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Title: An approximate reasoning-based method for screening high-level-waste tanks for flammable gas

Abstract

The in situ retention of flammable gas produced by radiolysis and thermal decomposition in high-level waste can pose a safety problem if the gases are released episodically into the dome space of a storage tank. Screening efforts at the Hanford site have been directed at identifying tanks in which this situation could exist. Problems encountered in screening motivated an effort to develop and improved screening methodology. Approximate reasoning (AR) is a formalism designed to emulate the kinds of complex judgments made by subject matter experts. It uses inductive logic structures to build a sequence of forward-chaining inferences about a subject. Approximate-reasoning models incorporate natural language expressions known as linguistic variables to represent evidence. The use of fuzzy sets to represent these variables mathematically makes it practical to evaluate quantitative and qualitative information consistently. In a pilot study to investigate the utility of AR for flammable gas screening, the effort to implement such a model was found to be acceptable, and computational requirements were found to be reasonable. The preliminary results showed that important judgments about the validity of observational data and the predictive power of models could be made. These results give new insights into the problems observed in previousmore » screening efforts.« less

Authors:
; ;
Publication Date:
Research Org.:
Los Alamos National Lab., NM (US)
OSTI Identifier:
20067742
Resource Type:
Journal Article
Journal Name:
Nuclear Technology
Additional Journal Information:
Journal Volume: 130; Journal Issue: 3; Other Information: PBD: Jun 2000; Journal ID: ISSN 0029-5450
Country of Publication:
United States
Language:
English
Subject:
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS; 12 MANAGEMENT OF RADIOACTIVE WASTES, AND NON-RADIOACTIVE WASTES FROM NUCLEAR FACILITIES; SAFETY ANALYSIS; HIGH-LEVEL RADIOACTIVE WASTES; RADIOACTIVE WASTE STORAGE; RADIOLYSIS; HANFORD RESERVATION; FUZZY LOGIC; HYDROGEN; AMMONIA; METHANE; RISK ASSESSMENT

Citation Formats

Eisenhawer, S.W., Bott, T.F., and Smith, R.E. An approximate reasoning-based method for screening high-level-waste tanks for flammable gas. United States: N. p., 2000. Web.
Eisenhawer, S.W., Bott, T.F., & Smith, R.E. An approximate reasoning-based method for screening high-level-waste tanks for flammable gas. United States.
Eisenhawer, S.W., Bott, T.F., and Smith, R.E. Thu . "An approximate reasoning-based method for screening high-level-waste tanks for flammable gas". United States.
@article{osti_20067742,
title = {An approximate reasoning-based method for screening high-level-waste tanks for flammable gas},
author = {Eisenhawer, S.W. and Bott, T.F. and Smith, R.E.},
abstractNote = {The in situ retention of flammable gas produced by radiolysis and thermal decomposition in high-level waste can pose a safety problem if the gases are released episodically into the dome space of a storage tank. Screening efforts at the Hanford site have been directed at identifying tanks in which this situation could exist. Problems encountered in screening motivated an effort to develop and improved screening methodology. Approximate reasoning (AR) is a formalism designed to emulate the kinds of complex judgments made by subject matter experts. It uses inductive logic structures to build a sequence of forward-chaining inferences about a subject. Approximate-reasoning models incorporate natural language expressions known as linguistic variables to represent evidence. The use of fuzzy sets to represent these variables mathematically makes it practical to evaluate quantitative and qualitative information consistently. In a pilot study to investigate the utility of AR for flammable gas screening, the effort to implement such a model was found to be acceptable, and computational requirements were found to be reasonable. The preliminary results showed that important judgments about the validity of observational data and the predictive power of models could be made. These results give new insights into the problems observed in previous screening efforts.},
doi = {},
journal = {Nuclear Technology},
issn = {0029-5450},
number = 3,
volume = 130,
place = {United States},
year = {2000},
month = {6}
}