IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v186y2019icp110-119.html
   My bibliography  Save this article

Robust on-line diagnosis tool for the early accident detection in nuclear power plants

Author

Listed:
  • Tolo, Silvia
  • Tian, Xiange
  • Bausch, Nils
  • Becerra, Victor
  • Santhosh, T.V.
  • Vinod, G.
  • Patelli, Edoardo

Abstract

Any loss of coolant accident mitigation strategy is necessarily bound by the promptness of the break detection as well as the accuracy of its diagnosis. The availability of on-line monitoring tools is then crucial for enhancing safety of nuclear facilities. The requirements of robustness and short latency implied by the necessity for fast and effective actions are undermined by the challenges associated with break prediction during transients.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:186:y:2019:i:c:p:110-119
    DOI: 10.1016/j.ress.2019.02.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832018304253
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2019.02.015?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. 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.
    2. Santosh, T.V. & Srivastava, A. & Sanyasi Rao, V.V.S. & Ghosh, A.K. & Kushwaha, H.S., 2009. "Diagnostic system for identification of accident scenarios in nuclear power plants using artificial neural networks," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 759-762.
    3. Magnus Nørgaard & Ole Ravn & Niels Kjølstad Poulsen, 2002. "NNSYSID-Toolbox for System Identification with Neural Networks," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 8(1), pages 1-20, March.
    4. Nabeshima, K & Suzudo, T & Ohno, T & Kudo, K, 2002. "Nuclear reactor monitoring with the combination of neural network and expert system," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 60(3), pages 233-244.
    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. Chen, Zhen & Zhou, Di & Zio, Enrico & Xia, Tangbin & Pan, Ershun, 2023. "Adaptive transfer learning for multimode process monitoring and unsupervised anomaly detection in steam turbines," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    2. Ma, Chenyang & Li, Yongbo & Wang, Xianzhi & Cai, Zhiqiang, 2023. "Early fault diagnosis of rotating machinery based on composite zoom permutation entropy," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    3. Vincenzo Destino & Nicola Pedroni & Roberto Bonifetto & Francesco Di Maio & Laura Savoldi & Enrico Zio, 2021. "Metamodeling and On-Line Clustering for Loss-of-Flow Accident Precursors Identification in a Superconducting Magnet Cryogenic Cooling Circuit," Energies, MDPI, vol. 14(17), pages 1-37, September.
    4. Waqar Muhammad Ashraf & Ghulam Moeen Uddin & Syed Muhammad Arafat & Sher Afghan & Ahmad Hassan Kamal & Muhammad Asim & Muhammad Haider Khan & Muhammad Waqas Rafique & Uwe Naumann & Sajawal Gul Niazi &, 2020. "Optimization of a 660 MW e Supercritical Power Plant Performance—A Case of Industry 4.0 in the Data-Driven Operational Management Part 1. Thermal Efficiency," Energies, MDPI, vol. 13(21), pages 1-33, October.
    5. Li, Ruopu & Arzaghi, Ehsan & Abbassi, Rouzbeh & Chen, Diyi & Li, Chunhao & Li, Huanhuan & Xu, Beibei, 2020. "Dynamic maintenance planning of a hydro-turbine in operational life cycle," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    6. Liu, Jiaxin & Yu, Deping & Yang, Taibo & Liu, Caixue & Wang, Guangjin & Liu, Xiaoming, 2023. "Discovering the causes for the change of the vibration characteristics of the core support barrel in PWR nuclear power plants: A combined investigation based on ex-core neutron noise analysis and nume," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    7. Zio, Enrico, 2022. "Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    8. Wu, Jingyao & Zhao, Zhibin & Sun, Chuang & Yan, Ruqiang & Chen, Xuefeng, 2021. "Learning from Class-imbalanced Data with a Model-Agnostic Framework for Machine Intelligent Diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 216(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. 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).
    2. 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).
    3. 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).
    4. Li, Zhanhang & Zhou, Jian & Nassif, Hani & Coit, David & Bae, Jinwoo, 2023. "Fusing physics-inferred information from stochastic model with machine learning approaches for degradation prediction," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    5. Gómez, M.J. & Castejón, C. & García-Prada, J.C., 2016. "Automatic condition monitoring system for crack detection in rotating machinery," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 239-247.
    6. 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).
    7. Zio, Enrico & Di Maio, Francesco, 2010. "A data-driven fuzzy approach for predicting the remaining useful life in dynamic failure scenarios of a nuclear system," Reliability Engineering and System Safety, Elsevier, vol. 95(1), pages 49-57.
    8. 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).
    9. 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).
    10. 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.
    11. Selimefendigil, Fatih & Bayrak, Fatih & Oztop, Hakan F., 2018. "Experimental analysis and dynamic modeling of a photovoltaic module with porous fins," Renewable Energy, Elsevier, vol. 125(C), pages 193-205.
    12. Oh, ChoHwan & Lee, Jeong Ik, 2020. "Real time nuclear power plant operating state cognitive algorithm development using dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    13. Peng Su & Guanjun Wang, 2022. "Reliability analysis of network systems subject to probabilistic propagation failures and failure isolation effects," Journal of Risk and Reliability, , vol. 236(2), pages 290-306, April.
    14. 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).

    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:186:y:2019:i:c:p:110-119. 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.