IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v242y2024ics0951832023007081.html
   My bibliography  Save this article

Reliability-oriented global sensitivity analysis using subset simulation and space partition

Author

Listed:
  • Ma, Yuan-Zhuo
  • Jin, Xiang-Xiang
  • Zhao, Xiang
  • Li, Hong-Shuang
  • Zhao, Zhen-Zhou
  • Xu, Chang

Abstract

This paper presents a novel reliability-oriented global sensitivity analysis method using the Subset Simulation (SS) method and the Space Partition (SP) scheme. It can exploit the inherent information of uncertainty within all the conditional samples in each simulation level of SS along the spirit of the SP scheme. The reasoning of the first order indices is firstly provided, followed by a heuristic study on the influence of parametric settings upon the statistical properties of the indices. By extending the calculation process to the higher order indices and formally optimizing the partition scheme considering the coefficient of variation of all the indices, the framework of the proposed reliability-oriented global sensitivity for arbitrary order of indices can be formed. The performance of the direct Monte Carlo method, the Quasi-Monte Carlo method, SP and the proposed method is compared through three numerical examples and two engineering applications, to demonstrate the merits of the proposed one.

Suggested Citation

  • Ma, Yuan-Zhuo & Jin, Xiang-Xiang & Zhao, Xiang & Li, Hong-Shuang & Zhao, Zhen-Zhou & Xu, Chang, 2024. "Reliability-oriented global sensitivity analysis using subset simulation and space partition," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:reensy:v:242:y:2024:i:c:s0951832023007081
    DOI: 10.1016/j.ress.2023.109794
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023007081
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109794?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tabandeh, Armin & Sharma, Neetesh & Gardoni, Paolo, 2022. "Uncertainty propagation in risk and resilience analysis of hierarchical systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    2. 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.
    3. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
    4. Marrel, Amandine & Chabridon, Vincent, 2021. "Statistical developments for target and conditional sensitivity analysis: Application on safety studies for nuclear reactor," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    5. Derennes, Pierre & Morio, Jérôme & Simatos, Florian, 2021. "Simultaneous estimation of complementary moment independent and reliability-oriented sensitivity measures," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 721-737.
    6. Sarazin, Gabriel & Morio, Jérôme & Lagnoux, Agnès & Balesdent, Mathieu & Brevault, Loïc, 2021. "Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    7. Barr, John & Rabitz, Herschel, 2023. "Kernel-based global sensitivity analysis obtained from a single data set," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    8. Shi, Wen & Zhou, Qing & Zhou, Yanju, 2023. "An efficient elementary effect-based method for sensitivity analysis in identifying main and two-factor interaction effects," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    9. Yuan, Xiukai & Qian, Yugeng & Chen, Jingqiang & Faes, Matthias G.R. & Valdebenito, Marcos A. & Beer, Michael, 2023. "Global failure probability function estimation based on an adaptive strategy and combination algorithm," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    10. Wei, Pengfei & Lu, Zhenzhou & Yuan, Xiukai, 2013. "Monte Carlo simulation for moment-independent sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 110(C), pages 60-67.
    11. Jung, WoongHee & Taflanidis, Alexandros A., 2023. "Efficient global sensitivity analysis for high-dimensional outputs combining data-driven probability models and dimensionality reduction," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    12. Ökten, Giray & Liu, Yaning, 2021. "Randomized quasi-Monte Carlo methods in global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    13. Lambert, Romain S.C. & Lemke, Frank & Kucherenko, Sergei S. & Song, Shufang & Shah, Nilay, 2016. "Global sensitivity analysis using sparse high dimensional model representations generated by the group method of data handling," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 128(C), pages 42-54.
    14. Ballester-Ripoll, Rafael & Leonelli, Manuele, 2022. "Computing Sobol indices in probabilistic graphical models," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    15. Wang, Zhenqiang & Jia, Gaofeng, 2023. "Extended sample-based approach for efficient sensitivity analysis of group of random variables," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    16. Vuillod, Bruno & Montemurro, Marco & Panettieri, Enrico & Hallo, Ludovic, 2023. "A comparison between Sobol’s indices and Shapley’s effect for global sensitivity analysis of systems with independent input variables," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    17. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
    18. Storlie, Curtis B. & Swiler, Laura P. & Helton, Jon C. & Sallaberry, Cedric J., 2009. "Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1735-1763.
    19. Zhai, Qingqing & Yang, Jun & Zhao, Yu, 2014. "Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 66-82.
    20. 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.
