IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v213y2021ics0951832021002970.html
   My bibliography  Save this article

Uncertainty analysis of ATF Cr-coated-Zircaloy on BWR in-vessel accident progression during a station blackout

Author

Listed:
  • Guo, Zehua
  • Dailey, Ryan
  • Feng, Tangtao
  • Zhou, Yukun
  • Sun, Zhongning
  • Corradini, Michael L
  • Wang, Jun

Abstract

The deposition of protective coatings on nuclear fuel cladding has been considered as a near-term Accident Tolerant Fuel (ATF) concept that will reduce the high-temperature oxidation rate and enhance accident tolerance of the cladding while providing additional benefits during normal operation and transients. In this study, an uncertainty analysis was employed to investigate the potential benefits of ATF Cr-coated-Zr cladding and canister for an unmitigated Short-Term Station Blackout (STSBO) sequence in a generic BWR plant using the MELCOR systems code. The MELCOR parameters that reflect the current state-of-knowledge of the relevant fuel assembly performance during core degradation were selected and characterized according to their ranges and distributions. An extensive set of simulations (240 MELCOR calculations) were performed for the Zr and Cr-coated-Zr cladding and canister materials, respectively, to determine their effect on core degradation with the associated uncertainties. The comparison between the Zr and Cr-coated-Zr calculations confirms that the use of ATF Cr-coated-Zr as cladding and canister component material in BWR might be an effective way to mitigate the accident progression and reduce the total hydrogen generation during the accident. The core degradation process was only delayed by less than a half hour, providing some additional time for compensatory actions to mitigate with the accident progression. In contrast, the effect of coated materials on total hydrogen generation was more substantial; i.e., hydrogen generation was almost reduced by half. In addition, a sensitivity analysis based on the Pearson and Spearman correlation coefficients was conducted to rank the significance of the considered parameter uncertainties. The Cr-coating failure temperature was identified as the dominant factor in the MELCOR simulations of core degradation and associated hydrogen generation. Understanding these effects will inform and guide researchers to focus on a more productive area of research and development for accident-tolerant fuel concepts and enhancement of core safety margins.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021002970
    DOI: 10.1016/j.ress.2021.107770
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832021002970
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2021.107770?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. Radaideh, Majdi I. & Borowiec, Katarzyna & Kozlowski, Tomasz, 2019. "Integrated framework for model assessment and advanced uncertainty quantification of nuclear computer codes under Bayesian statistics," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 357-377.
    2. Galushin, Sergey & Grishchenko, Dmitry & Kudinov, Pavel, 2020. "Implementation of framework for assessment of severe accident management effectiveness in Nordic BWR," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    3. Maljovec, D. & Liu, S. & Wang, B. & Mandelli, D. & Bremer, P.-T. & Pascucci, V. & Smith, C., 2016. "Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 262-276.
    4. Zugazagoitia, Eneko & Queral, Cesar & Fernández-Cosials, Kevin & Gómez, Javier & Durán, Luis Felipe & Sánchez-Torrijos, Jorge & Posada, José María, 2020. "Uncertainty and sensitivity analysis of a PWR LOCA sequence using parametric and non-parametric methods," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Zheng, Xiaoyu & Itoh, Hiroto & Kawaguchi, Kenji & Tamaki, Hitoshi & Maruyama, Yu, 2015. "Application of Bayesian nonparametric models to the uncertainty and sensitivity analysis of source term in a BWR severe accident," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 253-262.
    6. Karanki, D.R. & Rahman, S. & Dang, V.N. & Zerkak, O., 2017. "Epistemic and aleatory uncertainties in integrated deterministic and probabilistic safety assessment: Tradeoff between accuracy and accident simulations," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 91-102.
    7. 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.
    8. Wu, Xu & Kozlowski, Tomasz & Meidani, Hadi, 2018. "Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 422-436.
    9. Liu, Yang & Wang, Dewei & Sun, Xiaodong & Liu, Yang & Dinh, Nam & Hu, Rui, 2021. "Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    10. Di Maio, Francesco & Picoco, Claudia & Zio, Enrico & Rychkov, Valentin, 2017. "Safety margin sensitivity analysis for model selection in nuclear power plant probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 122-138.
