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A new effective screening design for structural sensitivity analysis of failure probability with the epistemic uncertainty

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  • Xiao, Sinan
  • Lu, Zhenzhou
  • Xu, Liyang

Abstract

In this paper, two new sampling strategies are proposed to estimate the Morris’ screening sensitivity measure and its improved version. The two new sampling strategies, which employ random sampling and quasi-random sampling respectively, compute the elementary effects of each factor at the same initial point and with a same step size in the input space. The new quasi-random sampling strategy performs better than the radial based sampling strategy and the new random sampling strategy performs almost the same with the radial based sampling strategy. Then, the improved version of the Morris’ screening sensitivity measure is applied to estimate the effects of the epistemic uncertainty of random variables’ distribution parameters on the failure probability using the new quasi-random sampling strategy. During this process, the principle of maximum entropy, fractional moments and dimension reduction method are used to estimate the failure probability with a good accuracy and a low computational demand. Several examples are employed to demonstrate the reasonability and the efficiency of the proposed strategy.

Suggested Citation

  • Xiao, Sinan & Lu, Zhenzhou & Xu, Liyang, 2016. "A new effective screening design for structural sensitivity analysis of failure probability with the epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 1-14.
    • Handle: RePEc:eee:reensy:v:156:y:2016:i:c:p:1-14
    DOI: 10.1016/j.ress.2016.07.014
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    References listed on IDEAS

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    5. Sudret, B. & Mai, C.V., 2015. "Computing derivative-based global sensitivity measures using polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 241-250.
    6. Ratto, M. & Pagano, A. & Young, P.C., 2009. "Non-parametric estimation of conditional moments for sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 237-243.
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    Citations

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    Cited by:

    1. Sinan Xiao & Zhenzhou Lu & Pan Wang, 2018. "Multivariate Global Sensitivity Analysis Based on Distance Components Decomposition," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2703-2721, December.
    2. Wu, Zeping & Wang, Wenjie & Wang, Donghui & Zhao, Kun & Zhang, Weihua, 2019. "Global sensitivity analysis using orthogonal augmented radial basis function," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 291-302.
    3. Shi, Wen & Chen, Xi, 2019. "Controlled Morris method: A new factor screening approach empowered by a distribution-free sequential multiple testing procedure," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 299-314.
    4. Deng, Jian, 2022. "Probabilistic characterization of soil properties based on the maximum entropy method from fractional moments: Model development, case study, and application," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    5. Chen, Jun-Yu & Feng, Yun-Wen & Teng, Da & Lu, Cheng & Fei, Cheng-Wei, 2022. "Support vector machine-based similarity selection method for structural transient reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    6. Yogesh P. Khare & Rajendra Paudel & Ruscena Wiederholt & Anteneh Z. Abiy & Thomas Van Lent & Stephen E. Davis & Younggu Her, 2021. "Watershed Response to Legacy Phosphorus and Best Management Practices in an Impacted Agricultural Watershed in Florida, U.S.A," Land, MDPI, vol. 10(9), pages 1-22, September.
    7. Zdeněk Kala, 2020. "Sensitivity Analysis in Probabilistic Structural Design: A Comparison of Selected Techniques," Sustainability, MDPI, vol. 12(11), pages 1-19, June.

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