Development of a Bayesian belief network for a boiling water reactor during fault conditions

Authors

  • Wiktor Frid Royal Institute of Technology
    Sweden
  • Michael Knochenhauer Relcon AB
    Sweden
  • Marcin Bednarski Silesian University of Technology
    Poland

Keywords:

nuclear reactors, source term, Bayesian belief network, severe accidents, probabilistic safety Assessment

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.

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.

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Published

2022-11-28

Issue

Vol. 12 No. 2-3 (2005)
pp. 133-145

Section

Articles

License

Copyright © The Author(s).

This work is licensed under the Creative Commons Attribution 4.0 International CC BY 4.0.

How to Cite

Frid, W., Knochenhauer, M., & Bednarski, M. (2022). Development of a Bayesian belief network for a boiling water reactor during fault conditions. Computer Assisted Methods in Engineering and Science, 12(2-3), 133-145. https://cames3.ippt.pan.pl/index.php/cames/article/view/983