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Uncertainty and sensitivity analysis for the nominal scenario class in the 2008 performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada

Author

Listed:
  • 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.
  • Vo, P.

Abstract

Extensive work has been carried out by the U.S. Department of Energy (DOE) in the development of a proposed geologic repository at Yucca Mountain (YM), Nevada, for the disposal of high-level radioactive waste. In support of this development and an associated license application to the U.S. Nuclear Regulatory Commission (NRC), the DOE completed an extensive performance assessment (PA) for the proposed YM repository in 2008. This presentation describes uncertainty and sensitivity analysis results for the nominal scenario class (i.e., for undisturbed conditions) obtained in the 2008 YM PA. The following topics are addressed: (i) uncertainty and sensitivity analysis procedures, (ii) drip shield and waste package failure, (iii) engineered barrier system conditions, (iv) radionuclide release results for the engineered barrier system, unsaturated zone, and saturated zone, and (v) dose to the reasonably maximally exposed individual specified in the NRC regulations for the YM repository. The present article is part of a special issue of Reliability Engineering and System Safety devoted to the 2008 YM PA; additional articles in the issue describe other aspects of the 2008 YM PA.

Suggested Citation

  • 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 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 272-296.
    • Handle: RePEc:eee:reensy:v:122:y:2014:i:c:p:272-296
    DOI: 10.1016/j.ress.2013.06.008
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    References listed on IDEAS

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    1. Storlie, Curtis B. & Swiler, Laura P. & Helton, Jon C. & Sallaberry, Cedric J., 2009. "Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1735-1763.
    2. Storlie, Curtis B. & Helton, Jon C., 2008. "Multiple predictor smoothing methods for sensitivity analysis: Description of techniques," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 28-54.
    3. 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.
    4. Storlie, Curtis B. & Helton, Jon C., 2008. "Multiple predictor smoothing methods for sensitivity analysis: Example results," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 55-77.
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    Cited by:

    1. Edoardo Tosoni & Ahti Salo & Enrico Zio, 2018. "Scenario Analysis for the Safety Assessment of Nuclear Waste Repositories: A Critical Review," Risk Analysis, John Wiley & Sons, vol. 38(4), pages 755-776, April.

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