Use of artificial intelligence in severe accident diagnosis for PWRs

Conference · Sun Dec 31 00:00:00 EST 1995

OSTI ID:560874

Wu, Zheng; Okrent, D ^[1]; Kastenberg, W E ^[2]

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1. Univ. of California, Los Angeles, CA (United States)
2. Univ. of California, Berkeley, CA (United States)

A combination approach of an expert system and neural networks is used to implement a prototype severe accident diagnostic system which would monitor the progression of the severe accident and provide necessary plant status information to assist the plant staff in accident management during the accident. The station blackout accident in a pressurized water reactor (PWR) is used as the study case. The current phase of research focus is on distinguishing different primary system failure modes and following the accident transient before and up to vessel breach.

• Research Organization: Univ. of California, Los Angeles, CA (United States)
• Sponsoring Organization: USDOE Office of Energy Research, Washington, DC (United States)
• DOE Contract Number: FG03-92ER75838
• OSTI ID: 560874
• Report Number(s): CONF-950914-11; ON: DE98000774; TRN: 98:000345
• Resource Relation: Conference: American Nuclear Society international topical conference on the safety of operating reactors, Seattle, WA (United States), 17-23 Sep 1995; Other Information: PBD: 1995
• Country of Publication: United States
• Language: English

Related Subjects

22 NUCLEAR REACTOR TECHNOLOGY
21 NUCLEAR POWER REACTORS AND ASSOCIATED PLANTS
99 MATHEMATICS
COMPUTERS
INFORMATION SCIENCE
MANAGEMENT
LAW
MISCELLANEOUS
ARTIFICIAL INTELLIGENCE
REACTOR ACCIDENTS
NEURAL NETWORKS
PWR TYPE REACTORS
DIAGNOSTIC TECHNIQUES