IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v178y2018icp55-68.html
   My bibliography  Save this article

Experimental estimation of time variant system reliability of vibrating structures based on subset simulation with Markov chain splitting

Author

Listed:
  • Sonal, S.D.
  • Ammanagi, S
  • Kanjilal, O
  • Manohar, C.S.

Abstract

The study investigates the application of ideas from variance reduction schemes, developed in the area of computational structural reliability modelling, to the problems of experimental estimation of time variant reliability of randomly excited vibrating structures. The study considers series/parallel system reliability of vibrating systems under multi-component random excitations. An experimental protocol, based on subset simulation with Markov chain splitting, is proposed to estimate probabilities of failure as low as 10−5 to 10−4 with a relatively smaller number of samples and hence with reduced test times. Illustrative examples consist of earthquake shake table studies on a three-storied bending-torsion coupled building frame under bi-axial nonstationary, random earthquake support motions.

Suggested Citation

  • Sonal, S.D. & Ammanagi, S & Kanjilal, O & Manohar, C.S., 2018. "Experimental estimation of time variant system reliability of vibrating structures based on subset simulation with Markov chain splitting," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 55-68.
    • Handle: RePEc:eee:reensy:v:178:y:2018:i:c:p:55-68
    DOI: 10.1016/j.ress.2018.05.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017306373
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2018.05.007?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. Li, Yuyin & Zhang, Yahui & Kennedy, David, 2018. "Reliability analysis of subsea pipelines under spatially varying ground motions by using subset simulation," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 74-83.
    2. Smith, Curtis & Kelly, Dana & Dezfuli, Homayoon, 2010. "Probability-informed testing for reliability assurance through Bayesian hypothesis methods," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 361-368.
    3. Awad, Mahmoud, 2016. "Economic allocation of reliability growth testing using Weibull distributions," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 273-280.
    4. Lambros Katafygiotis & Sai Hung Cheung & Ka-Veng Yuen, 2010. "Spherical subset simulation (S³) for solving non-linear dynamical reliability problems," International Journal of Reliability and Safety, Inderscience Enterprises Ltd, vol. 4(2/3), pages 122-138.
    5. Ahmed, Hussam & Chateauneuf, Alaa, 2014. "Optimal number of tests to achieve and validate product reliability," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 242-250.
    6. Zdravko I. Botev & Dirk P. Kroese, 2008. "An Efficient Algorithm for Rare-event Probability Estimation, Combinatorial Optimization, and Counting," Methodology and Computing in Applied Probability, Springer, vol. 10(4), pages 471-505, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jian Wang & Xiang Gao & Zhili Sun, 2021. "A Multilevel Simulation Method for Time-Variant Reliability Analysis," Sustainability, MDPI, vol. 13(7), pages 1-16, March.
    2. Zhang, Yu & Dong, You & Frangopol, Dan M., 2024. "An error-based stopping criterion for spherical decomposition-based adaptive Kriging model and rare event estimation," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    3. Jian Wang & Xiang Gao & Zhili Sun, 2021. "An Importance Sampling Framework for Time-Variant Reliability Analysis Involving Stochastic Processes," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    4. Qian, Hua-Ming & Li, Yan-Feng & Huang, Hong-Zhong, 2021. "Time-variant system reliability analysis method for a small failure probability problem," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    5. Jiang, Chen & Qiu, Haobo & Yang, Zan & Chen, Liming & Gao, Liang & Li, Peigen, 2019. "A general failure-pursuing sampling framework for surrogate-based reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 47-59.
    6. Wang, Zhonglai & Liu, Jing & Yu, Shui, 2020. "Time-variant reliability prediction for dynamic systems using partial information," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    7. Du, Weiqi & Luo, Yuanxin & Wang, Yongqin, 2019. "Time-variant reliability analysis using the parallel subset simulation," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 250-257.

