Use of artificial intelligence in severe accident diagnosis for PWRs

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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.

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9 p.

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Wu, Zheng; Okrent, D. & Kastenberg, W.E. December 31, 1995.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 11 times . More information about this article can be viewed below.

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Description

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.

Physical Description

9 p.

Notes

OSTI as DE98000774

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  • American Nuclear Society international topical conference on the safety of operating reactors, Seattle, WA (United States), 17-23 Sep 1995

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  • Other: DE98000774
  • Report No.: CONF-950914--11
  • Grant Number: FG03-92ER75838
  • Office of Scientific & Technical Information Report Number: 560874
  • Archival Resource Key: ark:/67531/metadc691390

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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Creation Date

  • December 31, 1995

Added to The UNT Digital Library

  • Aug. 14, 2015, 8:43 a.m.

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  • Nov. 5, 2015, 7:14 p.m.

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Wu, Zheng; Okrent, D. & Kastenberg, W.E. Use of artificial intelligence in severe accident diagnosis for PWRs, article, December 31, 1995; United States. (digital.library.unt.edu/ark:/67531/metadc691390/: accessed November 12, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.