IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v94y2009i12p1962-1974.html
   My bibliography  Save this article

Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model

Author

Listed:
  • Ching, Jianye
  • Leu, Sou-Sen

Abstract

This paper considers a difficult but practical circumstance of civil infrastructure management—deterioration/failure data of the infrastructure system are absent while only condition-state data of its components are available. The goal is to develop a framework for estimating time-varying reliabilities of civil infrastructure facilities under such a circumstance. A novel method of analyzing time-varying condition-state data that only reports operational/non-operational status of the components is proposed to update the reliabilities of civil infrastructure facilities. The proposed method assumes that the degradation arrivals can be modeled as a Poisson process with unknown time-varying arrival rate and damage impact and that the target system can be represented as a fault-tree model. To accommodate large uncertainties, a Bayesian algorithm is proposed, and the reliability of the infrastructure system can be quickly updated based on the condition-state data. Use of the new method is demonstrated with a real-world example of hydraulic spillway gate system.

Suggested Citation

  • Ching, Jianye & Leu, Sou-Sen, 2009. "Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model," Reliability Engineering and System Safety, Elsevier, vol. 94(12), pages 1962-1974.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:12:p:1962-1974
    DOI: 10.1016/j.ress.2009.07.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832009001641
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2009.07.002?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. Suo, Qinghui & Stewart, Mark G., 2009. "Corrosion cracking prediction updating of deteriorating RC structures using inspection information," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1340-1348.
    2. Stewart, Mark G. & Al-Harthy, Ali, 2008. "Pitting corrosion and structural reliability of corroding RC structures: Experimental data and probabilistic analysis," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 373-382.
    3. Richard C. Morey, 1966. "Some Stochastic Properties of a Compound-Renewal Damage Model," Operations Research, INFORMS, vol. 14(5), pages 902-908, October.
    4. Bae, Suk Joo & Kuo, Way & Kvam, Paul H., 2007. "Degradation models and implied lifetime distributions," Reliability Engineering and System Safety, Elsevier, vol. 92(5), pages 601-608.
    5. Sudret, B., 2008. "Probabilistic models for the extent of damage in degrading reinforced concrete structures," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 410-422.
    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. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2012. "Dynamic risk analysis using bow-tie approach," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 36-44.
    2. Gomes, Wellison J.S. & Beck, André T. & Haukaas, Terje, 2013. "Optimal inspection planning for onshore pipelines subject to external corrosion," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 18-27.
    3. Liu, Aihua & Chen, Ke & Huang, Xiaofei & Li, Didi & Zhang, Xiaochun, 2021. "Dynamic risk assessment model of buried gas pipelines based on system dynamics," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    4. Muhammad Zubair & Gyunyoung Heo, 2013. "Advancement in living probabilistic safety assessment to increase safety of nuclear power plants," Journal of Risk and Reliability, , vol. 227(5), pages 534-539, October.
    5. Pei, Liang & Chen, Chen & He, Kun & Lu, Xiang, 2022. "System reliability of a gravity dam-foundation system using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    6. Xu, Gaowei & Azhari, Fae, 2022. "Data-driven optimization of repair schemes and inspection intervals for highway bridges," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    7. Sou-Sen Leu & Quang-Nha Bui, 2016. "Leak Prediction Model for Water Distribution Networks Created Using a Bayesian Network Learning Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2719-2733, June.
    8. Lam, C.Y. & Cruz, A.M., 2019. "Risk analysis for consumer-level utility gas and liquefied petroleum gas incidents using probabilistic network modeling: A case study of gas incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 198-212.
    9. Yılmaz, Emre & German, Brian J. & Pritchett, Amy R., 2023. "Optimizing resource allocations to improve system reliability via the propagation of statistical moments through fault trees," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    10. Morteza Babaei & Abbas Roozbahani & S. Mehdy Hashemy Shahdany, 2018. "Risk Assessment of Agricultural Water Conveyance and Delivery Systems by Fuzzy Fault Tree Analysis Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(12), pages 4079-4101, September.