    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. Khalil, Y.F., 2019. "New statistical formulations for determination of qualification test plans of safety instrumented systems (SIS) subject to low/high operational demands," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 196-209.
    2. Yu, Weichao & Huang, Weihe & Wen, Kai & Zhang, Jie & Liu, Hongfei & Wang, Kun & Gong, Jing & Qu, Chunxu, 2021. "Subset simulation-based reliability analysis of the corroding natural gas pipeline," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. Mobin, Mohammadsadegh & Li, Zhaojun & Cheraghi, S. Hossein & Wu, Gongyu, 2019. "An approach for design Verification and Validation planning and optimization for new product reliability improvement," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    4. Reuven Rubinstein, 2009. "The Gibbs Cloner for Combinatorial Optimization, Counting and Sampling," Methodology and Computing in Applied Probability, Springer, vol. 11(4), pages 491-549, December.
    5. Li, Chao & Diao, Yucheng & Li, Hong-Nan & Pan, Haiyang & Ma, Ruisheng & Han, Qiang & Xing, Yihan, 2023. "Seismic performance assessment of a sea-crossing cable-stayed bridge system considering soil spatial variability," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Wei Wang & Yaofeng Xu & Liguo Hou, 2019. "Optimal allocation of test times for reliability growth testing with interval-valued model parameters," Journal of Risk and Reliability, , vol. 233(5), pages 791-802, October.
    7. Bansal, Sahil & Cheung, Sai Hung, 2017. "On the evaluation of multiple failure probability curves in reliability analysis with multiple performance functions," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 583-594.
    8. Rufo, M.J. & Martín, J. & Pérez, C.J., 2016. "A Bayesian negotiation model for quality and price in a multi-consumer context," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 132-141.
    9. Paul Dupuis & Bahar Kaynar & Ad Ridder & Reuven Rubinstein & Radislav Vaisman, 2011. "Counting with Combined Splitting and Capture-Recapture Methods," Tinbergen Institute Discussion Papers 11-062/4, Tinbergen Institute.
    10. Peng, Yizhen & Wang, Yu & Zi, YanYang & Tsui, Kwok-Leung & Zhang, Chuhua, 2017. "Dynamic reliability assessment and prediction for repairable systems with interval-censored data," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 301-309.
    11. Kleijnen, Jack P.C. & Ridder, A.A.N. & Rubinstein, R.Y., 2010. "Variance Reduction Techniques in Monte Carlo Methods," Other publications TiSEM 87680d1a-53c1-4107-ada4-7, Tilburg University, School of Economics and Management.
    12. Li, Zhengbing & Feng, Huixia & Liang, Yongtu & Xu, Ning & Nie, Siming & Zhang, Haoran, 2019. "A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo," International Journal of Critical Infrastructure Protection, Elsevier, vol. 27(C).
    13. Nafissa Jibet & Pascal Le Masson & Benoit Weil & Blandine Chazelle & Dominique Laousse, 2023. "Renovating engineering departements' creation heritage to meet contemporary challenges: frugal validation patterns and constructive proof logics for new engineering rules," Post-Print hal-04074841, HAL.
    14. Hao Ma & Henk A. P. Blom, 2022. "Random Assignment Versus Fixed Assignment in Multilevel Importance Splitting for Estimating Stochastic Reach Probabilities," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 2313-2338, December.
    15. Ali Eshragh & Jerzy Filar & Michael Haythorpe, 2011. "A hybrid simulation-optimization algorithm for the Hamiltonian cycle problem," Annals of Operations Research, Springer, vol. 189(1), pages 103-125, September.
    16. Pang, Rui & Zai, Dezhi & Xu, Bin & Liu, Jun & Zhao, Chunfeng & Fan, Qunying & Chen, Yuting, 2023. "Stochastic dynamic and reliability analysis of AP1000 nuclear power plants via DPIM subjected to mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    17. Qibin Duan & Dirk P. Kroese, 2018. "Splitting for Multi-objective Optimization," Methodology and Computing in Applied Probability, Springer, vol. 20(2), pages 517-533, June.
    18. Turati, Pietro & Pedroni, Nicola & Zio, Enrico, 2016. "Advanced RESTART method for the estimation of the probability of failure of highly reliable hybrid dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 117-126.
    19. Radislav Vaisman & Dirk P. Kroese, 2017. "Stochastic Enumeration Method for Counting Trees," Methodology and Computing in Applied Probability, Springer, vol. 19(1), pages 31-73, March.
    20. Heydari, Mohammadhossein & Sullivan, Kelly M., 2019. "Robust allocation of testing resources in reliability growth," Reliability Engineering and System Safety, Elsevier, vol. 192(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:178:y:2018:i:c:p:55-68. 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.