Development of a Bayesian belief network for a boiling water reactor during fault conditions
Abstract
This paper describes briefly the development and verification of a probabilistic system for the rapid diagnosis of plant status and radioactive releases during postulated severe accidents in a Boiling Water Reactor nuclear power plant. The probabilistic approach uses Bayesian belief network methodology, and was developed in the STERPS project in the European Union 5-th Euroatom Framework program.
Keywords
nuclear reactors, source term, Bayesian belief network, severe accidents, probabilistic safety Assessment,References
[1] E. Grindon, M. L. Ang, M. Kulig, M. Slootman, H. Löffler, G. Horvath, A. Bujan, W. Frid, W. Cholewa and M. Khatib-Rahbar. A rapid response source term indicator based on plant status for use in emergency response (STERPS). Proceedings of FISA 2003, November 2003, Luxemburg.[2] Norsys, NETICA Application for Belief Networks and Influence Diagrams - User's Guide, Norsys Software Corp. 1997.
[3] M. Johansson. Input data for the project STERPS. OKG report 2002-02102, February 2002.
[4] H. Dubik et al. Containment protection during severe accidents. Proceeding of SMIRT 16, Washington DC, August 2001.
[5] B. Berger. Oskarshamn Unit 3 - Source term analysis. OKG report 97-05336, 1998.
Published
Nov 28, 2022
How to Cite
FRID, Wiktor; KNOCHENHAUER, Michael; BEDNARSKI, Marcin.
Development of a Bayesian belief network for a boiling water reactor during fault conditions.
Computer Assisted Methods in Engineering and Science, [S.l.], v. 12, n. 2-3, p. 133-145, nov. 2022.
ISSN 2956-5839.
Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/983>. Date accessed: 27 july 2024.
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