    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. Suo, Qinghui & Stewart, Mark G., 2009. "Corrosion cracking prediction updating of deteriorating RC structures using inspection information," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1340-1348.
    2. Bigaud, David & Ali, Osama, 2014. "Time-variant flexural reliability of RC beams with externally bonded CFRP under combined fatigue-corrosion actions," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 257-270.
    3. Hariri-Ardebili, Mohammad Amin, 2020. "Safety and reliability assessment of heterogeneous concrete components in nuclear structures," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. Zhang, Jianchun & Zhao, Yu & Ma, Xiaobing, 2020. "Reliability modeling methods for load-sharing k-out-of-n system subject to discrete external load," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Ghosh, Jayadipta & Sood, Piyush, 2016. "Consideration of time-evolving capacity distributions and improved degradation models for seismic fragility assessment of aging highway bridges," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 197-218.
    6. Peihua Jiang, 2022. "Statistical Inference of Wiener Constant-Stress Accelerated Degradation Model with Random Effects," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    7. Wang, Lizhi & Pan, Rong & Li, Xiaoyang & Jiang, Tongmin, 2013. "A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 38-47.
    8. van der Weide, J.A.M. & Pandey, M.D. & van Noortwijk, J.M., 2010. "Discounted cost model for condition-based maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 236-246.
    9. Filippo De Carlo & Orlando Borgia & Mario Tucci, 2014. "Accelerated degradation tests for reliability estimation of a new product: A case study for washing machines," Journal of Risk and Reliability, , vol. 228(2), pages 127-138, April.
    10. Zhang, Jianchun & Li, Lei & Chen, Zhiwei, 2021. "Strength–redundancy allocation problem using artificial bee colony algorithm for multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    11. Wang, Jia & Bai, Guanghan & Li, Zhigang & Zuo, Ming J., 2020. "A general discrete degradation model with fatal shocks and age- and state-dependent nonfatal shocks," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    12. Lv, Ya-jun & Wang, Jun-wei & Wang, Julian & Xiong, Cheng & Zou, Liang & Li, Ly & Li, Da-wang, 2020. "Steel corrosion prediction based on support vector machines," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    13. Rougé, Charles & Mathias, Jean-Denis & Deffuant, Guillaume, 2014. "Relevance of control theory to design and maintenance problems in time-variant reliability: The case of stochastic viability," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 250-260.
    14. Liu, Di & Wang, Shaoping & Zhang, Chao & Tomovic, Mileta, 2018. "Bayesian model averaging based reliability analysis method for monotonic degradation dataset based on inverse Gaussian process and Gamma process," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 25-38.
    15. Gayathri, P. & Umesh, K. & Ganguli, R., 2010. "Effect of matrix cracking and material uncertainty on composite plates," Reliability Engineering and System Safety, Elsevier, vol. 95(7), pages 716-728.
    16. Pugliese, F. & De Risi, R. & Sarno, L. Di, 2022. "Reliability assessment of existing RC bridges with spatially-variable pitting corrosion subjected to increasing traffic demand," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    17. Wang, Changxi & Elsayed, Elsayed A., 2020. "Stochastic modeling of corrosion growth," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    18. Wang, Huan & Wang, Guan-jun & Duan, Feng-jun, 2016. "Planning of step-stress accelerated degradation test based on the inverse Gaussian process," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 97-105.
    19. Clerc, Romain & Oumouni, Mestapha & Schoefs, Franck, 2019. "SCAP-1D : A Spatial Correlation Assessment Procedure from unidimensional discrete data," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    20. Xie, Yi & Zhang, Jinsuo & Aldemir, Tunc & Denning, Richard, 2018. "Multi-state Markov modeling of pitting corrosion in stainless steel exposed to chloride-containing environment," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 239-248.

    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:94:y:2009:i:12:p:1962-1974. 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.