A new stochastic residual error based homotopy approach for stability analysis of structures with large fluctuation of random parameters. (14th September 2022)

• Record Type: Journal Article
• Authors: Zhang, Heng; Huang, Bin; Liu, Yuhao; Xiang, Xu; Wu, Zhifeng
• Is Part Of: International journal for numerical methods in engineering. Volume 124:Number 1(2023)
• Page Start: 183
• Page End: 216
• Publication Date: 2022-09-14
• Subjects: buckling load -- homotopy analysis method -- perturbation method -- stochastic finite element method -- stochastic residual error; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 620.001518
• DOI: 10.1002/nme.7117
• Languages: English
• ISSNs: 0029-5981

Abstract

Abstract: The large fluctuation of uncertain parameters introduces a great challenge in the stability analysis of structures. To address this problem, a novel stochastic residual error based homotopy method is proposed in this article. This new method used the concept of homotopy to reconstruct a new governing equation for stochastic elastic buckling analysis, and the closed‐form solutions of the isolated buckling eigenvalues and eigenvectors are obtained by the stochastic homotopy analysis method. On this basis, a p th order origin moment of the stochastic residual error with respect to the elastic buckling equation is defined. Then, the optimal form of the homotopy series can be determined automatically by minimizing the p th order origin moment, which overcomes the disadvantage of highly relying on sample values of the existing homotopy stochastic finite element method. Moreover, the proposed method is developed to deal with the stochastic closely spaced buckling eigenvalue problem. Three mathematical examples and three buckling eigenvalue examples, including a variable cross‐section column, a 7‐story frame, and a Kiewitt single‐layer latticed spherical shell, are performed to illustrate the accuracy and effectiveness of the proposed method by comparing with the existing methods when dealing with large fluctuation of random parameters.