IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v114y2013icp99-113.html
   My bibliography  Save this article

Quantification of margins and uncertainties using multiple gates and conditional probabilities

Author

Listed:
  • Iaccarino, Gianluca
  • Sharp, David
  • Glimm, James

Abstract

A methodology to perform the Quantification of Margins and Uncertainties (QMU) is introduced to enable the assessment of the safety associated with the operating conditions of complex engineering devices consisting of multiple subcomponents or coupled multi-physics processes. One of the key components of the approach is the possibility of decomposing the system into subcomponents characterized by critical metrics—gates—that collectively describe the reliability of the whole system. In the present study we formalize the process of constructing conditional probabilities for system performance and illustrate it with two applications: the evaluation of the test-time in a shock-tube experimental facility and the assessment of the unstart limit in the combustion chamber of a supersonic propulsion engine. In both cases, multiple uncertainties are considered and the gates are used as a mechanism to reduce the complexity of the resulting stochastic problem.

Suggested Citation

  • Iaccarino, Gianluca & Sharp, David & Glimm, James, 2013. "Quantification of margins and uncertainties using multiple gates and conditional probabilities," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 99-113.
    • Handle: RePEc:eee:reensy:v:114:y:2013:i:c:p:99-113
    DOI: 10.1016/j.ress.2012.11.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832012002608
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2012.11.026?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. Pilch, Martin & Trucano, Timothy G. & Helton, Jon C., 2011. "Ideas underlying the Quantification of Margins and Uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 965-975.
    2. Helton, Jon C., 2011. "Quantification of margins and uncertainties: Conceptual and computational basis," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 976-1013.
    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. Helton, Jon C. & Brooks, Dusty M. & Sallaberry, Cédric J., 2020. "Property values associated with the failure of individual links in a system with multiple weak and strong links," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    2. Helton, Jon C. & Brooks, Dusty M. & Sallaberry, Cédric J., 2020. "Margins associated with loss of assured safety for systems with multiple weak links and strong links," Reliability Engineering and System Safety, Elsevier, vol. 195(C).

    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. Helton, Jon C. & Brooks, Dusty M. & Sallaberry, Cédric J., 2020. "Property values associated with the failure of individual links in a system with multiple weak and strong links," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    2. Shah, Harsheel & Hosder, Serhat & Winter, Tyler, 2015. "Quantification of margins and mixed uncertainties using evidence theory and stochastic expansions," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 59-72.
    3. Sankararaman, S. & Mahadevan, S., 2013. "Separating the contributions of variability and parameter uncertainty in probability distributions," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 187-199.
    4. Helton, Jon C. & Brooks, Dusty M. & Sallaberry, Cédric J., 2020. "Margins associated with loss of assured safety for systems with multiple weak links and strong links," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. Di Maio, Francesco & Bandini, Alessandro & Zio, Enrico & Alberola, Sofia Carlos & Sanchez-Saez, Francisco & Martorell, Sebastián, 2016. "Bootstrapped-ensemble-based Sensitivity Analysis of a trace thermal-hydraulic model based on a limited number of PWR large break loca simulations," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 122-134.
    6. Hund, Lauren & Schroeder, Benjamin & Rumsey, Kellin & Huerta, Gabriel, 2018. "Distinguishing between model- and data-driven inferences for high reliability statistical predictions," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 201-210.
    7. Strigini, Lorenzo & Wright, David, 2014. "Bounds on survival probability given mean probability of failure per demand; and the paradoxical advantages of uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 128(C), pages 66-83.
    8. Teferra, Kirubel & Shields, Michael D. & Hapij, Adam & Daddazio, Raymond P., 2014. "Mapping model validation metrics to subject matter expert scores for model adequacy assessment," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 9-19.
    9. Certa, Antonella & Hopps, Fabrizio & Inghilleri, Roberta & La Fata, Concetta Manuela, 2017. "A Dempster-Shafer Theory-based approach to the Failure Mode, Effects and Criticality Analysis (FMECA) under epistemic uncertainty: application to the propulsion system of a fishing vessel," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 69-79.
    10. Benoumechiara Nazih & Bousquet Nicolas & Michel Bertrand & Saint-Pierre Philippe, 2020. "Detecting and modeling critical dependence structures between random inputs of computer models," Dependence Modeling, De Gruyter, vol. 8(1), pages 263-297, January.
    11. Helton, Jon C. & Johnson, Jay D., 2011. "Quantification of margins and uncertainties: Alternative representations of epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1034-1052.
    12. Helton, Jon C. & Pilch, Martin & Sallaberry, Cédric J., 2014. "Probability of loss of assured safety in systems with multiple time-dependent failure modes: Representations with aleatory and epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 171-200.
    13. Roger Flage & Terje Aven & Enrico Zio & Piero Baraldi, 2014. "Concerns, Challenges, and Directions of Development for the Issue of Representing Uncertainty in Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 34(7), pages 1196-1207, July.
    14. Cao, Jiaokun & Du, Farong & Ding, Shuiting, 2013. "Global sensitivity analysis for dynamic systems with stochastic input processes," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 106-117.
    15. Mathieu Balesdent & Jérôme Morio & Loïc Brevault, 2016. "Rare Event Probability Estimation in the Presence of Epistemic Uncertainty on Input Probability Distribution Parameters," Methodology and Computing in Applied Probability, Springer, vol. 18(1), pages 197-216, March.
    16. Benoumechiara Nazih & Bousquet Nicolas & Michel Bertrand & Saint-Pierre Philippe, 2020. "Detecting and modeling critical dependence structures between random inputs of computer models," Dependence Modeling, De Gruyter, vol. 8(1), pages 263-297, January.
    17. Price, Robert R. & Singh, Bhupinder P. & MacKinnon, Robert J. & David Sevougian, S., 2013. "The application of systems engineering principles to the prioritization of sustainable nuclear fuel cycle options," Energy Policy, Elsevier, vol. 53(C), pages 205-217.
    18. Helton, Jon C. & Brooks, Dusty M. & Sallaberry, Cédric J., 2022. "Probability of Loss of Assured Safety in Systems with Multiple Time-Dependent Failure Modes: Incorporation of Delayed Link Failure in the Presence of Aleatory Uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    19. Hund, Lauren & Schroeder, Benjamin, 2020. "A causal perspective on reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    20. Francesco, Di Maio & Matteo, Fumagalli & Carlo, Guerini & Federico, Perotti & Enrico, Zio, 2021. "Time-dependent reliability analysis of the reactor building of a nuclear power plant for accounting of its aging and degradation," Reliability Engineering and System Safety, Elsevier, vol. 205(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:114:y:2013:i:c:p:99-113. 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.