Sensitivity Analysis of Structural Dynamic Behavior Based on the Sparse Polynomial Chaos Expansion and Material Point Method

This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior. Physical models involving deformation, such as collisions, vibrations, and penetration, are developed using the material point method. To reduce the computational cost of Monte...

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Vydané v:Computer modeling in engineering & sciences Ročník 142; číslo 2; s. 1515 - 1543
Hlavní autori: Li, Wenpeng, Liu, Zhenghe, Ma, Yujing, Liu, Weisong, Meng, Zhuxuan, Ma, Ji, Nguyen, Vinh Phu
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Henderson Tech Science Press 2025
Predmet:
Accuracy
Adaptive algorithms
Algorithms
Civil engineering
Computational efficiency
Computing costs
Deformation
Efficiency
Finite element analysis
Greedy algorithms
Methods
Monte Carlo simulation
Polynomials
Response surface methodology
Sensitivity analysis
ISSN:1526-1506, 1526-1492, 1526-1506
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Shrnutí:This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior. Physical models involving deformation, such as collisions, vibrations, and penetration, are developed using the material point method. To reduce the computational cost of Monte Carlo simulations, response surface models are created as surrogate models for the material point system to approximate its dynamic behavior. An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order, effectively balancing the accuracy and computational efficiency of the surrogate model. Based on the sparse polynomial chaos expansion, sensitivity analysis is conducted using the global finite difference and Sobol methods. Several examples of structural dynamics are provided to demonstrate the effectiveness of the proposed method in addressing structural dynamics problems.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1526-1506
1526-1492
1526-1506
DOI:10.32604/cmes.2025.059235