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Improved metamodel-based importance sampling for the performance assessment of radioactive waste repositories

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  • Cadini, F.
  • Gioletta, A.
  • Zio, E.

Abstract

In the context of a probabilistic performance assessment of a radioactive waste repository, the estimation of the probability of exceeding the dose threshold set by a regulatory body is a fundamental task. This may become difficult when the probabilities involved are very small, since the classically used sampling-based Monte Carlo methods may become computationally impractical. This issue is further complicated by the fact that the computer codes typically adopted in this context requires large computational efforts, both in terms of time and memory. This work proposes an original use of a Monte Carlo-based algorithm for (small) failure probability estimation in the context of the performance assessment of a near surface radioactive waste repository. The algorithm, developed within the context of structural reliability, makes use of an estimated optimal importance density and a surrogate, kriging-based metamodel approximating the system response. On the basis of an accurate analytic analysis of the algorithm, a modification is proposed which allows further reducing the computational efforts by a more effective training of the metamodel.

Suggested Citation

  • Cadini, F. & Gioletta, A. & Zio, E., 2015. "Improved metamodel-based importance sampling for the performance assessment of radioactive waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 188-197.
    • Handle: RePEc:eee:reensy:v:134:y:2015:i:c:p:188-197
    DOI: 10.1016/j.ress.2014.10.018
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    References listed on IDEAS

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    1. Cadini, F. & Santos, F. & Zio, E., 2014. "An improved adaptive kriging-based importance technique for sampling multiple failure regions of low probability," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 109-117.
    2. Sallaberry, C.J. & Behie, G.A. & Bier, A. & Brooks, K.M. & Chen, Y. & Hansen, C.W. & Helton, J.C. & Hommel, S.P. & Lee, K.P. & Lester, B. & Mattie, P.D. & Mehta, S. & Miller, S.P. & Sevougian, S.D. & , 2014. "Uncertainty and sensitivity analysis for the igneous scenario classes in the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 354-379.
    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, J.C. & Gross, M.G. & Hansen, C.W. & Sallaberry, C.J. & Sevougian, S.D., 2014. "Expected dose for the seismic scenario classes in the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 380-398.
    5. Sallaberry, C.J. & Hansen, C.W. & Helton, J.C., 2014. "Expected dose for the igneous scenario classes in the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 339-353.
    6. Cadini, F. & Avram, D. & Pedroni, N. & Zio, E., 2012. "Subset Simulation of a reliability model for radioactive waste repository performance assessment," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 75-83.
    7. Helton, J.C. & Hansen, C.W. & Sallaberry, C.J., 2014. "Expected dose for the early failure scenario classes in the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 297-309.
    8. Helton, J.C. & Hansen, C.W. & Sallaberry, C.J., 2014. "Expected dose and associated uncertainty and sensitivity analysis results for all scenario classes in the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca ," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 421-435.
    9. Helton, J.C. & Hansen, C.W. & Sallaberry, C.J., 2014. "Conceptual structure and computational organization of the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 223-248.
    10. Fauriat, W. & Gayton, N., 2014. "AK-SYS: An adaptation of the AK-MCS method for system reliability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 137-144.
    11. Helton, J.C. & Hansen, C.W. & Sallaberry, C.J., 2014. "Expected dose for the nominal scenario class in the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 267-271.
    12. Hansen, C.W. & Behie, G.A. & Bier, A. & Brooks, K.M. & Chen, Y. & Helton, J.C. & Hommel, S.P. & Lee, K.P. & Lester, B. & Mattie, P.D. & Mehta, S. & Miller, S.P. & Sallaberry, C.J. & Sevougian, S.D. & , 2014. "Uncertainty and sensitivity analysis for the seismic scenario classes in the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 122(C), pages 406-420.
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    Cited by:

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    2. Razaaly, Nassim & Congedo, Pietro Marco, 2020. "Extension of AK-MCS for the efficient computation of very small failure probabilities," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    3. Buchwald, J. & Kolditz, O. & Nagel, T., 2024. "Design-of-Experiment (DoE) based history matching for probabilistic integrity analysis—A case study of the FE-experiment at Mont Terri," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    4. Tosoni, E. & Salo, A. & Govaerts, J. & Zio, E., 2019. "Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 561-573.
    5. Cadini, F. & Gioletta, A., 2016. "A Bayesian Monte Carlo-based algorithm for the estimation of small failure probabilities of systems affected by uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 15-27.
    6. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    7. Cadini, Francesco & Agliardi, Gian Luca & Zio, Enrico, 2017. "Estimation of rare event probabilities in power transmission networks subject to cascading failures," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 9-20.
    8. Cao, Quoc Dung & Choe, Youngjun, 2019. "Cross-entropy based importance sampling for stochastic simulation models," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    9. Francesco Di Maio & Nicola Pedroni & Barnabás Tóth & Luciano Burgazzi & Enrico Zio, 2021. "Reliability Assessment of Passive Safety Systems for Nuclear Energy Applications: State-of-the-Art and Open Issues," Energies, MDPI, vol. 14(15), pages 1-17, August.
    10. Zywiec, William J. & Mazzuchi, Thomas A. & Sarkani, Shahram, 2021. "Analysis of process criticality accident risk using a metamodel-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 207(C).

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