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Bootstrapped-ensemble-based Sensitivity Analysis of a trace thermal-hydraulic model based on a limited number of PWR large break loca simulations

Author

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  • Di Maio, Francesco
  • Bandini, Alessandro
  • Zio, Enrico
  • Alberola, Sofia Carlos
  • Sanchez-Saez, Francisco
  • Martorell, Sebastián

Abstract

The safety verification of nuclear systems can be done by analyzing the outputs of Best-Estimate Thermal-Hydraulic (BE-TH) codes, which allow predicting the system response under safe and accidental conditions with greater realism as compared to conservative TH codes. In this case, it is necessary to quantify and control the uncertainties in the analysis, which affect the estimated safety margins. This can be achieved by Sensitivity Analysis (SA) and Uncertainty Analysis (UA) techniques tailored to handle the large computational costs of TH codes. This work presents an Ensemble-Based Sensitivity Analysis (EBSA) based on Finite Mixture Model (FMM) as an effective solution to keep low the code runs and handle the uncertainty in the SA methods. The approach proposed is challenged against a situation of a very low number of code runs: the Bootstrap method is, then, used in support. Three different strategies based on EBSA and Bootstrap are set forth (i.e., bottom-up, all-out and filter strategies). An application is provided with respect to a Large Break Loss of Coolant Accident (LBLOCA) simulated by a TRACE model of the Zion 1 Nuclear Power Plant (NPP).

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:153:y:2016:i:c:p:122-134
    DOI: 10.1016/j.ress.2016.04.013
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    Cited by:

    1. 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).
    2. Matteo Vagnoli & Francesco Di Maio & Enrico Zio, 2018. "Ensembles of climate change models for risk assessment of nuclear power plants," Journal of Risk and Reliability, , vol. 232(2), pages 185-200, April.
    3. Sanchez-Saez, F. & Sánchez, A.I. & Villanueva, J.F. & Carlos, S. & Martorell, S., 2018. "Uncertainty analysis of a large break loss of coolant accident in a pressurized water reactor using non-parametric methods," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 19-28.
    4. 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.
    5. 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.
    6. Xiong, Qingwen & Du, Peng & Deng, Jian & Huang, Daishun & Song, Gongle & Qian, Libo & Wu, Zenghui & Luo, Yuejian, 2022. "Global sensitivity analysis for nuclear reactor LBLOCA with time-dependent outputs," Reliability Engineering and System Safety, Elsevier, vol. 221(C).

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