IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v93y2008i11p1616-1627.html
   My bibliography  Save this article

Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability

Author

Listed:
  • Bucci, Paolo
  • Kirschenbaum, Jason
  • Mangan, L. Anthony
  • Aldemir, Tunc
  • Smith, Curtis
  • Wood, Ted

Abstract

While the event-tree (ET)/fault-tree (FT) methodology is the most popular approach to probability risk assessment (PRA), concerns have been raised in the literature regarding its potential limitations in the reliability modeling of dynamic systems. Markov reliability models have the ability to capture the statistical dependencies between failure events that can arise in complex dynamic systems. A methodology is presented that combines Markov modeling with the cell-to-cell mapping technique (CCMT) to construct dynamic ETs/FTs and addresses the concerns with the traditional ET/FT methodology. The approach is demonstrated using a simple water level control system. It is also shown how the generated ETs/FTs can be incorporated into an existing PRA so that only the (sub)systems requiring dynamic methods need to be analyzed using this approach while still leveraging the static model of the rest of the system.

Suggested Citation

  • Bucci, Paolo & Kirschenbaum, Jason & Mangan, L. Anthony & Aldemir, Tunc & Smith, Curtis & Wood, Ted, 2008. "Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1616-1627.
    • Handle: RePEc:eee:reensy:v:93:y:2008:i:11:p:1616-1627
    DOI: 10.1016/j.ress.2008.01.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832008000343
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2008.01.008?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. David K. Backus & Bryan R. Routledge & Stanley E. Zin, 2005. "Exotic Preferences for Macroeconomists," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 319-414, National Bureau of Economic Research, Inc.
    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. KIM, Junyung & ZHAO, Xingang & SHAH, Asad Ullah Amin & KANG, Hyun Gook, 2021. "System risk quantification and decision making support using functional modeling and dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    2. 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.
    3. Kim, Junyung & Shah, Asad Ullah Amin & Kang, Hyun Gook, 2020. "Dynamic risk assessment with bayesian network and clustering analysis," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    4. Zengkai Liu & Yonghong Liu & Baoping Cai, 2014. "Reliability Analysis of the Electrical Control System of Subsea Blowout Preventers Using Markov Models," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    5. Park, Jong Woo & Lee, Seung Jun, 2022. "Simulation optimization framework for dynamic probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    6. Wu, Xingguang & Huang, Huirong & Xie, Jianyu & Lu, Meixing & Wang, Shaobo & Li, Wang & Huang, Yixuan & Yu, Weichao & Sun, Xiaobo, 2023. "A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. Bjorkman, Kim, 2013. "Solving dynamic flowgraph methodology models using binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 206-216.
    8. Wu, Daohua & Zheng, Wei, 2018. "Formal model-based quantitative safety analysis using timed Coloured Petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 62-79.
    9. Aldemir, T. & Guarro, S. & Mandelli, D. & Kirschenbaum, J. & Mangan, L.A. & Bucci, P. & Yau, M. & Ekici, E. & Miller, D.W. & Sun, X. & Arndt, S.A., 2010. "Probabilistic risk assessment modeling of digital instrumentation and control systems using two dynamic methodologies," Reliability Engineering and System Safety, Elsevier, vol. 95(10), pages 1011-1039.
    10. 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.
    11. Raoni, Rafael & Secchi, Argimiro R., 2019. "Procedures to model and solve probabilistic dynamic system problems," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    12. Maidana, Renan G. & Parhizkar, Tarannom & Gomola, Alojz & Utne, Ingrid B. & Mosleh, Ali, 2023. "Supervised dynamic probabilistic risk assessment: Review and comparison of methods," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    13. Dhople, S.V. & DeVille, L. & Domínguez-García, A.D., 2014. "A Stochastic Hybrid Systems framework for analysis of Markov reward models," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 158-170.
    14. Guanquan, Chu & Jinhui, Wang, 2012. "Study on probability distribution of fire scenarios in risk assessment to emergency evacuation," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 24-32.
    15. Mandelli, Diego & Yilmaz, Alper & Aldemir, Tunc & Metzroth, Kyle & Denning, Richard, 2013. "Scenario clustering and dynamic probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 146-160.

