IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v122y2014icp354-379.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.
  • 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 igneous intrusive scenario class and the igneous eruptive scenario class obtained in the 2008 YM PA. The following topics are addressed for the igneous intrusive scenario class: (i) engineered barrier system conditions, (ii) release results for the engineered barrier system, unsaturated zone, and saturated zone, (iii) dose to the reasonably maximally exposed individual (RMEI) specified in the NRC regulations for the YM repository, and (iv) expected dose to the RMEI. In addition, expected dose to the RMEI for the igneous eruptive scenario class is also considered. 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

  • 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.
    • Handle: RePEc:eee:reensy:v:122:y:2014:i:c:p:354-379
    DOI: 10.1016/j.ress.2013.06.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832013001828
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2013.06.017?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. 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.
    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. 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.
    2. 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.

    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. Zhou, Yuekuan & Zheng, Siqian, 2020. "Uncertainty study on thermal and energy performances of a deterministic parameters based optimal aerogel glazing system using machine-learning method," Energy, Elsevier, vol. 193(C).
    2. Helton, Jon C. & Johnson, Jay D. & Sallaberry, Cédric J., 2011. "Quantification of margins and uncertainties: Example analyses from reactor safety and radioactive waste disposal involving the separation of aleatory and epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1014-1033.
    3. Saurbayeva, Assemgul & Memon, Shazim Ali & Kim, Jong, 2023. "Integrated multi-stage sensitivity analysis and multi-objective optimization approach for PCM integrated residential buildings in different climate zones," Energy, Elsevier, vol. 278(PB).
    4. Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
    5. Guo, Zehua & Dailey, Ryan & Feng, Tangtao & Zhou, Yukun & Sun, Zhongning & Corradini, Michael L & Wang, Jun, 2021. "Uncertainty analysis of ATF Cr-coated-Zircaloy on BWR in-vessel accident progression during a station blackout," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    6. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).
    7. Zio, E. & Pedroni, N., 2010. "An optimized Line Sampling method for the estimation of the failure probability of nuclear passive systems," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1300-1313.
    8. Yildiz, Yusuf & Korkmaz, Koray & Göksal Özbalta, Türkan & Durmus Arsan, Zeynep, 2012. "An approach for developing sensitive design parameter guidelines to reduce the energy requirements of low-rise apartment buildings," Applied Energy, Elsevier, vol. 93(C), pages 337-347.
    9. Wu, Qiong-Li & Cournède, Paul-Henry & Mathieu, Amélie, 2012. "An efficient computational method for global sensitivity analysis and its application to tree growth modelling," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 35-43.
    10. Zio, E. & Pedroni, N., 2012. "Monte Carlo simulation-based sensitivity analysis of the model of a thermal–hydraulic passive system," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 90-106.
    11. Song, Xiaodong & Bryan, Brett A. & Almeida, Auro C. & Paul, Keryn I. & Zhao, Gang & Ren, Yin, 2013. "Time-dependent sensitivity of a process-based ecological model," Ecological Modelling, Elsevier, vol. 265(C), pages 114-123.
    12. Hou, Tianfeng & Nuyens, Dirk & Roels, Staf & Janssen, Hans, 2019. "Quasi-Monte Carlo based uncertainty analysis: Sampling efficiency and error estimation in engineering applications," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    13. Cui, Lijie & Lu, Zhenzhou & Wang, Pan & Wang, Weihu, 2014. "The ordering importance measure of random variable and its estimation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 105(C), pages 132-143.
    14. Iftikhar Ahmad & Ahsan Ayub & Uzair Ibrahim & Mansoor Khan Khattak & Manabu Kano, 2018. "Data-Based Sensing and Stochastic Analysis of Biodiesel Production Process," Energies, MDPI, vol. 12(1), pages 1-13, December.
    15. McFarland, John & DeCarlo, Erin, 2020. "A Monte Carlo framework for probabilistic analysis and variance decomposition with distribution parameter uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    16. Penttinen, Jussi-Pekka & Niemi, Arto & Gutleber, Johannes & Koskinen, Kari T. & Coatanéa, Eric & Laitinen, Jouko, 2019. "An open modelling approach for availability and reliability of systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 387-399.
    17. Ehre, Max & Papaioannou, Iason & Straub, Daniel, 2020. "Global sensitivity analysis in high dimensions with PLS-PCE," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    18. Narkuniene, Asta & Poskas, Povilas & Kilda, Raimondas & Bartkus, Gytis, 2015. "Uncertainty and sensitivity analysis of radionuclide migration through the engineered barriers of deep geological repository: Case of RBMK-1500 SNF," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 8-16.
    19. Brissaud, Florent & Barros, Anne & Bérenguer, Christophe & Charpentier, Dominique, 2011. "Reliability analysis for new technology-based transmitters," Reliability Engineering and System Safety, Elsevier, vol. 96(2), pages 299-313.
    20. Jåstad, Eirik Ogner & Bolkesjø, Torjus Folsland, 2023. "Offshore wind power market values in the North Sea – A probabilistic approach," Energy, Elsevier, vol. 267(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:122:y:2014:i:c:p:354-379. 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.