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  • Open Access


    AWK-TIS: An Improved AK-IS Based on Whale Optimization Algorithm and Truncated Importance Sampling for Reliability Analysis

    Qiang Qin1,2,*, Xiaolei Cao1, Shengpeng Zhang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1457-1480, 2023, DOI:10.32604/cmes.2023.022078

    Abstract In this work, an improved active kriging method based on the AK-IS and truncated importance sampling (TIS) method is proposed to efficiently evaluate structural reliability. The novel method called AWK-TIS is inspired by AK-IS and RBF-GA previously published in the literature. The innovation of the AWK-TIS is that TIS is adopted to lessen the sample pool size significantly, and the whale optimization algorithm (WOA) is employed to acquire the optimal Kriging model and the most probable point (MPP). To verify the performance of the AWK-TIS method for structural reliability, four numerical cases which are utilized as benchmarks in literature and… More >

  • Open Access


    Active Kriging-Based Adaptive Importance Sampling for Reliability and Sensitivity Analyses of Stator Blade Regulator

    Hong Zhang1, Lukai Song1,2,*, Guangchen Bai1

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1871-1897, 2023, DOI:10.32604/cmes.2022.021880


    The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like high-nonlinearity, multi-failure regions, and small failure probability, which brings in unacceptable computing efficiency and accuracy of the current analysis methods. In this case, by fitting the implicit limit state function (LSF) with active Kriging (AK) model and reducing candidate sample pool with adaptive importance sampling (AIS), a novel AK-AIS method is proposed. Herein, the AK model and Markov chain Monte Carlo (MCMC) are first established to identify the most probable failure region(s) (MPFRs), and the adaptive kernel density estimation (AKDE) importance sampling function is constructed to… More >

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