    11. Reyes-Fuentes, Melisa & del-Valle-Gallegos, Edmundo & Duran-Gonzalez, Julian & Ortíz-Villafuerte, Javier & Castillo-Durán, Rogelio & Gómez-Torres, Armando & Queral, Cesar, 2021. "AZTUSIA: A new application software for Uncertainty and Sensitivity analysis for nuclear reactors," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    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. Xiong, Qingwen & Qian, Libo & Song, Gongle & Yang, Jiewei & Liu, Yu & Deng, Jian & Qiu, Zhifang, 2024. "Realistic performance assessment of FeCrAl-UN/U3Si2 accident tolerant fuel under loss-of-coolant accident scenario," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. Piotr Darnowski & Piotr Mazgaj & Mateusz Włostowski, 2021. "Uncertainty and Sensitivity Analysis of the In-Vessel Hydrogen Generation for Gen-III PWR and Phebus FPT-1 with MELCOR 2.2," Energies, MDPI, vol. 14(16), pages 1-28, August.
    3. Cho, Jaehyun & Lee, Sang Hun & Bang, Young Suk & Lee, Suwon & Park, Soo Yong, 2022. "Exhaustive simulation approach for severe accident risk in nuclear power plants: OPR-1000 full-power internal events," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    4. Hamza, Mostafa & Joslin, Nick & Lawson, Glen & McSweeney, Luke & Liao, Huafei & Vivanco, Alaina & Diaconeasa, Mihai A., 2024. "Identifying and quantifying a complete set of full-power initiating events during early design stages of high-temperature gas-cooled reactors," Reliability Engineering and System Safety, Elsevier, vol. 242(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. Liu, Yang & Wang, Dewei & Sun, Xiaodong & Liu, Yang & Dinh, Nam & Hu, Rui, 2021. "Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    2. Xiong, Qingwen & Qian, Libo & Song, Gongle & Yang, Jiewei & Liu, Yu & Deng, Jian & Qiu, Zhifang, 2024. "Realistic performance assessment of FeCrAl-UN/U3Si2 accident tolerant fuel under loss-of-coolant accident scenario," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. 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.
    4. Li, Shen & Kim, Do Kyun & Benson, Simon, 2021. "A probabilistic approach to assess the computational uncertainty of ultimate strength of hull girders," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    5. Zheng, Xiaoyu & Tamaki, Hitoshi & Sugiyama, Tomoyuki & Maruyama, Yu, 2022. "Dynamic probabilistic risk assessment of nuclear power plants using multi-fidelity simulations," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    6. Mazgaj, Piotr & Darnowski, Piotr & Kaszko, Aleksej & Hortal, Javier & Dusic, Milorad & Mendizábal, Rafael & Pelayo, Fernando, 2022. "Demonstration of the E-BEPU methodology for SL-LOCA in a Gen-III PWR reactor," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    7. Wang, Zihan & Daeipour, Mohamad & Xu, Hongyi, 2023. "Quantification and propagation of Aleatoric uncertainties in topological structures," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    8. 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).
    9. 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.
    10. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    11. 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).
    12. Donghyeon Yoo & Jinhwan Park & Jaemin Moon & Changwan Kim, 2021. "Reliability-Based Design Optimization for Reducing the Performance Failure and Maximizing the Specific Energy of Lithium-Ion Batteries Considering Manufacturing Uncertainty of Porous Electrodes," Energies, MDPI, vol. 14(19), pages 1-15, September.
    13. 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.
    14. Javier Urquizo & Carlos Calderón & Philip James, 2017. "Using a Local Framework Combining Principal Component Regression and Monte Carlo Simulation for Uncertainty and Sensitivity Analysis of a Domestic Energy Model in Sub-City Areas," Energies, MDPI, vol. 10(12), pages 1-22, December.
    15. 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.
    16. Wang, Wei & Cammi, Antonio & Di Maio, Francesco & Lorenzi, Stefano & Zio, Enrico, 2018. "A Monte Carlo-based exploration framework for identifying components vulnerable to cyber threats in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 24-37.
    17. 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).
    18. Jingwen Song & Zhenzhou Lu & Pengfei Wei & Yanping Wang, 2015. "Global sensitivity analysis for model with random inputs characterized by probability-box," Journal of Risk and Reliability, , vol. 229(3), pages 237-253, June.
    19. Rehman, Hassam ur & Hirvonen, Janne & Sirén, Kai, 2017. "A long-term performance analysis of three different configurations for community-sized solar heating systems in high latitudes," Renewable Energy, Elsevier, vol. 113(C), pages 479-493.
    20. Auder, Benjamin & De Crecy, Agnès & Iooss, Bertrand & Marquès, Michel, 2012. "Screening and metamodeling of computer experiments with functional outputs. Application to thermal–hydraulic computations," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 122-131.

    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:213:y:2021:i:c:s0951832021002970. 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.