    21. Takeda, Satoshi & Kitada, Takanori, 2023. "Importance measure evaluation based on sensitivity coefficient for probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    22. Zdeněk Kala, 2021. "New Importance Measures Based on Failure Probability in Global Sensitivity Analysis of Reliability," Mathematics, MDPI, vol. 9(19), pages 1-20, September.
    23. Straub, Daniel & Ehre, Max & Papaioannou, Iason, 2022. "Decision-theoretic reliability sensitivity," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    24. Azzini, Ivano & Rosati, Rossana, 2021. "Sobol’ main effect index: an Innovative Algorithm (IA) using Dynamic Adaptive Variances," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    25. Antoniadis, Anestis & Lambert-Lacroix, Sophie & Poggi, Jean-Michel, 2021. "Random forests for global sensitivity analysis: A selective review," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    26. Li, Chenzhao & Mahadevan, Sankaran, 2016. "An efficient modularized sample-based method to estimate the first-order Sobol׳ index," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 110-121.
    27. Ehre, Max & Papaioannou, Iason & Straub, Daniel, 2020. "A framework for global reliability sensitivity analysis in the presence of multi-uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    28. Andrea Saltelli, 2002. "Sensitivity Analysis for Importance Assessment," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 579-590, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yun, Wanying & Lu, Zhenzhou & Feng, Kaixuan & Li, Luyi, 2019. "An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 99-108.
    2. Tatsuya Sakurahara & Seyed Reihani & Ernie Kee & Zahra Mohaghegh, 2020. "Global importance measure methodology for integrated probabilistic risk assessment," Journal of Risk and Reliability, , vol. 234(2), pages 377-396, April.
    3. Barr, John & Rabitz, Herschel, 2023. "Kernel-based global sensitivity analysis obtained from a single data set," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    4. Jung, WoongHee & Taflanidis, Alexandros A., 2023. "Efficient global sensitivity analysis for high-dimensional outputs combining data-driven probability models and dimensionality reduction," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    5. Derennes, Pierre & Morio, Jérôme & Simatos, Florian, 2019. "A nonparametric importance sampling estimator for moment independent importance measures," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 3-16.
    6. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
    7. Vuillod, Bruno & Montemurro, Marco & Panettieri, Enrico & Hallo, Ludovic, 2023. "A comparison between Sobol’s indices and Shapley’s effect for global sensitivity analysis of systems with independent input variables," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    8. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    9. Zhang, Kaichao & Lu, Zhenzhou & Cheng, Kai & Wang, Laijun & Guo, Yanling, 2020. "Global sensitivity analysis for multivariate output model and dynamic models," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    10. Derennes, Pierre & Morio, Jérôme & Simatos, Florian, 2021. "Simultaneous estimation of complementary moment independent and reliability-oriented sensitivity measures," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 721-737.
    11. Xiong, Qingwen & Du, Peng & Deng, Jian & Huang, Daishun & Song, Gongle & Qian, Libo & Wu, Zenghui & Luo, Yuejian, 2022. "Global sensitivity analysis for nuclear reactor LBLOCA with time-dependent outputs," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    12. Cheng, Lei & Lu, Zhenzhou & Zhang, Leigang, 2015. "Application of Rejection Sampling based methodology to variance based parametric sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 9-18.
    13. Wenbin Ruan & Zhenzhou Lu & Longfei Tian, 2013. "A modified variance-based importance measure and its solution by state dependent parameter," Journal of Risk and Reliability, , vol. 227(1), pages 3-15, February.
    14. Wenbin Ruan & Zhenzhou Lu & Pengfei Wei, 2013. "Estimation of conditional moment by moving least squares and its application for importance analysis," Journal of Risk and Reliability, , vol. 227(6), pages 641-650, December.
    15. Yun, Wanying & Lu, Zhenzhou & Jiang, Xian, 2019. "An efficient method for moment-independent global sensitivity analysis by dimensional reduction technique and principle of maximum entropy," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 174-182.
    16. Luo, Xiaopeng & Lu, Zhenzhou & Xu, Xin, 2014. "Non-parametric kernel estimation for the ANOVA decomposition and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 140-148.
    17. Zhou, Changcong & Shi, Zhuangke & Kucherenko, Sergei & Zhao, Haodong, 2022. "A unified approach for global sensitivity analysis based on active subspace and Kriging," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    18. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    19. Tong, Ming-Na & Zhao, Yan-Gang & Lu, Zhao-Hui, 2021. "Normal transformation for correlated random variables based on L-moments and its application in reliability engineering," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    20. Straub, Daniel & Ehre, Max & Papaioannou, Iason, 2022. "Decision-theoretic reliability sensitivity," Reliability Engineering and System Safety, Elsevier, vol. 221(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:242:y:2024:i:c:s0951832023007081. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.