    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. Kareen Rozen, 2010. "Foundations of Intrinsic Habit Formation," Econometrica, Econometric Society, vol. 78(4), pages 1341-1373, July.
    2. Benjamin Eden, 2004. "Substitution and Risk Aversion: Is Risk Aversion Important for Understanding Asset Prices?," Vanderbilt University Department of Economics Working Papers 0422, Vanderbilt University Department of Economics.
    3. Stephen Satchell & Susan Thorp, 2007. "Scenario Analysis with Recursive Utility: Dynamic Consumption Plans for Charitable Endowments," Research Paper Series 209, Quantitative Finance Research Centre, University of Technology, Sydney.
    4. repec:esx:essedp:770 is not listed on IDEAS
    5. Luo, Yulei & Young, Eric R., 2016. "Induced uncertainty, market price of risk, and the dynamics of consumption and wealth," Journal of Economic Theory, Elsevier, vol. 163(C), pages 1-41.
    6. Maria Demertzis, 2010. "An Operational Measure of Riskiness: A Comment," DNB Working Papers 262, Netherlands Central Bank, Research Department.
    7. Luo, Yulei & Nie, Jun & Young, Eric R., 2014. "Robust control, informational frictions, and international consumption correlations," European Economic Review, Elsevier, vol. 67(C), pages 1-27.
    8. Miller, Marcus, 2006. "Fear and Market Failure: Global Imbalances and 'Self-insurance'," CEPR Discussion Papers 6000, C.E.P.R. Discussion Papers.
    9. David Backus & Mikhail Chernov & Ian Martin, 2011. "Disasters Implied by Equity Index Options," Journal of Finance, American Finance Association, vol. 66(6), pages 1969-2012, December.
    10. Lex Borghans & Bart H. H. Golsteyn & James J. Heckman & Huub Meijers, 2009. "Gender Differences in Risk Aversion and Ambiguity Aversion," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 649-658, 04-05.
    11. Dominik Grafenhofer & Christian Jaag & Christian Keuschnigg & Mirela Keuschnigg, 2005. "Probabilistic Aging," University of St. Gallen Department of Economics working paper series 2005 2005-08, Department of Economics, University of St. Gallen.
    12. Bloise, Gaetano & Vailakis, Yiannis, 2018. "Convex dynamic programming with (bounded) recursive utility," Journal of Economic Theory, Elsevier, vol. 173(C), pages 118-141.
    13. Stanislav Khrapov, 2012. "Risk Premia: Short and Long-term," Working Papers w0169, Center for Economic and Financial Research (CEFIR).
    14. van Binsbergen, Jules H. & Fernández-Villaverde, Jesús & Koijen, Ralph S.J. & Rubio-Ramírez, Juan, 2012. "The term structure of interest rates in a DSGE model with recursive preferences," Journal of Monetary Economics, Elsevier, vol. 59(7), pages 634-648.
    15. Yulei Luo & Eric R. Young, 2010. "Risk-Sensitive Consumption and Savings under Rational Inattention," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(4), pages 281-325, October.
    16. Claudio Campanale & Rui Castro & Gian Luca Clementi, 2010. "Asset Pricing in a Production Economy with Chew-Dekel Preferences," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 13(2), pages 379-402, April.
    17. Christopher Ball & John Creedy, 2014. "Tax policy with uncertain future costs: Some simple models," New Zealand Economic Papers, Taylor & Francis Journals, vol. 48(2), pages 240-253, August.
    18. Patrick Augustin & Roméo Tédongap, 2021. "Disappointment Aversion, Term Structure, and Predictability Puzzles in Bond Markets," Management Science, INFORMS, vol. 67(10), pages 6266-6293, October.
    19. Jung, Kuk Mo, 2018. "Uncertainty-induced dynamic inefficiency and the optimal inflation rate," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 486-506.
    20. Backus, David & Ferriere, Axelle & Zin, Stanley, 2015. "Risk and ambiguity in models of business cycles," Journal of Monetary Economics, Elsevier, vol. 69(C), pages 42-63.
    21. Panetti, Ettore, 2022. "Banks’ liquidity provision and panic runs with recursive preferences," Finance Research Letters, Elsevier, vol. 47(PA).

    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:93:y:2008:i:11:p:1616-1627. 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.