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Structural Reliability Analysis via the Multivariate Gegenbauer Polynomial-Based Sparse Surrogate Model

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  • Yixuan Dong
  • Shijie Wang

Abstract

Structural reliability analysis is usually realized based on a multivariate performance function that depicts failure mechanisms of a structural system. The intensively computational cost of the brutal-force Monte-Carlo simulation motivates proposing a Gegenbauer polynomial-based surrogate model for effective structural reliability analysis in this paper. By utilizing the orthogonal matching pursuit algorithm to detect significant explanatory variables at first, a small number of samples are used to determine a reliable approximation result of the structural performance function. Several numerical examples in the literature are presented to demonstrate potential applications of the Gegenbauer polynomial-based sparse surrogate model. Accurate results have justified the effectiveness of the proposed approach in dealing with various structural reliability problems.

Suggested Citation

  • Yixuan Dong & Shijie Wang, 2021. "Structural Reliability Analysis via the Multivariate Gegenbauer Polynomial-Based Sparse Surrogate Model," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-16, October.
    • Handle: RePEc:hin:jnlmpe:8575107
    DOI: 10.1155/2021/8575107
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