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Ideas underlying the Quantification of Margins and Uncertainties

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  • Pilch, Martin
  • Trucano, Timothy G.
  • Helton, Jon C.

Abstract

Key ideas underlying the application of Quantification of Margins and Uncertainties (QMU) to nuclear weapons stockpile lifecycle decisions are described. While QMU is a broad process and methodology for generating critical technical information to be used in U.S. nuclear weapon stockpile management, this paper emphasizes one component, which is information produced by computational modeling and simulation. In particular, the following topics are discussed: (i) the key principles of developing QMU information in the form of Best Estimate Plus Uncertainty, (ii) the need to separate aleatory and epistemic uncertainty in QMU, and (iii) the properties of risk-informed decision making (RIDM) that are best suited for effective application of QMU. The paper is written at a high level, but provides an extensive bibliography of useful papers for interested readers to deepen their understanding of the presented ideas.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:96:y:2011:i:9:p:965-975
    DOI: 10.1016/j.ress.2011.03.016
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    References listed on IDEAS

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    1. J. C. Helton & D. R. Anderson & M. G. Marietta & R. P. Rechard, 1997. "Performance Assessment for the Waste Isolation Pilot Plant: From Regulation to Calculation for 40 CFR 191.13," Operations Research, INFORMS, vol. 45(2), pages 157-177, April.
    2. Trucano, T.G. & Swiler, L.P. & Igusa, T. & Oberkampf, W.L. & Pilch, M., 2006. "Calibration, validation, and sensitivity analysis: What's what," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1331-1357.
    3. Helton, Jon C. & Sallaberry, Cedric J., 2009. "Conceptual basis for the definition and calculation of expected dose in performance assessments for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 677-698.
    4. Helton, Jon C. & Sallaberry, Cedric J., 2009. "Computational implementation of sampling-based approaches to the calculation of expected dose in performance assessments for the proposed high-level radioactive waste repository at Yucca Mountain, Nev," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 699-721.
    5. Helton, J.C. & Johnson, J.D. & Sallaberry, C.J. & Storlie, C.B., 2006. "Survey of sampling-based methods for uncertainty and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1175-1209.
    6. Helton, J.C. & Johnson, J.D. & Oberkampf, W.L., 2006. "Probability of loss of assured safety in temperature dependent systems with multiple weak and strong links," Reliability Engineering and System Safety, Elsevier, vol. 91(3), pages 320-348.
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. Hund, Lauren & Schroeder, Benjamin, 2020. "A causal perspective on reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    7. 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.
    8. Robinson, Allen C. & Drake, Richard R. & Swan, M. Scot & Bennett, Nichelle L. & Smith, Thomas M. & Hooper, Russell & Laity, George R., 2021. "A software environment for effective reliability management for pulsed power design," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    9. 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).
    10. 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.
    11. 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.
    12. 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.

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