmann
Keyword(s):  
Stochastic Fem

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.

Probabilistic Analysis of Gun Barrel Ablation Life Based on the Modified Response Surface Model

2014 ◽  
Vol 1004-1005 ◽  
pp. 1076-1083 ◽  
Author(s):  
Wei Zhou ◽  
Jun Fang
Keyword(s):  
Response Surface ◽  
Estimation Error ◽  
Optimal Solution ◽  
Solution Space ◽  
Response Surface Model ◽  
Parameters Estimation ◽  
Surface Model ◽  
Gun Barrel ◽  
Stochastic Fem ◽  
Low Efficiency

The randomness of structural and material parameters needs to be considered in the reliability analysis of gun barrel ablation life. However, the traditional method, like Stochastic FEM sampling, results in huge computing workload and low efficiency. This paper proposed a modified response surface model for estimating the gun barrel ablation life. In which, the estimation error of the response surface model is the optimization goal. Gauss-Newton method (GNM) is used to get the optimal solution whose initial value is solved by Genetic-algorithm (GA). After that, ablation life can be calculated by the optimized response surface model. GA is effective in global solution space searching, while GNM is effective in local searching. The new method takes full advantages of both GA and GNM in parameters estimation. The simulation result shows that the combination of GA and GNM obtains a higher precision of ablation estimation and greatly improves the computational efficiency.

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