IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v203y2020ics0951832020305834.html
   My bibliography  Save this article

Comparison of statistical methods and deterministic sensitivity studies for investigation on the influence of uncertainty parameters: Application to LBLOCA

Author

Listed:
  • Kang, Dong Gu

Abstract

In the BEPU methodology, an identification of uncertainty parameters affecting an accident consequence and an evaluation of their influence are essential tasks. In this study, the BEPU calculations for APR-1400 LBLOCA were conducted with considering 18 uncertainty parameters. Based on these calculation results, the influence of uncertainty parameters on the blowdown and reflood PCTs was evaluated statistically by applying a correlation analysis and a multiple linear regression analysis, and the comparisons with the results of deterministic sensitivity studies were made. In the statistical evaluation, the important uncertainty variables were identified by a hypothesis test, and their ranking was determined through correlation coefficients and standardized regression coefficients. As a result, the correlation analysis showed a limitation in identifying the important uncertainty parameters to both blowdown and reflood PCTs. On the other hand, the multiple linear regression analysis provided good results in identifying and evaluating influential variables for the blowdown PCT. For the reflood PCT, it showed somewhat different results to those of the deterministic sensitivity studies. However, considering the fact that this discrepancy is mainly caused by an inherent perturbation characteristic of the reflood PCT, it could be concluded that the multiple linear regression analysis provided sufficiently reasonable assessment results.

Suggested Citation

  • Kang, Dong Gu, 2020. "Comparison of statistical methods and deterministic sensitivity studies for investigation on the influence of uncertainty parameters: Application to LBLOCA," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
  • Handle: RePEc:eee:reensy:v:203:y:2020:i:c:s0951832020305834
    DOI: 10.1016/j.ress.2020.107082
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832020305834
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2020.107082?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. Queral, C. & Gómez-Magán, J. & París, C. & Rivas-Lewicky, J. & Sánchez-Perea, M. & Gil, J. & Mula, J. & Meléndez, E. & Hortal, J. & Izquierdo, J.M. & Fernández, I., 2018. "Dynamic event trees without success criteria for full spectrum LOCA sequences applying the integrated safety assessment (ISA) methodology," Reliability Engineering and System Safety, Elsevier, vol. 171(C), pages 152-168.
    2. Martorell, S. & Sánchez-Sáez, F. & Villanueva, J.F. & Carlos, S., 2017. "An extended BEPU approach integrating probabilistic assumptions on the availability of safety systems in deterministic safety analyses," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 474-483.
    3. Di Maio, Francesco & Rai, Ajit & Zio, Enrico, 2016. "A dynamic probabilistic safety margin characterization approach in support of Integrated Deterministic and Probabilistic Safety Analysis," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 9-18.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    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. París, C. & Queral, C. & Mula, J. & Gómez-Magán, J. & Sánchez-Perea, M. & Meléndez, E. & Gil, J., 2019. "Quantitative risk reduction by means of recovery strategies," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 13-32.
    2. Queral, Cesar & Fernández-Cosials, Kevin & Zugazagoitia, Eneko & Paris, Carlos & Magan, Javier & Mendizabal, Rafael & Posada, Jose, 2021. "Application of Expanded Event Trees combined with uncertainty analysis methodologies," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    3. 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).
    4. Martorell, P. & Martón, I. & Sánchez, A.I. & Martorell, S. & Sanchez-Saez, F. & Saiz, M., 2018. "Evaluation of risk impact of completion time changes combining PSA and DSA model insight and human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 97-107.
    5. 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).
    6. Chi, Lixun & Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi & Zhang, Li & Fan, Lin & Zhou, Jing & Bai, Hua, 2020. "Integrated Deterministic and Probabilistic Safety Analysis of Integrated Energy Systems with bi-directional conversion," Energy, Elsevier, vol. 212(C).
    7. 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.
    8. Tolo, Silvia & Tian, Xiange & Bausch, Nils & Becerra, Victor & Santhosh, T.V. & Vinod, G. & Patelli, Edoardo, 2019. "Robust on-line diagnosis tool for the early accident detection in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 110-119.
    9. 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).
    10. Huang, Jia & You, Jian-Xin & Liu, Hu-Chen & Song, Ming-Shun, 2020. "Failure mode and effect analysis improvement: A systematic literature review and future research agenda," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    11. Francesco, Di Maio & Matteo, Fumagalli & Carlo, Guerini & Federico, Perotti & Enrico, Zio, 2021. "Time-dependent reliability analysis of the reactor building of a nuclear power plant for accounting of its aging and degradation," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    12. 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.
    13. 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).
    14. Santhosh, T.V. & Gopika, V. & Ghosh, A.K. & Fernandes, B.G., 2018. "An approach for reliability prediction of instrumentation & control cables by artificial neural networks and Weibull theory for probabilistic safety assessment of NPPs," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 31-44.
    15. Raoni, Rafael & Secchi, Argimiro R., 2019. "Procedures to model and solve probabilistic dynamic system problems," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Chi, Lixun & Su, Huai & Zio, Enrico & Qadrdan, Meysam & Li, Xueyi & Zhang, Li & Fan, Lin & Zhou, Jing & Yang, Zhaoming & Zhang, Jinjun, 2021. "Data-driven reliability assessment method of Integrated Energy Systems based on probabilistic deep learning and Gaussian mixture Model-Hidden Markov Model," Renewable Energy, Elsevier, vol. 174(C), pages 952-970.
    17. 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).
    18. Park, Jong Woo & Lee, Seung Jun, 2022. "Simulation optimization framework for dynamic probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    19. Antonello, Federico & Buongiorno, Jacopo & Zio, Enrico, 2022. "A methodology to perform dynamic risk assessment using system theory and modeling and simulation: Application to nuclear batteries," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    20. Medeiros, C.P. & Alencar, M.H. & de Almeida, A.T., 2017. "Multidimensional risk evaluation of natural gas pipelines based on a multicriteria decision model using visualization tools and statistical tests for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 268-276.

    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:203:y:2020:i:c:s0951832020305834. 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.