A novel univariate dimension‐reduction based interval finite element method for static response prediction of uncertain structures

Author:

Zhao Heng1ORCID,Li Feng1ORCID,Xu Qianhui1,Pei Chunyan1

Affiliation:

1. School of Mechanical and Aerospace Engineering Jilin University Changchun China

Abstract

AbstractTo eliminate the errors caused by the conventional interval perturbation finite element method due to classic interval arithmetic and neglect of higher‐order terms, we propose a novel univariate dimension‐reduction based interval finite element method to predict the static response bounds of structures with uncertain but bounded parameters. First, a univariate dimension‐reduction algorithm is derived using the generalized Taylor expansion. The global stiffness matrix is expressed as the sum of the median and the univariate disturbance radius. Compared with Taylor expansion approximation, the univariate dimension‐reduction approximation has higher accuracy and does not increase the amount of calculation. Then the inverse of the interval global stiffness matrix is approximated as an improved Neumann series. Higher‐ order terms are included by summing up the geometric terms in the Neumann series. Finally, the improved interval algorithm is used to solve the upper and lower bounds of the structural displacement response and the element stress response. The dependence between the interval parameters is accounted in comparison with the classic interval algorithm. The accuracy and effectiveness of the new method are validated by numerical cases on 2D truss, 3D frame and truck frame with multiple interval parameters.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Applied Mathematics,General Engineering,Numerical Analysis

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An ɛ-accelerated bivariate dimension-reduction interval finite element method;Computer Methods in Applied Mechanics and Engineering;2024-03

2. Identification of Interval Discrete Models based on the Bee Swarm Optimization Algorithm with Adaptive Tuning of the Probability of Selecting Structural Elements;2023 13th International Conference on Advanced Computer Information Technologies (ACIT);2023-09-21

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