Fuzzy rule-based modeling of vapor cloud explosion probabilities

Conference · Fri Jan 01 00:00:00 EST 1993 · Transactions of the American Nuclear Society; (United States)

OSTI ID:5823878

Kubic, Jr, W L ^[1]

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1. Los Alamos National Lab., NM (United States)

Estimating the frequency of accidents in nonreactor nuclear facilities is difficult because quantitative reliability data are lacking for many critical items. Because data are often lacking, the risk analysis relies on [open quotes]expert judgment[close quotes] or [open quotes]engineering judgment.[close quotes] This paper presents an alternative to the ad hoc use of engineering judgment in risk analysis. This alternative is fuzzy rule-based modeling. The fundamental principle of fuzzy rule-based modeling is that qualitative knowledge, which is the basis of engineering judgment, is valid knowledge. The intent of fuzzy rule-based modeling is to make better, systematic use of qualitative knowledge. The method is related to expert system technology. The basic concepts of fuzzy rule-based modeling, as applied to consequence modeling, have been discussed previously. This paper examines the application of these methods to the problem of estimating probabilities. The study considers a particular application, determining the probability of a deflagration-to-detonation transition in a vapor cloud.

• OSTI ID: 5823878
• Report Number(s): CONF-930601-; CODEN: TANSAO
• Journal Information: Transactions of the American Nuclear Society; (United States), Vol. 68; Conference: American Nuclear Society (ANS) annual meeting, San Diego, CA (United States), 20-24 Jun 1993; ISSN 0003-018X
• Country of Publication: United States
• Language: English

Related Subjects

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
ACCIDENTS
FUZZY LOGIC
PROBABILISTIC ESTIMATION
NUCLEAR FACILITIES
EXPERT SYSTEMS
RISK ASSESSMENT
MATHEMATICAL LOGIC
054000* - Nuclear Fuels- Health & Safety
990200 - Mathematics & Computers